Alex
Tonetti

Seasoned technology leader with a proven record of bridging data science, solution architecture, and customer success to drive meaningful innovation. Over a decade of experience delivering end-to-end solutions in AI, ML, and cloud environments for global clients across healthcare, supply-chain, government, and enterprise sectors. Adept at leading cross-functional teams, implementing robust product strategies, and improving operational efficiency. Recognized for driving measurable improvements in platform usability, client satisfaction, and streamlined development workflows. Passionate about leveraging a diverse technical background, entrepreneurial mindset, and customer-focused approach to deliver impactful, scalable solutions that align technology investments with strategic business goals.

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A portrait of Alex Tonetti against a colorful mural. Taken by Alex Tonetti.

More About Me

Alex Tonetti

Multidisciplinary Technologist

Current Occupation

Director of Customer Success at Rhino Health

Competencies

Solution Architecture
Software Development
Data Engineering
Customer Experience
Product Management
Technical Consulting
Customer Success
Entrepreneurship
Data Science
Web Development
Client Management
Pre-sales Engineering

Interests

Software Development
Artificial Intelligence
Web Development
Process Automation
3D Printing
Crypto & Web3
Finance
Angel Investing
Entrepreneurship
Graphic Design
Art & Architecture
Fashion
Music & Podcasts
Movies & TV
Travel
Photography
Hiking
Sneakers

Explore my photography in the Interests section below.

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Education

Undergraduate

University of Maryland, College Park

Bachelor of Science in Computer Engineering, Minor in International Engineering

Graduate

Georgia Institute of Technology

Master of Science in Computer Science, Specialization in Machine Learning

Education Abroad

Thailand

Supporting Vulnerable & At-risk Children

2008

A two-week cultural exchange in Thailand united a group of students and the school principal to support children in youth homes and orphanages. At three children’s centers, they offered care, education, and emotional support to kids, many of whom had endured trauma or survived human trafficking, witnessing firsthand the adversity these young people faced. The experience underscored the value of giving back, offering a humbling view of how middle-class American struggles pale in comparison, while volunteer service reinforced gratitude, resilience, and cross-cultural understanding.

New Zealand

Environmental Sustainability

2011

The Study Abroad program in New Zealand explored environmental sustainability, showcasing the country’s natural ecosystems, renewable energy practices, and cultural heritage. Participants visited geothermal, hydroelectric, and wind plants, seeing how natural resources drive sustainable energy solutions. An immersive Māori cultural experience revealed their deep respect for nature and tradition of sustainability. It highlighted how cultural values and sustainable living intersect through local communities, exploring diverse landscapes, and studying innovative environmental practices.

China

International Engineering & Business Cultures

2012

The Study Abroad program in China examined International Engineering and Business Cultures, showing how U.S. and Chinese business practices differ. In Beijing and Shanghai, participants visited offices of major U.S. and EU companies, interviewing employees on adapting to China. These talks revealed cultural challenges and strategies for success. Meetings with expatriate small-business owners offered fresh insight into entrepreneurship and China’s unique market. The program provided a broad view of cross-cultural business dynamics and their global impact.

Career

Present

Studio Labs

Founder

Present — 2024

Remote

List-Diff.Tools

(Present — 2024)

Link

Built and launched a client-side JavaScript web tool that enables users to compare and operate on two lists directly within the browser. The application supports functions such as counting duplicates, de-duplicating, set differences/unions/intersections, and random element selection while offering comprehensive customization options—ignore case/whitespace, output case conversion, sorting, CSV-formatted copying, and detailed list statistics.

Convert-Case.Tools

(Present — 2024)

Link

Developed a website for converting text between various lexicographical cases (i.e., lower case, upper case, sentence case, camel case, Pascal case, snake case, path case, etc.). The tool processes large text inputs in real-time using browser-side Javascript—ensuring data privacy—while offering additional features like text statistics—character count (ignore whitespace), (distinct) word count (case-insensitive), (empty or distinct) line count (case-insensitive), etc.

ACT Photography & Design

Founder

Present — 2013

Remote

Alex Tonetti Photography

(Present — 2013)

Link

Founded and managed a photography business selling original work through print-on-demand (POD) sites, overseeing website and graphic design, social media and email marketing, customer service, legal and financial administration, business development and partnerships, contractor hiring, and solo 401k management.
Engineered end-to-end automation solutions, including web upload scripts for multiple platforms, image tagging automation leveraging recognition and search trend analytics, and custom community engagement tools to interact with artists and potential customers—leading to a 25% monthly sales increase.
Developed a comprehensive weekly sales reporting system that scraped data, calculated key statistics, and delivered formatted HTML summaries, streamlining financial oversight and strategic decision-making.
Cultivated strategic partnerships with major brands and organizations—including SpringHill Suites by Marriott, Urban Outfitters, Showtime, NBC, Wayfair, Target, and The Washington Post—to increase brand visibility and expand market presence.
Leveraged the tools and processes that drove the success of the photography business to launch four additional POD graphic design brands—designed artwork in Adobe Illustrator, developed custom graphics, built WordPress websites, and managed social media channels.

Automated Meditation YouTube Channel

(Present — 2022)

Launched an automated mindfulness-focused YouTube channel utilizing self-created and public-domain audio & video assets with custom speech-to-text narration and LLM-driven content creation, complemented by a custom WordPress website. Within six months, the channel surpassed 500 subscribers and 3,000 public watch hours—the entry requirements for the YouTube Partner Program. Over 100 videos have been published thus far, garnering thousands of views, hours watched, and hundreds of thousands of organic impressions.
Scripted Python automation leveraging an LLM to craft tailored video copy for constructing blog posts via predefined HTML templates, generating platform-compliant captions and optimal social media tags. Architected a CMS in Notion to persist and organize video metadata, multi-media assets, and publishing details across social platforms.
Automated creation of visually appealing phone wallpapers featuring video affirmations using image processing techniques, distributed freely as part of a grassroots marketing campaign to boost brand awareness.
Developed a Python application to automatically produce tailored affirmation videos for YouTube, TikTok, Instagram, and Twitter (X). The process generates an audio track by blending custom text-to-speech narration (intro, affirmation, outro) with looped background music using audio crossfades for clarity; builds the video by looping relaxing visuals cropped to platform dimensions, splicing custom intro/outro placards, and superimposing affirmation text synchronized with narration; and overlays the final audio and visuals to yield a polished product tailored to each platform’s posting requirements.

Wacky Weasels NFT

(2018 — 2017)

Developed and launched a collection of 9,999 unique, algorithmically generated NFTs featuring over 340 distinct traits minted on Ethereum and Solana blockchains via OpenSea and SolSea. Implemented a sustainable revenue model through royalties on secondary sales to fund ongoing operations, marketing, and growth initiatives.

Best Crypto Faucets

(2018 — 2016)

Developed and launched BestCryptoFaucets.com, an aggregation and comparison affiliate website for cryptocurrency faucets like Bitcoin, Litecoin, Dogecoin, etc.

2024

Rhino Health

Director of Customer Success

2024 — 2022

Remote

Customer Success & Experience
Directed customer-centric product improvements by gathering user feedback and leveraging expert usage to influence roadmaps, PRDs, and feature releases. Championed usability enhancements to boost user satisfaction and reduce platform complexity, including removing mandatory Docker/AWS ECR usage, which decreased related support tickets by 90%, and streamlined onboarding by minimizing credential requirements and lowering entry barriers.
Spearheaded three recurring, data-driven forums (Weekly Platform Experience, Monthly Account Review, and Monthly Customer Experience/Usage Update), providing comprehensive visibility into project progress, feature adoption, and support metrics—directly informing executive decisions, accelerating account planning, and underpinning quarterly board reporting.
Established standard operating procedures for a tiered customer support model, user onboarding, client communication & release notes, identity and access management, and customer end-of-life, driving consistent process execution, operational reliability, and interdepartmental cohesion.
Elevated customer satisfaction by proactively resolving client issues and building strong client rapport, reducing ticket escalations. Implemented quarterly NPS surveys at the start of my tenure—capturing an initial (pre-engagement) -67 baseline—which rose to 100 in all subsequent surveys, reflecting a transformative and sustained boost in overall customer sentiment.
User Onboarding & Adoption
Directed the onboarding lifecycle, delivering 50+ tailored sessions to global audiences, navigating complex institutional InfoSec requirements, and ensuring seamless installations (hardware provisioning, firewall access, backend configuration). Maintained comprehensive customer onboarding tracking for executive visibility and developed a web automation tool for bulk user credential provisioning and distribution.
Developed and executed a comprehensive user onboarding strategy with clear success metrics, continuously refining educational materials based on customer feedback, support ticket analysis, and product updates. Optimized the customer check-in cadence, resulting in accelerated user proficiency, reduced support inquiries, and a more intuitive onboarding experience.
Customer Project Management & Technical Support
Delivered advanced technical support by resolving containerization challenges (including AWS ECR and specialized FCP containers), migrating centralized ML models to NVFlare, and debugging hardware and software systems using Datadog logs and Kubernetes job introspection. When geopolitical conflict halted the engineering efforts, assumed critical responsibilities beyond role expectations providing production hotfixes, new feature implementation, and first-line product testing to ensure business continuity.
Managed all post-sales engagements for commercial and peer-to-peer clients, encompassing solution design, project management, and implementation. Maintained regular client meetings and communication, proactively removed project obstacles, guided platform usage to align with client objectives, and assisted with customer code support to deliver timely, publishable outcomes for conferences and academic papers.
Supported over 60 global healthcare clients across multiple time zones while managing 10+ concurrent projects. Resolved 100+ monthly support tickets, acted as an early-warning outage detector to ensure uptime and stable releases in a continuous deployment environment, and delivered customized assistance for users of varying expertise levels—from platform power users to non-technical SMEs—resulting in efficient issue handling, boosted customer satisfaction and sustained project momentum.
Established a structured customer support framework, unifying Zendesk and Jira workflows to improve cross-team communication. Enhanced ticketing processes to provide more precise, actionable insights for engineering and tighten the feedback loop between customers and product development.
Strategic Product Initiatives & Proof of Concept Development
Developed a POC for two-way data synchronization between a Rhino Client-server and cloud storage solutions (e.g., S3, SMB), enabling seamless use of cloud-stored data for training or validation and automated return of results, eliminating the need for manual data transfers. The POC evolved into a key product feature that directly addressed multiple customers’ requirements, strengthening our product offering.
Mentored a junior team member while co-developing a groundbreaking demo of a containerized LLM model deployed on a remote client using the Rhino Health FCP. The LLM model generated code to harmonize local data for downstream processes, addressing the persistent challenge of unharmonized data in federated computing. The solution evolved into the product offering, Harmonization Co-Pilot.
Successfully piloted the first live, end-to-end integration between the American College of Radiology’s (ACR) system and an ACR partner hospital using the Rhino Health FCP platform. The pilot validated an AI developer’s model using diverse, on-site data from the hospital while ensuring all data remained securely behind the hospital’s firewalls. Announced as a concept at the 2022 RSNA conference, this milestone marked a significant advancement for medical imaging AI, enabling future collaborations between Rhino Health, the ACR, and their extensive network of partner hospitals.
Platform Analytics, Business Intelligence & Reporting
Led the creation of the company’s first unified BI ecosystem by integrating seven disparate data sources (Zendesk, HubSpot, Jira, Monday.com, Google Drive, & back-end systems) and developed processes to reconcile, clean, enrich, and map data. Selected Domo as the BI visualization platform and developed an MVP Account Review dashboard with a custom ETL script, delivering near-real-time insights into customer health, project tracking, and strategic initiatives.
Designed and implemented automated reporting and workflow optimization solutions, delivering data-driven insights for internal teams, executive presentations, product roadmaps, and board decks. Developed automation scripts for tracking OKRs/KPIs, preparing meeting pre-reads, and analyzing platform usage, customer health, product feature adoption, and inter-team operational efficiency. Implemented automation solutions reduced administrative workload by eliminating manual data consolidation, dismantling information silos, and democratizing data access, thereby enhancing cross-functional collaboration and increasing operational agility to adapt to market changes.
Remote Annotation Solutions
Architected and implemented a scalable remote annotation solution with customized workflows, secure collaboration features, comprehensive project plans, onboarding materials, and a Python toolkit for the FCP platform—including a customizable dataset partitioner, annotator productivity tracker, and extensible dataset consolidator. Delivered compelling customer demos that drove business growth and reactivated customers, increasing Annual Recurring Revenue (ARR) while enhancing team expertise through targeted training sessions.
Led two remote annotation projects: one for a large pharmaceutical company partnering with a third-party global network of certified radiologists and another for a world-renowned hospital system utilizing remote annotators from at least seven preeminent U.S. health organizations. Developed bespoke workflows on the FCP platform with role-based access controls, managed data preparation and software containerization, created detailed operating procedures, and facilitated tailored onboarding for annotators.
Technical Documentation & Knowledge Management
Built a centralized documentation center (docs.rhinohealth.com) on Zendesk by migrating outdated PDFs into over 200 help articles, FAQs, and tutorials. Produced system diagrams, data flow charts, and video walkthroughs to deliver a self-service experience that significantly improved user comprehension of a complex platform.
Instituted a documentation policy for every new feature, managed via a dedicated Jira board and SCRUM ceremonies. Prioritized and reduced documentation debt based on customer feedback, user tickets, and engineering input. Served as the final reviewer, publishing monthly release notes and notifying specific customers about relevant updates or fixes.
Continuously refined the documentation strategy through direct client feedback, envisioning next-phase improvements such as modular, action-driven tutorials, increased visual elements, deeper feature explorations, and multi-modal demonstrations (UI, Python SDK, API).
Expanded technical resources by creating a public-facing GitHub repository for code artifacts—complete with best practices, annotated scripts, and READMEs—and producing comprehensive documentation for newly developed sales tools, including custom personas, step-by-step guides, diagrams, and tailored visuals.
Community Engagement & Collaboration
Launched an MVP Community Platform on ZenDesk, uniting researchers, technologists, and data providers for AI-driven healthcare collaboration. This initiative accelerated knowledge sharing, fostering faster model development and validation efforts.
Security, Growth Strategy & Brand Development
Fortified security and user management by handling all provisioning, deactivation, and password resets across multiple environments, implementing secure code practices for sensitive credentials, and conducting quarterly inactivity reviews with executive leadership to uphold compliance and platform integrity.
Drove strategic lead generation with a PubMed-powered tool that mapped co-authorship networks, identifying high-value academic connections based on shared publication volume, which empowered the Partnerships team to engage with Key Opinion Leaders and accelerate new customer acquisition.
Developed a custom D3.js world map to visualize Rhino Health’s extensive client installation network, improving upon a static PowerPoint visualization. Led multimedia branding initiatives, managing the company’s YouTube channel, designing and refining brand graphics, and contributing to the website redesign through design and wireframe feedback to contractors, ensuring a cohesive and engaging online presence that enhanced brand visibility and user experience.

2022

Altana AI

Multiple Positions Held

2022 — 2021

Washington, DC

US Federal Implementations Tech Lead

(2022 — 2021)

Served as the primary technical liaison for contracts with US and UK federal agencies, leading a team to deliver customized Altana KGDB data, mission-specific API scripts, and targeted database queries that provided deep insights into client use cases. Successfully managed and supported up to 14 customers concurrently at peak, ensuring tailored solutions, timely delivery, and high levels of client satisfaction.
Created three quick-start analyst Jupyter notebooks using low-level data assets (API, KGDB parquet files, hybrid approach) for client use. These notebooks evolved into the Atlas Foundations product—a complete Python package featuring industry-specific use cases, a Python SDK, and additional tools for direct interaction with the KGDB.
Developed a suite of reusable tools for Implementations and US Federal teams, including a KGDB production graph release tool, hub-to-spoke data transfer utility, API test scripts, customizable data scrubbing scripts to remove PII and US Persons data, and tools for generating offline documentation for classified environments. These solutions enhanced operational efficiency, ensured compliance with data security standards, and supported deployment in sensitive and regulated environments.
Played a key role in talent acquisition by interviewing and evaluating candidates for diverse roles across the organization. Managed onboarding for new hires and developed upskilling initiatives for non-technical employees, enhancing team capabilities and fostering professional growth.

Senior Data Scientist & Solutions Manager

(2021 — 2021)

Pioneered the company’s first automation for constructing value chains from raw trade data networks. Utilized a novel application of the TF-IDF algorithm with synthetic documents and ontological trade metadata, reducing manual value-chain vetting by over 50%.
Expanded value chain automation by developing a comprehensive end-to-end PySpark solution for constructing customer value chains. The solution encompassed client data ingestion, alignment with Altana data, supply chain modeling, transaction noise filtering, and formatting for seamless integration with custom PowerBI dashboards.
Developed an auto-updating KGDB documentation suite for client distribution, ensuring comprehensive descriptions for all tables and fields, presenting data coverage metrics and update frequencies, and designing intuitive graphical representations of graph nodes and edges for enhanced clarity and usability.
Served as the primary technical liaison for contracts with two UK federal agencies, successfully delivering mission-specific API scripts and database queries to uncover client insights.

2021

Deloitte Consulting

Multiple Positions Held

2021 — 2019

Arlington, VA

Artificial Intelligence & Analytics Team Lead

(2021 — 2020)

Designed and implemented a large-scale data catalog by defining a common data model and integrating over 400 unique data sources. Advised the ETL team on best practices and developed a robust methodology for efficient data ingestion and management.
Led a team of 4 consultants through iterative requirement gathering to rapidly adapt to evolving client needs—collecting data via a custom web scraper and legacy APIs, forecasting metrics with an Auto-ARIMA model, and building Vue.js dashboards hosted on SharePoint using Python-based data science services.
Applied Human-Computer Interaction (HCI) principles to overhaul legacy applications by redesigning interfaces and optimizing workflows, making them more intuitive and easier for users to navigate.

SensingBridge Solution Architect

(2020 — 2019)

Concurrently served as SensingBridge’s Solution Architect, Data Science Lead, Deployment Specialist, and Development Lead while successfully managing a blended team of approximately 12 onshore/offshore resources across multiple time zones—driving strategic initiatives, ensuring technical excellence, and delivering successful project outcomes across various domains.
Built, managed, and administered a comprehensive product roadmap across DevOps, Front-end, Back-end, API, and Data Science layers evaluating technical feasibility for new initiatives, client requests, and emerging use cases.
Collaborated with management on staffing, technical interviews, and code interview assessments, evaluating client project SOWs, negotiating data source agreements, and coordinating with contractors and internal partnerships to drive strategic project success.
Spearheaded Agile sprint ceremonies, managing ticket lifecycle, backlog grooming, story estimation, and pull request reviews to ensure efficient development workflows.
Mentored and coached the entire SensingBridge team through regular checkpoint meetings, providing performance evaluations, actionable feedback, and professional development guidance. Facilitated collaboration with other Deloitte product teams to share lessons learned and best practices, fostering a culture of continuous improvement.
Led the data science team to explore advanced text summarization techniques (abstractive vs. extractive) while optimizing for speed, refining scenario monitoring strategies, implementing geoparsing for location extraction, and integrating LexisNexis News to enrich data sources and analytical capabilities.
Deployed, managed, and monitored over 15 client engagements, including a manual, classified deployment of SensingBridge. Deployment involved configuring AWS services (EC2, RDS, Elasticsearch, S3, ElastiCache-Redis) and manually installing backing services (JanusGraph, Elasticsearch, Cassandra) to meet various complex client requirements.
Created detailed architecture, data flow, and component diagrams for technical and non-technical audiences, contributing to a comprehensive data science pipeline overview deck that enhanced stakeholder understanding, clarity, and engagement with complex system workflows.

SensingBridge Data Science Team Lead

(2019 — 2019)

Instituted strategic improvements by modularizing a monolithic data ETL pipeline into microservices, parallelizing data source loading, leveraging Dask for distributed processing, and collaborating on a cloud-agnostic deployment strategy.
Managed a dynamic team that collectively developed advanced text analytics solutions, including a custom Word2Vec/FastText model for related term generation (with profanity filtering, client-defined terms, and alternate organization names), client-configurable tagging/scoring methods, and a fuzzy deduplication approach using locality-sensitive hashing. The team also launched large-scale data collection efforts—storing derived metadata and tracking named entities for trend integration.
Advised the Data Science team in pioneering scenario monitoring using dependency parsing, sentiment analysis, and SVM for ontology polarity detection while enhancing data querying with Word2Vec-based term integration and cleansing for more accurate results.
Architected and developed a suite of Flask APIs deployed with Gunicorn to deliver real-time data science microservices to the front-end UI.
Engineered a fail-fast initialization script that rigorously validated required configuration parameters and database fields, augmented with sophisticated checks for client-specific customizations to ontology root tagging, querying, and query methods, ensuring more successful, error-resistant deployments.
Mentored and coached the Data Science team and firm initiative members, sharing best practices across Deloitte product teams to foster a culture of continuous improvement and knowledge sharing.
Played a pivotal role in a $100 million federal proposal pursuit, successfully recruiting top talent for both SensingBridge and Deloitte to strengthen the bid.

SensingBridge Data Scientist

(2019 — 2019)

Refactored the codebase using the 12-factor application and object-oriented principles, boosting developer productivity, reusability, readability, and fault tolerance while increasing pipeline performance by over 500% through parallelism, vectorization, and optimized memory usage.
Enhanced data processing and analysis by developing methods for synonym generation, data cleansing, keyword tagging, text summarization, credibility scoring, deduplication, foreign language translation, relevancy scoring, document classification, and establishing direct database connections with SQLAlchemy.
Evaluated 196 unique providers and integrated 88 new data services, expanding the repository to over 100,000 diverse sources across news, patents, research, and government sectors.
Developed a suite of client-facing tools to jumpstart client projects, including ontology creation best-practice guidelines, automated ontology validity checks, and parameterized bash scripts for custom application scheduling.
Mentored the team on Git and development best practices, created a Jupyter Notebook environment for rapid prototyping, and thoroughly documented the application within code and Confluence for effective knowledge sharing.

2020

Georgia Institute of Technology

MS Computer Science

2020 — 2017

Remote

Specialized in Machine Learning
3.9 GPA

2019

IBM

Multiple Positions Held

2019 — 2014

Herndon, VA

Senior Artificial Intelligence Engineer

(2019 — 2017)

Developed a batch document translation application for a Watson Explorer customer project that leveraged IBM Cloud’s Watson Language Translation service to pre-translate documents before ingestion while also enabling custom model training through forced glossaries, parallel corpora, or monolingual corpora.
Designed and developed a Watson Conversation Service demo integrating multiple APIs to deliver historical weather and named storm data. Utilized a custom Node.js integration layer with advanced geolocation processing to determine the nearest weather station.
Leveraged Soul Machines’ Digital Human avatar technology as a Watson Conversation Service chatbot interface for a large financial services client. Developed a custom Speech-to-Text model to capture domain-specific terminology and integrated informational cards to highlight key user insights.
Developed a state-of-the-art proof-of-concept extending the integration between Watson Conversation Service and Soul Machine’s Digital Human to capture user mood and deliver emotionally appropriate responses.
Engineered a novel approach to generate a statistically relevant synthetic Speech-to-Text (STT) corpus using Watson Assistant (WA) training data and usage analytics. This innovative approach enhanced domain coupling and improved STT model accuracy and was subsequently published as a patent.
Developed a library of golden images for Watson products, drastically reducing deployment times and accelerating client onboarding and engagements.
Collaborated with business development and sales teams to oversee technical proposals, forecast precise project timelines, clarify client requirements, and recommend tailored solutions.
Consistently developed and delivered custom client demos throughout my tenure, highlighting Watson Discovery Advisor (WDA), Watson Conversation Service/Watson Assistant (WCS/WA), and Watson Engagement Advisor (WEA) to demonstrate product capabilities and drive client engagement effectively.
Consistently authored defensive patents and scholarly publications throughout my tenure, outlining groundbreaking innovations while safeguarding intellectual property.

Artificial Intelligence Engineer

(2017 — 2015)

Engineered a Java-based domain adaptation tool for IBM’s Watson Discovery Advisor, automating the creation of question-answer training and validation pairs. The tool intelligently generates answer variations based on type (e.g., name, location, measurement), enhancing domain-adaptation specialist productivity, consistency, and accuracy—resulting in improved system performance.
Performed comprehensive support for the Watson Discovery Advisor (WDA) system globally, encompassing client entity and lexicon development, creation of question-answer pairs, and ingestion of structured/unstructured data. Responsibilities also included loading the Knowledge Graph, domain adaptation, training and feature engineering of new ML models, testing and error analysis, defect logging, and documentation.
Developed an NLP-powered data cleansing pipeline for structured and unstructured client data, correcting issues like problematic characters, excessive whitespace, gibberish, and improper splitting, then converting documents into a format suitable for Watson Discovery Advisor ingestion.
Developed an automated dialog testing tool for the Watson Dialog cloud service, simulating conversational flows to verify Natural Language Classifier accuracy and ensure appropriate responses and completeness of required interactions.
Developed a first-of-its-kind Watson Engagement Advisor 3.0 system deployed for public consumption by designing a conversational chatbot that interfaced with a client’s customer management system. This solution enabled users to retrieve billing information, request extensions, process payments, and answer general inquiries.

IT Technical Consultant

(2015 — 2014)

Engineered a Java portlet to visualize system analytics within a state government’s unemployment compensation management system (UCMS), tracking key component statuses for enhanced operational insight and process optimization.
Managed a team of 2-3 external contractors to document the webMethods components of the UCMS.
Enhanced testability within a newly adopted continuous integration environment by developing Maven versions of each portlet project and creating unit test classes with Mockito and PowerMock while also creating over forty manual regression test scripts for the UAT environment for the UCMS.
Created a Java application that reformatted ClearCase-exported XML into a structure easily imported into Microsoft Excel for streamlined analysis.
Identified, investigated, and resolved Java defects in the UCMS while performing manual regression testing for new releases deployed into the UAT environment.

2018

PromotionBots

Founder

2018 — 2016

Remote

Engineered a suite of web automation tools in Java and Selenium, leveraging Google Chrome WebDriver to help customers increase exposure and drive sales on various POD platforms. The core product featured over 700 configurable options across 13 unique automated engagement strategies, allowing for precise audience targeting. Additionally, supplemental products accelerated customer growth with minimal effort.
Implemented anti-piracy protections, including license and hardware validation, to enforce single-device usage. Integrated Google Firebase to enable release-less patches, ensuring minimal downtime by seamlessly adapting to structural changes to POD platforms.
Designed, developed, and wrote all sales copy for a WordPress landing page, enabling direct purchase via PayPal and automated digital fulfillment through a third-party service, which delivered the product and unique license key via email.
Integrated and maintained a frontline web support chatbot, providing detailed responses and an escalation pathway. Continuously optimized based on user interactions, reducing escalations and improving user satisfaction.
Developed advanced email marketing strategies, leveraging a free PDF lead magnet to capture and segment audiences by POD platform. Implemented automated sales funnels to deliver targeted product recommendations, upsell complementary items, and provide post-sale engagement through usage tips and feedback collection. Deployed re-targeting campaigns featuring customer testimonials, case studies, product education, and limited-time offers to re-engage and convert prospects.
Designed a highly passive business model, streamlining the purchase process, automated product delivery, and self-service support through intuitive setup, comprehensive documentation, and optimized user experience—minimizing direct involvement to only complex or one-off customer support cases.
Oversaw all business operations as a solopreneur, managing legal compliance, financial administration, customer service, and product development. Responsibilities included LLC registration, licensing, and regulatory filings; maintaining financials and bookkeeping; administering a solo 401k; hiring contractors for special projects; handling customer support and troubleshooting; and ongoing software enhancements.

2013

University of Maryland

BS Computer Engineering

2013 — 2009

College Park, MD

Minor in International Engineering
Study Abroad in China & New Zealand

T–Rex Consulting

Computer Engineering Internship

2013 — 2012

College Park, MD

Served as the assistant project manager for a Department of Commerce contract, developing RFPs, gathering supplier quotes, and maintaining strict project timelines to consistently meet deadlines and requirements while driving third-party vendor costs down.
Developed a specialized application for imaging, tracking, and securing documents integral to a successful bid for a loan-scanning contract.
Developed web-based solutions streamlining departmental processes: created dynamic forms to digitize the HR hiring workflow and built an application to automate IT request forms, significantly improving efficiency and reducing manual paperwork.
Managed a team of typists to improve low-confidence OCR outputs, maintaining high throughput and data accuracy through streamlined workflows and effective quality assurance.
Conducted comprehensive troubleshooting and provided technical support for computer hardware and software, enabling the T-Rex back office team to resolve complex issues efficiently and maintain operational continuity.

2012

Connection Technology Center

Computer Engineering Co-op

2012 — 2011

Victor, NY

Summer 2012 Co-Op

(2012 — 2012)

Built on previous automation work for seven additional proximity probe product lines, streamlined product-specific applications into a user-friendly suite, and developed a manual version to accommodate future product lines, future-proofing the testing process.
Maintained and enhanced database schemas to support future infrastructure upgrades and new product lines, ensuring data integrity, scalability, and seamless integration with emerging initiatives.
Responded to a critical CEO request by developing a C# reporting service that emailed daily visualizations (via Google’s Charting API) and key statistics to track warehouse productivity, ensure stock levels met order demand, and monitor metrics against quarterly targets.

Summer 2011 Co-Op

(2011 — 2011)

Implemented an automated proximity probe testing application in LabVIEW for the first of eight product lines, reducing manual testing from 15 minutes to 2 minutes by manipulating a digital micrometer stage to verify probe distance readings.
Conducted QA testing of vibration sensors using machine-induced vibrations, performing signal analysis to validate sensor outputs against acceptable thresholds and ensure defect-free manufacturing.

Research

Select each item for more details.

Patents

Publication Dates:

August 8^th 2019, April 11^th, 2023

Links:

US-2019236471-A1, US-11625630-B2

Abstract:

A system, computer program product, and method are provided for use with an intelligent computer platform to identify intent and convert the intent to one or more physical actions. The aspect of converting intent includes receiving content, identifying potential variants, and statistically analyzing the variants with a confidence assessment. The variants are sorted based on a protocol associated with the confidence assessment. A variant from the sort is selected and applied to a physical device, which performs a physical action and an associated hardware transformation based on the variant.

Publication Dates:

August 26^th, 2021, October 18^th, 2022

Links:

US-2021264113-A1, US-11475222-B2

Abstract:

A controller accesses an initial taxonomy for a domain comprising one or more existing terms for the domain identified in a hierarchical structure. The controller analyzes a corpus documents for a domain to identify a selection of one or more documents with glossaries. The controller extracts, from the glossaries, one or more pairs each comprising a term and a definition. The controller attempts to map a respective term of each of the one or more pairs into the initial taxonomy for the domain based on text of a respective definition of each of the one or more pairs to generate an updated taxonomy for the domain.

Publication Date:

February 6^th, 2020, November 9^th 2021

Link:

US-20200043485-A1, US-11170770-B2

Abstract:

Method and apparatus improves the quality of responses from an automatic dialogue system by dynamically adjusting response thresholds. More particularly, the automatic dialogue system may dynamically determine response threshold values in response to user feedback. The response threshold values may be used to evaluate a confidence value. The confidence value may be assigned to or otherwise associated with an input class, or user intent. The system may automatically adjust the response threshold values to provide a better user experience as the amount of user-interaction with the system increases.

Publication Dates:

February 28^th, 2019, October 12^th, 2021

Links:

US-2019065599-A1, US-11151202-B2

Abstract:

A system and a computer program product are provided for evaluating question-answer pairs in an answer key by generating a predicted answer to a test question based on the answer key modification history for comparison matching against a generated answer that is generated in response to the test question, and then comparing the predicted answer and generated answer to determine an accuracy score match indication therebetween so as to present an indication that the answer key may have a problem if there is a match between the predicted answer and generated answer.

Publication Dates:

May 21^st, 2020, July 20^th, 2021

Links:

US-2020159825-A1, US-11068654-B2

Abstract:

An approach is provided in which an information handling system analyzes a message tone vector corresponding to a message against a target tone vector corresponding to a recipient of the message. The message tone vector includes a set of message tone attributes and the target tone vector includes a set of target tone thresholds. The information handling system, in response to determining a difference between the message tone vector and the target tone vector, creates a variant message by substituting words in the message with one or more similar words based on the target tone vector. In turn, the information handling system sends the variant message to the recipient.

Publication Dates:

May 23^rd, 2019, March 23^rd, 2021

Links:

US-20190155828-A1, US-10956463-B2

Abstract:

Embodiments can provide a computer implemented method, in a data processing system comprising a processor and a memory comprising instructions which are executed by the processor to cause the processor to implement an improved search query generation system, the method comprising inputting a natural language question; parsing the natural language question into a parse tree; identifying argument positions comprising one or more argument position terms; for each argument position: comparing a head term’s discriminator score against a threshold discriminator score; and if the head term surpasses the threshold discriminator score, adding the head term as a required term to an improved search query; and outputting the improved search query.

Publication Dates:

May 16^th, 2019, August 6^th, 2019

Links:

US-2019147099-A1, US-10902039-B2

Abstract:

According to one embodiment, a method, computer system, and computer program product for retraining a classifier-based automatic dialogue system with recorded user interactions is provided. The present invention may include receiving recorded interactions, where the interactions are between a user and an automatic dialogue system; determining, based on the recorded interactions, whether to pair a given input with one or more classes; pairing inputs with one or more classes; assessing the reliability of the paired inputs and classes; determining whether the reliable paired inputs and classes can be consistently mapped; and merging all consistently mapped reliable pairs with an initial training set.

Publication Date:

July 23^rd, 2020

Link:

US-2020234181-A1

Abstract:

A method, system and computer program product are provided for implementing enhanced training of a personality model for an embodied conversational agent. An adjustable personality model is provided for the conversational agent interacting with a user with the adjustable personality model configured to provide emotion and tone responses based on detected emotions of the user and a communication objective. Responsive to detecting a first emotion of the user in a conversation with the conversational agent, the adjustable personality model is utilized to embody the conversational agent with a first emotion and tone. Responsive to detecting a second emotion of the user different from the first emotion, the adjustable personality model is utilized to embody the conversational agent with a second emotion and tone possibly different from the first emotion and tone.

Publication Date:

April 30^th, 2020, July 13^th, 2021

Link:

US-2020135175-A1, US-11062697-B2

Abstract:

A device includes a processor configured to, in response to determining that an input phrase includes a first term that is included in a term hierarchy, generate a second phrase by replacing the first term in the input phrase with a second term included in the term hierarchy. The processor is configured to determine that interactive response (IR) training data indicates that the input phrase is associated with a user intent indicator. The processor is configured to determine that user interaction data indicates that a first proportion of user phrases received by an IR system correspond to the user intent indicator. The processor is configured to update speech-to-text training data based on the input phrase and the second phrase so that a second proportion of training phrases of the speech-to-text training data correspond to the user intent indicator. The second proportion is based on the first proportion. A speech-to-text model is trained based on the speech-to-text training data.

Publication Dates:

March 5^th, 2020, November 3^rd, 2020

Links:

US-2020073998-A1, US-11062697-B2

Abstract:

The temporal stability of an answer from a deep question answering system is predicted using a natural language classifier. A training corpus is divided into time-ordered slices having uniform granularity. A series of candidate answers to a training question is generated based on the slices, and a temporal profile for the series is identified by associating candidate answers with respective temporal intervals. The temporal profile is translated to a temporal stability value (representing a time period) using a temporal stability model. The classifier is trained using such training questions correlated with respective temporal stability values. Thereafter, when a user submits a natural language query to the deep question answering system, the query is also applied to the classifier which determines its temporal stability. The temporal stability is presented to the user with the answer to give a sense of how long the answer can be deemed reliable.

Publication Dates:

January 16^th, 2020

Links:

US-2020019641-A1

Abstract:

A dialog system receives a multi-intent input from a user, wherein the multi-intent input comprises a selection of multiple intents in a single conversational input. The dialog system splits the multi-intent input into multiple segments, wherein each of the segments comprises a subsequence of the multi-intent input. The dialog system applies a classifier to classify each segment of the multiple segments by at least one pair of a plurality of pairs in a matrix, each pair of a separate class of multiple classes and a separate confidence level of classification, each of the multiple classes associated with a separate intent from among the multiple intents. The dialog system selects one or more outputs for each separate class in each separate pair, in view of the separate confidence level. The dialog system outputs a response comprising a concatenation of the one or more outputs to the user.

Publication Dates:

January 11^th, 2018, March 27^th, 2018

Links:

US-20180011837-A1, US-9928235-B2

Abstract:

A mechanism is provided in a data processing system having a processor and a memory storing a store of semantic types and instructions for implementing a natural language processing engine for generating semantically equivalent variants of a natural language term. The mechanism receives an input term for variant analysis. The natural language processing engine executing on the data processing system identifies a semantic type of the input term based on a store of semantic types. The natural language processing engine performs a type-specific series of rule-based expansions of the input term based on the identified semantic type of the input term to form a set of semantically equivalent variants of the input term. The natural language processing engine performs a natural language processing operation using the input term and the set of semantically equivalent variants of the input term.

Publication Dates:

January 11^th, 2018, March 6^th, 2018

Links:

US-20180011838-A1, US-9910848-B2

Abstract:

A mechanism is provided in a data processing system having a processor and a memory storing instructions for implementing a natural language processing engine, a store of semantic types, and a store of units, conversions among units, and variants of unit names, for generating semantically equivalent variants of a natural language term. The mechanism receives an input term for variant analysis. The natural language processing engine executing on the data processing system identifies a semantic type of the input term based on the store of semantic types. The natural language processing engine extracts a quantity and a unit from the input term based on the store of units, conversions among units, and variants of unit names. The natural language processing engine populates type-specific templates at a level of specificity based on the input term based on the identified semantic type of the input term and the extracted quantity and unit to form a set of semantically equivalent variants of the input term. The natural language processing engine performs a natural language processing operation using the input term and the set of semantically equivalent variants of the input term.

Publication Dates:

September 19^th, 2017

Links:

US-9767094-B1

Abstract:

A mechanism is provided in a data processing system having a processor and a memory storing a store of semantic types and instructions for implementing a natural language processing engine for generating a question/answer pair list with semantically equivalent variants. The mechanism generates a user interface for generating a question/answer pair list. The mechanism receives user input in the user interface specifying a question and an answer term and specifying an answer type from a list of previously created answer types. The input term comprises the answer term. The natural language processing engine executing on the data processing system identifies a semantic type of the answer term based on the store of semantic types. The natural language processing engine performs a type-specific series of rule-based expansions of the answer term based on the identified semantic type of the answer term of the answer term. The natural language processing engine adds at least one semantically equivalent variant from the set of semantically equivalent variants of the answer term in association with the specified question to the question/answer pair list to form an expanded question/answer pair list. The natural language processing engine trains a question answering machine learning model for a question answering cognitive system using the expanded question/answer pair list as ground truth.

Publications

Publication Year:

2024

Links:

Society for Imaging Informatics in Medicine (SIIM24) Abstract
International Society for Magnetic Resonance in Medicine (ISMRM) Abstract

Introduction:

Deep learning (DL) has been demonstrated to result in robust and accurate prostate gland segmentation on MRI. DL models, however, are susceptible to batch artifacts arising from site- and scanner-specific variations, impacting reliability and clinical translation.

Publication Year:

2024

Links:

Society of Photo-Optical Instrumentation Engineers (SPIE) Presentation + Poster.

Introduction:

Chest X-rays (CXRs) play a pivotal role in cost-effective clinical assessment of various heart and lung related conditions. The urgency of COVID-19 diagnosis prompted their use in identifying conditions like lung opacity, pneumonia, and acute respiratory distress syndrome in pediatric patients. We propose an AI-driven solution for binary COVID-19 versus non-COVID-19 classification in pediatric CXRs. We present a Federated Self-Supervised Learning (FSSL) framework to enhance Vision Transformer (ViT) performance for COVID-19 detection in pediatric CXRs. ViT’s prowess in vision-related binary classification tasks, combined with self-supervised pre-training on adult CXR data, forms the basis of the FSSL approach. We implement our strategy on the Rhino Health Federated Computing Platform (FCP), which ensures privacy and scalability for distributed data. The chest X-ray analysis using the federated SSL (CAFES) model, utilizes the FSSL-pre-trained ViT weights and demonstrated gains in accurately detecting COVID-19 when compared with a fully supervised model. Our FSSL-pre-trained ViT showed an area under the precision-recall curve (AUPR) of 0.952, which is 0.231 points higher than the fully supervised model for COVID-19 diagnosis using pediatric data. Our contributions include leveraging vision transformers for effective COVID-19 diagnosis from pediatric CXRs, employing distributed federated learning-based self-supervised pre-training on adult data, and improving pediatric COVID-19 diagnosis performance. This privacy-conscious approach aligns with HIPAA guidelines, paving the way for broader medical imaging applications.

Publication Year:

2024

Links:

American Association for Cancer Research (AACR) Abstract

Introduction:

Reliability of machine and deep learning models on medical images can be compromised by the presence of image artifacts of variability in image acquisition. This is further exacerbated when validating model performance across multiple institutions, where multiple acquisition protocols and scanner equipment may result in significant numbers of outlier scans. We developed a privacy-preserving outlier identification algorithm via federated MR imaging quality evaluation of a distributed multi-institutional cohort of prostate MRI scans.

Publication Year:

2023

Links:

Bio-IT World Poster

Introduction:

The development of an NLP-based federated learning model for clinical risk prediction task is proposed as a solution to improve the accuracy and efficiency of clinical risk prediction.
This model will be trained on locally stored clinical data at different healthcare institutions. Federated learning approach will be used for model training and testing to maintain patient privacy.
By leveraging the power of NLP and the distributed nature of federated learning, this model has the potential to significantly enhance clinical risk prediction by leveraging diverse datasets while also preserving patient privacy.

Publication Year:

2018

Links:

IP.com Prior Art Database Journal

Introduction:

Software simulation models a real phenomenon using parameters, mathematical formulae, and allows a user to observe an operation through simulation without actually performing that operation. These parameters are embedded into the software code by designers. In some situations, the parameters keep changing based on legal requirements or policy considerations that play a direct role in designing. Presently, such policies are articulated in unstructured textual documents and a designer has to identify parameters that are affected by the policy changes. And then the designer has to make modifications in the identified parameters of the software code, which is an onerous task. Therefore, there is a need of intelligent system that updates the parameters in the software code based on modifications of the policy documents without human involvement.

Publication Year:

2018

Links:

IP.com Prior Art Database Journal

Introduction:

Disclosed is a method and system for training avatars with personality models to generate appropriate emotional responses. The method and system enables the avatars (embodied conversational agents) to determine a user’s mood and semantic intent of speech and expressions in the user input and generate an emotional response based on the user’s emotional state.

Publication Year:

2017

Links:

IP.com Prior Art Database Journal

Introduction:

A method and system is disclosed for configuring a system by reading task recipes and schematic user inputs and engaging in a dialog with a user through a conversational interface to execute appropriate commands to complete a task.

Publication Year:

2016

Links:

IP.com Prior Art Database Journal

Introduction:

Disclosed is a system for automatically generating a set of domain-specific question-answer (QA) pairs from a domain-specific corpus and an existing set of domain-general QA pairs. The output of the system is a high-quality QA set with good coverage suitable for training a QA system to the new domain.

Alex joined the SensingBridge asset team almost exactly one year ago. During that time, he has gone from a Staff Data Scientist to Lead Data Scientist and now is our Solution Architect. We have consistently given him more and more responsibility in quick succession as he has displayed his strong technical capability (and rare skillset) along with a creative, problem-solving mentality.

Senior Manager

SensingBridge, Deloitte

I appreciate that you embody the idea of “we’re a small company, everyone wears lots of hats”. You have a huge hat collection here and are willing to wear them all depending on the day, the combination of which is extremely helpful… I am really glad that we have found someone with a disparate skill set and a willingness to learn about then help solve pretty varied challenges across the team.

Chief Operating Officer

Rhino Health

Alex has been the core engine of helping to stabilize our platform as we have grown from 1 production instance to nearly 10 production instances of SensingBridge. Without Alex’s leadership, I would not feel confident in both the underlying guts of our asset nor with our ability to deploy a production-ready platform consistently. Alex is special!

Senior Manager

SensingBridge, Deloitte

Alex is not playing “just” a typical customer success role—he has touched product, engineering, marketing, etc. This flexibility is very helpful in a small team. (…) Alex is the first port of call for our users, and we consistently receive positive feedback from those users who appreciate Alex’s help. This stems from Alex being personable, knowledgeable, and helpful…

Chief Operating Officer

Rhino Health

In the [Customer] engagement, Alex took a leading role in client and partner engagement in a very challenging environment. He was able to provide effective coordination of the technical tasking among three partner groups (and within the [Customer] between the Testing and the Design groups). This required skill and patience.

Technical Delivery Lead

Data and AI Expert Labs and Learning, IBM Watson

I have every confidence that you’ll be able to learn a new feature or workflow, and help our customers to operationalize it… Along the way, you have built a solid foundation of processes and workflows for us as a team, which has helped us provide a good customer experience, surface interesting insights & opportunities, [and] avoid fire drills.

Chief Operating Officer

Rhino Health

Alex, thank you for your continued support and drive. Without your ideas and guidance, SensingBridge would not be where it is today. Your leadership and ability to handle difficult situations are truly appreciated.

Managing Partner

Federal Strategy & Analytics Assets, Deloitte

Honors

Select each item for more details.

Career

Year:

2020

Background:

Recognized for rapid progression from Data Science Team Member to Team Lead and, ultimately, Solution Architect on the SensingBridge product. As the Data Science Team Lead implemented strategic initiatives to optimize the data pipeline, such as componentization, dependency injection, parallelized data loading, and distributed processing with Dask. Led a dynamic team in achieving innovations, including custom Word2Vec and FastText models for term generation, enhanced tagging and scoring configurability, fuzzy deduplication methods, scalable data collection, and scenario monitoring using parts-of-speech dependency parsing and sentiment analysis. Improved data querying, developed client engagement tools, and delivered six cloud-agnostic client deployments. Actively contributed to client proposals, mentoring team members, and enhancing team collaboration.

As Solution Architect, oversaw a blended team of 12 onshore and offshore members across multiple time zones, managing the product roadmap encompassing DevOps, Front-end, Back-end, API, and Data Science layers. Assessed technical feasibility, created action plans for client use cases, and successfully deployed over 15 solutions, including manual AWS configurations for sensitive clients: organized sprint ceremonies, refined text summarization strategies, integrated geoparsing capabilities, and additional news data sources, developed technical diagrams tailored for diverse audiences. Mentored and evaluated team members, identified growth opportunities and collaborated with stakeholders to share lessons learned and best practices while supporting business development efforts.

Alex joined the SensingBridge asset team almost exactly one year ago. During that time, he has gone from a staff data scientist to lead data scientist and now is our solution architect. We have consistently given him more and more responsibility in quick succession as he has displayed his strong technical capability (and rare skillset) along with a creative, problem solving mentality. Alex has been the core engine of helping to stabilize our platform as we have grown from 1 production instance to nearly 10 production instances of SensingBridge. Without Alex’s leadership, I would not feel confident in both the underlying guts of our asset nor with our ability to deploy a production ready platform consistently. Alex is special!

Senior Manager,

SensingBridge, Deloitte

Year:

2019

Background:

Recognized for significant contributions to the SensingBridge product, including refactoring the codebase using 12-factor Application principles and object-oriented programming to enhance productivity, reusability, and fault tolerance. Achieved a 500% improvement in pipeline efficiency by implementing parallelism, vectorizing functions, and optimizing memory usage. Developed advanced features, including synonym generation, data cleansing, keyword tagging, text summarization, document scoring and classification, deduplication of documents, relevancy scoring, and efficient database integration. Expanded the data network to over 100,000 sources across various domains by integrating and evaluating numerous data services. Spearheaded the adoption of Git and development best practices, developed tools for rapid prototyping, and delivered comprehensive documentation to enhance team collaboration and streamline application usability.

Alex, thank you for your continued support and drive. Without your ideas and guidance, SensingBridge would not be where it is today. Your leadership and ability to handle difficult situations are truly appreciated.

Managing Partner,

Federal Strategy & Analytics Assets, Deloitte

Year:

2018

Background:

Recognized for leadership in developing multiple proof-of-concept conversational agents using Watson Conversation Service for various government agencies. Each proof-of-concept integrated unique APIs to deliver relevant, real-time information tailored to client needs. These initiatives were undertaken in addition to regular project responsibilities, demonstrating a commitment to innovation and client-focused solutions.

Year:

2018

Background:

Recognized for reaching the second plateau, an achievement awarded to inventors whose creativity and technical expertise have resulted in patents and publications totaling 24 points. Each patent idea, valued at up to 3 points, signifies at least eight distinct concepts thoroughly reviewed and ranked by a committee of master inventors and thought leaders within the organization.

Year:

2017

Background:

Awarded for contributions to the enhancement and ongoing support of the domain-adaptation tool, named QABuilder, the subject of three patent disclosures and formed the basis of the 2016 Watson Public Sector Global Delivery Lab Services Award. Continuous improvements to the tool included adding robust new features designed to streamline workflows further, enabling domain adaptation specialists to work even more efficiently. These enhancements significantly improved consistency and accuracy by automating complex processes, mitigating the errors typically associated with manual data entry.

The advancements delivered tangible benefits, increasing the precision of Watson training while elevating domain adaptation specialists’ productivity and overall job satisfaction. By addressing critical needs and optimizing processes, the tool met and exceeded expectations for efficiency and usability in the domain adaptation process.

Year:

2017

Background:

Recognized for designing and implementing the Miami-Dade Water & Sewer chatbot, AVA, leveraging Watson Engagement Advisor 3.0—a solution integrating IBM’s Bluemix services, Dialog, and Natural Language Classifier. In the project’s first phase, the chatbot addressed general billing inquiries and enabled billing extensions for customers, with plans for expanded functionality in future phases. The chatbot was successfully deployed on the main page of the Miami-Dade water utilities website, enhancing customer interaction and support.

Year:

2016

Background:

Recognized for reaching the first plateau, an achievement awarded to inventors whose creativity and technical expertise have resulted in patents and publications totaling 12 points. Each patent idea, valued at up to 3 points, signifies at least four distinct concepts thoroughly reviewed and ranked by a committee of master inventors and thought leaders within the organization.

Year:

2016

Background:

Recognized alongside a teammate for designing and developing a Java-based tool that supports domain adaptation efforts for the Watson question-and-answer system. The tool facilitates the creation of question-answer pairs used to train Watson by automatically generating standard variations for diverse answer types, reducing the need for manual input by domain adaptation specialists. Drawing on expertise in natural language processing (NLP), question-answer systems, and software development, this innovative solution addressed a long-standing request to enhance usability and automation in the domain adaptation process.

The tool delivers significant business impact by enabling specialists to work more efficiently while improving consistency and accuracy, mitigating the error-prone nature of manual data entry. As a result, the Watson training process becomes more precise, and domain adaptation specialists benefit from increased productivity and job satisfaction.

Year:

2016

Background:

Recognized alongside a teammate for designing and developing a Java-based tool to support domain adaptation efforts for the Watson question-and-answer system. The tool streamlines the creation of question-answer pairs used to train Watson by automatically generating standard variations for various answer types, reducing the need for manual specification and input by domain adaptation specialists. This innovation leveraged expertise in natural language processing (NLP), question-answer systems, and software development, effectively addressing a long-standing request for greater automation and improved usability in the adaptation process.

The tool delivers substantial business impact by enabling specialists to work more efficiently while enhancing consistency and accuracy, mitigating the errors inherent in manual data entry. This advancement improves the precision of Watson training and increases domain adaptation specialists’ productivity and job satisfaction.

Year:

2015

Background:

Awarded for contributions to a contract with the United States Air Force, this achievement highlights implementing the Watson Engagement Advisor application—a retrieve-and-rank service designed to simplify the complexities of Federal Acquisition Regulations (FAR) and Defense Federal Acquisition Regulations (DFAR). The system enables users to interact with the regulations by asking natural language questions and receiving concise, accurate answers. This innovation significantly accelerated information retrieval and reduced the time required to train employees on regulatory content. The project’s success garnered recognition, with articles published in Fortune Magazine and The Washington Post.

Photography

Year:

2016

Description:

A photo captured for one of Alco Products Inc. client’s homes was awarded the grand prize in the Exteriors category for homes valued between $100,000 and $200,000.

Alex Tonetti’s Award-Winning Photo – 2016 CotY Grand Prize Winner, Exterior Renovations $100,000-200,000

Year:

2016

Description:

The photo, Circus Affair, was selected to be featured in D/City Style’s holiday print issue, showcased alongside work from several other prominent photographers capturing recent events around Washington, DC. The featured photo is a long-exposure shot of a woman twirling illuminated hula hoops during a circus-themed night outside an apartment complex in the District’s Shaw neighborhood.

Alex Tonetti's 'Circus Affair' - Featured Image in Issue #11 of D/CITY Style Magazine

2016 D/CITY Style Magazine, Issue #11: Happening Now, Featured Image.

Year:

2016

Description:

On November 17th, 2016, my photo, Lady Liberty, was selected for the Featured Instagrammer blog post. The image captured the supermoon hovering above the Lady Liberty sculpture atop the U.S. Capitol building. The post highlighted my work alongside other talented and prominent DC, Maryland, and Virginia photographers. View the post here.

Alex Tonetti's 'Lady Freedom' - Featured as ExposedDC's Instagrammer of the Week on November 17, 2016

ExposedDC: Featured Instagrammer of the Week, November 17th, 2016.

Year:

2016

Description:

My photo, titled Reflections on the Potomac, was selected for display in the Community Collective Photography Showcase, which featured 48 hand-selected, unique works chosen from over 300 submissions by DC-based artists. The image captures the reflection of a rusted Metro bridge on the calm waters of the Potomac River on a frigid winter morning.

Alex Tonetti's 'Reflections on the Potomac' - Selected for the 2016 Capital Fringe Festival Community Collective Photography Showcase

2016 Capital FRINGE Festival: Community Collective Photography Showcase, Exhibiting Artist.

Year:

2015

Description:

When a friend’s former alma mater faced closure, I photographed a protest they organized during a meeting attended by the Virginia governor. The group spoke with the governor, and I captured several moments from the event. The Washington Post wrote an article about the event and featured my photo. Read the article here.

Alex Tonetti's Photography Featured in 2015 Washington Post Article: 'Va. attorney general offers to help Sweet Briar opponents reach a compromise'

2015 The Washington Post Feature: Va. attorney general offers to help Sweet Briar opponents reach a compromise.

Interests

A curious explorer at heart, I’m passionate about discovering the world both literally and figuratively. From traveling to new destinations and capturing moments through photography to tackling trails on a good hike, I find inspiration in every corner of life. When I’m not outdoors, I’m immersed in the world of technology—whether it’s crafting elegant code, exploring the possibilities of artificial intelligence, or diving into web development. I have a knack for automation and RPA (because who doesn’t love making the mundane a bit smarter?) and a growing fascination with the ever-evolving crypto space.

Outside of tech, my interests include creative pursuits like graphic design, 3D printing, and a solid appreciation for fashion and sneakers. I’m also a big fan of music and podcasts, often multitasking between entrepreneurial ventures and diving into the latest finance trends. In short, I’m a mix of a tech geek, a creative mind, and a lover of life’s little adventures—always seeking the next exciting thing to learn, create, or explore.

Alex Tonetti lounging in the Jordan 1's he hand-stoned.

Interests

Photography

What started as a way to unwind from the stresses of college life quickly blossomed into a deep passion for photography. A casual hobby became a creative outlet to capture and share moments of beauty and emotion. As my skills sharpened and my confidence grew, I realized there was potential to transform this passion into something more. Leveraging social media and print-on-demand platforms, I’ve reached a wider audience, sharing my work and bringing the art of photography into homes around the globe.

Flying Flock

Speeding Through Time

Twin Houses

Cuba P109033

Paper Bouquet

Sun Over the Horizon

Proudly Featured in:

Photography Stores:

RedBubble

Inprnt

Saatchi Art

Along the Salt Flats

P.Y.T. (Pretty Young Thing)

Monochrome Winter

The Old West

Blue Coast

On the Pier

Interests

Beyond the Lens

Beyond photography, my interests span a variety of creative and technical ventures. I’ve channeled my passion for design into creating four print-on-demand brands, including Infinite Hue and Natural Collective, where I showcase unique artwork and designs that resonate with diverse audiences. These brands are an extension of my love for creativity and entrepreneurship, allowing me to explore different styles and connect with people through wearable and functional art.

On the tech side, I’ve developed two practical tools to solve everyday problems. Convert-Case.tools is a text conversion tool that simplifies tasks like switching between uppercase and lowercase or formatting text quickly and efficiently. The other, List-Diff.tools, is a list comparison tool that identifies duplicates, missing items, and mismatches—ideal for streamlining data organization. Additionally, I’m diving into the world of finance with my upcoming blog, Take a Penny, Leave a Penny, where I’ll share insights, tips, and strategies to make personal finance approachable and engaging. These projects reflect my drive to combine creativity with functionality, always looking for ways to make life a little more intelligent and inspiring.

Contact

If you’d like to learn more about my work, explore my interests, or connect over photography, don’t hesitate to reach out. I’m always open to collaborations, opportunities, or a good conversation!

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