Todd Gillette is CTO for onAir Tech, a startup chartered in Virginia building an innovative knowledge sharing platform. Todd is also Chair of onAir Networks, the 501c3 nonprofit overseeing the implementation of the onAir platform for public online networks.

Todd currently serves as a Staff Software Engineer at Northrop Grumman Corporation’s Mission Systems as well as Todd earned his PhD in Neuroscience in 2015 from George Mason University, having researched informatics and data analytics methods applied to neuronal morphology and function. He holds a BS in Engineering and BA in Computer Science from Swarthmore College.

Along with his many years working with software, Todd’s experience includes mission engineering and systems engineering, determining and documenting the key problems to be solved, deriving requirements, architecting and evaluating candidate solutions, and verifying designs and implementations. He has worked with cyber systems and software engineers to address anti-tamper and unintended emissions concerns and to integrate defensive and offensive cyber capabilities.

Todd has also studied and applied artificial intelligence, including machine learning and logical ontology-based techniques. The intersections of AI and biological brains, and how to leverage them to enhance human capabilities in an ethical and human-centered manner, continue to be one of Todd’s primary interests.

Data Scientist & Full Stack Engineer

I am a dedicated Computer Science graduate student specializing in Artificial Intelligence, with 6 months of hands-on experience as a full stack developer.

I’m passionate about translating complex data into actionable insights and developing intelligent systems that solve real-world problems. Currently seeking opportunities in AI engineering and data analytics where I can apply my technical expertise to drive innovation and deliver business value.

Passionate about data innovation, AI applications, and delivering scalable engineering solutions in fast-paced environments. Results-driven Computer Science graduate student at George Mason University with 3+ years of experience as a Data Engineer at NTT DATA Services. Adept at building and optimizing ETL/ELT pipelines using tools like Talend, Snowflake, and AWS to support real-time data processing and cloud migration.

Proven track record in transforming legacy systems, improving billing accuracy, and enabling data-driven decision-making through Power BI dashboards. Skilled in Python, SQL, Apache Spark, AWS Glue, and Kafka, with hands-on DevOps experience deploying CI/CD pipelines using Docker, Kubernetes, and Jenkins.

👋 Hi, I’m Sai Sriram Uppada – a Data Analytics Engineering graduate, AWS Certified Data Engineer, and AI enthusiast who enjoys building end‑to‑end data, ML, and LLM‑powered systems that solve real problems in a scalable way.

I recently completed my Master’s in Data Analytics Engineering at George Mason University (GPA 3.85/4.0), where I focused on data engineering, machine learning, and LLM-based analytics. Over the past few years, through academic projects, research work, and internships, I’ve worked across the full data lifecycle: from ingestion and ETL to modeling, evaluation, and deployment for analytics and intelligent applications. I’m actively seeking full-time and internship opportunities as a Data Engineer, Data Analytics Engineer, or Data Analyst where I can contribute to data platforms, AI-driven products, and cloud-native solutions.

Software Developer @ onAir Tech | AI-Driven Systems | Cloud & Scalable Architectures | MS Computer Science

Software Developer at onAir Tech, building scalable AI-driven and cloud-native systems supporting the onAir platform and affiliated nonprofit networks. Recently earned a Master’s degree in Computer Science from George Mason University, with academic focus on machine learning, distributed systems, and applied data engineering.

Experience includes developing a machine learning-based stock market prediction system using pattern mining techniques, engineering a blockchain-based distributed wallet architecture, and building full-stack applications deployed on AWS cloud infrastructure. Worked across the full software development lifecycle — from requirements analysis and system design to implementation, optimization, and deployment.

Data Scientist | AI/ML & Generative AI | AWS Certified | Building Scalable Predictive & Data-Driven Solutions

AWS Certified Data Engineer with 4+ years of experience designing scalable data pipelines, automating ETL workflows, and delivering cloud native solutions across healthcare, AI, and speech analytics domains.

Built real-time and batch pipelines using AWS (S3, Lambda, RDS, EC2),  Python, SQL, and Spark—reducing processing latency by 25%, cutting manual effort by 50%, and enhancing data reliability.

Developed Power  BI dashboards and optimized SQL/Oracle queries for 1M+ records, improving analytics speed and operational insights.

Software Engineer with 2 years of experience specializing in backend development for fintech applications. Expertise in designing and  delivering RESTful services with Java and Python, optimizing performance, and maintaining large codebases on AWS and Kubernetes.

Proven track record of modernizing legacy platforms, improving reliability, and collaborating across teams to deliver scalable solutions.

I am a Computer Science graduate student at George Mason University with a strong focus on building reliable, scalable, and cloud-ready software systems. My experience includes full-stack development, backend engineering, and DevOps workflows, with hands-on work across the complete software development lifecycle from design and implementation to deployment and maintenance.

My technical background includes Java, Python, Spring Boot, Django, RESTful API development, and relational database design. I have experience developing backend services, implementing secure and efficient data models, and integrating frontend frameworks such as Vue.js and React.js to deliver responsive, user-centric applications.

I have also worked extensively with DevOps and cloud technologies, including CI/CD pipeline automation using Jenkins, containerization with Docker, orchestration with Kubernetes, and deploying applications on AWS. These experiences have strengthened my understanding of deployment automation, system scalability, and operational reliability in modern software environments.

I am highly detail-oriented and approach engineering with a strong emphasis on clean code, maintainability, and continuous learning. I am motivated by solving complex problems, improving system efficiency, and applying modern engineering practices to build robust and impactful software solutions.

Chair, onAir Tech Corporation
Curation Director,  onAir Networks
Chair, Future onAir Advisory Board

Interests:  Knowledge Networks, Catalyzing Innovation, Tech Entrepreneurship, Healthy and Sustainable Communities

Pioneer in identifying, developing, and applying new information and communication technologies:

• The first consumer applications of the microprocessor (4bit & LSIs) … for the toy and game industry and for education
• The first internet cafe with online news, games, and computer conferencing
• The first prototype smartphone working with the developers of the Amiga computer, the first graphical computer

My current focus has been on developing the onAir Knowledge Network System, a knowledge sharing software platform with many unique features such as enabling authors to own and share their content across multiple public and custom Hubs.

The 2-minute video  gives an overview of many of the capabilities of the onAir platform and the US onAir network of 50 state hubs and national hub at us.onair.cc.  The nonpartisan nonprofit onAir Networks, a 501c3, oversees the public onAir networks and hubs licensing the onAir software from onAir Tech corporation (formerly AIR Networks, LLC).

Hasini Pulimate ….