Neha Angadi

- Organized the AI and Education Forum: Reimagining Teaching and Learning in the Age of AI - Co-Lead for the AI, Education, and the Future Town Hall series - Turning Data into Direction: Shaping Careers in Data Science - Data Science Day 2025: Data Science Institute flagship event - iCubed (Institute, Industry, Innovation) seminars: Recurring sessions with industry experts and working professionals in Data Science - Data Science Career Fair - Panel discussions with academic experts over the latest real-life growth in technology across diverse domains and the corresponding effects of the technological advancements - Computer Science Research Fair - AI & Society Catalyst Seminar Series - Columbia University AI Summit; DSI Program Partner for the workshop "The Columbia Class of 2035: Will We Need To Reinvent Higher Education?" - AI for Sciences & Engineering Workshop with the Computing Systems Research Center

- Engineered and trained GNN-based RL models in PyTorch on Protobuf-encoded control streams to predict next-state drone/UAV maneuvers, improving autonomous target-tracking stability and reducing target-loss events by 30% in obstacle-dense environments. - Designed PPO algorithms with visibility-driven reward shaping, accelerating policy convergence by 25% and delivering more stable, reliable control behavior compared to non-ML baselines. - Integrated the ML pipeline into the RapidEdge™ Mission System via Git-orchestrated simulation to hardware-in-the-loop deployment, enabling real-time autonomous agent inference and coordinated behavior across a fleet of networked UAVs. - Validated system performance through simulation and live-flight drone tests, showing 40% higher target-visibility retention and smoother control responses compared to traditional GNC methods.

- Software and Data Engineer in the Data Analytics squad. - Optimized Kafka operation modules and retention policies by fine-tuning partitioning and consumer lag metrics, reducing redundant utilization and improving cluster usage efficiency. - Developed FastAPI microservices to bridge Snowflake-based data lake with internal reporting portal, reducing reporting latency through asynchronous query execution. - Automated ETL pipelines across five hybrid data sources into Snowflake using Python and task orchestration workflows, enabling consistent audit and resource-usage analytics. - Implemented monitoring dashboards using SQL on the reporting portal to visualize data and trends in tabular form, enhancing early detection for data integrity issues.

TAP (Technology Analyst Program) grad 2023 - Developed modular functions to query Confluent Cloud APIs for cluster data and metadata, powering the Kafka self-service tool used for real-time visibility and management. - Modernized automation infrastructure by migrating legacy Bash scripts to modular Python, introducing parameterized job execution and error handling, which enhanced scalability and code maintainability. - Developed Python-based API scripts to enable audit logging and log-driven health checks across Kafka clusters, improving monitoring accuracy, error handling, and operational reliability.

- Worked on improving campus placement experience. - Bridged the gap between campus and corporate.

- Data and Analytics Intern - Developed event-driven Python workflows to consume Kafka messages, perform schema validation, and store data in Snowflake for analytics and auditing. - Developed interactive SQL-based dashboards for an internal reporting tool to tabularize archived data and support operational analytics across teams. - Implemented automated quality checks and Kafka cluster health alerts using Prometheus and Grafana, reducing manual debugging time and improving data delivery uptime.

Course : Algorithms for Intelligence Web and Information Retrieval - Created assignments on NLP text preprocessing, inverted index (dictionary, postings list) and positional postings list (included introduction to kaggle) - Prepared relevant study material and reference links for the assignments - Prepared the course material for web ontology

- Cloud intern in the Data Analytics and Platform Development team. - Configured team-specific Snowflake environment by setting up accounts, role hierarchies, and security integrations, ensuring data governance and access control compliance. - Migrated 70% of on-prem datasets to Snowflake and automated onboarding pipelines using Python and SQL, creating a unified data lake for analytics. - Developed a Python-based manifest generation tool to automate Collibra data cataloging, reducing manual effort by 90%.

Courses: 1. Algorithms for Data Science 2. Probability and Statistics for Data Science 3. Exploratory Data Analysis and Visualization with R 4. Applied Machine Learning 5. Data Mining 6. Forecasting: A Real-World Application 7. Statistical Inference and Modelling 8. Robot Learning 9. Big Data Analytics

First Class with Distinction Specialization: Machine Intelligence and Data Science