• Conducting RL/NLP/CV research in the Intelligent Robot Lab under Prof. George Konidaris, focusing on Robot Planning and 6D Pose Estimation/Manipulation

• Built an active learning framework that leverages foundation models to autonomously learn symbolic abstractions of robot skills, enabling zero-shot task planning with PDDL-style operators

• Co-Authored RSS Workshop Paper and submitting expanded manuscript to ICLR in October

Presentation at The Gilbert W. Beebe Symposium

• Conducted Computational Oncology research in the Department of Radiation Oncology under Prof. Igor Shurak

• Developed CAST (Causal Analysis for Survival Trajectories), a novel framework that extends causal survival forests to model the time-varying treatment effects across medical interventions

• Analyzed Radiotherapy Effects on HNSCC Prognosis (Oropharyngeal Cancer) through Causal ML, optimizing models through cross-validation, hyperparameter tuning and simulation BED validation

• Second Author Presenter at the Gilbert W. Beebe Symposium on AI and ML Applications in Radiation Therapy, Medical Diagnostics, and Radiation Occupational Health and Safety

• Developed Generative AI application with automated ingestion, transformation, and querying of operational data using AWS S3, Lambda, Glue, Athena, and OpenSearch

• Built a Retrieval-Augmented Generation (RAG) architecture integrating AWS Bedrock to support natural language queries across structured and unstructured enterprise data

• Designed a secure, containerized CI/CD infrastructure using Docker, Amazon ECS Fargate, CodePipeline, and CloudWatch for reliable deployment, monitoring, and access control

NASA Publication in IEEE WiSEE

My Intern Exit Presentation

• Conducted Antenna Data Science research on Wi-Fi signal propagation for pressurized spacecraft; used ISS signal surveys from Astrobee, NASA's autonomous free-flying robot

• First Author NASA publication in IEEE International Conference; research used for future missions such as the Artemis program, Lunar Gateway, Orbital Reef; publication is first in the field; received $1.5k award from the NASA Rhode Island Space Grant

• Spearheaded Python/Bash/Flux scripts for real-time KPI network monitoring of Lunar Wi-Fi and 3GPP (4G LTE) field testing; fixed issues related to GPS tracking, TCP/UDP/RSSI, GUI systems, and iperf on LattePanda SBCs

• Developed visualization software using InfluxDB, Grafana, and Docker; wrote YAML file to auto-configure JSON dashboards as provisioning text files for version control; wrote design docs & presented to Division Chief - [Received Return Offer to any NASA Space Center]

• Conducted Computational Neuroscience research under Professor Meenakshi Khosla: Built PyTorch-based Deep Neural Network framework for auditory recognition tasks to better understand AI explainability

• Processed 100 GB of raw audio stimuli/data to analyze specific trends and developed Deep Learning algorithms directly with PI

• Unfortunately, I had to leave the lab because of transferring to Brown, but I had a great time, learned a lot, and was able to pass off my project to another student!

Publication in JSR

• Conducted Time Series Machine Learning research under Dr. Yong Zhuang: Created Auto-Regressive Integrated Moving Average (ARIMA) models to forecast river streamflow, a key indicator of flooding

• Analyzed Ganges River dataset measured in Q (m3/s) discharge volume. Plotted streamflow Log Volume using ADF tests and KL Divergence and accounted for seasonality. Found ARIMA parameters (p, d, q)

• First Author publication in Journal of Student Research (peer-reviewed and open-access)