- Enhanced the data usability by using Generative AI (AWS Bedrock/Sagemaker) to convert unstructured free text data into structured formats, enabling data analysis, feature engineering and predictive modeling. - Developed various statistical models (Regression/Clustering) and fine tuned LLM model responses, leading to improved data-driven decision-making.- Worked in a small team of just two data scientists, with diverse responsibilities. Collaborated with business stakeholders, data engineers, data vendors, and consultants to execute end-to-end data science projects, from understanding business problems to deploying models.

- Researcher in Prof. Kristin A. Persson's Group at the DoE Lawerence Berkeley National Lab and UC Berkeley. - Funded by the National Department of Defense Fellowship (NDSEG). - Designed & published first ever Python based graph algorithm that automates the identification of highly probable chemical reactions from millions of potential reactions which otherwise takes researchers 10+ years to pinpoint manually. Largest network to be ever published in a peer-reviewed journal.- Contributed to opensource quantum calculation workflow packages and published a rich molecular dataset on http://materialsproject.org/ for machine learning.- Managed government funded HPC project proposals, resource allocation, and training for scientists.

As a researcher in Prof. Seok-Woo Lee's lab:- Measured temperature-dependent strength of single crystal metals using spherical nano indentation.- Published in Scripta and Nature CommunicationAs a University Scholar: - University Scholar is the highest academic honor that the University of Connecticut bestows upon an undergraduate student at graduation. Only 3 engineering students selected out of the entire University. - Completed Masters-level research while taking academically rigorous courses.As a researcher in Prof. Avinash Dongara's lab:- Investigated melting mechanics of silicon nanoparticles using molecular dynamics.- Studied 2D layered materials using DFT and machine learning for Li/Na ion batteries.- Won first place at the UConn Senior Design capstone presentation for the work DFT + ML-based work.

Teaching Assistant for core MSE classes:MSE 2053: Materials Characterization and Processing LaboratoryMSE 3004: Mechanical Behavior of MaterialsMSE 3055: Materials Processing and Microstructures Laboratory- Trained, instructed, and supervised 45+ second year students in the materials characterization and processing laboratory with 6+ hours of active student interactions weekly

- Fine-tuned parameters of deep learning models on microscopic metal images for its property prediction.- Performed regression tests on various neural network models to understand model requirements.- Implemented ImageJ’s random forest algorithm to automate image classification for titanium alloys.- Supported nickel super alloys processing project through characterization and metallography.

- In the Big Data & Analytics team as part of the Technology Early Career Development Program (TECDP).- Built compliance and alerting dashboard using Looker for continuous workflow performance monitoring.- Conceived unit tests to check key functionalities of major software in the Big Data system.- Developed Python-based quality assurance tool for data validation on 30k+ tables in the database.- Teamed up with other interns to develop and pitch a primary care provider selection app targeted at millennials.- Worked in an agile environment and regularly presented findings & demos to the users and the leadership.