CV

Computational Biology Intern - MITRE Corporation

Mclean, Virginia

• Developed automation software to optimize high-throughput training and fine-tuning processes for open-source large language models (LLMs).
• Developed an LLM-driven retrieval augmented generation system to extract and summarize key insights from complex scientific literature, streamlining knowledge access for synthetic biology workflows (Used scientific python, LangChain, LlamaIndex, Kubernetes).
• Developed the BioNet Domain-Specific Language, an open-source programming language designed to enable extensive scaling of synthetic biology experiments and industrial workflows.

Co-Founder, CEO - Omniwear AI

Palo Alto, California

• Led the development of a cutting-edge B2B virtual try-on platform for e-commerce powered by computer vision and generative AI, catering specifically to the D2C retail clothing sector.
• Spearheaded the B2B growth strategy, successfully acquiring early customer brands. Notably, secured partnerships with a retail giant valued at over $1 billion and a retailer valued at around $250 million
• Established and maintained direct communication channels with corporate executives, ensuring seamless collaboration and addressing clients' unique needs and concerns.
• Participated in Launchpad (Stanford’s premier graduate accelerator) Spring ‘23 and Entrepreneur First’s NYC unicorn training program.

M.S. Computer Science - Artificial Intelligence

Stanford University

• Artificial Intelligence: Principles and Techniques
• Translational Bioinformatics
• Computational Biology: Structure and Organization of Biomolecules and Cells

B.S. Bioengineering

Stanford University

• Biochemistry & Molecular Biology
• Physical Biology of Cells
• Systems Physiology and Design
• Fundamentals for Engineering Biology Lab
• Biomedical System Prototyping Lab

CV Image Processing for CT and Ultrasound-based Tumor Detection

• Developed a computer vision pipeline for lung CT scans using Python and OpenCV.
• Achieved high accuracy in tumor segmentation using an Attention U-Net model.
• Implemented K-means clustering for lung tissue classification.

CV Image Processing for Meal Nutritional Analysis

• Developed a computer vision (CV)-based web application that detects and classifies food items from user-uploaded images.
• Trained a ResNet18 convolutional neural network model on a Food image dataset from Kaggle (using Tensorflow).
• Implemented an object detection pipeline to localize and identify food items before classification.
• Built a full-stack web interface using HTML (frontend) and a Python Flask backend to allow users to upload images for real-time food classification.

Computational Analysis of NMDA Receptor Antagonist Binding for Chronic Pain Therapeutics

• Investigated the molecular interactions between NMDA receptor antagonists and their binding sites using molecular docking simulations with SwissDock and AutoDock Vina.
• Designed and optimized docking workflows, refining model parameters to maximize accuracy in predicting ligand-receptor interactions.
• Quantified binding affinities to assess antagonist efficacy, providing computational insights for drug repurposing in chronic pain management.

Custom Heap Allocator (Memory Management & Systems Programming)

• Designed and implemented a custom heap allocator in C, featuring both implicit and explicit free lists for dynamic memory allocation.
• Optimized memory utilization and allocation efficiency by integrating block coalescing, splitting, and best-fit/free-list strategies.
• Implemented a custom malloc, free, realloc, and calloc, improving memory allocation speed and fragmentation handling.

Synthetic Biosensor Development for Pathogen Detection

• Engineered a novel biosensor using SynNotch receptors for Salmonella detection.
• Optimized receptor expression using flow cytometry and Western blotting.
• Utilized PCR, gel electrophoresis, and mammalian cell cultures.