Passionate about AI/ML and building scalable systems
I'm a Master's student in Computer Science at UC San Diego (GPA: 4.0/4.0), currently working as an AI/ML Engineer Intern at Good AI. With experience at Deutsche Bank and J.P. Morgan, I specialize in building intelligent systems, distributed architectures, and scalable backend solutions. My research focuses on transformer-based models for cancer genomics and multimodal learning for biological pathway prediction.
GPA: 4.0/4.0
Relevant Coursework: Network Systems, Algorithm Design and Analysis, Probabilistic Reasoning & Learning, Statistical NLP, Recommender Systems, Machine Learning Theory, Machine Learning with Few Labels, Fair & Transparent ML
GPA: 3.93/4.0
Relevant Coursework: Data Structures and Algorithms, Discrete Structures, Operating Systems, Database Management Systems, Machine Learning, Artificial Intelligence, Software Engineering
From FinTech giants to AI startups
AI/ML Engineer Intern
Jul 2025 – Present
Senior Analyst
Jul 2022 – Aug 2024
FinTech Intern
Jan 2021 – Jun 2021
Advancing AI in healthcare and bioinformatics
Cancer Genomics
May 2025 – Present
Drug Discovery
Sep 2024 – Apr 2025
Accessibility Research
Jan 2023 - Jul 2023
Showcasing technical expertise across various domains
Engineered a distributed, horizontally scalable video storage backend using consistent hashing. Designed custom gRPC-based protocols and built a fault-tolerant content service supporting dynamic node addition/removal with zero data loss.
Developed a binary classification model using RandomForestClassifier to predict COVID-19 severity from mass spectrometry data. Applied supervised feature selection on 100k+ peptide features, outperforming published benchmarks.
Built a vision-language-based navigation pipeline in UE5 simulation. Integrated GPT-4o-mini as a zero-shot waypoint planner with pixel-to-world coordinate transformations and closed-loop control for realistic navigation.
Developed an inclusive Hindi-English MT model combining data augmentation and adversarial learning to mitigate gender bias. Integrated Gradient Reversal Layer (GRL) in PyTorch for adversarial learning.
Designed and implemented three strategies to sink randomly placed ships on an N×N board. Developed a Seek-Sink algorithm using checkerboard-style probing and BFS expansion to minimize moves.
Built a responsive web app with integrated chatbot for tracking personal finances. Developed intelligent expense categorization using NLP with neural networks trained on GloVe vectors and LSTM-based RNN for dialog flow.
Collaborated to develop an interactive website deployed on Heroku for sharing interview experiences. Employed Postgres database with Django framework and implemented content validation requiring admin approval.
Led a project focused on digitizing handwritten words for electronic search and editing. Utilized hybrid CNN-RNN architecture trained on IAM dataset, producing CTC outputs for sequence-related challenges.
Comprehensive expertise across the tech stack
Blogs and articles I find insightful
Distill is dedicated to clear explanations of machine learning research. Features interactive visualizations and in-depth explorations of neural networks, transformers, and feature visualization.
AI Research VisualizationComprehensive blog by OpenAI's VP of Research & Safety covering cutting-edge topics in AI including attention mechanisms, prompt engineering, RLHF, and diffusion models with clear mathematical explanations.
NLP LLMs RLChristopher Olah's highly visual explanations of neural networks, including LSTMs, CNNs, and neural network visualization. Known for making complex concepts accessible through intuitive diagrams.
Deep Learning VisualizationInsights from former Tesla AI Director and OpenAI founding member. Covers practical aspects of training neural networks, computer vision, and the philosophy of building AI systems.
Computer Vision Neural NetworksOfficial blog featuring the latest research and product developments from Google AI. Covers topics from transformers and LLMs to healthcare applications and responsible AI.
AI Research IndustryAndrew Ng's weekly newsletter covering AI news, research breakthroughs, career advice, and practical insights. A great way to stay updated on the rapidly evolving AI landscape.
AI News CareerResearch blog from Carnegie Mellon University's Machine Learning Department. Features cutting-edge research in deep learning, NLP, computer vision, and fairness in ML.
Academic Research Fair MLDeep dives into Natural Language Processing research, transfer learning, and multilingual models. Known for comprehensive surveys and clear explanations of NLP advancements.
NLP Transfer LearningDaily summaries of interesting and influential computer science papers. Covers distributed systems, databases, machine learning, and software engineering research.
Systems Research PapersPractical guides on ML engineering, experiment tracking, model deployment, and MLOps best practices. Great resource for production machine learning.
MLOps EngineeringContinuous learning and skill development
Giving back and empowering others
