Interested in the full stack of machine learning — from the systems and infrastructure that run models at scale, to the research and training that makes those models better.
I want to work at the boundary where algorithms meet hardware constraints, where a smarter scheduler or a better architecture can make the difference. Whether that's optimizing inference pipelines, building distributed training systems, or pushing model quality through better fine-tuning — that's the work I'm drawn to.
I'm a Computer Science Honors student at Stony Brook University with a deep passion for Artificial Intelligence and Machine Learning.
My journey over the last two years has been a rapid cycle of learning, building, and adapting. I thrive in environments where I can dive headfirst into challenges and take ownership from start to finish.
At Mailgator.AI, I built a complete CI pipeline from scratch, accelerating QA runtimes by 26×. At Stony Brook's LUNR AI Lab, I optimized research pipelines and fine-tuned CodeLlama-7B, improving RAG accuracy and achieving 73.5% faster benchmark runtimes.
What drives me isn't just technical skill—it's a relentless work ethic and genuine curiosity. When frustrated with generic phone notifications, I taught myself Kotlin and built NotiSentry, an AI-powered notification filter. This scrappy, problem-solving approach defines how I tackle challenges.
I'm looking for opportunities where I can contribute to a larger vision, learn from talented teams, and apply my "builder, owner, partner" mindset to real-world problems. Let's connect!
| Skills• Programming Languages: MIPS, Python, Java, C, Kotlin (for Android Jetpack Compose), OCaml, JavaScript, HTML/CSS, Matlab.
• Frameworks & Libraries: TensorFlow, LangChain, HuggingFace, OpenCV, Pandas, NumPy, Flask, Bootstrap
• Developer Tools & Platforms: Docker, AWS, Git, GitHub, Linux/Unix, HPC Clusters (Slurm), MySQL, SQLite3
| Education• Degree: BSc Computer Science, Specializing in AI and ML
• University: Stony Brook University, New York, USA
• CGPA: 3.9
• Honors: SUNY SOAR Research Fellow, URECA Fellow, Computer Science Honors, University Scholars, Dean's List 2023 - 2026
• Awards: Academic Achievement Award, YouAreWelcomeHere Award, Global Excellence Award
• Relevant Coursework: Object-Oriented Programming, Data Structures, System Fundamentals, Linear Algebra, Probability and Statistics, Discrete Math, Calculus I & II
| Hobbies• Photography: I love taking photographs of landscape, nature and the nightsky. Check out some of the pictures I have taken on my Instagram!
• Sailing: I recently started sailing with the Stony Brook University's Sailing Club and I am a huge fan now. I absolutely love sailing!
• Sketching: I recently bought a new iPad Air and I have been learning how to sketch on it. So far... I'd say for someone who has never touched a sketch pen before, I am doing pretty decent.
• Video Games: When I am not taking photographs and editing them, not sailing or sketching then I am probably playing video games. It is one of my favourite indoor passtimes.
Bank of Montreal (BMO) | Berkeley Heights, NJ
• Incoming software engineering internship focused on AI infrastructure and machine learning systems.
Reliable Systems Lab | Stony Brook University, NY
• Engineering a lightweight encoder-only attention architecture for multi-agent systems, leveraging permutation equivariance to process jagged input arrays and eliminate data sorting overhead.
• Improving UAV Agent target seeking efficiency by 34.6% by architecting a Curriculum Weight Tuning API using CMA-ES through a grouped parameter strategy.
• Enabling 100% collision-free horizontal scaling on the SeaWulf HPC cluster by building a distributed isolation framework using dynamic sandboxing to eliminate MATLAB/MEX race conditions.
Mailgator | Palo Alto, CA (Hybrid)
• Accelerating QA runtimes by 26×, enabling controlled testing across 700+ cases, by engineering and deploying a RESTful mock server (FastAPI) with full CRUD support on AWS EC2.
• Increasing data accuracy and system reliability by resolving critical parsing bugs, enhancing OpenAI prompts for data extraction and ensuring comprehensive handling of sender-recipient edge cases.
• Developing LLM systems for email analysis with a 5-person agile team, building prompt QA and UX test infrastructure for ML backend (FastAPI, Node.js, React, PostgreSQL).
LUNR AI Lab | Stony Brook University, NY
• Improving Coding RAG accuracy by +5.4% (MBPP Eval) and +1.6% (ODEX Eval) by fine-tuning CodeLlama-7B on a custom 460K+ sample dataset in a 4-person team, targeting two ACL 2026 publication.
• Achieving 73.5% faster benchmark runtimes against existing baselines by designing a parallelized RAG benchmark system using vLLM and multiple commercial APIs.
• Reduced LLM inference costs by up to 100% by integrating SQLite3 caching system into the model distillation pipeline.
Humanity Unleashed (humun.org) | Remote
Volunteered at Humanity Unleashed, a self-funded volunteer-only research organization and contributed in the following ways:
• Built pipelines processing 700k rows of economic data, publishing 5 datasets to HuggingFace with 1,400+ downloads.
• Collaborated with 2 other peers to develop a policy generation and summarization pipeline utilizing LangChain to translate complex economic data into nuanced policy explanations.
University Scholars Fellowship | Stony Brook University, NY
• Demonstrated leadership & mentorship skills as a leader for incoming University Scholars students at Stony Brook University.
• Acquired valuable teaching experience as a Teaching Assistant as part of the SCH 275 pre-fellowship program.
• Assisted the University Scholars Director as a Teaching Assistant by bringing my own life experiences and teaching style into the class.
• Designed creative presentations, graphics & videos to make weekly student workshops engaging and fun.
iGEM, Stony Brook University | Stony Brook, NY
• Achieved 90% retrieval accuracy on embedded research documents by building a RAG Q&A chatbot using Transformers and LangChain, improving research wiki UX.
• Helped secure over $50K in funding by leading a 3-person team to develop a research wiki (Flask) that attracted 15+ stakeholders.
Faculty Student Association at Stony Brook University | Stony Brook University, NY
• Developed and maintained databases using MySQL and Google Sheets, automated processes by building Google AppScript algorithms like Binary Sort and Search, improving automation and work efficiency.
• Inventoried, performed maintenance and resolved issues in over 400 systems across the university campus.
• Installed and configured computer hardware & software, including Windows and Linux operating systems, in 40+ systems.
Omniscience Corporation, Palo Alto, CA | Remote
• Created a life insurance flask WebApp with 3000+ lines of code using HTML, CSS, JavaScript, Jinja, MySQL and Bootstrap Library.
• Containerized the application using Docker and deployed it on Amazon Web Services to ensure a reliable & scalable environment.
• Improved accessibility using Bootstrap HTML Framework, prioritizing user experience and effective communication.
Highlighting my most impactful work in AI, systems programming, and full-stack development
Engineered a high-performance C fuzzer utilizing Unix signals and syscalls (fork, waitpid) to stress-test executables via mutated input streams, achieving 100% process isolation and automated memory leak detection.
Built a local-first, AI-powered command-tracking system (FastAPI, ReactJS, MongoDB) that streams shell activity (<1s latency), performs PII scrubbing, and semantically indexes commands for natural language search and automatic project-based organization.
GitHub Project DevpostOptimizing system performance to <1% battery drain over 5 hours and achieving 1.3s worst-case latency for an intelligent notification filtering and summarization app to minimize user distractions and improve focus using Firebase Gemini API and Jetpack Compose.
Refactored research implementation of REPLUG to enable LM-Supervised Retrieval (LSR) fine-tuning for code generation tasks by architecting a high-performance training pipeline with a local vLLM server.
GitHub Project (Coming Soon)Implementation of core functions for a Red-Black Tree data structure, written entirely in MIPS assembly language, focusing on low-level memory operations, register conventions, and complex balanced data structures.
GitHub ProjectIn-memory emulation of a Linux-like filesystem written entirely in C, managing core filesystem structures like i-nodes and data blocks, handling memory allocation, and implementing a hierarchical file and directory system from the ground up.
GitHub ProjectMulti-threaded poker server built in Java supporting concurrent client connections, game state management, and real-time gameplay with robust error handling and network communication.
GitHub ProjectImplementation of the single-player puzzle game "Skyscrapers" in C, including both an interactive version and an automatic solver based on logical heuristics.
GitHub ProjectLow-level data manipulation in C, implementing a custom network protocol (AFLENT) and a block cipher for data encryption/decryption with byte and bit-level computations.
GitHub ProjectImage processing program implementing the Sobel operator algorithm to detect edges of objects in images.
GitHub ProjectJava program for comparing text files and checking authorship similarity using cosine similarity algorithms.
GitHub ProjectJava simulation of a social media network using graph data structures to model followers and followings.
GitHub ProjectImage processing program applying box blur algorithm to images, optimized for images under 800x800 pixels.
GitHub ProjectImage filter applying black and white conversion by averaging RGB values of each pixel.
GitHub ProjectJava implementation of the Playfair cipher for encrypting and decrypting text.
GitHub ProjectJava tool for tracking C code blocks and variables initialized/updated within them.
GitHub ProjectJava simulation of a complete hiring system manager for job applicants.
GitHub ProjectC program that validates credit card numbers using the Luhn algorithm.
GitHub ProjectEnabled 100% collision-free horizontal scaling on the SeaWulf HPC cluster using dynamic sandboxing and isolation.
Reliable Systems Lab
Reduced LLM inference costs by up to 100% by architecting an SQLite3 caching layer for model distillation pipelines.
LUNR AI Lab
Accelerated validation latency by 99.9% via a scalable AWS EC2 CI/CD pipeline with asynchronous integrity checks.
Mailgator
Improved Coding RAG accuracy by 5.4% and accelerated runtimes by 73.5% by fine-tuning CodeLlama-7B via LoRA.
LUNR AI Lab