I’m a curious and driven Master’s student at UT Austin, specializing
in Machine Learning and Data Science within Electrical and Computer
Engineering. Currently, I’m machine learning engineer at Synthefy
working on time-series diffusion models. I’m passionate about
reinforcement learning and natural language processing fields where I
get to combine optimization with creative problem-solving to tackle
real-world challenges.
For more information checkout my resume:
Experiences
Synthefy
Machine Learning Engineer | Austin, TX | Sep 2025 – Present
- Architected a foundational Patched Diffusion Transformer with In-Context Learning to synthesize physiological signals.
- Engineered a scalable Hydra-based ETL pipeline unifying 20+ datasets and reduced downstream error by 12% via a TRSTR framework.
AMD
Machine Learning Infrastructure Intern | Austin, TX | May 2025 – Aug 2025
- Built a scalable semantic retrieval pipeline using OpenAI embeddings to match hardware logs via vector similarity.
- Compressed logs by 97% to enable long-context embeddings, improving ETL speed by 45x and automating ingestion workflows.
The University of Texas at Austin
Machine Learning Researcher | Austin, TX | Aug 2023 – May 2025
- Advanced a novel human activity classification model using feature fusion with real-time acoustic and inertial data.
- Adapted a MobileNet V2 architecture via transfer learning and deployed lightweight computer vision models for edge devices.
Cvent
Software Engineer Intern | Tysons Corner, VA | Jun 2024 – Aug 2024
- Designed JavaScript date-time modals with optimized state management using Redux and React Hooks.
- Implemented real-time data visualization with Datadog to monitor GraphQL queries.
FirstParty
Applied Machine Learning Intern | New York, NY | Jun 2023 – Jun 2024
- Built embedding-based similarity pipelines in SageMaker using GPT embeddings and designed an NLP-based classification system achieving 95% accuracy via Levenshtein distance algorithms.
Projects
Here are some of my projects that I have worked on. Feel free to click
on the images or title to learn more.
A trace-driven simulator and characterization suite designed to evaluate dynamic batching strategies for diffusion-based large language models (dLLMs).
A conversational recommender system integrating an LLM with a traditional recommender engine for context-aware recommendations.
An agent-driven approach to semantic segmentation for 2D images and 3D point clouds using reinforcement learning.
An image re-identification application from a clothing dataset
A method to improve text-to-image diffusion models on complex prompts using hindsight experience replay and RL.
Fine-tuned a Llama 2 model to solve complex rational Natural Language Inference (NLI) tasks.
A web application for a Hardware-as-a-Service (HaaS) system.
A web application designed to provide personalized financial
advice and investment strategies based on your current financial
situation and goals.
APL Catalog Management System
A comprehensive library management system enabling clients to check out and return books, movies, and other media.
A high-frequency trading algorithm designed for the Ready Trader Go
competition hosted by Optiver.
A Reinforcement Learning Competition for the UT Machine Learning &
Data Science Club.
A simulation of the online Cat Trap game utilizing C and assembly
languages on a TM4C board.
Get In Touch
Let me know if there are any questions, or comments on my projects or
potential work to collaborate on.
Open to Connect!