I build and evaluate learning systems, from robot policies running on real hardware to the data pipelines that feed them.
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Showing all 17 projects
Scored 92% pick-and-place success and 2.49 cm mean placement error over 50 physical rollouts, by training an Action Chunking Transformer on 50 teleoperated demonstrations and scoring it against a protocol locked before evaluation.
Graduate Research Assistant, SJSU Applied Data Science · Mar 2026 to present
Kept résumé parsing and embedding matching off the request path across 17 containers, by routing them through Kafka and caching profile reads in Redis for 6× faster repeat lookups, with an AI assistant that pauses for human approval.
SJSU DATA 236, Distributed Systems · Spring 2026
Matched models 30 to 50 times its size on a four-class emotion benchmark with a 1.57M-parameter audio-video network trained from scratch, then showed which facial regions and frequency bands drove every prediction.
SJSU deep learning course, team project · Feb to May 2026
Served the same taxi data to dashboards and to live monitoring, by building it twice: a scheduled Airflow, dbt and Snowflake warehouse joined with weather, and a Kafka path that validates trips on arrival and publishes rolling metrics.
Personal project · Nov to Dec 2025
Keeps everything you read on your own machine, with zero external API calls, by running Gemini Nano on-device inside a Chrome MV3 extension paired with a SwiftUI iOS app that tracks focus sessions across both.
Personal project · Jul 2026 to present
Blocks 100% of payment actions until a person approves them, by reading invoice amounts and dates with Llama 3.2 Vision, scoring its own confidence in each field, and gating every write behind a LangGraph human-approval step.
Personal project · Jun 2026
Reached 0.90 F1 flagging suspicious host pairs in 27.1 million Zeek flows, by condensing them into a connection graph with Airflow, dbt and Snowflake, classifying links with a graph neural network, and having Llama 3.3 explain each alert.
SJSU capstone, team project · Feb to May 2026
Reached 0.711 F1 predicting flight delays across 9.5 million U.S. flights, by training a Spark MLlib random forest on 15 monthly BTS files and running it inside a Kafka stream so each incoming flight gets a probability within seconds.
SJSU big data course, team project · Dec 2025
Takes physical robot time out of the iteration loop, by locating the real cube and bowl with ArUco markers from a calibrated overhead camera and mirroring their coordinates into Isaac Sim, so policies train against the real table's layout.
Personal project, built on NVIDIA's Sim-to-Real SO-101 workshop · Aug 2026 to present
Surfaces Wikipedia pages turning contentious in real time, by streaming every English edit through Kafka as it happens and scoring the tone of each edit summary with RoBERTa.
Personal project · Nov 2025
Keeps a full history of every revision to the data, by loading daily stock prices into Snowflake on an Airflow schedule and computing the indicators traders actually use as dbt models with snapshots.
Personal project · Oct to Nov 2025
Took a cancer-recurrence model the whole way to production, by wrapping scikit-learn in a FastAPI service, containerizing it, and redeploying to AWS EC2 automatically on every commit through GitHub Actions.
Personal project · Apr 2025
Detects an API failure, diagnoses a root cause, and acts on it without a human, by wiring FastAPI health probes into a Railtracks LLM agent that tunes its own alert thresholds from prior incidents. Built in five hours at a hackathon.
SJSU Applied Data Science Hackathon 2026 · Mar 2026
Makes articles searchable by meaning rather than exact keywords, by embedding them with Sentence Transformers on an Airflow schedule and serving nearest-neighbour lookups from a Pinecone index.
Personal project · Nov 2025
Reconciled 112 years of California field measurements into one trainable table, by resolving units and station naming that changed repeatedly between 1913 and 2025, then predicting a water-quality score with scikit-learn in Streamlit.
SJSU DATA 245, Machine Learning · Nov to Dec 2025
Let each part of the system fail and recover independently, by rebuilding a Yelp-style application so services communicate through Kafka events instead of calling each other directly.
SJSU DATA 236, Distributed Systems · Spring 2026
Reduced robotics environment setup to one command on macOS and Linux, by packaging ROS 2 Jazzy, Gazebo Harmonic, RViz and TurtleBot3 into a version-pinned Docker Compose stack with a browser desktop that removes X11 failures.
Personal project · Mar 2026
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Filtering above narrows this list. These go further: each track has a page of its own with the positioning, the results, and the parts of my experience that bear on that role, and everything else left out.
Where I learned the internals rather than the API: a GPT-2 and a byte-pair tokenizer written from first principles, attention made measurably faster, a Phi-3 fine-tune, and then the same treatment for vision models and reinforcement learning. Smaller in scope than the work above, but several have live demos you can try in the browser.
| Project | What it does | Links |
|---|---|---|
| GPT-2 from scratch | Built and trained a GPT-2 language model from first principles | CodeLive demo |
| Transformers from scratch | Built the attention mechanism, then made training measurably faster | Code |
| Tokenizers | Byte-pair encoding tokenizer built for Hindi text | CodeLive demo |
| Phi-3 fine-tuning | Fine-tuned Microsoft's Phi-3 model into a chat assistant | CodeLive demo |
| Multimodal AI system | Combined text, image, and audio inputs in one model | Code |
| Project | What it does | Links |
|---|---|---|
| FastSAM segmentation | Fast image segmentation, deployed as a live demo | CodeLive demo |
| Stable Diffusion | Image generation with style-transfer experiments | Code |
| YOLOv9 object detection | Trained an object detector on a custom dataset | Code |
| UNet & variational autoencoders | Image segmentation and generative models, compared across variants | Code |
| Widget Detector | Turns hand-drawn UI sketches into Flutter components | CodeLive demo |
| Grad-CAM explainability | Visualized which pixels a classifier actually used | Code |
| Project | What it does | Links |
|---|---|---|
| Lightning + Hydra template | A reusable training setup for reproducible experiments | Code |
| CNN foundations | Backpropagation, normalization, and augmentation, worked through by hand | Code |
| PPO reinforcement learning | Agent trained to land a spacecraft in simulation | CodeLive demo |
I'm available from December 2026 and open to relocating. Email me and I'll reply within a day.