Postwise
GitHub ↗A privacy focused email agent that runs entirely on device: it categorizes Gmail, answers questions about your inbox, and drafts replies that only send after approval.
(Python, Ollama, Next.js, Gmail API, 2026)
Hi, I'm Dhruv, a Computer Science and Electrical & Computer Engineering student at Cornell. I care about efficiency, in models, in code, and in the machines they run on. I enjoy working across robotics, AI/ML, and GPU/low-level programming. In my off hours, you'll find me watching and playing soccer, ping pong, pickleball, exploring new restaurants, and reading.
Built Python and SQL pipelines that turn unstructured documents into structured, queryable data, combining rule based parsing with an LLM fallback.
Modeled human motion as time series data and benchmarked vision language models, self supervised backbones, and temporal segmentation methods to localize events without labeled data.
Built U-Net and Vision Transformer models in Python to segment organoid microscopy images, reaching 89% IoU and cutting manual analysis time by 75%.
Built vision inference and data logging tools in Python and C++ that helped lab scientists classify nematode species in the field.
A privacy focused email agent that runs entirely on device: it categorizes Gmail, answers questions about your inbox, and drafts replies that only send after approval.
(Python, Ollama, Next.js, Gmail API, 2026)
A study of covert communication between AI agents: a sender hides payloads in ordinary text using acrostic, codebook, and parity schemes while a monitor tries to catch it. The channel lands payloads undetected over 80% of the time.
(Python, Hugging Face Transformers, Qwen2.5, 2026)
A control tower for Claude Code: preflight token checks, a stall watcher, and landing reports that check claimed changes against what actually ran. Fully local.
(Node.js, CLI, lifecycle hooks, 2026)
Reconstructs 3D soccer ball trajectories from single camera broadcast footage: calibrates the camera from pitch geometry, tracks the ball, then fits drag and Magnus force physics models to resolve depth.
(Python, computer vision, physics modeling, 2025)
80 tiny neural nets evolve to clear obstacles, live on this page: no ML frameworks, no training data. Watch them learn below.
(TypeScript, canvas, neuroevolution, 2026)
A benchmark of CNNs, boosting, and multiplicative weight update ensembles for MRI brain tumor diagnosis, reaching 96% accuracy across datasets. Published in the Journal of Student Research.
(TensorFlow, Keras, 2023)