I build intelligent systems end-to-end — right now that means TrafficPulse, a traffic scene-understanding platform, alongside AI/ML and full-stack work that earned a PBL First Place. Typed, testable software that stays honest in production.
Software engineer building intelligent systems — with AI, computer vision, and full-stack technologies as the tools of the trade.
Traffic analytics platform that turns raw video into structured scene understanding, not just detections.
The long-term objective is to move beyond simple object detection by combining scene understanding, traffic semantics, and rule-based reasoning into a production-ready analytics platform.
Traffic footage carries more meaning than a bounding box can express. Detection alone misses the semantics — who is doing what, where, and whether it violates the rules of the road. TrafficPulse targets that gap: turning raw video into scene understanding a human operator would recognize.
Three cooperating layers: perception (detection, segmentation, multi-object tracking), scene modeling (typed relations between actors, lanes, and signals), and a reasoning layer that maps observations onto traffic semantics. Each layer has a stable interface so components can be replaced independently.
The hard parts sit between the layers — stable identity assignment across occlusions, calibrating camera geometry to real-world coordinates, keeping the inference budget honest at streaming rates, and building evaluation that scores scene semantics rather than per-frame accuracy.
Near-term: perception and tracking backbone, a first pass at the scene representation, and a single-camera dashboard for live review. Further out: multi-camera fusion, a rules engine for violation semantics, and a hardened FastAPI service around the pipeline.
Three frames from a longer roll — shipped systems and active builds beyond TrafficPulse, each written up as an engineering case study.
I care more about software that quietly works for years than software that demos well for a week — measuring honestly before optimizing, and building the retrieval, guardrails, and deploy paths around a model that turn it from a demo into a product.
I'm open to internships, research collaborations, and contract work where engineering quality is taken seriously. The best way in is a short note describing what you're building and why.