Software Engineer with BSE + MEng in Electrical & Computer Engineering from Princeton University. Currently building the future of recruiting in the Skilled Trades. I’m strongly drawn towards impact oriented work and research that puts people first. Feel free to connect!
Implemented multi-object tracking for parcels on industrial conveyor belt systems across multiple camera views, reducing manual security checks from 5 minutes per parcel to real-time automation
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Applied fine-tuned YOLO models and developed 3D pose estimation for parcel detection and localization
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Developed data visualizations for parcel detection and tracking performance analysis
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Optimized forward kinematics computations within a proprietary simulator for a curbside delivery robot
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Streamlined the transition to high-performance computing by refactoring and documenting core simulator modules and overcoming key performance bottlenecks
Owned the complete development and deployment of a Retrieval-Augmented Generation (RAG)-based solution, enabling publishers to track and monetize proprietary data in LLM applications, leading to a joint venture with a strategic partner and $100k+ in external investment
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Developed a scalable AI-powered platform that enables research groups and e-commerce businesses to access publisher data on an as-needed basis through tailored AI Agents, reducing data-acquisition costs compared to traditional subscription packages
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Thrived in a fast-paced early-stage startup environment, constantly adapting to rapidly changing requirements, adopting new skills, and independently scoping and defining technical tasks
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Optimized system performance by iterating on open-source LLMs (e.g., LLaMA, Mixtral), embedding models (using transformers and the HuggingFace API), RAG techniques (LangChain), and vector databases (chromadb, ElasticSearch) to improve search accuracy and response time
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Built internal tools, rapidly iterating on Streamlit apps, to test hypotheses and automate dataset creation, reducing manual workload and development time
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Streamlined CI/CD workflows with GitHub Actions and Docker, reducing deployment time and improving system reliability through automated unit and performance testing
