Machine Learning Consultant2019 - PRESENTUrban Complexity Lab, New York University
Technologies: Scikit-learn, PyTorch, Python
- Created low dimensional representation from high dimensional transport data using autoencoders.
- Worked on a non-linear traffic prediction model for the outflow of traffic from JFK.
- Worked on anomaly detection pipelines based on Gaussian mixture models.
Senior Machine Learning Engineer2019 - PRESENTHazen
Technologies: OpenCV, PyTorch, Python
- Worked on vehicle detection and tracked research and development for an automatic traffic violation detection system based on road facing cameras.
- Re-implemented a state-of-the-art solution for vehicle tracking by detection proposed in the paper "Extending IOU Based Multi-Object Tracking by Visual Information."
Computer Vision Intern2018 - 2019Applied Research in Government Operations (ARGO)
Technologies: Python, Microsoft Visio
- Wrote scripts to collect image datasets from open source web resources like OpenStreetMap (OSM) and Google street view.
- Utilized Microsoft custom vision API for data annotation and model training.
- Developed a model used to build a report to analyze the comparative distribution of taxis on roads across Manhattan.
Computer Vision Engineer2016 - 2018Confiz
Technologies: .NET, Python
- Led a team to develop a Computer Vision product that uses the security infrastructure (cameras) in retail stores to provide customer behavior analytics such as footfall, dwell time in different zones, and heat maps.
- Integrated a repeat customer identification system based on FaceNet Siamese embeddings. Improved the accuracy from 60% to 90% by writing a custom temporal tracking layer over the base single shot face detector.
- Worked on a .NET web application for retail store performance management, which involved near real-time integration of heterogeneous data sources and extensive dashboarding.
- Involved in multiple proof of concept solutions, including retail demand forecasting and a product-level price recommendation engine.
Research Assistant2015 - 2017Biomedical Informatics Research Lab, LUMS
Technologies: CUDA, .NET
- Developed a next-generation top-down protein search engine.
- Created parallel versions of several algorithms developing respective CUDA kernels for execution on Nvidia GPUs.