Applied AI research scientist working on deployable computer vision, multimodal systems, edge AI, urban sensing, and medical robotics.
Summary
- Applied AI research scientist with 8+ years of experience deploying computer vision and multimodal AI systems in real-world, resource-constrained settings where latency and reliability matter.
- I turn modern AI models into practical systems through large-scale data collection and annotation, edge inference, VLM/VLA workflows, synthetic data generation, object detection, trajectory forecasting, and deployable research software.
Selected Contributions
- Fielded AI systems: Leading multimodal perception projects for sensing models intended to scale across 900+ New York City intersections and CS3's three urban testbeds: COSMOS PAWR in New York City, DataCity in New Brunswick, and FAU MobIntel in West Palm Beach.
- Work at leading venues: Recent work in CVPR, ICML, ACM UIST, ACM/IEEE SEC, IEEE INFOCOM, IEEE PerCom, EDM, eLife, and Surgical Endoscopy.
- Publication and systems record: 30+ public publications, preprints, software systems, and datasets spanning urban AI, medical robotics, neuroscience, and education.
- Open-source systems: Built public AI systems including DART and generative-agents with 1,200+ combined GitHub stars.
- Sponsored research: Proposal development, technical reporting, sponsor reviews, and engineering delivery across approximately $30M in institutional research supported by NSF, DARPA, AFOSR, and Con Edison, with additional project support from NVIDIA and EmpireAI.
- Teaching and mentorship: Taught Columbia graduate deep learning courses, mentored Master's and high school researchers, and served as the main engineering instructor for the CS3 Research Experience for Teachers in 2024-2026.
Experience
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2024 - Present Associate Research Scientist
Columbia University, Center for Smart Streetscapes and Civil Engineering & Engineering Mechanics - Lead large-scale applied ML projects for real-time urban perception, multimodal sensing, edge AI, vision-language systems, and medical robotics.
- Created DART, a real-time open-vocabulary detector with TensorRT deployment and 300+ GitHub stars; led UrbanOmniDetect, an oral paper at the CVPR 2026 DriveX Workshop with public code, models, and data.
- Published and released public work on adaptive data collection, distributed VLMs, real-time edge analytics, security for edge and cloud systems, and medical robotics foundation model datasets.
- Designed and led the engineering curriculum for the CS3 Research Experience for Teachers in 2024, 2025, and 2026.
- Contributed technical plans and engineering work supporting research awards from NVIDIA and EmpireAI and challenge recognition from INRIX x MetroLab.
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2022 - 2024 Postdoctoral Research Scientist
Columbia University, Electrical Engineering - Built computer vision systems and digital twins for urban intersections, including object detection, multi-object tracking, trajectory forecasting, and safety warning workflows.
- Applied computer vision to robotic surgery and endoscopy training with Northwell Health collaborators, yielding journal publications and conference presentations.
- Mentored 11 Master's students across deep learning, computer vision, and applied AI research projects.
- Received the Columbia University Electrical Engineering Distinguished Teaching Award and a National Postdoc Appreciation Week Excellence Award.
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2023 Lecturer in Deep Learning
Columbia University - Designed and taught Neural Networks & Deep Learning and Advanced Deep Learning to 123 students, covering computer vision, transformers, diffusion models, and modern generative AI.
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2017 - 2022 Ph.D. Researcher
Columbia University - Built FlyBrainLab from scratch as an early research-oriented AI workbench, combining free-form scientific querying with literature and ontology retrieval, an OrientDB-backed connectome knowledge graph, large-scale executable queries, GPU-accelerated neural simulation, and interactive 3D visualization through a TypeScript/JupyterLab interface.
- Published connectome-scale computational neuroscience work in eLife and Frontiers in Neuroinformatics.
Sponsored Research Contributions
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2022 - Present NSF Engineering Research Center for Smart Streetscapes (CS3)
NSF EEC-2133516 · $26M center award - Coordinate applied AI research, annual reporting, and cross-team demonstrations across a five-institution center; present DART, UrbanOmniDetect, and related systems at annual NSF site visits.
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2021 - Present NSF CPS: Hybrid Twins for Urban Transportation
NSF CNS-2038984 · $1.3M Columbia award - Led engineering delivery, prepared annual technical reports, and presented project reviews to NSF for traffic sensing, prediction, and digital twin systems spanning individual intersections and citywide operations.
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2019 - 2020 DARPA Robust Learning in Brain Circuits of Synthetic Miniature Insects
DARPA HR0011-19-9-0035 · $620K Columbia award - Contributed to proposal development, authored project reports, and conducted grant-supported doctoral research on robust learning and executable brain circuit models.
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2017 - 2021 AFOSR Foundations of Neuroinformation Processing
AFOSR FA9550-16-1-0410 · $1.11M Columbia award - Developed computational systems and models for phase- and spike-based neural information processing, including work underlying the FlyBrainLab platform.
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2017 - 2019 NSF Collaborative Research: The Digital Fly Brain
NSF DBI-1544383 · $795K Columbia award - Engineered connectome data, graph query, simulation, and visualization capabilities for the open-source Fruit Fly Brain Observatory and FlyBrainLab systems.
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2015 - 2016 Con Edison Underground Infrastructure and Public Safety Analytics
Con Edison CU09-1331, Amendments 21-23 - Graduate Researcher: Developed theoretical models, implementations, and data processing pipelines for a Visual Data Capture pilot using thermal imagery, high-resolution photographs, and video of underground electrical structures. The work examined automated hotspot detection, inspection targeting, and estimation of avoided serious events.
- Extended the analysis system with infrared camera data assimilation, equipment and cable density models, temperature differential extraction along cable lengths, and visual features associated with later failures; delivered project outputs to Con Edison.
- Contributed cost-benefit and portfolio optimization analysis for Con Edison's secondary public safety programs.
Awards and Recognition
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2026 Best Storytelling Runner-Up, MetaMorph AI Award
FLEA, Kedi Kat Studios -
2025 Best Paper Award, ACM/IEEE Symposium on Edge Computing
Real-Time Video Analytics for Urban Safety -
2025 INRIX x MetroLab Challenge Finalist
Transportation and traffic solutions for New York City -
2024 Columbia University Electrical Engineering Distinguished Teaching Award
Columbia University -
2023 Smart Cities North America Awards Winner, Transportation
IDC Government Insights -
2023 National Postdoc Appreciation Week Excellence Award
Columbia University
Selected Publications and Public Systems
- Calibration-Free View-Agnostic Monocular 3D Object Detection for Urban Scenes. CVPR Workshops 2026.
- Worst-Case Attacks in Reactive Edge-Cloud Systems: Expected Latency and SLA Violation. IEEE INFOCOM 2026.
- Digital Eyes on the Road: Using Street Cameras to Verify Traffic Integrity and Detect Sybil Attacks at City Scale. USENIX VehicleSec 2026, to appear.
- Detect Anything in Real Time: From Single-Prompt Segmentation to Multi-Class Detection. DART, arXiv 2026. Public code and models.
- Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics. arXiv 2026.
- Harnessing Floating Car Data, Traffic Camera Observations, and Network Flow Analysis for Traffic Volume Estimation. arXiv 2026.
- Real-Time Video Analytics for Urban Safety: Deployment over Edge and End Devices. ACM/IEEE SEC 2025, Best Paper Award.
- Boundless. Unreal Engine 5-based photorealistic synthetic data generation for object detection in urban streetscapes, arXiv 2024.
- Constellation Dataset. High-altitude urban object detection benchmark with 13K images, arXiv 2024.
- Adaptive Data Collection for Robust Learning Across Multiple Distributions. ICML 2025.
- Distributed VLMs: Efficient Vision-Language Processing through Cloud-Edge Collaboration. IEEE PerCom Workshops 2025.
- StreetNav: Leveraging Street Cameras to Support Precise Outdoor Navigation for Blind Pedestrians. ACM UIST 2024.
- FlyBrainLab: Accelerating the Discovery of the Functional Logic of the Drosophila Brain. eLife 2021.
Technical Skills
AI and Machine Learning
- Computer vision
- Object detection, segmentation, tracking, monocular 3D detection, video analytics
- Generative and multimodal AI
- VLMs, VLAs, diffusion models, world models, RAG, agents
- Data-centric AI
- Large-scale collection, annotation, synthetic data, benchmarks, adaptive sampling
- Knowledge and graph systems
- Ontology-backed retrieval, OrientDB/NeuroArch graph databases, large-scale graph querying
Systems and Deployment
- Edge inference
- TensorRT, ONNX, WebGPU, NVIDIA Jetson, edge and cloud collaboration, low-latency pipelines
- Frameworks
- PyTorch, JAX, TensorFlow, Hugging Face, CUDA
- Languages
- Python, C/C++, CUDA, TypeScript, JavaScript, SQL
Product and Communication
- Technical leadership
- Cross-institution projects, mentoring, curriculum design, public demos
- Design and media
- Unreal Engine, photorealistic synthetic data, visual storytelling, Figma, Photoshop, Illustrator, InDesign, Premiere
Education
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2022 Ph.D. in Electrical Engineering
Columbia University, New York, USA - Research area: Systems Biology and Neuroengineering
- GPA: 4.10/4.33
- Herbert French Fellowship; Helmsley Fellowship for the Cold Spring Harbor Laboratory Drosophila Neurobiology course
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2016 M.Sc. in Computer Science
Columbia University, New York, USA - Machine learning and thesis track
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2015 B.Sc. in Electronics and Communication Engineering
Istanbul Technical University, Istanbul, Turkey
Leadership and Teaching
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2024 - 2026 Main Engineering Instructor, Research Experience for Teachers
Center for Smart Streetscapes - Designed and led the core engineering curriculum for three annual cohorts, covering neural networks, model evaluation, computer vision, annotation, YOLO training, object tracking, generative AI, and edge deployment.
- Supported K-12 educators in developing reproducible, classroom-ready lesson plans that connect AI engineering to science, mathematics, civics, and career education.
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2024 - 2025 Co-Chair, CS3 Student Leadership Council
Center for Smart Streetscapes -
2023 Lecturer, ECBM E4040 Neural Networks and Deep Learning
Columbia University -
2023 Lecturer, EECS E6691 Advanced Deep Learning
Columbia University
Selected Presentations
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May 2026 Center for Smart Streetscapes NSF Annual Site Visit
DART, UrbanOmniDetect, and applied AI system demonstrations -
Feb 2026 From Sensors to Systems: Real-Time Traffic Analysis for Faster Decision-Making
CS3 Innovation Summit, Columbia University -
Jan 2026 Port Authority Tomorrow Summit Workshop
Port Authority of New York and New Jersey, World Trade Center -
Nov 2025 Evaluating Micromobility & Dangerous Riding Behaviors
Eighth Annual Vision Zero Research on the Road, New York City -
Nov 2020 FlyBrainLab - An Interactive Open Computing Platform
PyData Global
Professional Service
- Conference reviewing: CVPR 2026, ICML 2026, ICMLA 2026, WACV 2025, and ACM MobiCom 2024.
- Journal reviewing: IEEE/ACM Transactions on Networking, IEEE Transactions on Very Large Scale Integration Systems, Sensors (MDPI), Electronics (MDPI), and Smart Cities (MDPI).