Niluthpol Mithun
Senior Computer Scientist at SRI
Princeton, New Jersey, United States
Summary
👤
Senior🎓
Top SchoolNiluthpol Mithun is a Senior Computer Vision Scientist at SRI International with eight years of experience bridging academic research and applied R&D in computer vision and machine learning. He holds a Ph.D. in Electrical and Computer Engineering from UC Riverside, where he developed video computing and ML expertise that now informs mission-driven projects at SRI’s Center for Vision Technologies. His career combines research roles, multiple SRI senior scientist promotions, and industry engineering experience at Samsung and Bosch, giving him fluency in taking algorithms from prototype to production. Based in Princeton, he is comfortable leading technically complex efforts while mentoring junior researchers and iterating rapidly on experimental systems. Notably, his background spans both signal-processing fundamentals from BUET and contemporary deep learning, enabling practical solutions for challenging perception problems.
8 years of coding experience
13 years of employment as a software developer
Doctor of Philosophy (Ph.D.) in Electrical and Computer Engineering, Computer Vision, Machine Learning, Doctor of Philosophy (Ph.D.) in Electrical and Computer Engineering, Computer Vision, Machine Learning at University of California, RiversideMaster of Science (M. Sc.), Communication and Signal Processing, Master of Science (M. Sc.), Communication and Signal Processing at Bangladesh University of Engineering and Technology
English, Bengali
Github Skills (11)
multimodal8
retrieval8
localization5
robot4
scene-graph2
robotics2
3d-models2
pytorch1
computer-vision1
deep-learning1
3d1
Programming languages (1)
Github contributions (5)
niluthpol/niluthpol.github.io
Jul 2019 - Apr 2024
Contributions:112 pushes, 1 branch in 4 years 9 months
niluthpol/multimodal_vtt
Apr 2018 - Apr 2020
Joint Embedding with Multimodal Cues for Cross-Modal Video-Text Retrieval
Contributions:36 commits, 34 pushes, 1 branch in 1 year 11 months
multimodal
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