Tushar Sandhan
Indian Institute of Technology Kanpur, Samsung Electronics, Seoul National University, Indian Institute of Technology Guwahati
About
Dr. Tushar Sandhan received B.Tech degree in Electronics & Communication Engineering from IIT Guwahati. He was recipient of the GSP-SNU scholarship & complete funding for postgraduate research program, through which he received MS degree and best MS thesis award in Electrical and Computer Engineering from Seoul National University, South Korea. Thereafter his Ph.D. thesis, “Constrained Optimization for Translucent Hindrance Removal from a Single Image”, was awarded the distinguished dissertation award from the Seoul National University, South Korea. Before joining IIT Kanpur, he was working at advanced research lab, multimedia R&D, Samsung Electronics HQ, South Korea for 5 years. He was recipient of IEI Young Engineers Award 2023, INAE Young Associate 2024 and inventor of more than 60 patents. He is currently working as an assistant professor in the Department of Electrical Engineering at IIT Kanpur and his research interests include computer vision and machine learning.
Employment
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Indian Institute of Technology Kanpur Asst Professor2022 - Present
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Samsung Electronics Senior Engineer2014 - 2022
Education
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Seoul National University PhD2014 - 2018
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Seoul National University MS2012 - 2014
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Indian Institute of Technology Guwahati BTech2008 - 2012
Projects & Funding
Projects & funding information is unavailable.
Publications (8)
- Complex AFNet: A Hybrid Complex-Valued Deep Network for Atrial Fibrillation Detection Save
- Bin-Picking With Category-Agnostic Segmentation for Unreliable Depth Scenarios Save
- NeuralPathLite: Fast and Robust Diffusion-Based Path Planning for Autonomous Navigation Save
- MalaNet: A Small World Inspired Neural Network for Automated Malaria Diagnosis Save
- A cyber-physical system based unmanned ground vehicles for safety inspection and rescue support in an underground mine Save
- Binary Classification of Laryngeal Images Utilising ResNet-50 CNN Architecture Save
- ENADL: Towards Performance Improvement of IoT Networks Using Deep Learning-Based Node Fault Prediction Save
- Scalable and Time-Efficient Bin-Picking for Unknown Objects in Dense Clutter Save