Adarsh Kumar Kosta
Engineering · Purdue University West Lafayette
Publications
37
Citations
491
Est. group size
~4
Recurring co-author estimate
Active years
11
Publishing since 2015
Adarsh Kumar Kosta works on neuromorphic computing, which involves designing brain-inspired chips and algorithms (such as spiking neural networks) that process information more efficiently than conventional hardware. Much of the recent work applies these ideas to robotics and autonomous systems, including event-based cameras for vision, navigation, and object tracking, as well as new hardware architectures for AI processing. The research spans from low-level hardware design to algorithms and real-world robotic demonstrations.
Publication output has grown notably over the past decade, rising from little to no output before 2020 to a steady, higher rate of 5-8 publications per year since 2022.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Neuromorphic computing for robotic vision: algorithms to hardware advances
Communications Engineering · 2025
- Breaking the memory wall: next-generation artificial intelligence hardware
Frontiers in Science · 2025
- Intelligent Sensing-to-Action for Robust Autonomy at the Edge: Opportunities and Challenges
2025
- TOFFE -- Temporally-binned Object Flow from Events for High-speed and Energy-Efficient Object Detection and Tracking
arXiv (Cornell University) · 2025
- Intelligent Sensing-to-Action for Robust Autonomy at the Edge: Opportunities and Challenges
arXiv (Cornell University) · 2025
- SHIRE: Enhancing Sample Efficiency using Human Intuition in REinforcement Learning
2025
- Real-Time Neuromorphic Navigation: Guiding Physical Robots with Event-Based Sensing and Task-Specific Reconfigurable Autonomy Stack
arXiv (Cornell University) · 2025
- Wired for the Future: How AI Hardware is Changing the Tech World
Frontiers for Young Minds · 2025
- Best of Both Worlds: Hybrid SNN-ANN Architecture for Event-based Optical Flow Estimation
2024
- FEDORA: A Flying Event Dataset fOr Reactive behAvior
2024
- SHIRE: Enhancing Sample Efficiency using Human Intuition in REinforcement Learning
arXiv (Cornell University) · 2024
- Unlocking the Potential of Spiking Neural Networks: Understanding the What, Why, and Where
IEEE Transactions on Cognitive and Developmental Systems · 2023
- Adaptive-SpikeNet: Event-based Optical Flow Estimation using Spiking Neural Networks with Learnable Neuronal Dynamics
2023
- Best of Both Worlds: Hybrid SNN-ANN Architecture for Event-based Optical Flow Estimation
arXiv (Cornell University) · 2023
- Lightning Talk: A Perspective on Neuromorphic Computing
2023
- arXiv (Cornell University)×12
- IEEE Journal on Emerging and Selected Topics in Circuits and Systems×2
- 2022 International Conference on Robotics and Automation (ICRA)×2
- ACM Computing Surveys×1
- Communications Engineering×1
- Chankyu Lee
Engineering · Purdue University West Lafayette
- Wachirawit Ponghiran
Engineering · Purdue University West Lafayette
- Chamika Liyanagedera
Engineering · Purdue University West Lafayette
- Indranil Chakraborty
Engineering · Purdue University West Lafayette
- Utkarsh Saxena
Engineering · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
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