Adarsh Kumar Kosta

20 papers A* 4A 5Journal 10Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	A	`conf`	Intelligent Sensing-to-Action for Robust Autonomy at the Edge: Opportunities and Challenges. DATE Amit Ranjan Trivedi, Sina Tayebati, Hemant Kumawat, Nastaran Darabi, Divake Kumar, Adarsh Kumar Kosta, Yeshwanth Venkatesha, Dinithi Jayasuriya, Nethmi Jayasinghe, Priyadarshini Panda, Saibal Mukhopadhyay, Kaushik Roy
2025	J	`jnl`	Intelligent Sensing-to-Action for Robust Autonomy at the Edge: Opportunities and Challenges. CoRR Amit Ranjan Trivedi, Sina Tayebati, Hemant Kumawat, Nastaran Darabi, Divake Kumar, Adarsh Kumar Kosta, Yeshwanth Venkatesha, Dinithi Jayasuriya, Nethmi Jayasinghe, Priyadarshini Panda, Saibal Mukhopadhyay, Kaushik Roy
2025	J	`jnl`	TOFFE - Temporally-binned Object Flow from Events for High-speed and Energy-Efficient Object Detection and Tracking. CoRR Adarsh Kumar Kosta, Amogh Joshi, Arjun Roy, Rohan Kumar Manna, Manish Nagaraj, Kaushik Roy
2024	A	`conf`	Best of Both Worlds: Hybrid SNN-ANN Architecture for Event-based Optical Flow Estimation. IROS Shubham Negi, Deepika Sharma, Adarsh Kumar Kosta, Kaushik Roy
2024	J	`jnl`	Hardware/Software Co-Design With ADC-Less In-Memory Computing Hardware for Spiking Neural Networks. IEEE Trans. Emerg. Top. Comput. Marco Paul E. Apolinario, Adarsh Kumar Kosta, Utkarsh Saxena, Kaushik Roy
2024	J	`jnl`	SHIRE: Enhancing Sample Efficiency using Human Intuition in REinforcement Learning. CoRR Amogh Joshi, Adarsh Kumar Kosta, Kaushik Roy
2024	A	`conf`	Unearthing the Potential of Spiking Neural Networks. DATE Sayeed Shafayet Chowdhury, Adarsh Kumar Kosta, Deepika Sharma, Marco Paul E. Apolinario, Kaushik Roy
2024	J	`jnl`	Unlocking the Potential of Spiking Neural Networks: Understanding the What, Why, and Where. IEEE Trans. Cogn. Dev. Syst. Buddhi Wickramasinghe, Sayeed Shafayet Chowdhury, Adarsh Kumar Kosta, Wachirawit Ponghiran, Kaushik Roy
2023	A	`conf`	AcouSkin: Full Surface Contact localization Using Acoustic Waves. IROS Adarsh Kumar Kosta, Alexis Burns, Siddharth Rupavatharam, Caleb Escobedo, Daewon Lee, Richard E. Howard, Larry D. Jackel, Volkan Isler
2023	A*	`conf`	Adaptive-SpikeNet: Event-based Optical Flow Estimation using Spiking Neural Networks with Learnable Neuronal Dynamics. ICRA Adarsh Kumar Kosta, Kaushik Roy
2023	J	`jnl`	Best of Both Worlds: Hybrid SNN-ANN Architecture for Event-based Optical Flow Estimation. CoRR Shubham Negi, Deepika Sharma, Adarsh Kumar Kosta, Kaushik Roy
2023	A*	`conf`	Lightning Talk: A Perspective on Neuromorphic Computing. DAC Deepika Sharma, Adarsh Kumar Kosta, Kaushik Roy
2023	—	`conf`	Live Demonstration: ANN vs SNN vs Hybrid Architectures for Event-based Real-time Gesture Recognition and Optical Flow Estimation. CVPR Workshops Adarsh Kumar Kosta, Marco Paul E. Apolinario, Kaushik Roy
2022	J	`jnl`	Adaptive-SpikeNet: Event-based Optical Flow Estimation using Spiking Neural Networks with Learnable Neuronal Dynamics. CoRR Adarsh Kumar Kosta, Kaushik Roy
2022	A*	`conf`	Fusion-FlowNet: Energy-Efficient Optical Flow Estimation using Sensor Fusion and Deep Fused Spiking-Analog Network Architectures. ICRA Chankyu Lee, Adarsh Kumar Kosta, Kaushik Roy
2022	J	`jnl`	Hardware/Software co-design with ADC-Less In-memory Computing Hardware for Spiking Neural Networks. CoRR Marco Paul E. Apolinario, Adarsh Kumar Kosta, Utkarsh Saxena, Kaushik Roy
2022	A*	`conf`	RAPID-RL: A Reconfigurable Architecture with Preemptive-Exits for Efficient Deep-Reinforcement Learning. ICRA Adarsh Kumar Kosta, Malik Aqeel Anwar, Priyadarshini Panda, Arijit Raychowdhury, Kaushik Roy
2021	A	`conf`	Exploring Spike-Based Learning for Neuromorphic Computing: Prospects and Perspectives. DATE Nitin Rathi, Amogh Agrawal, Chankyu Lee, Adarsh Kumar Kosta, Kaushik Roy
2021	J	`jnl`	Fusion-FlowNet: Energy-Efficient Optical Flow Estimation using Sensor Fusion and Deep Fused Spiking-Analog Network Architectures. CoRR Chankyu Lee, Adarsh Kumar Kosta, Kaushik Roy
2021	J	`jnl`	RAPID-RL: A Reconfigurable Architecture with Preemptive-Exits for Efficient Deep-Reinforcement Learning. CoRR Adarsh Kumar Kosta, Malik Aqeel Anwar, Priyadarshini Panda, Arijit Raychowdhury, Kaushik Roy

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.