TinyML & Neuromorphic Computing for Edge Intelligence

Manan Suri

Prof. Manan Suri leads the Neuromorphic Hardware Research group at IIT-Delhi. Recognized by MIT Technology Review as one of the world’s Top 35 Innovators under 35, he has received numerous awards, including the IEEE EDS Early Career Award and the INAE Young Engineer’s Award. He has filed several patents, authored over 90 publications, delivered 70+ invited talks, and led multiple research projects. He has been a visiting scientist at CNRS, France, and has worked at NXP Semiconductors, Belgium, and CEA-LETI, France. He holds a PhD from INP-Grenoble, France, and Masters/Bachelors from Cornell University, USA.

Gitesh Kulkarni

Gitesh Kulkarni is working as Senior Scientist in TCS research. He is an accomplished designer of embedded systems design and a Maker at heart. He is Master of Science in Electrical engineering from Colorado State University, Fort Collins, Colorado, USA. His research interests are at the cusp of edge computing, computer architectures, and sensing.  In one of pioneering works, he was the lead designer of the first industrial safety watch for TATA sons. Prior to joining TCS, Gitesh created embedded systems and systems products for leading technology companies. When not playing with Linux and soldering gun, he is busy reading novels, comics, and musing about philosophy. He is a licensed Ham radio operator as well.

Ayon Borthakur

Prof. Ayon Borthakur is an Assistant Professor at the Mehta Family School of Data Science and Artificial Intelligence, IIT Guwahati. Previously, he served as an Assistant Professor in the Department of Artificial Intelligence at IIT Hyderabad. Before his academic appointments, Ayon worked at Innatera Nanosystems in the Netherlands as a Senior Neuromorphic Engineer-Machine Learning. At Innatera, he focused on integrating deep learning with analog computing for ultra-low power and latency radar target recognition, leading to multiple patent applications. He completed his Ph.D. at Cornell University, USA, where he researched neuroscience-inspired Artificial Intelligence for learning in the wild, particularly its implementation in neuromorphic chips such as Intel Loihi. His Ph.D. work contributed to an international patent sponsored by Cornell. Ayon earned his Bachelor of Technology in Electrical Engineering from IIT Dhanbad.

Sounak Dey

Sounak Dey is a Senior Scientist at TCS Research, India, and the principal investigator of the Neuromorphic Computing research group. His research focuses on theoretical and algorithmic improvements in spike encoding and learning mechanisms, as well as exploring the applicability of Neuromorphic Computing in various industry use cases. Sounak holds an MCA from Birla Institute of Technology, Mesra, and is currently pursuing his PhD from Jadavpur University, Kolkata. He is a member of IEEE and ACM India, with over 40 international publications and 15+ granted patents across different geographies. Sounak was a tutor on neuromorphic computing at ICASSP 2023 and has been part of the organizing committees of various workshops at other venues.

Utpal Garain

Utpal Garain is a Professor at the Indian Statistical Institute, Kolkata, specializing in deep learning for language, image, and video analysis. He received his B.E. and M.E. in Computer Science and Engineering from Jadavpur University and earned a Ph.D. from the Indian Statistical Institute in 2005. He began his career in the software industry before transitioning to academia. His research spans OCR, handwriting analysis, NLP, and computational forensics, with strong ties to Indian language technologies (TDIL). Prof. Garain has held prestigious fellowships including a postdoctoral stint in France (CNRS), the Indo-US Research Fellowship (IUSSTF, 2011), and the JSPS Invitational Fellowship in Japan (2016). He serves as Associate Editor for IJDAR and chairs IAPR TC-6 on Computational Forensics. He regularly contributes to top conferences like ICPR and ICDAR and reviews for journals including IEEE PAMI and PR. His contributions earned him the INAE Young Engineer Award in 2006.

Shiwei Liu

Shiwei Liu is an incoming Principal Investigator at the ELLIS Institute Tübingen and a Group Leader at the Max Planck Institute for Intelligent Systems. He is currently a Royal Society Newton International Fellow at the University of Oxford and a Junior Research Fellow at Somerville College. Previously, he was a postdoctoral fellow in the VITA group at UT Austin, working with Atlas Wang, funded by IFML. Shiwei earned his Ph.D. in Computer Science from Eindhoven University of Technology (TU/e), the Netherlands, under the supervision of Mykola Pechenizkiy and Decebal Constantin Mocanu.

His research focuses on understanding and harnessing low-dimensional structures in machine learning. This perspective informs efficient training and inference of foundation models, advances reasoning in large language models, and drives the development of hardware-friendly ML algorithms. His work sits at the intersection of theoretical insight and scalable, resource-aware AI design.

Arpan Pal

Dr. Arpan Pal is a Distinguished Chief Scientist and Research Area Head at TCS Research, leading Embedded Devices and Intelligent Systems. With over 30 years of experience, his expertise spans intelligent sensing, signal processing, AI at the edge, and affective computing, with impactful work in Connected Health, Smart Manufacturing, Retail, and Remote Sensing. He has filed over 180 patents (95+ granted globally) and published 160+ papers and book chapters, along with three books on IoT, digital twins, and AI in cardiac screening.

Dr. Pal serves on editorial boards of ACM TECS and Springer’s Journal of Computer Science, and program committees of IEEE Sensors, ICASSP, and EUSIPCO. He advises government bodies like CSIR and MeitY, and academic institutions including IITs and IIITs. A two-time Tata InnoVista innovation awardee, he previously worked at DRDO and Rebeca Technologies. He holds a Ph.D. from Aalborg University and B.Tech/M.Tech from IIT Kharagpur.

Swarnava Dey

Swarnava Dey is a Senior Scientist at TCS Research with over 24 years of industrial research experience in embedded systems, spanning computer vision, sensor analytics, speech processing, and edge AI. He holds an M.Tech from IIT Kharagpur and is currently pursuing a Ph.D. there. At TCS Research, he leads AutoML efforts within the Embedded Devices and Intelligent Systems team, focusing on Neural Architecture Search and model reduction for tinyML applications in health, manufacturing, retail, and remote sensing. Swarnava has filed 80+ patents (35+ granted globally) and published over 40 papers in top-tier venues. He was a winner of IEEE BigData Hackathon (2018) and IJCNN AI Competition (2023), and is Google-certified in ML and Cloud. A regular reviewer for CVPR, ICCV, TPAMI, IJCV, and major AI journals & conferences, he is among the few researchers exploring adversarial and OOD robustness in compact vision models.

Arijit Ukil

Dr. Arijit Ukil (Senior Member, IEEE) has over 22 years of industrial research experience. He is currently serving as a Principal Scientist at TCS Research, Tata Consultancy Services. He previously worked at the Defence Research and Development Organization (DRDO) as Scientist 'C'. He holds a master’s degree in engineering from Jadavpur University, Kolkata. He holds PhD (Cum Laude) from University of Murcia, Spain.

Dr. Ukil’s research spans deep learning, Gen Ai, causal AI, and model optimization. He has authored over 60 publications, four book chapters, and filed 50+ patents, with 40+ patents granted globally across regions including the US, EU, China, and Japan. He actively promotes edge AI, having spoken at the tinyML forum on ECG classification for wearable and implantable devices. He was a keynote speaker at IEEE AINA-2016, panel moderator at CIKM 2020, and serves as Steering Committee Member of HealthyIoT. He served as the general chair in KDAH workshop of ACM CIKM and ICASSP 2024 workshop of Deep Neural Network Model Compression. He delivered tutorials on edge analytics and deep model compression in top conferences like IEEE ICASSP (2024, 2025), ACM SAC (2025).