Prof. Arindam BASU B. Tech, M. Tech in e & ECE (I.I.T Kharagpur), M.S in Mathematics, PhD in ECE (GaTech)

SMIEEE


Professor


Contact Information Office: G6410YEUNG
Phone: 34426077
Email: arinbasu@cityu.edu.hk
Web: BRAIN Systems Lab


Research Interests Neuromorphic circuits and systems, Brain-machine interface, Spiking Neural Networks and HW Security, Non-volatile memory


Press releases https://www.eurekalert.org/pub_releases/2020-10/ntu-nss101520.php
https://www.eenewseurope.com/news/distributed-ai-helps-robots-recognise-pain-and-self-repair
https://www.thehindu.com/sci-tech/technology/ai-powered-mini-brains-to-help-robots-perceive-pain-self-repair/article32901129.ece
https://www.unite.ai/robots-use-ai-to-feel-pain-and-self-repair/
https://www.eurekalert.org/pub_releases/2016-02/ntu-nns021116.php
https://www.sciencedaily.com/releases/2016/02/16.htm
https://www.theengineer.co.uk/implantable-chip-has-potential-for-parkinsons-and-prosthetic-control/
https://futurism.com/ntu-develops-new-wireless-smart-chip

Media Interviews https://www.youtube.com/watch?v=oau6iXTgqpU


Arindam Basu received the B.Tech and M.Tech degrees in Electronics and Electrical Communication Engineering from the Indian Institute of Technology, Kharagpur in 2005, the M.S. degree in Mathematics and PhD. degree in Electrical Engineering from the Georgia Institute of Technology, Atlanta in 2009 and 2010 respectively. Dr. Basu received the Prime Minister of India Gold Medal in 2005 from I.I.T Kharagpur. He is currently a Professor in City University of Hong Kong in the Department of Electrical Engineering and was a tenured Associate Professor at Nanyang Technological University before this.
He is currently an Associate Editor of IEEE Sensors journal, Frontiers in Neuroscience and IEEE Transactions on Biomedical Circuits and Systems. He has served as IEEE CAS Distinguished Lecturer for 2016-17 period.
Dr. Basu received the best student paper award at Ultrasonics symposium, 2006, best live demonstration at ISCAS 2010 and a finalist position in the best student paper contest at ISCAS 2008. He was awarded MIT Technology Review's inaugural TR35@Singapore award in 2012 for being among the top 12 innovators under the age of 35 in SE Asia, Australia and New Zealand. He is a technical committee member of the IEEE CAS societies of Biomedical Circuits and Systems, Neural Systems and Applications (Chair) and Sensory Systems. His research interests include bio-inspired neuromorphic circuits, non-linear dynamics in neural systems, low power analog IC design and programmable circuits and devices.


Awards and Achievements 2012 “TR35 Asia Pacific” MIT Technology Review. Top 10 innovators under the age of 35 in SE-Asia, Australia and NZ.
2016 “Distinguished Lecturer” IEEE CASS. ~10 experts selected worldwide each year. [Past DL]
2015 “Industry choice award” IEEE Biomedical Circuits and Systems (BioCAS) conference.
2010 “Best Live Demonstration Award” IEEE International Symposium on Circuits and Systems (ISCAS).
2008 “Best Student Paper finalist” IEEE International Symposium on Circuits and Systems (ISCAS).
2006 “Best Student Paper Award” IEEE International Ultrasonics Symposium.
2021 “GT 40 under 40” Georgia Tech Alumni Association. The program, which has been launched since 2020, aims to recognize the achievements of Georgia Institute of Technology alumni who innovated industries and positively impacted communities across the globe while under the age of 40. Forty distinguished honorees are selected each year and Prof Basu is one of the forty honorees in 2021. [URL]



Previous Experience 2016 - 2021, Associate Professor, Nanyang Technological University. School of EEE.
2010 - 2016, Assistant Professor, Nanyang Technological University. School of EEE.



Patents Pankaj Sethi, Chandrasekhar Murapaka, Wen Siang Lew, Arindam Basu , Magnetic random number generator, US Patent No. 10127016 .
Arindam Basu, Enyi Yao, Yi Chen, Systems and methods for classifying electrical signals, US Patent No. 10311375.
P. Hasler and A. Basu, Systems and methods for improved floating-gate transistor programming, US Patent No. 7965559.



Publications Show All Publications Show Prominent Publications
Journal Bose, Sumon. Kumar. , Singla, Deepak. & Basu, Arindam. (2021). A 51.3-TOPS/W, 134.4-GOPS In-Memory Binary Image Filtering in 65-nm CMOS. IEEE Journal of Solid-State Circuits.
Basu, Arindam. , Shah, Nimesh. , Basu, Arindam. , Mathews, Nripan. & et, al. (2021). Halide Perovskite Memristors as Flexible and Reconfigurable Physical Unclonable Functions. Nature Communications.
Acharya, Jyotibdha. & Basu, Arindam. (2020). Deep Neural Network for Respiratory Sound Classification in Wearable Devices Enabled by Transfer Learning. IEEE Trans. on Biomedical Circuits and Systems.
Abraham, Rohit. John. , Acharya, Jyotibdha. , Basu, Arindam. , Mathews, Nripan. & et, al. (2020). Optogenetics-Inspired Light-Driven 2D TMDC Computational Circuits Enable In-Memory Computing for Deep Recurrent Neural Networks. Nature Communications.
Abraham, Rohit. John. , Tiwari, Nidhi. , Basu, Arindam. , Mathews, Nripan. & et, al. (2020). Self-Healable Neuromorphic Memtransistor Elements for Decentralized Sensory Signal Processing in Robotics. Nature Communications.
Shaikh, Shoeb. Dawood. , So, Rosa. , Basu, Arindam. & et, al. (2020). Sparse Ensemble Machine Learning to improve robustness of long-term decoding in iBMIs. IEEE Trans. on Neural Systems and Rehabilitation Engineering.
Basu, Arindam. , Acharya, Jyotibdha. & et, al. (2018). Low-Power, Adaptive Neuromorphic Systems: Recent Progress and Future Directions. IEEE Journal on Emerging Topics in Circuits and Systems.
Roy, Subhrajit. & Basu, Arindam. (2017). An Online Unsupervised Structural Plasticity Algorithm for Spiking Neural Networks. IEEE Trans. on Neural Networks and Learning Systems.
Chen, Yi. , Yao, Enyi. & Basu, Arindam. (2016). A 128 channel Extreme Learning Machine based neural decoder for Brain Machine Interfaces. IEEE Trans. on Biomedical Circuits & Systems.
Husain, Shaista. , Liu, Shih-Chii. & Basu, Arindam. (2015). Biologically plausible, Hardware-friendly Structural Learning for Spike-based pattern classification using a simple model of Active Dendrites. Neural Computation,.
Basu, Arindam. & et, al. (2013). Silicon Spiking Neurons for Hardware Implementation of Extreme Learning Machines. Neurocomputing.
Basu, Arindam. & et, al. (2010). A Floating-gate based Field Programmable Analog Array. IEEE Journal of Solid State Circuits.
Basu, Arindam. & Hasler, Paul. E. (2010). Nullcline based design of Silicon Neurons. IEEE Trans. on Circuits and Systems-I.




External Services
Professional Activity 2021 - 2023, Chair, Neural Systems and Applications TC, IEEE CASS.
2015 - Now, Member, Sensory Systems TC, IEEE CASS.
2013 - Now, Member, Biomedical Circuits TC, IEEE CASS.




Last update date : 08 Jul 2021