Academic Profile

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 (awarded to the top student). In the summer of 2008, he worked at Texas Instruments, Dallas and developed automatic tuning strategies for LNAs designed in 45nm and 65nm. He joined Nanyang Technological University as an Assistant professor in June 2010.

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. His research interests include bio-inspired neuromorphic circuits, non-linear dynamics in neural systems, low power analog IC design and programmable circuits and devices.
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Assoc Prof Arindam Basu (No longer with NTU)
Associate Professor, School of Electrical & Electronic Engineering

Low-power Reconfigurable Mixed-signal design, Neural recording systems, Computational neuroscience, Nonlinear dynamics, Smart sensors for hearing-aids/ultrasound etc, Neuromorphic VLSI
  • Ionic Halide Perovskites for Opto-Neuromorphic In-network Computing (IONIC)
  • Pradeep Gopalakrishnan, Bapi Kar, Sumon Bose, Mohendra Roy and Arindam Basu. (2019). Live Demo: Autoencoder-based Predictive Maintenance for IoT. The IEEE International Symposium on Circuits and Systems (ISCAS) 2019.

  • Sumon Kumar Bose; Bapi Kar; Mohendra Roy; Pradeep Kumar Gopalakrishnan; Arindam Basu. (2019). ACM ISBN 978-1-4503-6007-4/19/01: ADEPOS: Anomaly Detection based Power Saving for Predictive Maintenance using Edge Computing. 24th Asia and South Pacific Design Automation Conference (ASPDAC ’19) (pp. 597-602)Tokyo, Japan: ACM.

  • V. M. Suresh, R. Sidhu, P. Karkare, A. Patil, Z. Lei, A. Basu. (2018). Powering the IoT Through Embedded Machine Learning and LoRa. IEEE World Forum on Internet of Things 2018.

  • J. Acharya, A. Patil, X. Li, Y. Chen, S-C Liu, A. Basu. (2018). A Comparison of Low-complexity Real-Time Feature Extraction for Neuromorphic Speech Recognition. Frontiers in Neuroscience, .

  • S. Roy and A. Basu. (2016). An Online Structural Plasticity Rule for Generating Better Reservoirs. Neural Computation, .