|Academic Profile |
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Assoc Prof Arindam Basu
School of Electrical & Electronic Engineering
College of Engineering
Phone: (+65)6790 4439
- PhD Georgia Institute of Technology 2010
- MSc (Maths) Georgia Institute of Technology 2009
- MTech (Auto & Comp Vision) Indian Institute of Tech, Kharagpur 2005
- BTech (Elec & Elect Comm Eng) (Hons) Indian Institute of Tech, Kharagpur 2005
|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.
|Low-power Reconfigurable Mixed-signal design, Neural recording systems, Computational neuroscience, Nonlinear dynamics, Smart sensors for hearing-aids/ultrasound etc, Neuromorphic VLSI|
- Academic Research Fund Tier 1 (2016-2018) [by Ministry of Education (MOE)]
- Academic Research Fund Tier 2 (2013-2016) [by Ministry of Education (MOE)]
- Academic Research Fund Tier 2 (2014-2017) [by Ministry of Education (MOE)]
- Delta Electronics International (Singapore) Pte Ltd (2014-2016) [by Delta Electronics International (Singapore) Pte Ltd, Nanyang Technological University]
- Delta-NTU Corporate Laboratory (2016-2019) [by National Research Foundation (NRF)]
- SMART-NTU Innovation Grant (2015-2017) [by SMART Innovation Centre]
- ST Electronics (Info-Comm Systems) Pte Ltd (2016-2020) [by ST Electronics (Info-Comm Systems) Pte Ltd]
- Adaptation in Brain Machine Interfaces: From Simulation Models to Integrated Circuits
- Low Power Embedded Platform for Machine Learning in IoT
- Low Power Embedded Platform for Machine Learning in LoT
- Neuro-inspired Reconfigurable Processor: Circuits with `Emergent' Structure
- Ultra Low Power Neuromorphic Computing with Spin-devices
- Ultra Low-Power Embedded Machine Learner For Image/Video Processing In Robotics And Portable/ Wearable Devices
- S. Roy and A. Basu. (2016). An Online Structural Plasticity Rule for Generating Better Reservoirs. Neural Computation, .
- S. Roy and A. Basu. (2016). An Online Unsupervised Structural Plasticity Algorithm for Spiking Neural Networks. IEEE Transactions on Neural Networks and Learning Systems, .
- Govind Narasimman, Subhrajit Roy, Xuanyao Fong, Kaushik Roy, Chip-Hong Chang and Arindam Basu. (2016). A Low-voltage, Low power STDP Synapse implementation using Domain-Wall Magnets for Spiking Neural Networks. International Symposium of Circuits and Systems.
- Subhrajit Roy, Phyo Phyo San, Shaista Hussain, Lee Wang Wei and Arindam Basu. (2015). Learning Spike time codes through Morphological Learning with Binary Synapses. IEEE Transactions on Neural Networks and Learning Systems, .
- S. Korde, S. Roy, E. Yao and A. Basu. (2015). On-chip Machine Learner for Spike Sorting in Implantable Brain Machine Interfaces (BMI). IRC Conference on Science, Engineering and Technology.
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