|Academic Profile |
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Asst 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 Techn, 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 (2013-2016) [by Nanyang Technological University]
- Academic Research Fund Tier 2 (2013-2016) [by Ministry of Education (MOE)]
- Academic Research Fund Tier 2 (2014-2017) [by Ministry of Education (MOE)]
- Singapore-MIT Alliance for Research and Technology (SMART) Centre (2015-2017) [by Singapore-MIT Alliance for Research and Technology (SMART)]
- Epileptic Seizures as Emerging Patterns in Complex Dynamical Networks
- Integrated Microsystem with Energy Scavenging, Sensor and Radio Integration using TSV Technology
- 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
- 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.
- A. Banerjee, S. Kar, S. Roy, A. Bhaduri and A. Basu. (2015). A Current-mode Spiking Neural Classifier with Lumped Dendritic Nonlinearity. IEEE ISCAS.
- Y. Enyi and A. Basu,. (2015). A 1 V, Compact, Current-Mode Neural Spike Detector with Detection Probability Estimator in 65 nm CMOS. IEEE ISCAS.
- Chen Yi, Yao Enyi and A. Basu. (2015). A 128 channel 290 GMACs/W Machine Learning based Co-processor for Intention Decoding in Brain Machine Interfaces. IEEE ISCAS.
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