Assistant Professor, Electrical and Computer Engineering
B.E., Jadavpur University (2004)
Ph.D., National University of Singapore (2014)
Research Interests Design of algorithms and architecture for neuromorphic computing; machine learning particularly unsupervised learning using spiking neural networks; in-memory computing using non-volatile memories; dataflow-based design of neuromorphic systems; design of scalable computing system; hardware-software co-design and management; thermal and power management of many-core embedded systems.
Bio Dr. Anup Das obtained his Ph.D. in 2014 from National University of Singapore in the field of computer engineering, with emphasis on machine learning based power and thermal optimization of embedded systems. After graduation, Dr. Das worked as a post-doctoral fellow at the ARM-ECS Research Center at the University of Southampton. During this time, Dr. Das worked on multiple EPSRC sponsored research programs for thermal and power management of many-core embedded systems using reinforcement learning inside the operating system. Following this, Dr. Das was a researcher at IMEC, one of the leading nanoelectronics research center in Europe. At IMEC, Dr. Das led a team of researchers for the development of scalable architectures for neuromorphic computing. Dr. Das was the Co-Principal Investigator for NeuRAM3, a 5.5 Million Euro H2020 program on 3D neuromorphic systems, leading the development of spiking neural network based applications. Dr. Das was also the Co-Principal Investigator for STW’s Efficient Deep Learning Initiative in the Netherlands and two other European programs – H2020 MNEMOSENE (Computation-in-memory architecture based on resistive devices) and ITEA3 PARTNER (Patient-care Advancement with Responsive Technologies aNd Engagement together).
Prior to this Ph.D., Dr. Das was a senior design engineer at STMicroelectronics (between 2004 to 2007) and LSI Corporation (between 2007 and 2011), leading a team of engineers for the development of HDMI and its copy protection HDCP IPs and Read Channel for Solid State Drive. Dr. Das also various aspects front-end IC design, such as RTL Design, Static Timing Analysis and Design for Testability.
Currently, Dr. Das is a full-time Assistant Professor at Drexel University, leading research on in-memory computing and neuromorphic computing. Dr. Das is serving the technical program committee of all leading design automation conferences. Dr. Das is a member of the IEEE.