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I am an Assistant Professor of Electrical and Computer Engineering at the Drexel University. I hold a Ph.D in Embedded Systems from the National University of Singapore in 2014. I have been a researcher in the Neuromorphic Computing Group of IMEC, Netherlands (2015 - 2017) and a post-doctoral fellow in the School of Electronics and Computer Science (ECS) at the University of Southampton, UK (2014 - 2015). Between 2004 and 2011, I have worked at LSI Corporation and STMicroelectronics, as senior IC design engineer.

My research interests include design of algorithms for neuromorphic computing, particularly using spiking neural networks; dataflow-based design of neuromorphic computing system; design of scalable computing system; non-volatile memories; hardware-software co-design and management; thermal and power management of many-core embedded systems.

Multiple fully-funded PhD positions available starting October 2020 in topics related to hardware and software for neuromorphic computing. More information here.

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Selected Publications All Publications»

• IJCNN'20 "PyCARL: A PyNN Interface for Hardware-Software Co-Simulation of Spiking Neural Network", Adarsha Balaji, Prathyusha Adiraju, Hirak J. Kashyap, Anup Das, Jeffrey L. Krichmar, Nikil D. Dutt, and Francky Catthoor, IEEE International Joint Conference on Neural Networks (IJCNN), 2020.
• CAL'19 "A Framework to Explore Workload-Specific Performance and Lifetime Trade-offs in Neuromorphic Computing", Adarsha Balaji, Shihao Song, Anup Das, Nikil D. Dutt, Jeffrey L. Krichmar, Nagarajan Kandasamy, and Francky Catthoor, IEEE Computer Architecture Letters (CAL), 2019.
• TVLSI'19 "Mapping Spiking Neural Networks to Neuromorphic Hardware", Adarsha Balaji, Anup Das, Yuefeng Wu, Khanh Huynh, Francesco Dell'Anna, Giacomo Indiveri, Jeffrey L. Krichmar, Nikil D. Dutt, Siebren Schaafsma, and Francky Catthoor, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2019.

All Publications »

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Courses

• ECEC 355 Computer Organization and Architecture
• ECEC 412 Modern Processor Design
• ECEC 621 High Performance Computer Architecture
• ECEC 623 Advanced Computer Architecture

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Professional Service

Conference Committees

• DAC (2017 - 2019), DATE (2018 - 2019), CASES (2017 - 2018), FPL (2015 - 2018), IGSC (2017 - 2018), ICCD (2018), GLSVLSI (2018), ICCAD (2018)

Journal Referee

• Elsevier Neural Networks, IEEE TVLSI, IEEE TCAD, IEEE TCAS, IEEE TPDS, IEEE TC

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Advising

• Shihao Song (Fall 2018 -): Ph.D. Student. B.S. CE. Drexel University, 2018
• Adarsha Balaji (Winter 2018 -): Ph.D. Student. M.S. CE. Drexel University, 2017

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Grants

• NSF CAREER Facilitating Dependable Neuromorphic Computing: Vision, Architecture, and Impact on Programmability.

Role: Principal Investigator

• NSF RTML Design of System Software to Facilitate Real-Time Neuromorphic Computing.

Role: Principal Investigator

• NSF SCH Smart and Connected Health for Newborn Ventilation.

Role: Co-Investigator

• ITEA3 PARTNER Patient-care Advancement with Responsive Technologies aNd Engagement togetheR.

Role: Co-principal Investigator

• H2020 MNEMOSENE Computation-in-memory architecture based on resistive devices.

Role: Co-principal Investigator

• H2020 NeuRAM3 Neural Computing Architectures in Advanced Monolithic 3D-VLSI Nano-technologies.

Role: Co-principal Investigator

• STW EDL Efficient Deep Learning (Sub-project: Low power hardware for neural networks).

Role: Principal Investigator

• EPSRC PRiME Power-efficient, Reliable, Many-core Embedded systems.

Role: Post-doctoral Fellow

• EPSRC Graceful Continuous on-line adaptation in many-core systems: From graceful degradation to graceful amelioration.

Role: Post-doctoral Fellow

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Contact

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