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I am an Assistant Professor of Electrical and Computer Engineering Department at 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.

I direct the Distributed, Intelligent, and Scalable COmputing (DISCO) Lab at Drexel. My research group works at the intersection of machine learning and computer architecture, with focus on neuromorphic and in-memory computing.

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Recent Publications All Publications»

• ICCAD'21 "A Design Flow for Mapping Spiking NeuralNetworks to Many-Core Neuromorphic Hardware", Shihao Song, M. Lakshmi Varshika, Anup Das, and Nagarajan Kandasamy, IEEE/ACM International Conference On Computer Aided Design, (ICCAD), 2021.
• ICCAD'21 "Automated Generation of Integrated Digital and Spiking Neuromorphic Machine Learning Accelerators", Serena Curzel, Nicolas Bohm Agostini, Shihao Song, Ismet Dagli, Ankur Limaye, Cheng Tan, Marco Minutoli, Vito Giovanni Castellana, Vinay Amatya, Joseph Manzano, Anup Das, Fabrizio Ferrandi, and Antonino Tumeo, IEEE/ACM International Conference On Computer Aided Design, (ICCAD), 2021.
• TECS'21 "DFSynthesizer: Dataflow-based Synthesis of Spiking Neural Networks to Neuromorphic Hardware", Shihao Song, Harry Chong, Adarsha Balaaji, Anup Das, James Shackleford, and Nagarajan Kandasamy, ACM Transactions on Embedded Systems (TECS), 2021.
• ASAP'21 "Improving Inference Lifetime of Neuromorphic Systems via Intelligent Synapse Mapping", Shihao Song, Twisha Titirsha, and Anup Das, IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP), 2021.
• ICONS'21 "NeuroXplorer 1.0: An Extensible Framework for Architectural Exploration with Spiking Neural Networks", Adarsha Balaji, Shihao Song, Twisha Titirsha, Anup Das, Jeffrey L. Krichmar, Nikil D. Dutt, James Shackleford, Nagarajan Kandasamy, and Francky Catthoor, International Conference on Neuromorphic Systems (ICONS), 2021.
• JETC'21 "Dynamic Reliability Management in Neuromorphic Computing", Shihao Song, Jui Hanamshet, Adarsha Balaji, Anup Das, Nikil D. Dutt, Jeffrey L. Krichmar, Nagarajan Kandasamy, and Francky Catthoor, ACM Journal on Emerging Technologies in Computing Systems (JETC), 2021.
• CF'21 "On the Role of System Software in Energy Management of Neuromorphic Computing", Twisha Titirsha, Shihao Song, Adarsha Balaji, and Anup Das, ACM Computing Frontiers (CF), 2021.
• TPDS'21 "Endurance-Aware Mapping of Spiking Neural Networks to Neuromorphic Hardware", Twisha Titirsha, Shihao Song, Anup Das, Nikil D. Dutt, Jeffrey L. Krichmar, Nagarajan Kandasamy, and Francky Catthoor, IEEE Transactions on Parallel and Distributed Systems (TPDS), 2021.
• ASP-DAC'21 "Aging Aware Request Scheduling for Non-Volatile Main Memory", Shihao Song, Anup Das, Onur Mutlu, and Nagarajan Kandasamy, Asia and South Pacific Design Automation Conference (ASP-DAC), 2021
• ATS 2021 "Machine Learning Validated Screening Tool to Predict Obstructive Sleep Apnea in Cancer Patients", Ankita Paul, Karen Wong, Anup Das, Diane Lim, and Miranda Tan, The American Thoracic Society (ATS), 2021
• SLEEP 2021 "STOP-Bang Score and History of Radiation Predicts Risk of Obstructive Sleep Apnea in Cancer Patients: A Machine Learning Study", Ankita Paul, Karen Wong, Anup Das, Diane Lim, and Miranda Tan, Sleep 2021: The 35th Annual Meeting of the Associated Professional Sleep Societies, LLC (APSS), 2021

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
• ECEC 6XX Neuromorphic Computing

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Professional Service

Journal Editorial

• Associate Editor, Frontiers in Neuroscience
• Guest Editor, Computing Innovations for Scale-Up Brain-Inspired Intelligence , Frontiers in Neuroscience
• Guest Editor, Neuromorphic Sensing and Computing Systems, Electronics

Conference Committees

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

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PhD Students

• Arghavan Mohammadhassani (Sep 2022 -): MS, Sharif University, 2020
• M. Lakshmi Varshika (Sep 2022 -): MS, University of California, Santa Barbara, 2021
• Murat Isik (Sep 2022 -): BE, Inönü University, 2020
• Ankita Paul (Fall 2020 -): BTech, RCC Institute Of Information Technology, Kolkata, 2016
• Abhishek Kumar Mishra (Fall 2020 -): MS, University of Buffalo, 2020
• Shihao Song (Fall 2018 -): MS, Drexel University, 2018
• Adarsha Balaji (Winter 2018 -): MS, Drexel University, 2017

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Grants

• DOE CAREER Architecting the Hardware-Software Interface for Neuromorphic Computers.

Role: Principal Investigator, Amount: $750,004, Period: 2021-2026

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

Role: Principal Investigator, Amount: $540,240, Period: 2020-2025

• NSF CORE Online Performance Monitoring of Neuromorphic Services.

Role: Co-Investigator, Amount: $494,073, Period: 2020-2023

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

Role: Principal Investigator, Amount: $484,855, Period: 2019-2022

• NIH RO1 Smart and Connected Health for Newborn Ventilation.

Role: Co-Investigator, Amount: $1,197,557, Period: 2019-2023

• Drexel DARE Internet of Things for Future Smart Campus and City.

Role: Co-Investigator, Amount: $250,000, Period: 2019-2020

• 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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