Dr. Wang Bo, Angela is an Assistant Professor at SUTD since September 2020. Her research interests span various aspects of energy-efficient computing systems, architecture and circuit design, including on-device artificial intelligence, neuromorphic computing, biomedical wearables and ultra-low voltage memories. Particularly, her research work on biomedical wearables was featured by The Straits Times in 2020. She authored and co-authored many papers in prestigious journals and conferences, including JSSC, TCAS-I, TVLSI, A-SSCC, MobiSys, DATE, etc. She has served as a reviewer for journals and conferences such as TCAS-I, TVLSI, TCAS-II and ISCAS. Since 2021, she has also served as an editorial board member of JCSC. She was the recipient of IEEE Circuits & Systems Seoul Chapter Award in 2014.
Dr. Wang received her Ph.D. degree from Nanyang Technological University in 2015. Prior to joining SUTD, she was a research fellow, working with Prof. Peh Li-Shiuan (IEEE Fellow) at National University of Singapore from 2016 to 2020. Before that, she was a staff engineer at MediaTek Singapore. She is an IEEE senior member.
The research group of Prof. Wang Bo invites applications for the position of Research Assistant or Associate on Neuromorphic Computing Accelerators. Neuromorphic Computing deploys Spiking Neuron Networks (SNN) models and learning rules to solve machine learning problems in a more energy-efficient way compared to Artificial Neural Networks. Candidates are expected to work with the Principal Investigator and possibly with Prof. Peh Li-Shiuan at NUS to (1) design and validate energy-efficient on-chip training architecture and circuits and (2) assist in novel device modeling and integration. Familiarity with RTL design with Verilog or hardware-software co-design strategies will be a strong plus. Please feel free to contact Prof. Wang via firstname.lastname@example.org for more information.
“Track Your Health with Sensor Integrated into Smartwatch? No Sweat” by The Straits Times, https://www.straitstimes.com/singapore/track-your-health-with-sensor-integrated-into-smartwatch-no-sweat
“How She Got There: Women in AI and Robotics” by SGInnovate, https://www.youtube.com/watch?v=dSPlAn9le_Q&feature=youtu.be
“Wearable Sweat Sensor”, Singapore Non-provisional Patent Application 11201911412T
“Wearable Sweat Sensor”, International Patent Application PCT/SG2020/050689
- “Shenjing: A low power reconfigurable neuromorphic accelerator with partial-sum and spike networks-on-chip”, by B. Wang, J. Zhou, W. Wong and L. Peh. Design, Automation and Test in Europe Conference, Mar. 2020.
- “HyCUBE: A 0.9V 26.4 MOPS/mW, 290 pJ/cycle, Power Efficient Accelerator for IoT Applications” by B. Wang, M. Karunaratne, A. Kulkarni, T. Mitra and L. Peh. IEEE Asian Solid-State Circuits Conference, Nov. 2019.
- “pH Watch – Leveraging Pulse Oximeters in Existing Wearables for Reusable, Real-time Monitoring of pH in Sweat” by A. Balaji, C. Yuan, B. Wang, L. Peh and H. Shao. International Conference on Mobile Systems, Applications, and Services, Jun. 2019.
- “Read bitline sensing and fast local write-back techniques in hierarchical bitline architecture for ultra-low voltage SRAMs” by B. Wang, Q. Li, and T. Kim. IEEE Transactions on Very Large Scale Integration Systems, vol 24, no. 6, 2016.
- “Design of an ultra-low voltage 9T SRAM with equalized bitline leakage and CAM-assisted energy efficiency improvement” by B. Wang, T. Q. Nguyen, A. Do, J. Zhou. M. Je, and T. Kim. IEEE Transactions on Circuits and Systems-I, vol 62, no. 2, 2015.
- “A 457-nW near-threshold cognitive multi-functional ECG processor CMOS for long-term cardiac monitoring” by X. Liu, J. Zhou, Y. Yang, B. Wang, J. Lan, C. Wang, J. Luo, W. L. Goh, T. Kim, and M. Je. IEEE Journal of Solid-State Circuits, vol 49, no. 11, 2014.
- “0.2V 8T SRAM with Improved Bitline Sensing Using Column-based Data Randomization” by A. Do, Z. Lee, B. Wang, I. Chang, and T. Kim. IEEE Asian Solid-State Circuits Conference, Nov. 2014.
- “A 0.18V charge-pumped DFF with 50.8% energy-delay reduction for near-/sub-threshold circuits” by B. Wang, J. Zhou, K. H. Chang, M. Je, and T. Kim. IEEE Asian Solid-State Circuits Conference, Nov. 2013.
- “A 457-nW Cognitive Multi-Functional ECG Processor” by X. Liu, J. Zhou, Y. Yang, B. Wang, J. Lan, C. Wang, J. Luo, W. L. Goh, T. Kim, and M. Je. IEEE Asian Solid-State Circuits Conference, Nov. 2013.
- “A 0.2V 16Kb 9T SRAM with bitline leakage equalization and CAM-assisted write performance boosting for improving energy efficiency” by B. Wang, T. Q. Nguyen, A. Do, J. Zhou. M. Je, and T. Kim. IEEE Asian Solid-State Circuits Conference, Nov. 2012.
- “A 5.61 pJ, 16 kb 9T SRAM with Single-ended Equalized Bitlines and Fast Local Write-back for Cell Stability Improvement” by Q. Li, B. Wang, and T. Kim. IEEE European Solid-State Device Research Conference, Sep. 2012.
- Architectures and Circuits of Neuromorphic Computing
- Energy-Efficient AI for Edge Computing Systems
- Research Assistant/Associate Positions on Neuromorphic Computing Acceleration
- Ph.D Scholarships available for International/Singaporean/SPR students on Energy-Efficient On-device AI
- Visiting Research Scholar positions available