Shiya Liu

Degree Objective: Ph.D.

Research Interests:

• Analog IC Design
• Neuromorphic Computing System
• Hardware accelerator

Education:

• Ph.D., Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA, USA (Since Jan 2019 | Expected Graduation: Dec 2022)
• M.S., Electrical Engineering, Iowa State University, Ames, IA, USA
• B.S., Electrical Engineering, Iowa State University, Ames, IA USA

Research Experiences:

Virginia Tech

• Implementation of Reservoir Computing System on FPGA. Iowa State University

• Identifying Multiple Operating Points in self-biasing circuit (Band-Gap Reference, Bias Generator, Temperature Sensor, and VCO)

• Thermal noise analysis in Switched-Capacitor circuit

Work Experience:

Computer Vision Algorithm Engineer

• Design and build object detection and recognition algorithms for ADAS (Advanced driver-assistance systems).

Power Integrity EDA Engineer

• Build power integrity models of mixed signal circuits for chip level power integrity analysis. Enhance and automate flows of building power  integrity models.

Publications:

Liu, Shiya & Ha, Dong & Shen, Fangyang & Yi, Yang. (2021). Efficient neural networks for edge devices. Computers & Electrical Engineering. 92. 107121. 10.1016/j.compeleceng.2021.107121.

Liu, Shiya & Liu, Lingjia & Yi, Yang. (2020). Quantized Reservoir Computing on Edge Devices for Communication Applications. 445-449. 10.1109/SEC50012.2020.00068.

Liu, Shiya & Liang, Yibin & Gan, Victor & Liu, Lingjia & Yi, Yang. (2020). Accurate and Efficient Quantized Reservoir Computing System. 364-369. 10.1109/ISQED48828.2020.9136986.

Shang, Bodong & Liu, Shiya & Lu, Sidi & Yi, Yang & Shi, Weisong & Liu, Lingjia. (2020). A Cross-Layer Optimization Framework for Distributed Computing in IoT Networks. 440-444. 10.1109/SEC50012.2020.00067.

Hamedani, Kian & Liu, Lingjia & Liu, Shiya & He, Haibo & Yi, Yang. (2020). Deep Spiking Delayed Feedback Reservoirs and Its Application in Spectrum Sensing of MIMO-OFDM Dynamic Spectrum Sharing. Proceedings of the AAAI Conference on Artificial Intelligence. 34. 1292-1299. 10.1609/aaai.v34i02.5484.

Bai, Kangjun & Liu, Shiya & Yi, Yang. (2019). High speed and energy efficient deep neural network for edge computing. 347-349. 10.1145/3318216.3363453.

Fan, Qiang & Bai, Jianan & Li, Lianjun & Liu, Shiya & Huang, Joe & Burgess, John & Berlinsky, Allan & Pidwerbetsky, Alex & Ashdown, Jonathan & Turck, Kurt & Liu, Lingjia. (2020). Intelligent DSA-assisted clustered IoT networks: neuromorphic computing meets genetic algorithm. 1-6. 10.1145/3411295.3411320.

Shiya Liu, Randall L. Geiger, Degang Chen “A Graphical Method for Identifying Positive Feedback Loops automatically in Self-Biasing Circuit for Determining the Uniqueness of Operating Points,” National Aerospace & Electronics Conference, June. 2014