Siyuan Liang

Siyuan Liang

Ph.D student, Department of Computer Science and Engineering, The Chinese University of Hong Kong

Publications

Late Breaking Results: Efficient Built-in Self-Test for Microfluidic Large-Scale Integration (mLSI)

Published in Get the paper The 61th Design Automation Conference (DAC), 2024

This paper presents a novel and practical microfluidic logic gate. Based on the logic gate design, this paper proposes a powerful multiplexer that can address at least 100% more channels with the same control resources, comparing to existing multiplexer designs.

Recommended citation: M.C. Li, H.C. Gu, Y.S. Zhang, S.Y. Liang, H. Gasvoda, R. Altay, I. Araci, T.-M. Tseng, T.-Y. Ho and U. Schlichtmann, "Late Breaking Results: Efficient Built-in Self-Test for Microfluidic Large-Scale Integration (mLSI)," The 61th Design Automation Conference (DAC), 2024.

LaMUX: Optimized Logic-Gate-Enabled High-Performance Microfluidic Multiplexer Design

Published in Get the paper The 61th Design Automation Conference (DAC), 2024

This paper presents a novel and practical microfluidic logic gate. Based on the logic gate design, this paper proposes a powerful multiplexer that can address at least 100% more channels with the same control resources, comparing to existing multiplexer designs.

Recommended citation: S.Y. Liang, Y.S. Zhang, R. Altay, H. Gasvoda, M.C. Li, I.E. Araci, T.-M. Tseng, U. Schlichtmann, T.-Y. Ho, "LaMUX: Optimized Logic-Gate-Enabled High-Performance Microfluidic Multiplexer Design," The 61th Design Automation Conference (DAC), 2024.

Rotor Angle Stability Prediction using Temporal and Topological Embedding Deep Neural Network Based on Grid-Informed Adjacency Matrix

Published in Get the paper Journal of Modern Power Systems and Clean Energy, 2023

Formal journal version of former arxiv paper “Fast Transient Stability Prediction Using Grid-informed Temporal and Topological Embedding Deep Neural Network”

Recommended citation: P.Y. Sun, L. Huo, X. Chen, S.Y. Liang, "Rotor Angle Stability Prediction using Temporal and Topological Embedding Deep Neural Network Based on Grid-Informed Adjacency Matrix," Journal of Modern Power Systems and Clean Energy, 2023.

ARMM: Adaptive Reliability Quantification Model of Microfluidic Designs and Its Graph-Transformer-Based Implementation

Published in Get the paper The 42nd IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2023

This paper presents the first reliability quantification model of flow-based microfluidic biochips, and is adaptive to different manufacturing processings. To provide more timely feedback for designers and enable more efficent reliability improvements, a graph-transformer-based implementation was also proposed.

Recommended citation: S.Y. Liang, M. Lian, M.C. Li, T.-M. Tseng, U. Schlichtmann, T.-Y. Ho, "ARMM: Adaptive Reliability Quantification Model of Microfluidic Designs and Its Graph-Transformer-Based Implementation," The 42nd IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2023.

Optimal Inter-area Oscillation Damping Control: A Transfer Deep Reinforcement Learning Approach with Switching Control Strategy

Published in Get the paper arXiv preprint arXiv:2301.09321, 2023

This paper adpots a Deep Reinforcement Learning (DRL) method which uses a physical-information-aided reward to suppress the wide-area oscillation in power grids, and proposes a novel Switching Control Strategy (SCS) to achieve hybrid control, and boost the performance of the DRL method.

Recommended citation: S.Y. Liang, L. Huo, X. Chen, P.Y. Sun, "Optimal Inter-area Oscillation Damping Control: A Transfer Deep Reinforcement Learning Approach with Switching Control Strategy," arXiv preprint arXiv:2301.09321, 2023.

CoMUX: Combinatorial-Coding-Based High-Performance Microfluidic Control Multiplexer Design

Published in Get the paper The 41st IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2022

This paper is about a novel microfluidic control multiplexer design which achieves the theoretical maximum coding capacity, saves up to 44% areas comparing to the classic design and is reliability-aware.

Recommended citation: S.Y. Liang, M.C. Li, T.-M. Tseng, U. Schlichtmann, T.-Y. Ho, "CoMUX: Combinatorial-Coding-Based High-Performance Microfluidic Control Multiplexer Design," The 41st IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2022.

Finite Element Analysis based Optimized Vehicle Mounted Antenna Deployment

Published in Get the paper IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (APS/URSI), 2021

This paper is about how the electromagnetic field distribution is affected by different antenna deployment positions of the vehicle.

Recommended citation: S.Y. Liang, Y.S. Li, C. Gao, "Finite Element Analysis based Optimized Vehicle Mounted Antenna Deployment," IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (APS/URSI), 2021.