Siyuan Liang

Siyuan Liang

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

Publications

MMPack: Multi-Mask Co-Design for Ultra-Large Wafer-Scale Package Integration

Published in The 44th ACM/IEEE International Conference on Computer-Aided Design (ICCAD), Paper, 2025

This paper presents MMPack, a framework for chiplet-package co-design in large interposer-based systems. It introduces performance-driven partitioning, stitching-aware floorplanning, and stress-aware optimization to improve performance and reliability while maintaining scalability.

Recommended citation: S.Y. Li, Z. Zhuang, S.Y. Liang, B. Yu, T.-Y. Ho, "MMPack: Multi-Mask Co-Design for Ultra-Large Wafer-Scale Package Integration," The 44th ACM/IEEE International Conference on Computer-Aided Design (ICCAD), 2025.

Deep-Reinforcement-Learning-based Adaptive State-Feedback Control for Inter-Area Oscillation Damping with Continuous Eigenvalue Configurations

Published in CSEE Journal of Power and Energy Systems (CSEE JPES), Paper, 2025

This is the journal version of our previous arxiv paper “Optimal Inter-area Oscillation Damping Control: A Transfer Deep Reinforcement Learning Approach with Switching Control Strategy”, a work completed during my undergraduate career, introducing a novel Deep-Reinforcement-Learning-based approach to supress inter-area oscillations in power grids.

Recommended citation: S.Y. Liang, L. Huo, W.Y. Qin, X. Chen, and P.Y. Sun, "Deep-Reinforcement-Learning-based Adaptive State-Feedback Control for Inter-Area Oscillation Damping with Continuous Eigenvalue Configurations," CSEE Journal of Power and Energy Systems (CSEE JPES), 2025.

Multi-Layer Package Power/Ground Planes Synthesis with Balanced DC IR Drops: A Game-Theoretic Optimization Approach

Published in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), Paper, 2025

As one of the earliest works focusing on the design automation of power/ground plane in packages, this paper introduces a game-theoretic optimization method aimed at evenly mitigating DC IR drops across the multi-layer package power/ground planes. Experimental results demonstrate that the maximum DC IR drop and the IR drop difference can both be significantly reduced.

Recommended citation: S.Y. Liang, Z. Zhuang, K.-Y. Chao, B. Yu, and T.-Y. Ho, "Multi-Layer Package Power/Ground Planes Synthesis with Balanced DC IR Drops: A Game-Theoretic Optimization Approach," IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2025.

AutoRE: Bayesian-Optimization-based Automatic Reliability Enhancement Tool for Flow-based Microfluidic Biochips

Published in The 62nd Design Automation Conference (DAC), Paper, 2025

This paper presnts the first automatic reliability enhancement tool for microfluidic biochiops. Experimental results demonstrate that AutoRE can efficiently and effectively improve the reliability across all testcases by around 40% on average.

Recommended citation: S.Y. Liang, Y.S. Zhang, M.C. Li, T.-M. Tseng, U. Schlichtmann, T.-Y. Ho, "AutoRE: Bayesian-Optimization-based Automatic Reliability Enhancement Tool for Flow-based Microfluidic Biochips," The 62nd Design Automation Conference (DAC), 2025.

Combinatorial-Coding-Based High-Performance Microfluidic Control Multiplexer: Design, Synthesis, and Adaptation

Published in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), Paper, 2024

This is the extension of our ICCAD’ 22 CoMUX paper. This paper offers users a comprehensive guide to the design, synthesis, and adaptation of CoMUX. Experimental results show that CoMUXes can reliably address more independent control channels with fewer resources. The proposed adaptation method is also tested to be capable of significantly reducing area usage, total length of control channels, and the risk of having defects.

Recommended citation: S.Y. Liang, M.C. Li, T.-M. Tseng, U. Schlichtmann, T.-Y. Ho, "Combinatorial-Coding-Based High-Performance Microfluidic Control Multiplexer: Design, Synthesis, and Adaptation," IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2024.

RABER: Reliability-Aware Bayesian-Optimization-based Control Layer Escape Routing for Flow-based Microfluidics

Published in The 43rd ACM/IEEE International Conference on Computer-Aided Design (ICCAD), Paper, 2024

This paper presents a practical and novel control layer escape routing methodology, which can efficiently connects microvalves to user-specified boundaries. This is very helpful to help designers place ports on boundaries of designs, thereby benefitting experiments. Moreover, this is also supportive to integrate our MUX works into users’ circuits.

Recommended citation: S.Y. Liang, R.L. Fu, M.C. Li, T.-M. Tseng, U. Schlichtmann, T.-Y. Ho, "RABER: Reliability-Aware Bayesian-Optimization-based Control Layer Escape Routing for Flow-based Microfluidics," The 43rd ACM/IEEE International Conference on Computer-Aided Design (ICCAD), 2024.

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

Published in The 61st Design Automation Conference (DAC), Paper, 2024

This paper presents a built-in self-test (BIST) method that drastically improves the test efficiency for microfluidic large-scale integration (mLSI) chips. Given n to-be-tested control channels, the proposed method reduces the number of test patterns for blockage and leakage tests from up to n/2 to 1, and from up to log2(n+1) to up to log2(X(G)+1), respectively, where X(G) denotes the vertex chromatic number of a graph G consisting of n vertices.

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 61st Design Automation Conference (DAC), 2024.

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

Published in The 61st Design Automation Conference (DAC), Paper, 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 61st 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 Journal of Modern Power Systems and Clean Energy, Paper, 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 (MPCE), 2023.

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

Published in The 42nd IEEE/ACM International Conference on Computer-Aided Design (ICCAD), Paper, 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 arXiv preprint arXiv:2301.09321, Paper, 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 The 41st IEEE/ACM International Conference on Computer-Aided Design (ICCAD), Paper, Code, 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 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (APS/URSI), Paper, 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.