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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
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Posts
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portfolio
Graduate from Xi’an Jiaotong University
2022-7-2, A photo with the department head at the degree awarding site. 
Start the Ph.D career at The Chinese University of Hong Kong
2022-8-1, Start the new journey as a Ph.D student at CUHK.
The CoMUX paper is accepted by ICCAD 2022
2022-8-15, Thanks to the hard work of co-authors, the CoMUX paper is finally accepted by ICCAD this year!
The ARMM paper is accepted by ICCAD 2023
2023-8-9, Really good news, the ARMM paper is formally accepted by ICCAD this year!
The LaMUX paper is accepted by DAC 2024
2024-2-14, Great news during the Chinese New Year, the LaMUX paper gets accepted by DAC this year!
The RABER paper is accepted by ICCAD 2024
2024-6-25, Good news, the RABER paper gets accepted by ICCAD this year!
The CoMUX extension paper is accepted by TCAD
2024-8-15, Cheers, the CoMUX extension paper is accepted by TCAD!
publications
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.
Fast Transient Stability Prediction Using Grid-informed Temporal and Topological Embedding Deep Neural Network
Published in arXiv preprint arXiv:2201.09245, Paper, 2022
This paper is about using DL method to predict the transient stability of power grids.
Recommended citation: P.Y. Sun, L. Huo, S.Y. Liang, X. Chen, "Fast Transient Stability Prediction Using Grid-informed Temporal and Topological Embedding Deep Neural Network," arXiv preprint arXiv:2201.09245, 2022.
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.
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.
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.
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.
LaMUX: Optimized Logic-Gate-Enabled High-Performance Microfluidic Multiplexer Design
Published in The 61th 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 61th Design Automation Conference (DAC), 2024.
Late Breaking Results: Efficient Built-in Self-Test for Microfluidic Large-Scale Integration (mLSI)
Published in The 61th 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 61th Design Automation Conference (DAC), 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.
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.
talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
TA of ENGG 2440A Discrete Mathematics
Undergraduate Course, The Chinese University of Hong Kong, Department of Computer Science and Engineering, 2022
Working as the teaching assitant in the undergraduate course Discrete Mathematics during 2022-2023 term1. Responsible for giving tutorials, marking assignments and answering students’ questions.
TA of ENGG 2780A Statistics for Engineers
Undergraduate Course, The Chinese University of Hong Kong, Department of Computer Science and Engineering, 2023
Working as the teaching assitant in the undergraduate course Statistics for Engineers during 2022-2023 term2. Responsible for giving tutorials, marking assignments and answering students’ questions.
TA of ENGG 2440A Discrete Mathematics
Undergraduate Course, The Chinese University of Hong Kong, Department of Computer Science and Engineering, 2023
Working as the teaching assitant in the undergraduate course Discrete Mathematics during 2023-2024 term1. Responsible for giving tutorials, marking assignments and answering students’ questions.
TA of ENGG 1003 Digital Literacy and Computational Thinking
Undergraduate Course, The Chinese University of Hong Kong, Department of Computer Science and Engineering, 2024
Working as the teaching assitant in the undergraduate course Digital Literacy and Computational Thinking during 2023-2024 term2. Responsible for tutoring lab sessions, marking assignments and answering students’ questions.