About
Yingjie is currently a PhD candidate in Computer Engineering, University of Maryland, College Park. Her research focuses on physics-aware infrastructure for optical computing platforms, hardware-software co-design, and efficient AI/ML algorithms. She also works in electronic design automation (EDA), focusing on machine learning for synthesis and verification. Her work received the Best Paper Award at DAC (2023), American Physical Society DLS poster award (2022) and Best Poster Presentation Award at DAC Young Fellow (2020). Yingjie won the Second Place at the ACM/SIGDA Student Research Competition (2023) and was selected as the EECS Rising Star (2023).
Resume: CV
Education
- Doctor of Philosophy, Computer Engineering, University of Maryland, College Park 2023 - present
- Doctor of Philosophy, Computer Engineering, University of Utah 2020 - 2023
- M.Eng, Electrical and Computer Engineering, Cornell University 2018 - 2019
- B.S., Electrical and Computer Engineering, Huazhong University of Science and Technology, Wuhan, China 2014 - 2018
Experience
- Research Intern, Google X 05/2024 - 11/2024
- Research Intern, Nvidia 05/2023 - 08/2023
- Hardware Engineer, DELL EMC, Shanghai, China 2019 - 2020
Publications
2024
Differentiable Combinatorial Scheduling at Scale
Yingjie Li (co-first), Mingju Liu, Jiaqi Yin, Zhiru Zhang, Cunxi Yu
International Conference on Machine Learning (ICML'24)
BoolGebra: Attributed Graph-learning for Boolean Algebraic Manipulation
Yingjie Li, Anthony Agnesina, Yanqing Zhang, Haoxing Ren, Cunxi Yu
IEEE Design, Automation and Test in Europe Conference (DATE'24)
DAG-aware Synthesis Orchestration
Yingjie Li, Mingju Liu, Alan Mishchenko, Haoxing Ren, Cunxi Yu
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) (to appear)
orchestrate@ABC
Survey of Machine Learning for Software-assisted Hardware Design Verification: Past, Present, and Prospect
Nan Wu, Yingjie Li, Hang Yang, Hanqiu Chen, Steve Dai, Cong Hao, Cunxi Yu, Yuan Xie
ACM Transactions on Design Automation of Electronic Systems (TODAES), 2024.
2023
LightRidge: An End-to-end Agile Design Framework for Diffractive Optical Neural Networks
Yingjie Li, Ruiyang Chen, Minhan Lou, Berardi Sensale-Rodriguez, Weilu Gao, Cunxi Yu
The ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS'24).RubikONNs: Multi-task Learning with Rubik's Diffractive Optical Neural Networks
Yingjie Li, Weilu Gao, Cunxi Yu
The 32nd International Joint Conference on Artificial Intelligence (IJCAI-23).Physics-aware Roughness Optimization for Diffractive Optical Neural Networks
Yingjie Li(co-first), Shanglin Zhou, Minhan Lou, Weilu Gao, Cunxi Yu, Caiwen Ding
IEEE/ACM 60th Design Automation Conference (DAC '23).RESPECT: Reinforcement Learning based Edge Scheduling on Pipelined Coral Edge TPUs
Jiaqi Yin, Yingjie Li, Daniel Robinson, Cunxi Yu
IEEE/ACM 60th Design Automation Conference (DAC '23).Gamora: Graph Learning based Symbolic Reasoning for Large-scale Boolean Networks
Nan Wu, Yingjie Li, Cong (Callie) Hao, Steve Dai, Cunxi Yu, Yuan Xie
IEEE/ACM 60th Design Automation Conference (DAC '23) (Best Paper Award, 2/1157).
Effects of interlayer Reflection and Interpixel Interaction in Diffractive Optical Neural Networks
Minhan Lou, Yingjie Li, Cunxi Yu, Berardi Sensale-Rodriguez, Weilu Gao
Optical Letter. Jan 2023.
2022
FlowTune: End-to-end Automatic Logic Optimization Exploration via Domain-specific Multi-armed Bandi
Walter Lau Neto, Yingjie Li, Pierre-Emmanuel Gaillardon, Cunxi Yu
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD'22). Github
Physics-aware Complex-valued Adversarial Machine Learning in Reconfigurable Diffractive All-optical Neural Network
Ruiyang Chen(co-first), Yingjie Li(co-first), Minhan Lou, Jichao Fan, Yingheng Tang, Berardi Sensale-Rodriguez, Cunxi Yu, Weilu Gao
Laser & Photonics Reviews. Vol 16, July 2022.Physics-aware Differentiable Discrete Codesign for Diffractive Optical Neural Networks
Yingjie Li, Ruiyang Chen, Weilu Gao, Cunxi Yu
IEEE/ACM 41st 2022 International Conference on Computer-Aided Design (ICCAD'22).Physics-aware Adversarial Machine Learning: An Experimental Study in Diffractive Optical Neural Networks
Yingjie Li, Ruiyang Chen, Minhan Lou, Jichao Fan, Yingheng Tang, Berardi Sensale-Rodriguez, Weilu Gao, Cunxi Yu
Invited talk at workshop 3rd ROAD4NN@Design Automation Conference (DAC '22 ROAD4NN).
Presentation Video
Pre-print
An Open-source Compiler Framework for Diffractive Optical ML Architectures
Yingjie Li, Ruiyang Chen, Minhan Lou, Berardi Sensale-Rodriguez, Weilu Gao, Cunxi Yu
Workshop talk at 1st OSCAR@International Symposium on Computer Architecture (ISCA '22 OSCAR).RubikONNs: Multi-task Learning with Rubik's Diffractive Optical Neural Networks
Yingjie Li, Weilu Gao, Cunxi Yu
IEEE/ACM 58th Design Automation Conference (DAC '22 WIP).Combinatorial RL-based Scheduling for Pipelined Edge TPUs
Jiaqi Yin, Yingjie Li, Cunxi Yu
Github (to appear)
TinyML Research Symposium 2022 (TinyML'22)Complex-valued Reconfigurable Diffractive Optical Neural Networks using Cost-effective Spatial Light Modulators
Ruiyang Chen, Yingjie Li, Minhan Lou, Cunxi Yu, Weilu Gao
Conference on Lasers and Electro-Optics (CLEO'22).
2021
Real-time Multi-Task Learning in Diffractive Deep Neural Networks via Hardware-Software Co-design
extended version @ arXiv
Yingjie Li, Ruiyang Chen, Berardi Sensale Rodriguez, Weilu Gao, Cunxi Yu
Nature Scientific Reports
Late Breaking Results: Physical Adversarial Attacks of Diffractive Deep Neural Networks
Yingjie Li, Cunxi Yu
IEEE/ACM 58th Design Automation Conference (DAC '21).SLAP: A Supervised Learning Approach for Priority Cuts Technology Mapping (to appear)
[Github (to appear)]
Walter Lau Neto, Matheus Trevisan Moreira, Yingjie Li, Luca Amaru, Cunxi Yu, and Pierre-Emmanuel Gaillardon
IEEE/ACM 58th Design Automation Conference (DAC '21).
Service
Offical Reviewer: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD)
