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Yawen Wu

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Summary

I am Yawen Wu, a Senior AI Research Engineer at Qualcomm. I am building high-performance artificial intelligence (AI) technologies while considering resource requirements. Prior to Qualcomm, I was a Postdoctoral Research Associate at the University of Notre Dame working with Dr. Yiyu Shi. Prior to Notre Dame, I obtained my Ph.D. from the University of Pittsburgh advised by Dr. Jingtong Hu. I am open to various kinds of collaboration, please drop me an email if you are interested in my research.

I received the MICCAI Young Scientist Award Nomination for my work on medical applications of on-device AI. My research internships at Meta and Baidu USA have resulted in technologies delivered to industrial production.


Recent News

  • 04/2024: One paper was accepted to Nature Electronics.
  • 04/2024: Invited to be an ICCAD 2024 TPC member.
  • 02/2024: Invited to be an MICCAI 2024 reviewer.
  • 02/2024: Invited to be a GLSVLSI 2024 TPC member.
  • 01/2024: Invited to be an ACCV 2024 reviewer.
  • 01/2024: Invited to be an ECCV 2024 reviewer.
  • 10/2022: Invited to be a CVPR 2024 reviewer.
  • 07/2023: Invited to be the AAAI 2024 Program Committee (PC).
  • 05/2023: One paper was accepted to MICCAI 2023 (Early acceptance).
  • 05/2022: Invited to be a MICCAI 2023 Distributed, Collaborative and Federated Learning Workshop reviewer.
  • 05/2023: I started my new position as a Senior AI Research Engineer at Qualcomm, developing next-generation mobile vision technologies.
  • 05/2023: Our paper about federated self-supervised learning from streaming data is accepted by TCAD.
  • 05/2023: Invited to be an ICCAD 2023 TPC member.
  • 04/2023: Invited to be an ASP-DAC 2024 TPC member.
  • 03/2023: Invited to be a NeurIPS 2023 reviewer.
  • 03/2023: I started my new position as a Postdoctoral Research Associate at the University * of Notre Dame.
  • 02/2023: I successfully defended my Ph.D. dissertation.
  • 02/2023: Invited to be an ICCV 2023 reviewer.
  • 02/2023: Invited to be a MICCAI 2023 reviewer.
  • 02/2023: Invited to be a KDD 2023 PC member.
  • 01/2023: Invited to be a GLSVLSI 2023 TPC member.
  • 12/2022: Our paper about self-supervised learning is accepted by AAAI 2023 (Oral presentation).
  • 10/2022: Invited to be a CVPR 2023 reviewer.
  • 10/2022: Invited to be a NeurIPS 2022 MetaLearn Workshop reviewer.
  • 07/2022: Invited to be a MICCAI 2022 Distributed, Collaborative and Federated Learning * Workshop reviewer.
  • 05/2022: Invited to be an ECCV 2022 reviewer.
  • 05/2022: I started my new position as a machine learning research intern at Meta.
  • 04/2022: Our paper about self-supervised federated learning is accepted by IJCAI 2022.
  • 02/2022: Invited to be a MICCAI 2023 reviewer.

Research Interests

Machine Learning, Deep Learning, Large Language Model (LLM), Computer Vision, AI for Healthcare, Self-supervised Learning, Federated Learning, AI Fairness, On-device AI.


Professional Experience

1, Senior AI Research Engineer - Qualcomm Technologies Inc, San Diego, CA, USA. (May 2023 - Current)
2, Postdoctoral Research Associate - University of Notre Dame, Notre Dame, IN, USA. (Mar. 2023 – May 2023)
Project: Fair and efficient machine learning on mobile devices for healthcare.
3, Machine Learning Research Intern - Meta (formerly Facebook), Reality Labs Research, Redmond, WA, USA. (May 2022 - Aug. 2022)
Project: On-device machine learning for distributed AR glasses.
4, Machine Learning Research Intern, Baidu USA, Sunnyvale, CA, USA. (Sept. 2021 - Dec. 2021)
Project: Efficient machine learning model deployment on AI Infrastructures.


Selected Publications

Google Scholar Profile and DBLP

Synthetic Data Can Also Teach: Synthesizing Effective Data for Unsupervised Visual Representation Learning (Acceptance rate 19.6%) [pdf]
Yawen Wu, Zhepeng Wang, Dewen Zeng, Yiyu Shi, Jingtong Hu
in Proc. of the Thirty-Seventh AAAI Conference on Artificial Intelligence(AAAI 2023), Feb. 2023.

Additional Positive Enables Better Representation Learning for Medical Images (Early acceptance, acceptance rate 14%) [pdf]
Dewen Zeng, Yawen Wu, Xinrong Hu, Xiaowei Xu, Jingtong Hu, and Yiyu Shi
in Proc. of the 26th Medical Image Computing and Computer Assisted Interventions (MICCAI 2022), Oct. 2023.

Decentralized Unsupervised Learning of Visual Representations (Acceptance rate 15%) [pdf]
Yawen Wu, Zhepeng Wang, Dewen Zeng, Meng Li, Yiyu Shi, Jingtong Hu
in Proc. of the 31st International Joint Conference on Artificial Intelligence(IJCAI 2022), July 2022.

Enabling On-Device CNN Training by Self-Supervised Instance Filtering and Error Map Pruning [Video][Slides][arXiv]
Yawen Wu, Zhepeng Wang, Yiyu Shi, Jingtong Hu
in Proc. of International Conference on Compilers, Architecture, and Synthesis for Embedded Systems (CASES), in conjunction with ESWEEK, Oct. 2020.
Also appears as part of the ESWEEK-TCAD Special Issue, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (IEEE TCAD).

Intermittent Inference with Nonuniformly Compressed Multi-Exit Neural Network for Energy Harvesting Powered Devices [Video][Slides][arXiv]
Yawen Wu, Zhepeng Wang, Zhenge Jia, Yiyu Shi, Jingtong Hu
in Proc. of IEEE/ACM Design Automation Conference (DAC), 2020. (acceptance rate 23%)

Enabling On-Device Self-Supervised Contrastive Learning With Selective Data Contrast [Video][Slides][arXiv]
Yawen Wu, Zhepeng Wang, Dewen Zeng, Yiyu Shi, Jingtong Hu
in Proc. of IEEE/ACM Design Automation Conference (DAC), 2021.

FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosis (Early accept, acceptance rate 13%) [arxiv]
Yawen Wu*, Dewen Zeng* (* equal contribution), Xiaowei Xu, Yiyu Shi, Jingtong Hu
in Proc. The 25th Medical Image Computing and Computer Assisted Interventions (MICCAI 2022), Sept. 2022.

Federated Contrastive Learning for Dermatological Disease Diagnosis via On-device Learning [arXiv]
Yawen Wu, Dewen Zeng, Zhepeng Wang, Yi Sheng, Lei Yang, Alaina J. James, Yiyu Shi, Jingtong Hu
in Proc. of IEEE/ACM International Conference on Computer-Aided Design (ICCAD 2021), Nov. 2021.

Federated Contrastive Learning for Volumetric Medical Image Segmentation (Early accept, acceptance rate 13%) [arXiv]
Award Nomination: MICCAI Society Young Scientist
Yawen Wu, Dewen Zeng, Zhepeng Wang, Yiyu Shi, Jingtong Hu
in Proc. The 24th Medical Image Computing and Computer Assisted Interventions (MICCAI 2021), Sept. 2021.

Distributed Contrastive Learning for Medical Image Segmentation [pdf]
Yawen Wu, Dewen Zeng, Zhepeng Wang, Yiyu Shi, Jingtong Hu
Medical Image Analysis (in print) (Impact factor=8.5), 2022.

Cooperative Communication Between Two Transiently Powered Sensor Nodes by Reinforcement Learning
Yawen Wu, Zhenge Jia, Fei Fang, Jingtong Hu
IEEE Transactions on COMPUTER-AIDED DESIGN of Integrated Circuits and Systems (TCAD), Jan. 2021.

Positional Contrastive Learning for Volumetric Medical Image Segmentation [arXiv]
Dewen Zeng, Yawen Wu, Xinrong Hu, Xiaowei Xu, Haiyun Yuan, Meiping Huang, Jian Zhuang, Yiyu Shi, Jingtong Hu
in Proc. The 24th Medical Image Computing and Computer Assisted Interventions (MICCAI 2021), Sept. 2021.

The Larger The Fairer? Small Neural Networks Can Achieve Fairness for Edge Devices
Yi Sheng, Junhuan Yang, Yawen Wu, Kevin Mao, Yiyu Shi, Jingtong Hu, Weiwen Jiang, Lei Yang
in Proc. The 59th IEEE/ACM Design Automation Conference (DAC 2022) , July 2022.

Energy-Aware Adaptive Multi-Exit Neural Network Inference Implementation for a Millimeter-Scale Sensing System
Yuyang Li, Yawen Wu, Xincheng Zhang, Jingtong Hu, Inhee Lee
IEEE Transactions on Very Large Scale Integration (VLSI) Systems (TVLSI), April 2022.

Algorithm-Hardware Co-design of Attention Mechanism on FPGA Devices
Xinyi Zhang, Yawen Wu, Peipei Zhou, Xulong Tang, Jingtong Hu
in Proc. International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS) in conjunction with (ESWEEK), Virtual, Oct. 2021.
Also appears as part of the ESWEEK-TECS Special Issue, ACM Transactions on Embedded Computing Systems (ACM TECS).

Enabling Weakly-Supervised Temporal Action Localization from On-Device Learning of the Video Stream
Yue Tang, Yawen Wu, Peipei Zhou, Jingtong Hu
in Proc. International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS) in conjunction with (ESWEEK), Shanghai, China, Oct. 7-14, 2022.
Also appears as part of the ESWEEK-TECS Special Issue, ACM Transactions on Embedded Computing Systems (ACM TECS).

Developing a Miniature Energy-Harvesting-Powered Edge Device with Multi-Exit Neural Network
Yuyang Li, Yawen Wu, Xincheng Zhang, Ehab Hamed, Jingtong Hu, Inhee Lee
in Proc. IEEE Int'l Symposium on Circuits & Systems (ISCAS 2021), May, 2021.

Lightweight Run-Time Working Memory Compression for Deployment of Deep Neural Networks on Resource-Constrained MCUs
Zhepeng Wang, Yawen Wu, Zhenge Jia, Yiyu Shi, Jingtong Hu
The 26th Asia and South Pacific Design Automation Conference (ASP-DAC 2021), Jan. 2021.

Cooperative Communication Between Two Transiently Powered Sensors by Reinforcement Learning: Work-in-Progress
Yawen Wu, Zhenge Jia, Fei Fang, Jingtong Hu
in Proc. of International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS). IEEE, 2019.

Prototyping Energy Harvesting Powered Systems with Nonvolatile Processor
Yawen Wu, Yinan Sun, Zhenge Jia, Lefan Zhang, Yongpan Liu, Jingtong Hu
in Proc. of International Symposium on Rapid System Prototyping (RSP). IEEE, 2018.

Implementation of Multi-Exit Neural-Network Inferences for an Image-Based Sensing System with Energy Harvesting
Yuyang Li, Yuxin Gao, Minghe Shao, Joseph T. Tonecha, Yawen Wu, Jingtong Hu, Inhee Lee
Journal of Low Power Electronics and Applications (JLPEA), Sept. 2021.

Opportunistic Communication with Latency Guarantees for Intermittently-Powered Devices
Kacper Wardega, Wenchao Li, Hyoseung Kim, Yawen Wu, Zhenge Jia, Jingtong Hu
in Proc. The ACM/IEEE Design, Automation and Test in Europe (DATE 2022) , ANTWERP, BELGIUM, March 2022.


Professional Services

TPC and Reviewer

  • IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR 2023, 2024)
  • AAAI Conference on Artificial Intelligence (AAAI 2023, 2024)
  • Conference on Neural Information Processing Systems (NeurIPS 2023)
  • ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023)
  • The European Conference on Computer Vision (ECCV 2022, 2024)
  • Asian Conference on Computer Vision (ACCV 2024)
  • International Conference on Computer Vision (ICCV 2023)
  • Asia and South Pacific Design Automation Conference (ASP-DAC 2024, TPC)
  • IEEE/ACM International Conference on Computer-Aided Design (ICCAD 2023, TPC)
  • Design Automation Conference (DAC 2018)
  • Great Lakes Symposium on VLSI (GLSVLSI 2023, 2024, TPC)
  • International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2022, 2023, 2024)
  • International Conference on Machine Learning Workshop (ICML Workshop 2022)
  • International Conference on Learning Representations Workshop (ICLR Workshop 2022)
  • Conference on Machine Learning and Systems, Artifact Evaluations (MLSys AE 2022)
  • IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
  • IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (IEEE TCAD)
  • ACM Transactions on Cyber Physical Systems (ACM TCPS)
  • IEEE Transactions on Circuits and Systems (IEEE TCAS)
  • ACM Transactions on Embedded Computing Systems (ACM TECS)
  • IEEE Transactions on Emerging Topics in Computational Intelligence (IEEE TETCI)
  • IEEE Transactions on Vehicular Technology (IEEE TVT)
  • IEEE Transactions on Medical Imaging (IEEE TMI)
  • Medical Image Analysis (MIA)
  • Scientific Reports - Nature
  • Patterns - Cell Press
  • Applied Intelligence (APIN)
  • Journal of Medical Artificial Intelligence (JMAI)
  • Integration - the VLSI Journal
  • Journal of Systems Architecture (JSA)
  • Machine Intelligence Research (MIR)

Teaching Experience

  • ECE 0301 Problem Solving with C++, Teaching Assistant, Teaching Assistant, Aug. 2019 - Dec. 2019
  • ECE 1770 Electronic Microprocessor Systems, Teaching Assistant, Aug. 2018 - April 2019
  • ECE 0142 Computer Organization, Teaching Assistant, Jan. 2018 - April 2018

Supervised Students

  • Gelei Xu, Summer 2022 (Current: PhD Student at University of Notre Dame, USA)
  • Jiahe Shi, Fall 2022 - Spring 2023 (Current: Master Student at Fudan University, China)

Awards

  • MICCAI Society Young Scientist Award Nomination - MICCAI Conference. 2021
  • MICCAI Student Travel Award - MICCAI Conference. 2021
  • Young Student Fellow Award - Design Automation Conference (DAC). 2019, 2020
  • Student Travel Grant - ACM SIGBED/SIGDA. 2019
  • National Scholarship - Ministry of Education of China 2010
  • Grand Prize in National Student Intelligent Car Competition - Ministry of Education of China. 2012
  • First Prize in National Electronic Design Competition - Education Department of Shandong Province. 2011
  • First-class Outstanding Students Scholarship - Shandong University. 2010, 2011, 2012
  • Research and Innovation Scholarship - Shandong University. 2011, 2012
  • Outstanding Individual of Innovation Activities - Shandong University. 2013
  • First Prize in Science and Technology Innovation Contest - Shandong University. 2012
  • Third Prize in Information Tech. Innovation - Dept. of Science and Technology of Shandong Province. 2012