Pin-Yu Chen (陳品諭)

Research Staff Member, AI Foundations - Learning Group & MIT-IBM AI Lab

IBM Research AI, IBM Thomas J. Watson Research Center, NY

Link to my Twitter Google scholar profile CV Academic activities

Contact: pinyuchen.tw at gmail.com (primary reviewer account) , pin-yu.chen at ibm.com

- I am a Research Staff Member of the AI Foundations - Learning Group & MIT-IBM AI Lab, IBM Thomas J. Watson Research Center. My recent research focus has been on adversarial machine learning and studying the robustness of neural networks. My research interest includes graph learning and network data analytics and their applications to data mining, machine learning, signal processing, and cyber security.

- I am open to collaboration with highly motivated researchers!

- I received my Ph.D. degree in electrical engineering and computer science and M.A. degree in Statistics from the University of Michigan Ann Arbor in 2016, under the supervision of Prof. Alfred Hero.

- Editorial board: PLOS ONE, IEEE J-IOT (Guest)

- Selected conference reviewers: NIPS, ICML, AAAI, ICLR, ICDM, INFOCOM, GLOBECOM, ICC, WCNC, ACC, ICASSP, ICME

- Selected journal reviewers: IEEE T-SP, T-IP, J-STSP, T-SIPN, T-KDE, T-PAMI, J-SAC, ToN, TWC, CL, SPL, T-PDS, T-IFS, WCM, WCL, J-IoT, SPL, T-CNS, ACCESS, J-ETCAS; PLOS ONE

- News coverage of my research:

RecentEvents

Research Interests

  • Machine Learning: adversarial machine learning, online and distributed learning, unsupervised and semi-supervised learning on graphs
  • Cyber Security: attack and defense models, action recommendations for network resilience, malware propagation models
  • Graph Learning and Network Data Analytics: spectral graph theory and algorithms, graph signal processing, community detection, graph clustering, event propagation and control in networks, complex network

Selected Awards and Honors

  • NIPS Best Reviewer Award (2017) <Link>
  • Best Paper Finalist, ACM Workshop on Artificial Intelligence and Security (2017)
  • Outstanding Performance Award at Pacific Northwest National Laboratory (2015)
  • Rackham International Student Fellowship (Chia-Lun Lo Fellowship) (2013-2014) <Link>
  • EE:Systems Fellowship, University of Michigan, Ann Arbor (2012-2013)
  • Best Master Thesis Award of GICE, NTU (2011)
  • Second Best Master Thesis Award of Chinese Institute of Electrical Engineering (2011)
  • IEEE GLOBECOM GOLD Best Paper Award (2010) <Link>
  • Ranked 1st Place (Full Scores) in Taiwan National College Entrance Exam (2005)

Selected Papers

Adversarial Machine Learning and Robustness of Neural Networks

Cyber Security, Network Resilience

Graph Learning and Network Data Analytics

Event Propagation Models in Networks

Optimization for Machine Learning and Signal Processing

Model Interpretability and Explainability

Preprints

U.S. Patents

[PA1] System and Methods for Automated Detection, Reasoning, and Recommendations for Resilient Cyber Systems

Technical Reports

[T4] Hongge Chen, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Cho-Jui Hsieh, “Show-and-Fool: Crafting Adversarial Examples for Neural Image Captioning

[T3] Yash Sharma and Pin-Yu Chen, “Bypassing Feature Squeezing by Increasing Adversary Strength

[T2] Zhuolin Yang, Bo Li, Pin-Yu Chen, Dawn Song, “Towards Mitigating Audio Adversarial Perturbations

[T1] Pin-Yu Chen, Meng-Hsuan Sung, and Shin-Ming Cheng, “Buffer Occupancy and Delivery Reliability Tradeoffs for Epidemic Routing

Internship

  • Pacific Northwest National Laboratory (PNNL) - Data Science PhD Intern
    • action recommendations for real-time service degradation attacks
    • user segmentation and host hardening against lateral movement attacks

Fun and Proud Fact: My Erdos number is 4 (through two distinct paths)!!

  1. Me -> Alfred Hero -> Wayne Stark -> Robert McEliece -> Paul Erdos
  2. Me -> Pai-Shun Ting -> John. P. Hayes -> Frank Harary -> Paul Erdos