Biography

I am a Research Scientist at Meta. Previously, I completed my PhD degree in EE at University of Southern California, supervised by Prof. Konstantinos Psounis. I received my Bachelor’s Degree of Science in Automation from Beijing Institute of Technology in 2019, supervised by Prof. Yuanqing Xia and Prof. Yufeng Zhan.

Education

• University of Southern California, 08/2019-05/2024
  • Degree: PhD
  • Major: Electrical Engineering
  • GPA: 3.9/4.0
• University of Southern California, 08/2019-12/2022
  • Degree: MS
  • Major: Computer Science
  • GPA: 3.9/4.0
• University of Southern California, 08/2019-05/2021
  • Degree: MS
  • Major: Electrical Engineering
  • GPA: 4.0/4.0
• Beijing Institute of Technology, 09/2015-06/2019
  • Degree: Bachelor
  • Major: Automation (Xu Teli Elite Class)
  • GPA: 92.31/100 (rank: 1/17)

Research Experience

• 08/19/2019-05/08/2024: Research Asistant
  • NetPD Lab, Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California
  • Research interests: Machine learning and data privacy with applications to computer networks
  • Supervisor: Prof. Konstantinos Psounis
  • Publications: NDSS (1), PETS (2), AAAI (1) etc.
• 03/05/2019-06/30/2019: Research Internship
  • AST Lab, Department of Computer Science, ETH Zurich,
  • Research interests: LLVM IR and sanitizers
  • Supervisor: Prof. Zhendong Su
  • Publications: OSDI (1).
• 01/01/2017 - 03/04/2019: Research Assistant
  • National Key Laboratory of Complex System Intelligent Control and Decision, Beijing Institute of Technology
  • Research interests: Deep reinforcement learning, mobile crowdsensing and control theory
  • Supervisor: Prof. Yuanqing Xia, Prof. Yufeng Zhan
  • Publications: INFOCOM (1), TMC (1), TC(1), etc.

Work Experience

• 05/13/2024 - Present: Research Scientist
  • Meta
• 05/15/2023 - 07/28/2023: Applied Scientist Internship
  • AGI, Amazon
  • Research on toxic content detection using LLMs
• 05/16/2022 - 08/19/2022: Applied Scientist Internship
  • Alexa AI, Amazon
  • Research on zero-shot cross-lingual named entity recognition
• 05/17/2021 - 08/20/2021: Applied Scientist Internship
  • Alexa AI, Amazon
  • Research on detecting personal identifiable information
• 05/18/2020 - 08/21/2020: Applied Scientist Internship
  • Alexa AI, Amazon
  • Research on heuristics for effective quantization

See my LinkedIn for more details.

Conference Publications (* means equal contributions)

• Jiang Zhang, Qiong Wu, Yiming Xu, Cheng Cao, Zheng Du, Konstantinos Psounis. Efficient Toxic Content Detection by Bootstrapping and Distilling Large Language Models [C]. AAAI, 2024.
• Jiang Zhang, Hadi Askari, Konstantinos Psounis, Zubair Shafiq. No Video Left Behind: A Utility-Preserving Obfuscation Approach for YouTube Recommendations [C]. PETS, 2023(4).
• Ahmed Roushdy Elkordy*, Jiang Zhang*, Yahya H. Ezzeldin, Konstantinos Psounis, Salman Avestimehr. How Much Privacy Does Federated Learning with Secure Aggregation Guarantee? [C]. PETS, 2023(1).
• Jiang Zhang, Konstantinos Psounis, Muhammad Haroon, Zubair Shafiq. HARPO: Learning to Subvert Online Behavioral Advertising [C]. NDSS, 2022.
• Jiang Zhang, Shuai Wang, Manuel Rigger, Pingjia He, and Zhendong Su. SanRazor: Reducing Redundant Sanitizer Checks in C/C++ Programs [C]. OSDI, 2021.
• Yufeng Zhan, Jiang Zhang. An Incentive Mechanism Design for Efficient Edge Learning by Deep Reinforcement Learning Approach [C]. INFOCOM, 2020.

Journal Publications

• Evita Bakopoulou, Mengwei Yang, Jiang Zhang, Konstantinos Psounis, Athina Markopoulou. Location Leakage in Federated Signal Maps. IEEE Transactions on Mobile Computing, 2023.
• Jiang Zhang, Lillian Clark, Matthew Clark, Konstantinos Psounis, Peter Kairouz. Privacy-Utility Trades in Crowdsourced Signal Map Obfuscation [J]. Computer Networks, 2022.
• Yufeng Zhan, Song Guo, Peng Li, Jiang Zhang. A deep reinforcement learning based offloading game in edge computing [J]. IEEE Transactions on Computers, 2020.
• Jiang Zhang, Yuanqing Xia, Ganghui Shen. A Novel Learning-based Global Path Planning Algorithm for Planetary Rovers [J]. Neurocomputing, 2019.
• Yufeng Zhan, Chi Harold Liu, Yinuo Zhao, Jiang Zhang, Jian Tang. Free Market of Multi-Leader Multi-Follower Mobile Crowdsensing: An Incentive Mechanism Design by Deep Reinforcement Learning [J]. IEEE Transactions on Mobile Computing, 2019.
• Yufeng Zhan, Jiang Zhang, Peng Li, Yuanqing Xia. Crowdtraining to Mobile Edge Devices in Industry Internet of Things by Deep Reinforcement Learning Approach [J]. IEEE Network, 2019.

See my Google Scholar for more details.

Skills

• Programming languages: C, C++, Matlab, Python, LLVM.
• Development environments or tools: Ubuntu, Tensorflow, PyTorch, Spark, Ray, Docker, Selenium.

Awards and Honors

• USC Annenberg Fellowship, 2019
• Meritorious Winner of the MCM (top 9%, global), 2017
• First Scholarship of BIT (five semesters, top 10%), 2015-2018
• First Prize of the China Undergraduate Mathematics Competition (Non Mathematical Speciality, rank 20 in Beijing), 2016
• National Scholarship (top 5%), 2016