Xinqiao Zhang

I am a final year Computer Engineering PhD candidate and my research topics are Trust-worthy machine learning, adversarial machine learning, hardware trojan and hardware design & acceleration.

View My LinkedIn Profile

View My Resume

View My GitHub Profile

(last update 04/12/2024)

EXPERIENCE

UC San Diego, La Jolla, CA

Dec 2019 - Current
Graduate Student Researcher
Core contributor of TrojAI Project funded by IARPA.
- Built efficient methods to detect backdoored AI models and got 2nd out of 16 teams in the competition.
Resulted in numerous top-tier publications.

Arm, Austin, TX

June 2023 - Sep. 2023
Research Intern
Conducted in-depth research on security detection using Large Language Models
Developed and implemented a data distillation framework, achieving a significant reduction in data size without compromising efficiency.

PUBLICATION & PATENTS

(* indicates equal contribution)

Highlighted publications and patents

(Trustworthy ML) Z. Ghodsi*, M, Javaheripi*, N. Sheyban*, X. Zhang*, K, Huang, & F. Koushanfar, (2023).zPROBE: Zero Peek Robustness Checks for Federated Learning, (ICCV23)

[zPROBE: Zero Peek Robustness Checks for Federated Learning] 2022 (Serial No.63/496,157.)

(Trustworthy ML) Z. Ghodsi*, M, Javaheripi*, N. Sheybani*,X. Zhang*, K, Huang, & F. Koushanfar, (2022).zPROBE: Zero Peek Robustness Checks for Federated Learning, (NeurIPS’22-TSRML) [Outstanding paper award]

(Trustworthy ML) X. Zhang, M. Samragh, S. Hussain, K. Huang, & F. Koushanfar. Scalable Binary Neural Network applications in Oblivious Inference, (ACM TECS)

(Watermarking) P. Neekhara, S. Hussain, X. Zhang, K. Huang, J. McAuley, F. Koushanfar, (2023).zPROBE: FaceSigns: Semi-Fragile Neural Watermarks for Media Authentication and Countering Deepfakes (TOMM-2024, ACM Transactions on Multimedia Computing Communications and Applications)

(Trustworthy ML) Z. Ghodsi*, M, Javaheripi*, N. Sheyban*, X. Zhang*, K, Huang, & F. Koushanfar, (2023).zPROBE: Zero Peek Robustness Checks for Federated Learning, (ICCV23)

(Trustworthy ML) M. Samragh, S. Hussain, X. Zhang, K. Huang, & F. Koushanfar (2021). On the Application of Binary Neural Networks in Oblivious Inference. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 4630-4639)

(Watermarking) S. Hussain, N, Sheybani, P. Neekhara, X. Zhang, J. Duarte, F. Koushanfar (2022) FastStamp: Accelerating Neural Steganography and Digital Watermarking of Images on FPGAs. ICCAD’22)

Other publications and patents

(Crypto) N. Sheybani, X. Zhang, S. U. Hussain, F. Koushanfar. SenseHash: Computing on Sensor Values Mystified at the Origin. IEEE (TETC-2021)

(Hardware Security) H. Chen, X. Zhang, K. Huang, F. Koushanfar. “AdaTest: Reinforcement Learning and Adaptive Sampling for On-chip Hardware Trojan Detection,” ACM Transactions on Embedded Computing Systems (TECS) 2022.

[FACESIGNS: SEMI-FRAGILE NEURAL WATERMARKS FOR MEDIA AUTHENTICATION AND COUNTERING DEEPFAKES] 2022 (Serial No.63/323,470.)

(Hardware Security) K. Huang, M.T.H. Anik, X. Zhang, and N. Karimi, “Real-Time IC Aging Prediction via On-Chip Sensors.” 2021 IEEE Computer Society Annual Symposium on VLSI (ISVLSI). IEEE, 2021

(Hardware Security) D. Ma, X. Zhang, et al. “DEVoT: Dynamic Delay Modeling of Functional Units under Voltage and Temperature Variations.” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021).

(Hardware Security) K. Huang, X. Zhang, and N. Karimi, “Real-time prediction for IC aging based on machine learning. “IEEE Transactions on Instrumentation and Measurement (TIM), vol. 68, no. 12, pp. 4756-4764, 2019.

[Peasants Joy precisely pushes guiding device], CN205754440U, 2016

[Bicycle lock based on bluetooth], CN205621091U , 2016

[Portablely lead blind waistband] CN204766395U, 2015

My Projects

Project: On the Application of Binary Neural Networks in Oblivious Inference

Project: Optimization and Acceleration of Deep Learning on Various Hardware Platforms

Project: TrojAI

Project: Leakage Power Minimization (ECO)

Project :IC Aging Prediction based on Machine Learning (Master’s Thesis)

Project :Regression model for auto insurance claim probability predictions

Project: Clock Tree Optimization using Useful Skew (ECO)

Project: MIPs Processor Design with System Verilog

Professional Services:

Reviewer: IEEE Transactions on Dependable and Secure Computing(TDSC-2020) IEEE Transactions on Dependable and Secure Computing(TDSC-2022)

Award

Outstanding paper award (NeurlPS 2022 TSRML) DAC Young Fellow (58th Design Automation Conference) Nov. 2021