Shengjun(Daniel) Zhang

Shengjun(Daniel) Zhang

Ph.D. in Electrical Engineering

Huazhong University of Science and Technology

About Me

Daniel receieved his Ph.D. degree from University of North Texas in 2022, advised by Dr. Colleen P. Bailey. He’s been affiliated with Optimization, Signal, Control, and Algorithms Research (OSCAR Lab) since 2019 summer. Before joining OSCAR Lab, since 2018 he had been fortunate to work with Dr. Tao Yang before he left UNT for one year and a half.

Before coming to UNT, he received a Master’s degree in Electrical Engineering at New York University in 2017, where he worked with Dr. Farshad Khorrami. He received a Bachelor’s degree with honor in Automation of Honors Program at China Agricultural University in 2014, where he worked with Dr. Jianhan Lin and Dr. Li Li.

In 2018 summer, he was also fortunate to visit Dr. Ye Yuan’s group at Huazhong University of Science and Technology, working on accelerating distributed optimization of multi-agent systems.

Fun fact, his Erdős number is 3 through Dr. Karl H. Johansson and Dr. Béla Bollobás.

Download his resumé.

Interests

  • Distributed Optimization
  • Statistical Learning
  • Control Theory

Education

  • Ph.D in Electrical Engineering, May 2022

    University of North Texas

  • M.S in Electrical Engineering, January 2017

    New York University

  • B.S in Electrical Engineering, June 2014

    China Agricultural University

Experience

 
 
 
 
 

Postdoctoral Researcher

Huazhong University of Science and Technology

May 2022 – Sep 2022 Wuhan, Hubei, China

Responsibilities include:

  • Artificial Intelligence on Healthcare
 
 
 
 
 

Research Scientist Intern

Pacific Northwest National Laboratory

Jun 2021 – Aug 2021 Richland, Washington, U.S

Responsibilities include:

  • Apply distributed optimization algorithms on power systems
  • Investigate transportation problems
 
 
 
 
 

Research Assistant

University of North Texas

Aug 2018 – Jun 2021 Denton, Texas, U.S

Responsibilities include:

  • Develop algorithms on distributed optimization
  • Implement and test algorithms
 
 
 
 
 

Visiting Scholar

Huazhong University of Science and Technology

May 2018 – Jul 2018 Wuhan, China

Responsibilities include:

  • Develop algorithms on accelerating distributed optimization of multi-agent systems
  • Implement and test algorithms
 
 
 
 
 

Research Assistant

New York University

Jan 2016 – May 2016 New York, New York, U.S

Responsibilities include:

  • Develop SLAM algorithms on a UGV mobile platform
  • Model System and control

Publications

Shengjun Zhang, Colleen P. Bailey (2022). Accelerated Zeroth-order Algorithm for Stochastic Distributed Nonconvex Optimization. In ACC 2022.

PDF DOI

Shengjun Zhang, Tan Shen, Yunlong Dong, Heng Zhang (2022). Zeroth-Order Stochastic Coordinate Methods for Decentralized Non-convex Optimization. In IEEE L-SP (In Submission).

PDF

Xinlei Yi, Shengjun Zhang, Tao Yang, Tianyou Chai, Karl H. Johansson (2022). Sublinear and Linear Convergence of Modified ADMM for Distributed Nonconvex Optimization. In IEEE TCNS.

DOI

Xinlei Yi, Shengjun Zhang, Tao Yang, Karl H. Johansson (2022). Zeroth-order Algorithms for Distributed Stochastic Nonconvex Optimization. In Automatica.

PDF DOI

Xinlei Yi, Shengjun Zhang, Tao Yang, Tianyou Chai, Karl H. Johansson (2022). A Primal-Dual SGD Algorithm for Distributed Nonconvex Optimization. In IEEE-JAS.

PDF Code DOI

Xinlei Yi, Shengjun Zhang, Tao Yang, Tianyou Chai, Karl H. Johansson (2022). Communication Compression for Distributed Nonconvex Optimization. In IEEE TAC (Under Review).

PDF Code

Shengjun Zhang, Colleen P. Bailey (2021). Accelerated Primal-Dual Algorithm for Distributed Nonconvex Optimization. In IEEE SSCI 2021.

PDF DOI

Shengjun Zhang, Yunlong Dong, Dong Xie, Lisha Yao, Colleen P. Bailey, Shengli Fu (2021). Convergence Analysis of Nonconvex Distributed Stochastic Zeroth-order Coordinate Method. In CDC 2021.

PDF DOI

Shengjun Zhang, Colleen P. Bailey (2021). A Primal-Dual Algorithm for Distributed Sparse Principal Component Analysis. In ICDSCA 2021.

PDF DOI

Xinlei Yi, Shengjun Zhang, Tao Yang, Tianyou Chai, Karl H. Johansson (2021). Linear Convergence of First- and Zeroth-Order Primal-Dual Algorithms for Distributed Nonconvex Optimization. In IEEE TAC.

PDF Code DOI

Yunlong Dong, Shengjun Zhang, Xing Liu, Yu Zhang, Tan Shen (2021). Variance Aware Reward Smoothing for Deep Reinforcement Learning. In Neurocomputing.

PDF DOI

Tao Yang, Lei Xu, Xinlei Yi, Shengjun Zhang, Yuzhe Li (2021). Event-Triggered Proportional-Integral Algorithms for Distributed Optimization (Invited Session Extended Abstract). In CCC2021.

Tao Yang, Lei Xu, Xinlei Yi, Shengjun Zhang, Ruijuan Chen, Yuzhe Li (2021). Event-triggered Distributed Optimization Algorithms (in Chinese). In ACTA AUTOMATICA SINICA (自动化学报).

PDF DOI

Xinlei Yi, Shengjun Zhang, Tao Yang, Tianyou Chai, Karl H. Johansson (2020). Linear Convergence for Distributed Optimization Without Strong Convexity. In CDC 2020.

PDF Slides DOI

Shengjun Zhang, Colleen P. Bailey (2020). Optimal Control Under Communication Constraints for Multi-agent Unmanned Vehicles. In SPIE Security + Defence.

PDF Slides Video DOI

Xinlei Yi, Shengjun Zhang, Tao Yang, Tianyou Chai, Karl H. Johansson (2020). Exponential Convergence for Distributed Smooth Optimization Under the Restricted Secant Inequality Conditions. In IFAC 2020.

PDF Slides Source Document DOI

Shengjun Zhang, Colleen P. Bailey (2020). Obstacle Avoidance and Navigation Utilizing Reinforcement Learning with Reward Shaping. In SPIE Defense + Commercial Sensing.

PDF Poster Slides Video DOI

Xinlei Yi, Shengjun Zhang, Tao Yang, Junfeng Wu, Karl H. Johansson (2019). Event-Triggered Control for Consensus of Multi-Agent Systems with Output Saturation and Directed Topologies. In CCC 2019.

PDF DOI

Shengjun Zhang, Xinlei Yi, Jemin George, Tao Yang (2019). Computational Convergence Analysis of Distributed Optimization Algorithms for Directed Graphs. In ICCA 2019 (Best Student Paper Shorten List).

PDF DOI

Wen Du, Xinlei Yi, Shengjun Zhang, Jemin George, Tao Yang (2019). Distributed Proportional-Integral Optimization Algorithms with Event-triggered Communication.

Junfeng Wu, Shengjun Zhang, Tao Yang, Ling Shi, Hong Wang (2018). Distributed Economic Dispatch over Networks with Markovian Communication Losses.

Yahui Chen, Jianhan Lin, Qing Jiang, Qi Chen, Shengjun Zhang, Li Li (2016). A Magnetic Nanoparticle Based Nucleic Acid Isolation and Purification Instrument for DNA Extraction of Escherichia Coli O157: H7. In Journal of Nanoscience and Nanotechnology.

PDF DOI

Recent & Upcoming Talks

Convergence Analysis of Nonconvex Distributed Stochastic Zeroth-order Coordinate Method

This paper investigates the stochastic distributed nonconvex optimiztion problem of minimizing a global cost function formed by the …
Dec 13, 2021 — Dec 17, 2020 Online

Accelerated Primal-Dual Algorithm for Distributed Nonconvex Optimization

This paper investigates how to accelerate the convergence of distributed optimization algorithms on nonconvex problems. We propose a …
Dec 4, 2021 — Dec 7, 2020 Online

A Primal-Dual Algorithm for Distributed Sparse Principal Component Analysis

This paper investigates the problem of sparse principal component analysis (SPCA), which is an extension of principal component …
Oct 29, 2021 — Oct 31, 2020 Online

Optimal Control Under Communication Constraints for Multi-agent Unmanned Vehicles

This paper considers the linear quadratic regulator (LQR) optimal control problem of multi-agent unmanned vehicle systems under …
Sep 20, 2020 1:00 PM — 1:30 PM Online
PDF Slides Video
Optimal Control Under Communication Constraints for Multi-agent Unmanned Vehicles

Obstacle Avoidance and Navigation Utilizing Reinforcement Learning with Reward Shaping

In this paper, we investigate the obstacle avoidance and navigation problem in the robotic control area. For solving such a problem, we …
Apr 21, 2020 1:00 PM — 1:30 PM Online
PDF Slides Video
Obstacle Avoidance and Navigation Utilizing Reinforcement Learning with Reward Shaping

Service

Teaching Assistant Experience

  • EENG 5810: Digital Communications (Spring 2022, Instructor: Dr. Hua Sun)
  • EENG 3510: Electronics I (Spring 2022, Instructor: Dr. Shuping Wang)
  • EENG 3920: Modern Communication System Design Project (Spring 2022, Instructor: Dr. Shuping Wang)
  • EENG 3510: Electronics I (Fall 2021, Instructor: Dr. Shuping Wang)
  • EENG 3520: Electronics II (Fall 2021, Instructor: Dr. Shuping Wang)
  • EENG 3920: Modern Communication System Design Project (Fall 2021, Instructor: Dr. Shuping Wang)
  • EENG 5940: Optimization Theory (Fall 2020, Instructor: Dr. Colleen Bailey)
  • EENG 2620: Signals and Systems (Spring 2019, Fall 2018, Instructor: Dr. Tao Yang)
  • EENG 5940: Power System & Optimization (Fall 2018, Instructor: Dr. Tao Yang)

Journal Reviewer

Conference Reviewer

Conference Chair

  • Co-Chair (Substitute Dr. Tao Yang) of Distributed Optimization and Learning for Networked Systems II Session at CDC 2021