Can Chen

Office: East Hall 1836
Email: canc at umich dot edu

About Me

I am a Ph.D. candidate in the Applied & Interdisciplinary Mathematics program and a Master's student in the Electrical & Computer Engineering program, at University of Michigan. I am also a member of (Cell & Genome) Reprogramming Lab, at University of Michigan, Medical School. 

I am interested in control theory, numerical analysis, network theory and bioinformatics. Currently, I am working with Dr. Anthony Bloch, Dr. Indika Rajapakse and Dr. Amit Surana, on data-guided control of multiway dynamical systems. 

Curriculum Vitae 

Education

I received my B.S., Summa Cum Laude, in Mathematics with minor in Statistics, at the University of California, Irvine in 2016. 

Thesis: Two Branched Cell Lineages for Proliferative Control, supervised by Dr. John Lowengrub

Publications

  1. Multilinear Time Invariant System Theory, with Amit Surana, Anthony Bloch, Indika Rajapakse, Proceedings of SIAM Conference on Control and its Applications (2019), pp. 118-125. [Article][Arxiv]
  2. Tensor Entropy for Uniform Hypergraphs, with Indika Rajapakse, IEEE Transactions on Network Science and Engineering, vol. 7, no. 4 (2020), pp. 2889-2900. [Article] [Arxiv]
  3. Multilinear Control Systems Theory, with Amit Surana, Anthony Bloch, Indika Rajapakse, SIAM Journal on Control and Optimization (accepted to appear). [Arxiv]
  4. Controllability of Hypergraphs, with Amit Surana, Anthony Bloch, Indika Rajapakse (preprint). [Arxiv]
  5. Data-Driven Model Reduction for Multilinear Control Systems via Tensor Trains, with Amit Surana, Anthony Bloch, Indika Rajapakse (preprint)[Arxiv]
  1. Cellular Reprogramming: Mathematics Meets Medicine, with Gabrielle Dotson, Charles Ryan, Lindsey Muir, Indika Rajapakse, WIREs Systems Biology and Medicine (2020). [Article]
  2. Functional Organization of the Maternal and Paternal Human 4D Nucleome, with Stephen Lindsly, Wenlong Jia, Haiming Chen, Sijia Liu, Scott Ronquist, et al. (preprint). [BioRxiv]
  3. Network Dynamics of Hypothalamic Feeding Neurons, with Sweeney Patrick, Roger Cone, Indika Rajapakse (submitted).

Conferences

  1. DMD Based Control of Multiway Dynamical Systems, SIAM Conference on Applications on Dynamical Systems, Snowbird, Utah, May 2019. [Drive]
  2. Multilinear Time Invariant System Theory, SIAM Conference on Control and its Application, Chengdu, China, June 2019. [Drive]

Course Projects 

  1. Asymptotically Efficient Adaptive Allocation Rules, with Bo Lu, Jiaxin Liang, Henry Oskar Singer, EECS 558 Stochastic Control, Fall 2017. [Drive]
  2. A Review of Control System Analysis and Design via the ''Second Method" of Lyapunov: I - Continuous Time Systems, EECS 562 Nonlinear Control, Winter 2018. [Drive]
  3. Manifold Learning in Differentiating Cancer Cells, with Yuting Liu, Peter Paquet, James Connolly, EECS 545 Machine Learning, Fall 2018. [Drive]
  4. A Survey of Reinforcement Learning Methods in Stock Trading Games, with Xinyue Yang, Zeyuan Zhu, Royce Hwang, Peter Paquet, EECS 598 Special Topic: Deep Learning, Winter 2019. [Drive]
  5. Complexity Analysis of Computing Piecewise Quadratic Lyapunov Functions for Switched Linear Systems, with Bingwen Yang, Ming Li, EECS 563 Hybrid Control, Fall 2020. [Drive]

Teaching 

  1. Math 105: Data, Functions and Graphs (Fall 2016, Winter 2017)
  2. Math 115: Calculus I (Fall 2017, Winter 2018, Fall 2018, Fall 2019, Fall 2020)
  3. Math 216: Introduction to Differential Equations (Winter 2020)