Signal Processing Algorithm Design and Analysis

SPADA LogoOur lab studies algorithms for statistical signal processing and machine learning with applications in data analysis, computer vision, environmental monitoring, image processing, control systems, power grids, genetic expression data analysis, consumer preference modeling, and computer network analysis. We are interested in algorithmic design using principles from optimization theory, as well as mathematical analysis answering questions regarding algorithmic convergence behavior and performance, required sample complexity, algorithmic robustness. See the projects page for descriptions of some of our research areas and the publications page for our research papers. For prospective postdocs or students at all levels interested in joining SPADA lab, please read to the end of this page.

SPADA lab April 2019:


Ph.D. Students

I have the pleasure of working with the following outstanding students and postdocs. Listed is their most recent publication with the SPADA lab.

Amanda Bower | website(part of the AIM program, co-advised with Martin Strauss)

Zhe Du | (co-advised with Necmiye Ozay)

Yutong Wang | website | (co-advised with Clay Scott)

Kyle Gilman | website

Alex Ritchie | website | (co-advised with Clay Scott)



Haroon Raja | website


Former Ph.D. Students and Postdocs

Ali Soltani-Tehrani

Dejiao Zhang | website
Defended May 2019, “Extracting Compact Knowledge from Massive Data”
Next position: Applied research scientist at Amazon Web Services, New York

David Hong | website | (co-advised with Jeff Fessler)
Defended March 2019, “Learning Low-Dimensional Models for Heterogeneous Data”
Next position: Postdoctoral scholar at Penn – Wharton Statistics Department

Greg Ongie | website
Next position: Postdoctoral scholar at University of Chicago – Statistics and Computer Science Departments

John Lipor | website
Defended September 2017, “Sensing Structured Signals with Active and Ensemble Methods”
Next position: Assistant Professor in the Portland State University ECE Department


Former MS lab members:

Pengyu Xiao
Saket Dewangan

Former undergraduate researchers:

Austin Xu
Andrew Gitlin
Bob Malinas
Nora Farouk
William Zhang
Richard Ortman


Prospective students and postdocs:

If you are interested in joining my research lab, either working on a small project, a Ph.D. thesis, or a postdoctoral project, please read this information.

In the SPADA lab, we enjoy working with students and collaborators who have an enthusiastic curiosity for mathematics and algorithms and their applications in machine learning and signal processing. Our work will draw on tools from probability, linear algebra, and functional analysis as well as contemporary mathematics. You must also demonstrate independent thinking, patience, and integrity. For students already at Michigan, both graduate and undergraduate: Please email me with your CV and the types of projects you’d be interested in, and we can set up a time to meet during my office hours. For prospective postdocs: Please email me with your CV and a research statement, and highlight our shared interests and potential collaborative projects. For prospective graduate students: Please start by applying to the ECE Michigan graduate program. Include my name in your research statement along with reasons why you’d be interested in working with me. Note that I am unlikely to add any Ph.D. students to my group in 2018 or 2019, but I am always open to working with truly outstanding students.

Please make your email subject line “Joining the Balzano lab” to show me you have read this. I will do my best to respond as soon as I can. Since I am busy taking care of my current students, it may take a few weeks before I find the time, so I encourage your patience. You will appreciate these priorities if you end up at Michigan. Best of luck to you in your search for a research mentor.

SPADA lab December 2017: