Mahdi Imani

Assistant Professor

Department of Electrical and Computer Engineering

Northeastern University

Profile: Google Scholar

Email: m.imani [AT] northeastern.edu




Short Bio

I am an Assistant Professor in the Department of Electrical and Computer Engineering at Northeastern University. Prior to Northeastern, I was an Assistant Professor in the Department of Electrical and Computer Engineering at the George Washington University for two years. I received my Ph.D. degree in Electrical Engineering from Texas A&M University in 2019, and my B.Sc. and M.Sc. degrees in Mechanical Engineering and Electrical Engineering from University of Tehran respectively. My research includes Machine Learning, Control Theory, and Signal Processing, focused on the development of highly scalable, efficient, explainable and reliable design, learning and decision-making frameworks using Bayesian Statistics and Reinforcement Learning.

 

Open Positions

I am looking for self-motivated Ph.D. students to join my group. The areas of interest include machine learning, control theory, reinforcement learning, and signal processing. All candidates are expected to have excellent programming skills. Prospective students may have background in electrical and computer engineering, computer science, applied mathematics, or statistics. If you are interested, please email me a copy of your CV and transcripts at m.imani [AT] northeastern.edu. Please use “Ph.D. Application” as the subject of your email.

 

Highlights

  • I have joined the Editorial Board of IEEE Transactions on Vehicular Technology [Sep 20121].
  • I joined as an Assistant Professor to the ECE department at Northeastern University in Fall 2021 [Aug 20121].
  • I received a four-year Army Research Office award for a project entitled “Scalable and Reliable Optimization of Expensive Multi-Modal Functions: A Bayesian Perspective” [July 2021].
  • I elevated to the grade of IEEE Senior member [February 2021].
  • I organized a half-day workshop titled “Scalable, Reliable and Online Bayesian Learning” in IEEE 16th International Conference on Automation Science and Engineering (CASE) [August 2020].
  • I organized a half-day workshop titled “Machine Learning for Scalable, Reliable and Online Design and Decision Making” in IEEE Conference on Control Technology and Applications (CCTA) [August 2020].
  • I received a two-year National Science Foundation (NSF) award for a project entitled “Informative Bayesian Learning and Data Gathering Through Expert-Acquired Data” [July 2020].
  • I received a one year award ($19,710) through GW Office of Vice-President for Research’s University Facilitating Fund (UFF) program [April 2020].
  • I visited and gave a talk on “Scalable and Reliable Experimental Design: A Bayesian Perspective” in the National Institute of Standards and Technology (NIST), Gaithersburg, MD [January 2020].
  • I gave a talk on “Bayesian Learning and Decision Making in Business” in the Wells Fargo in McLean, Virginia [January 2020].
  • I gave a talk on “Practical Bayesian Learning and Decision Making: Scalability, Explainability and Reliability” in the Boeing company [January 2020].
  • I visited the National Center for Toxicological Research (NCTR) at U.S. Food and Drug Administration (FDA) and gave a talk on “Scalable Bayesian Learning and Modeling in  Genomics and Metagenomics” in Jefferson County, Arkansas [January 2020].

Honors and Awards

  • Elevated to the grade of IEEE Senior member, February 2021.
  • Selected as an Aspiring PI Awardee to participate in 2021 Smart Health in the AI and COVID Era hosted by the SCH Program at NSF, Virtual, March 2021.
  • Selected as an Aspiring PI Awardee to participate in 2020 Advancing Health Through Science Workshop hosted by the SCH Program at NSF, NIH and IHMS Laboratory, VA, 2020.
  • IBM Research Almaden Distinguished Speaker, San Jose, CA, November 2019.
  • Recipient of the Association of Former Students Distinguished Graduate Student Award for Excellence in Research-Doctoral, Texas A&M University, 2019.
  • Finalist nominee for the Outstanding Graduate Student Award, Texas A&M University, 2018.
  • Recipient of the Best PhD Student Award, Department of Electrical and Computer Engineering, Texas A&M University, 2015.
  • Recipient of the Best Paper Finalist Award, the 49th Asilomar Conference on Signals, Systems, and Computers, 2015.