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Welcome!

I’m Mohammad Alali, a third-year Ph.D. candidate at Northeastern University, and I’m working under supervision of Professor Mahdi Imani. My research interests lie in the domains of Reinforcement Learning, Bayesian Statistics, and Experimental Design. More specifically, I’m currently investigating several projects with a focus on inference, and perturbation of various Markov Models. Before joining here as a Ph.D. student, I received my B.Sc. degree in Electrical Engineering from University of Tehran, in 2018, and my M.Sc. degree in Electrical Engineering from Montana State University in 2021.

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 News

 

  • (April 2024) Our paper “Kernel-Based Particle Filtering for Scalable Inference in Partially Observed Boolean Dynamical Systems” is accepted for presentation at the 20th IFAC Symposium on System Identification (SYSID 2024). I’ll be attending the conference (held in Boston) from July 17-19, 2024.

  • (March 2024) Our paper titled “Deep Reinforcement Learning Sensor Scheduling for Effective Monitoring of Dynamical Systems” (link to the paper) has been accepted for publication in Systems Science and Control Engineering journal.

  • (February 2024) I am pleased to announce that my poster titled “AI-Driven Data Collection for Effective Monitoring of Dynamical Systems” won the Audience Choice Award at the “6th Annual Engineering  Research Expo” event at Northeastern University. Please check out the following link from Northeastern University College of Engineering covering this event.
    6th Annual Engineering Research Expo Audience Choice Award Certificate
    • (November 2023) Presented our poster titled “AI-Driven Data Collection for Accurate Modeling of Genomics Systems” at the “Cutting-Edge Connections in Ph.D. Research : Healthcare Innovation Today” event at Northeastern University.
    Cutting-Edge Connections in Ph.D. Research
    • (June 2023) I attended the American Control Conference (ACC) 2023 in San Diego and presented our paper “Reinforcement Learning Data-Acquiring for Causal Inference of Regulatory Networks” at both a regular session and a special session for Best Paper Award. Please check out the following link from Northeastern University College of Engineering covering this event.
    American Control Conference 2023 Best Paper Award Finalist Certificate
    • (February 2023) Exciting news! I have been selected as one of the five finalists for the Best Paper Award at American Control Conference (ACC) 2023 (Link), among more than 1000 participants. Travel expenses including hotel, transportation, and conference registration will be covered to enable the finalists to attend the conference. Can’t wait to present our paper on May 31st, in San Diego.

    • (January 2023) Our paper “Reinforcement Learning Data-Acquiring for Causal Inference of Regulatory Networks” (link to the paper)  is accepted for presenting in American Control Conference (ACC) 2023. I’ll be attending the conference (held in San Diego) from May 31-June 2, 2023.

    • (November 2022) Our paper titled “Inference of Regulatory Networks Through Temporally Sparse Data” (link to the paper) was accepted for publication in Frontiers in Control Engineering – AI and Machine Learning Control.

    • (October 2022) I passed my Ph.D. qualifying exam; I am now a Ph.D. candidate!

    • (July 2022) I received an NSF travel grant ($1250) to attend the CNB-MAC 2022 workshop. I’m excited to present our paper in Chicago on August 7th!

    • (July 2022) Our paper titled “Inference of Regulatory Networks Through Temporally Sparse Data” (pre-print) was accepted for a talk at the CNB-MAC 2022 workshop. Check out their website for more info!

    • (May 2022) Finished my Ph.D. course requirements; Yay!

    • (August 2021) Started my Ph.D. at Northeastern University!