Welcome!

I’m Mohammad Alali, a fourth-year Ph.D. candidate at Northeastern University, and I’m working under the supervision of Dr. Mahdi Imani. My research interests lie in the domains of Reinforcement Learning, Bayesian Statistics, Machine Learning, and Experimental Design. More specifically, I’m currently investigating several projects with a focus on fast and efficient inference of various observable/ partially observable 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.

External Links:

• My Google Scholar 
• My LinkedIn Page

News

• (October 2024) I am excited to announce that I have started a new role as an ML Intern at NXP Semiconductors in San Jose, California.

• (July 2024) I am honored and excited to share that I have been recognized as a Best Paper Finalist at the 20th IFAC Symposium on System Identification (SYSID 2024) for my paper, “Kernel-Based Particle Filtering for Scalable Inference in Partially Observed Boolean Dynamical Systems” (link to the paper). Please check out the following link from Northeastern University College of Engineering covering this event.

• (June 2024) Our paper titled “Bayesian Reinforcement Learning for Navigation Planning in Unknown Environments” (link to the paper) has been accepted for publication in Frontiers in Artificial Intelligence journal.

• (May 2024) Our paper “Bayesian Optimization for State and Parameter Estimation of Dynamic Networks with Binary Space” is accepted for presentation at the 8th IEEE Conference on Control Technology and Applications (CCTA). The conference will be held in Newcastle upon Tyne, UK from August 21-23, 2024.

• (May 2024) Our paper titled “Bayesian Lookahead Perturbation Policy for Inference of Regulatory Networks” (link to the paper) has been accepted for publication in IEEE/ACM Transactions on Computational Biology and Bioinformatics. 
  

• (April 2024) I attended the College of Engineering (COE) Graduate Student Awards Reception on April 30th, and I was recognized for being one of the Best Paper Award finalists at American Control Conference (ACC) 2023. Following is a photo of me, with the COE dean, Dr.  Gregory Abowd, and my advisor, Dr. Mahdi Imani. 

• (April 2024) Our paper “Kernel-Based Particle Filtering for Scalable Inference in Partially Observed Boolean Dynamical Systems” (link to the paper) 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.

• (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.

• (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.

• (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!