Muhammad Noor E Alam

About

Muhammad Noor E Alam is an Associate Professor in the Department of Mechanical & Industrial Engineering and Director of the Decision Analytics Lab at Northeastern University. Dr. Alam also holds a faculty associate position at the Centre for Health Policy and Healthcare Research and an affiliated faculty position at both the Global Resilience Institute, and the School of Public Policy and Urban Affairs. Prior joining to Northeastern, Dr. Alam was a Postdoctoral Research Fellow in Sloan School of Management at the Massachusetts Institute of Technology. He has completed his PhD in Engineering Management in the Department of Mechanical Engineering at the University of Alberta (UofA), and received a B.Sc. and M.Sc. in Industrial and Production Engineering from Bangladesh University of Engineering & Technology (BUET). Before coming to UoA, Dr. Alam served as a faculty member in the Department of Industrial and Production Engineering at BUET. Dr. Alam is a recipient of a National Science Foundation Faculty Early Career Development (CAREER) Award (2021). He served as a board of directors for the Logistics and Supply Chain division of the Institute of Industrial and Systems Engineers (IISE) from the year 2018 to 2020.

Selected Publications

• Sahil Shikalgar, Scott Weiner, Gary Young and Md. Noor-E-Alam, “Self-Help Groups and Opioid Use Disorder Treatment: An Investigation Using a Machine Learning-Assisted Robust Causal Inference Framework”, International Journal of Medical Informatics, Published Online 24 June 2024, DOI: doi.org/10.1016/j.ijmedinf.2024.105530.
• Marco Morucci, Md. Noor-E-Alam and Cynthia Rudin, “A Robust Approach to Quantifying Uncertainty in Matching Problems of Causal Inference”, INFORMS Journal on Data Science, 2022 (preprint).
• Md Saiful Islam, M. S. Morshed and Md. Noor-E-Alam, “A Computational Framework for Solving Nonlinear Binary Optimization Problems in Robust Causal Inference”, IINFORMS Journal on Computing, 2022. (preprint)
• M. S. Morshed, Md Saiful Islam and Md. Noor-E-Alam, “Sampling Kaczmarz Motzkin Method for Linear Feasibility Problems: Generalization & Acceleration”, Mathematical Programming, 2021. https:doi.org10.1007s10107-021-01649-8
• M. S. Morshed, Md Saiful Islam and Md. Noor-E-Alam, “Accelerated Sampling Kaczmarz Motzkin Algorithm for Linear Feasibility Problem”, Journal of Global Optimization, 2019. doi.org10.1007s10898-019-00850-6
• M. S. Morshed and Md. Noor-E-Alam, “Generalized Affine Scaling Algorithms for Linear Programming Problems”, Computers & Operations Research, 2019. doi.org10.1016j.cor.2019.104807
• Md Mahmudul Hasan, Tasnim Ibn Faiz, Alicia Sasser Modestino, Gary Young, Md. Noor-E-Alam, “Optimizing Return and Secure Disposal of Prescription Opioids to Reduce the Diversion to Secondary Users and Black Market”, Socio-Economic Planning Sciences, 2022. (“preprint”).
• Md Mahmudul Hasan, Md. Noor-E-Alam, Jiesheng Shi, Leonard Young, Gary J. Young, “Long-term Patient Outcomes from Buprenorphine/Naloxone Treatment for Opioid Use Disorder: A Retrospective Analysis for a Commercially Insured Population”, The American Journal of Drug and Alcohol Abuse, 2022.
• Razan A. H. Al-Lawati, Jose L. Crespo-Vazquez, Tasnim Ibn Faiz, Xin Fang and Md. Noor-E-Alam, “A Two-Stage Stochastic Optimization Approach to Aid in Decision Making Under Uncertainty for a Variable Resource Generator Participating in a Sequential Energy Market”, Applied Energy, Applied Energy, Vol. 252, 15 June 2021, 116882.
• Jose L. Crespo-Vazquez, C. Carrillo, E. Diaz-Dorado, Jose A. Martinez Lorenzo and Md. Noor-E-Alam, “A Machine Learning Based Stochastic Optimization Framework for a Wind and Storage Power Plant Participating in Energy Pool Market”, Applied Energy, Vol. 232, pp. 341-357, 2018.
• Jose L. Crespo-Vazquez, C. Carrillo, E. Lorenzo Diaz-Dorado, Jose A. Martinez and Md. Noor-E-Alam, “Evaluation of a Data Driven Stochastic Approach to Optimize the Participation of a Wind and Storage Power Plant in Day-Ahead and Reserve Markets”, Energy, Vol. 156, pp. 278-291, 2018.
• Md Mahmudul Hasan, Gary J. Young, Jiesheng Shi, Prathamesh Mohite, Leonard Young, Scott G. Weiner, Md. Noor-E-Alam, “Predicting Patients Discontinuation from Opioid Use Disorder Treatment: A Two-Stage Clinical Decision Support System Using Machine Learning”, BMC Medical Informatics and Decision Making, 2021.
• Md Mahmudul Hasan, Gary Young, Mehul R. Patel, Alicia Sasser Modestino, Leon Sanchez, Md. Noor-E-Alam, “A Machine Learning Framework to Predict the Risk of Opioid Use Disorder”, Machine Learning with Applications, 2021.
• Md Mahmudul Hasan, Md. Noor-E-Alam, Prathamesh Mohite, Md Saiful Islam, Alicia Sasser Modestino, Alyssa Peckham, Leonard D. Young, and Gary J. Young, “Patterns of Patient Discontinuation from Buprenorphine/Naloxone Treatment for Opioid Use Disorder: A Study of a Commercially Insured Population in Massachusetts”, Journal of Substance Abuse Treatment, Vol. 131, December 2021, 108416.
• Richard Paulsen, Alicia Sasser Modestino, Md Mahmudul Hasan, Md. Noor-E-Alam, Leonard Young and Gary Young, “Patterns of BuprenorphineNaloxone Prescribing: An Analysis of Claims Data from Massachusetts”, The American Journal of Drug and Alcohol Abuse, 2019. doi.org10.1080/00952990.2019.1674863

Faculty

Sep 09, 2024

Machine Learning Models Applied to Opioid Use Disorder Treatment Research

A recent paper, “Self-Help Groups and Opioid Use Disorder Treatment: An Investigation Using a Machine Learning-Assisted Robust Causal Inference Framework,” by MIE Associate Professor Muhammad Noor E Alam and his research team was published in the International Journal of Medical Informatics and featured in the The ASAM Weekly, a newsletter of the American Society of Addiction Medicine.

Faculty

Jan 24, 2024

Using AI/OR Collaboration To Tackle Opioid Epidemic

MIE Associate Professor Muhammad Noor E Alam’s Challenge Problem “AI/OR to Address Opioid Epidemic Crisis”, has been selected for inclusion in the 3rd Computing Community Consortium AI/OR workshop.

Spotlight Story

Oct 12, 2023

PhD Spotlight: Razan Al Lawati, PhD’23, Industrial Engineering

Razan Al Lawati, PhD’23, industrial engineering, conducted research focusing on using stochastic optimization in various ways to develop decision-making tools for systems that deal with uncertainty. She developed a novel framework and her entrepreneurial drive led her to found a solar consulting firm in Oman. Her research contributions were published in the Journal of Applied Energy.

Faculty

Aug 07, 2023

Young Scholars Program for Local High School Students Finishes Strong

High school seniors engage in diverse engineering research during Northeastern’s Young Scholars Program, mentored by COE faculty and students.

Spotlight Story

Oct 14, 2022

PhD Spotlight: Md Mahmudul Hasan, PhD’22 – Industrial Engineering

As a PhD student of the Decision Analytics Lab advised by Md Noor E Alam, assistant professor of mechanical and industrial engineering, Md Mahmudul Hasan, PhD’22 industrial engineering, conducted data-driven research to address complex challenges in public health, contributing to healthcare decision-making, policy, and management. From a methodological standpoint, he leveraged management and data science […]

Faculty

May 27, 2021

Alam Receives NSF CAREER Award for Causal Inference in Large-Scale Studies

MIE Assistant Professor Md. Noor E Alam received a $500K NSF CAREER Award for developing “Robust Matching Algorithms for Causal Inference in Large Observational Studies.”

Faculty

May 11, 2021

Just What the Doctor Ordered

Human beings are some of the most complex systems in the world, and responses to illness, disease, and impairments manifest in countless different ways. When it comes to making sure that your system stays up and running, healthcare professionals typically have their own deep well of knowledge—but the addition of artificial intelligence tools offers unprecedented […]

Faculty

Nov 12, 2019

Noor-E-Alam’s Collaborative Work Won 1st Place at APPAM

MIE Assistant Professor Md. Noor-E-Alam’s collaborative work “A Community Health Center Buyback Program to Reduce the Supply of Opioids to Secondary Users” with CSSH Associate Professor Alicia Modestino and D’Amore-McKim Professor Gary Young won 1st place for poster presentation at the Association for Public Policy Analysis and Management (APPAM) Fall Research Conference.

Faculty

Jun 10, 2019

Stopping Opioid Addiction Before It Starts

MIE Assistant Professor Muhammad Noor E. Alam is working with DMSB/Bouve Professor Gary Young, Bouve Clinical Assistant Professor Alyssa Peckham, and CSSH Associate Professor Alicia Modestino to determine methods of reducing the number of opioid addictions in the country before they even start.

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