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Mohammad Arif Ul Alam

Mohammad Arif Ul Alam, Ph.D. Assistant Professor


Mobile Computing, Machine Learning, Bioinformatics

Research Interests

Ubiquitous Computing, Healthcare Robotics, Deep Learning, Causal and Explainable AI, Biomedical Informatics, Text Mining


  • Research Affiliate, Massachusetts Institute of Technology (2018 - 2019), Cambridge, MA 
  • Research Staff Member, IBM Research, MIT-IBM Watson AI Lab (2018 - 2019), Cambridge, MA 
  • Ph.D.: Information Systems, (2017), University of Maryland Baltimore County - Baltimore, MA 
  • B.Sc: Computer Science and Engineering, (2011), Bangladesh University of Engineering and Technology - Dhaka, Bangladesh 


Mohammad Arif Ul Alam is serving as a tenure-track Assistant Professor in the Department of Computer Science at University of Massachusetts Lowell and a volunteer Assistant Professor at University of Massachusetts Medical School. He is also a Research Partner of Israel-based hydroponic company, Start-up-roots. Prior to joining University of Massachusetts Lowell, he was a Research Staff Member at MIT-IBM Watson AI Lab and a Research Affiliate at Massachusetts Institute of Technology for ~2 years. He did his Ph.D. in Information Systems from University of Maryland Baltimore County under the supervision of Nirmalya Roy, Ph.D. The primary focus of his research lies on machine learning, ubiquitous computing, healthcare robotics and artificial intelligence ethics in human-centered computing. With the goal of impacting the practice of computer and information science, my work consists of design, experimentation, quantitative and qualitative evaluation, analytic modeling and simulation to answer questions about computer systems and methodologies related to their application to human behavior and cognition. I also solve complex robotic vision problems using multi-modal sensor fusion and deep learning techniques and apply in healthcare.

Selected Publications

1. Samuel Claflin, Mohammad Arif Ul Alam, A Low-Cost Radar-based Domain Adaptive Breast Cancer Screening System, IEEE MIT Undergraduate Research Technical Conference (MIT URTC) 2020.
2. Mohammad Arif Ul Alam, Fernando Mazzoni, Md Mahmudur Rahman, LAMAR: Lidar based Adaptive Multi-inhabitant Activity Recognition, EAI Mobiquitous 2020.
3. Mohammad Arif Ul Alam, Sarah Holmes, Nirmalya Roy, A. Gangopadhya, E. Galik, AutoCogniSys: IotAssisted Cognitive Health Assessment of Older Adults, arXiv:2003.07492, EAI Mobiquitous 2020.
4. Mohammad Arif Ul Alam, AI-Fairness Towards Activity Recognition of Older Adults, EAI Mobiquitous 2020.
5. Mohammad Arif Ul Alam, Dhawal Kapadia, LAXARY: A Trustworthy Explainable Twitter Analysis Model for Post-Traumatic Stress Disorder Assessment, IEEE SmartComp 2020.
6. Mohammad Arif Ul Alam, Aliza Heching, Nicola Palmarini, Scaling Longitudinal Functional Health Assessment in Multi-Inhabitant Smarthome, IEEE International Conference on Distributed Computing Systems (ICDCS 2019)
7. Lee Martie, Mohammad Arif Ul Alam, Gaoyuan Zhang, Ryan R. Anderson, Reflecting After Learning for Understanding, Seventh Annual Conference on Advances in Cognitive Systems, MIT, Cambridge, 2019.
8. Mohammad Arif Ul Alam and Nirmalya Roy. Unseen Activity Recognition: A Hierarchical Active Transfer Learning Approach, in Proceedings of the 37th IEEE International Conference on Distributed Computing (ICDCS 2017), Atlanta, USA, June 2017.
9. Mohammad Arif Ul Alam, Nirmalya Roy, Archan Misra, Joseph Taylor, CACE: Exploiting Behavioral Interactions for Improved Activity Recognition in Multi-Inhabitant Smart Homes, International Conference on Distributed Computing Systems (ICDCS) 2016, Nara, Japan.
10. Mohammad Arif Ul Alam, Nilavra Pathak, Nirmalya Roy, Mobeacon: An iBeacon-Assisted smart-phoneBased Real Time Activity Recognition Framework, MobiQuitous 2015, Coimbra, Portugal

Selected Intellectual Property

1. Nirmalya Roy, Sajjad Hossain and Mohammad Arif Ul Alam, Scalable Activity Recognition for Independent Living Applications, UMBC Ref. No. 2015-004
2. Susann Marie Keohane, Scott Gerard, Aliza Heching, Samuel Scott Adams, Mohammad Arif Ul Alam, System to map and interpret sensors firing patterns in a physical space to identifying causes of anomalies
3. Mohammad Arif Ul Alam, Scott Gerard, Susann Marie Keohane, Aliza Heching, Cognitive Stress Assessment
4. Scott Gerard, Susann Marie Keohane, Aliza Heching, Mohammad Arif Ul Alam, Sensor2Vec: Aggregating sensor data to construct a home-independent sensor vector for improved machine learning
5. Scott Gerard, Susann Marie Keohane, Aliza Heching, Mohammad Arif Ul Alam, Interpreting Sensor Transmission Patterns To Analyze Anomalies in a Smart Environment
6. Peter Fay, Mohammad Arif Ul Alam, Lee Martie, Gaoyuan Zhang, Nicola Palmarini, Dynamic Personalization of Mobile Device for People with Disabilities

Selected Contracts, Fellowships, Grants and Sponsored Research

1. National Institute of Health (NIH) (NIH R01 HL125089-01) PI: Hong Yu, Co-Investigator: Mohammad Alam, Title: EHR Anticoagulants Pharmacovigilance Award: Amount $4.3 million Period: 2015-2021
2. University of Massachusetts Lowell (Seed Grant), Category: Research Partnerships Leading to Understanding of the COVID-19 Pandemic Title: Monitoring The Voices of Nurses in Social Media During Pandemic, Ainat Koren, Lisa Abdallah, Benyuan Liu, Mohammad Alam Award: Amount 10,000.00 USD Period 2020 - 2022