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Mohammad Arif Ul Alam

Mohammad Arif Ul AlamAssistant Professor

Research Interests

Cognitive, affective, mobile, pervasive and sensor computing Healthcare, clinical, time series and big data analytics Machine learning, deep learning, data science, optical spectroscopy


  • Ph D: Information Systems, (2017), University of Maryland Baltimore County - Baltimore
    Supporting Area: Health Care and Life Sciences
    Dissertation/Thesis Title: Context-Aware Multi-Inhabitant Functional and Physiological Health Assessment in Smart Home Environment
  • BSc: Computer Science and Engineering, (2011), Bangladesh University of Engineering and Technology - Dhaka, Bangladesh
    Dissertation/Thesis Title: Bangla Speech to Text Conversion Using Dynamic Bayesian Network


Arif is an Assistant Professor of Computer Science at University of Massachusetts Lowell. Prior joining UML, he worked as a Research Staff Member at IBM Research under MIT-IBM Watson AI Lab.

Selected Publications

  • Alam, M.A., Heching, A., Palmarini, N. (2019). Scaling Longitudinal Functional Health Assessment in Multi-Inhabitant Smarthome.
  • Alam, M.A. (2017). Context-Aware Multi-Inhabitant Functional and Physiological Health Assessment in Smart Home Environment.
  • Alam, M.A., Roy, N., Gangopadhyay, A., Galik,, ., Elizabeth, . (2017). Infrequent Non-Speech Gestural Activity Recognition using Smart Jewelry: Challenges and Opportunities for Large Scale Adaptation. Springer-Verlag 2017, New York, USA
  • Taylor, J., Hossain, H.S., Alam, M.A., Khan, Md Abdullah Al Hafiz, ., Roy, N., Galik, E., Gangopadhyay, A. (2017). SenseBox: A Low-Cost Smart Home System.
  • Alam, M.A., Roy, N. (2017). Single BSN-Based Multi-Label Activity Recognition.
  • Alam, M.A., Roy, N. (2017). Unseen Activity Recognition: A Hierarchical Active Transfer Learning Approach.
  • Alam, M.A., Roy, N., Gangopadhyay, A., Galik, E. (2016). A Smart Segmentation Technique Towards Improved Infrequent Non-Speech Gestural Activity Recognition Model. Pervasive and Mobile Computing, (Special Issue on Gerontechnology).
  • Alam, M.A., Roy, N., Holmes, S., Gangopadhyay, A., Galik, E. (2016). Automated Functional and Behavioral Health Assessment of Older Adults with Dementia.
  • Alam, M.A., Roy, N., Misra, A., Taylor, J. (2016). CACE: Exploiting Behavioral Interactions for Improved Activity Recognition in Multi-Inhabitant Smart Homes.
  • Alam, M.A., Pathak, N., Roy, N. (2015). Mobeacon: An iBeacon-Assisted Smartphone-based Real Time Activity Recognition Framework. EAI Endorsed Transactions on Ubiquitous Environments 2015.
  • Roy, N., Hossain, H.M., Alam, M.A. (2015). Scalable Activity Recognition for Independent Living Applications.
  • Alam, M.A., Roy, N. (2014). GeSmart: A Gestural Activity Recognition Model for Predicting Behavioral Health (pp. 193--200).
  • Zaffke, A., Jain, N., Johnson, N., Alam, M.A., Magiera, M., Ahamed, S.I. (2014). ICanLearn: A Mobile Application for Creating Flashcards and Social Stories™ for Children with Autism (pp. 225--230).
  • Williams, D., Alam, M.A., Ahamed, S.I., Chu, W. (2013). Considerations in Designing Human-Computer Interfaces for Elderly People (pp. 372--377).
  • Ge, R., Vogt, R., Majumder, J., Alam, A., Burtscher, M., Zong, Z. (2013). Effects of Dynamic Voltage and Frequency Scaling on a k20 GPU (pp. 826--833).
  • Alam, M.A., Wang, W., Ahamed, S.I., Chu, W. (2013). Elderly Safety: A Smartphone Based Real Time Approach (pp. 134--142).
  • Rahman, F., Hoque, M.E., Ahamed, S.I., Alam, M.A. (2013). Preserving User Privacy in Pervasive Environments with a Collaborative Model (pp. 84--93).