Md Shaad Mahmud

MD Shaad Mahmud

Associate Professor
Phone: (603) 862-1326
Office: Kingsbury Hall, Durham, NH 03824
Websites:
The advancement in wireless body sensor network and micro fabrication techniques have created a great opportunity for using miniaturized wireless microelectronic devices in a variety of health and life science applications. With big data and machine learning exponential growth in healthcare and clinical treatments, accurate analysis of clinical data helps in early disease detection, patient care, and community services. Keeping this mind, our research interests lie in 1) designing and implementing novel sensors and remote health monitoring systems, (2) IoT based wearable biosensor for personalized mobile health, (3) reliable and secure data communication, and (4) early disease detection using machine learning.

Courses Taught

  • ECE 583: Designing w/Programmable Logic
  • ECE 649: Emb Microcomputer Based Design
  • ECE 715/815: Introduction to VLSI
  • ECE 791/791H: Senior Project I
  • ECE 792/792H: Senior Project II
  • ECE 796/896/993: Special Topics
  • ECE 900: R&D Concept to Communication
  • ECE 900A: R&D Concept to Communication 1
  • ECE 900B: R&D Concept to Communication 2
  • ECE 925: Biosensors
  • ECE 992: Adv Topics Electrical Engineer
  • ECE 999: Doctoral Research
  • NSB 799H: Honors Senior Thesis

Education

  • Ph.D., Electrical and Communication Engineering (ECE), University of Massachusetts - Dartmouth
  • M.S., Electrical and Communications Engineering (ECE), University of Massachusetts - Dartmouth
  • B.S., Electrical and Electronics Engineering (EEE), American International University Bangladesh (AIUB)

Research Interests

  • Artificial Intelligence/Cybernetics
  • Big Data
  • Biochemical Engineering
  • Bioengineering
  • Human-Machine Interface
  • Medical Biotechnology Diagnostics (incl. Biosensors)
  • Mobile Health (mHealth)

Selected Publications

  • Keesee, A. M., Pinto, V., Coughlan, M., Lennox, C., Mahmud, M. S., & Connor, H. K. (2020). Comparison of Deep Learning Techniques to Model Connections Between Solar Wind and Ground Magnetic Perturbations. FRONTIERS IN ASTRONOMY AND SPACE SCIENCES, 7. doi:10.3389/fspas.2020.550874

  • Mahmud, M. S., Fang, H., & Wang, H. (2019). An Integrated Wearable Sensor for Unobtrusive Continuous Measurement of Autonomic Nervous System. IEEE INTERNET OF THINGS JOURNAL, 6(1), 1104-1113. doi:10.1109/JIOT.2018.2868235

  • Mahmud, M. S., Wang, H., Kim, Y., & IEEE. (2019). Accelerated Prediction of Bradycardia in Preterm Infants Using Time-Frequency Analysis. In 2019 INTERNATIONAL CONFERENCE ON COMPUTING, NETWORKING AND COMMUNICATIONS (ICNC) (pp. 468-472). Retrieved from https://www.webofscience.com/

  • Mahmud, M. S., Fang, H., Wang, H., Carreiro, S., & Boyer, E. (2018). Automatic Detection of Opioid Intake Using Wearable Biosensor.. In Int Conf Comput Netw Commun Vol. 2018 (pp. 784-788). United States. doi:10.1109/ICCNC.2018.8390334

  • Mahmud, M. S., Fang, H., Carreiro, S., Wang, H., & Boyer, E. W. (2018). Wearables technology for drug abuse detection: A survey of recent advancement. Smart Health.

  • Mahmud, M. S., Wang, H., & Fang, H. (2018). SensoRing: An Integrated Wearable System for Continuous Measurement of Physiological Biomarkers. In 2018 IEEE International Conference on Communications (ICC) (pp. 1-7). IEEE.

  • Mahmud, M. S., Wang, H., Esfar-E-Alam, A. M., & Fang, H. (2017). A wireless health monitoring system using mobile phone accessories. IEEE Internet of Things Journal, 4, 2009-2018.

  • Mahmud, M. S., Wang, H., & Fang, H. (2017). Design of a Wireless Non-Contact Wearable System for Infants Using Adaptive Filter. In Proceedings of the 10th EAI International Conference on Mobile Multimedia Communications (pp. 83-88). ICST (Institute for Computer Sciences, Social-Informatics and ….

  • Mahmud, M. S., Wang, H., Alam, E. E., & Fang, H. (2016). A real time and non-contact multiparameter wearable device for health monitoring. In 2016 IEEE Global Communications Conference (GLOBECOM) (pp. 1-6). IEEE.

  • Mahmud, M. S., Wang, H., & Kim, Y. (2016). Real time non-contact remote cardiac monitoring. In 2016 IEEE International Conference on Communications (ICC) (pp. 1-6). IEEE.

View All
  • Most Cited Publications