Our research primarily falls under the umbrella of multi-sensor data fusion (MSDF) or data fusion — a broad interdisciplinary field that can be (loosely) defined as "... a multi-level, multi-faceted process dealing with the automatic detection, association, correlation, estimation, and combination of data and information from multiple sources," (US Department of Defense, 1991). While much of early MSDF research & developments were focused around defense and space exploration applications, data fusion has slowly moved into mainstream with recent growth and popularity of ubiquitous sensing & computing methods. In addition, as a key enabler of smart, intelligent and connected capabilities in many up-and-coming technologies, such as intelligent transportation systems (ITS), internet-of-things (IoT), and smart infrastructure systems, data fusion is likely to be a household term in the near future.
From multi-domain battles to intelligent transporation systems, next-gen technologies envision cross-domain synergy and perfect harmony between humans and machines to achieve truly smart, aware and connected behavior. A fundamental tenet to such capability is the ability to integrate inputs/outputs from both humans (i.e., soft data) and machines (i.e., hard data) to carry out numerous estimation, detection, inference, and decision-making tasks in a swift, systematic and robust fashion. With this vision in place, by drawing from signal processing, control, machine learning, probability theories, and various branches of mathematics, we focus on developing novel data fusion with a particular emphasis on the use of ubiquitous sensing and computing for situational awareness applications, both in defense and civilian domains.
Primarily in modeling, estimation & detection, inference, and decision-making tasks in data-driven computational and engineered systems
Signal processing for big-data, with an emphasis on uncertainty handling in stream-processing environments
Intelligent Transportation Systems (ITS), with a focus on safety, efficiency and infrastructure
Distributed inference in highly dynamic networks with a focus on opinion dynamics and influence propagation
Smart Infrastructure Systems and Cyber-Physical Systems, with an emphasis on detection of anomalies and failure precursors, deception-aware processing
We are currently looking for creative, highly-motivated and self-activated students to join our group. If interested in joining,
Check out our research and other data fusion work in defense, automotive, robotics, and healthcare domains.
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More details on current openings and the kind of students that we are looking for is described here.
Projects and publications illustrative of our research
Our research group members come from all over the world and bring different experiences, skills and backgrounds. We welcome highly motivated students with various backgrounds, but priority will be given to those who best match ongoing or upcoming projects. Read this to see if you match our interests and vice versa.
Thanuka Wickramarathne, Ph.D.
I've always been fascinated by creative processing of signals, whether its music, images or Radar. For complex processing tasks involving signals generated by disparate multi-modal sensors, including soft (i.e., human-based) and hard (i.e., physics-based) sensors, multi-sensor data fusion provides a perspective on how one may systematically organize, simplify and tackle the required processing. While such tasks have always been around in the defense community, recent highly data-driven trends are slowly bringing these notions into the mainstream. With a particular interest in enhanced situational awareness with ubiquitous sensing, I work in the general area of multi-sensor data fusion involving both soft and hard sensors.
Dr. Wickramarathne is currently a tenure-track Assistant Professor with the Department of Electrical & Computer Engineering at University of Massachusetts Lowell. Previously, he was Research Assistant Professor in the Departments of Electrical Engineering and Computer Science & Engineering at the University of Notre Dame, Engineering Intern with the DSP group at Motorola Solutions (Plantation, FL) and RNP Engineer (short stint) at Celltel Lanka (now Etiselat, in Sri Lanka). He received his B.Sc. in Electronics and Telecommunication Engineering from University of Moratuwa, Sri Lanka and both of his MS and PhD degrees in Electrical & Computer Engineering from University of Miami, Coral Gables, FL. He is a Senior Member of IEEE and currently serves on the Board of Governers of IEEE Vehicular Technology Society (VTS) and Administrative Committee of IEEE Sensors Council.
Dr. Wickramarathne grew up with his parents and two younger siblings in the beautiful island of Sri Lanka. He enjoys competitive sports and weekend projects, played competitive Table Tennis (20+yrs ago), was a practitioner of Kyokushin-Kai Kan for 10+yrs (and planning to get back into it after tenure ☺). He's now an avid Tennis player, occasional skier, amateur drummer, and a cyclist.
Feel free to contact us about our research, potential collaborations or joining the group. Prof. Wick is best reached via email and please make sure to include a descriptive subject line.
Department of Electrical & Computer Engineering
University of Massachusetts Lowell
One University Avenue, Lowell, MA 01854 USA
+1 (978) 934-5375