Matthew Burlick

Matthew Burlick is an Associate Teaching Professor in the Department of Computer Science at Drexel University's College of Computing and Informatics. His academic background includes a PhD and MS in Computer Science from Stevens Institute of Technology and a BS in Electrical Engineering with a concentration in Computer Engineering from the University of Delaware. He previously served as an Assistant Professor at Stevens Institute of Technology, where he taught undergraduate courses in scientific computing, discrete structures, algorithms, and interactive computer graphics.

Dr. Burlick's research focuses on real-time multi-sensor fusion for detection and classification, with strong emphasis on machine learning, computer vision, and image processing. His work involves developing feature vectors, building classifiers, and creating novel clustering algorithms that leverage temporally relative data. Key areas include object detection, spatio-temporal tracking, unsupervised dynamic class discovery, and applications in biomedical imaging and acoustics.

The available information does not list any recent publications, but his research profile suggests a strong trend in applied machine learning and real-time systems, particularly in multi-modal and multi-sensor environments spanning computer vision and signal processing domains.

Dr. Burlick has been involved in teaching core computer science curriculum and co-taught a senior capstone design course with a software engineering focus. There are no listed scientific awards or fellowships in the provided material.

He has extensive experience in both academic instruction and applied research, particularly in developing real-time systems for detection and classification tasks. While no formal advisees or grants are mentioned, his background indicates a deep engagement with undergraduate education and practical software engineering training through capstone project supervision.

His work bridges theoretical computer science with practical engineering applications, particularly in the domains of real-time data processing and intelligent systems. Though specific labs or research teams are not named, his expertise implies involvement in projects requiring interdisciplinary collaboration in computing, signal processing, and potentially biomedical engineering.