Research Areas

Dr. Haitham Abu Ghazaleh (Electrical Engineering): He received his BEng in Electronics and Electrical Engineering from the University of Manchester, UK in 1999, his M.Sc. and Ph.D. in Electrical and Computer Engineering from the University of Manitoba in 2006 and 2010, respectively. He further worked as a graduate student researcher at TRLabs Winnipeg and was involved in the research areas of wireless networking for eHealth and telemedicine applications. Between 2009 and 2015, he worked in the Network Planning and Engineering department at MTS Allstream. His research interests are in the areas of wireless communication systems, network teletraffic modeling and performance analysis, queueing systems, adaptive network resource management, mobility in future generation wireless networks, cognitive radio systems, wireless sensor networks, smart cities and the Internet of Things. He is also a member of the Institute of Electrical and Electronics Engineers (IEEE), and the Association of Professional Engineers and Geoscientists of the Province of Manitoba (APEGM).

Dr. Mircea Agapie (Computer Science): He received the Electrical Engineer diploma from the Politehnica University of Bucharest, Romania in 1992, with a thesis in mechatronics. In March-August 1992 he studied on a TEMPUS (Trans-European Mobility Project for University Studies) scholarship in the Dept. of Mechanics, Polytechnic Institute of Turin, Italy, where he conducted research towards his thesis. He received the Ph.D. degree in Computer Science from the University of Missouri – Kansas City, USA, in 2000, with a dissertation on queueing theory (a branch of applied probability), applied to computer and telecommunications networks.

Between 2000 and 2003, he was a network engineer for the MCI company UUNET, where he worked on a variety of projects, including traffic collection, analysis and performance prediction using self-similar statistical models. After joining Tarleton in 2003, he continued research in applied probability (evolutionary algorithms), and also developed an interest in AI, robot navigation, and robot vision – areas in which he mentored numerous students in undergraduate research projects. He helped launch the AI and Data Science concentration in the CS program, and taught courses in machine learning with Python. Since fall 2020, he serves as graduate coordinator and advisor for Tarleton’s M.S. in Computer Engineering program, and teaches graduate courses in advanced computer networks, parallel algorithms and advanced computer architecture. He is a member of the Institute of Electrical and Electronics Engineers (IEEE).

Dr. Sotirios Diamantas (Computer Science): My research interests span the entire spectrum of Robotics and Computer Vision. In particular, my research focus has been on Active Vision, Robot Navigation, Perception of Autonomous Systems, Visual Odometry, Probabilistic Algorithms and Deep Learning. Prior to joining TSU, I was a senior researcher at the University of Nevada, Reno, carrying out research in the area of perception for autonomous vehicles. Before that, I worked on target recognition and tracking, and multiple-view geometry algorithms for camera-laser calibration as a senior researcher at Athens Information Technology and a research associate at Femto-St Institute in Besancon, France.

I have also worked on:

  • Visual metrics and optical-flow based robot navigation while I was a researcher at the University of Nebraska, Omaha (funded by Office of Naval Research), and a Brain Korea (BK21) postdoctoral research fellow at Pusan National University in South Korea.
  • Biologically-inspired robotics and visual odometry, as part of my PhD research at the University of Southampton, UK.

Dr. Emadeldin Elgamal (Computer Science/Cybersecurity): My research interests include network security and wireless networking. More specifically, I am focusing on vehicle to everything communications (V2X). In V2X, a vehicle can communication with another vehicle (V2V), a nearby device such as that carried by a pedestrian (V2P), the network infrastructure (V2I), and the cellular network (V2N). Examples of challenges that face V2X are resource allocation, routing, and transmission power optimization. Security in V2X faces other challenges such as key management, authentication, and preventing denial of service attacks. Currently, I am exploring how to utilize computational intelligence methods to provide near optimal solutions to the V2X resource allocation problem and how to integrate encryptions with channel coding.

Dr. Thejas Gubbi Sadashiva (Computer Science): Dr. Thejas Gubbi Sadashiva has been an Assistant Professor at the Department of Computer Science and Electrical Engineering at Tarleton State University (TSU), The Texas A&M University System, since 2020. His research areas include Machine Learning, Deep Learning, click fraud detection, Human-Computer Interaction (HCI), and Performance Optimization using parallel computing. He directs the Machine Intelligence and Security Research Laboratory (MISR Lab). He worked as a trainee for one year at the Defence Research and Development Organization/Electronic and RADAR Development Establishment (DRDO/LRDE). He worked as an Assistant Professor for five years at Siddaganga Institute of Technology (SIT), India. He is a recipient of the Best Graduate Student in Service Award, Dissertation Year Fellowship Award, two times FIU School of Computing and Information Sciences Travel Award, FIU Graduate and Professional Student Committee (GPSC) travel grant, and Graduate Assistantship award at FIU. Thejas’s research has successfully produced one book chapter, 20 papers in top conferences and journals, and has an Indian Patent. Thejas has served as a mentor and resource person in National Science Foundation (NSF) supported program Research Experience for Teachers (RET, K-12, and Miami-Dade school teachers) for three successive years at FIU. He has also served as a mentor and coordinator for Undergraduate students in Science without Borders summer program for three consecutive years at Discovery Lab. He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and the Association for Computing Machinery (ACM). Elsevier News Board: Based on the work entitled “A hybrid and effective learning approach for Click Fraud detection” have recognized and appeared in Elsevier’s news board as “Curbing the clicking con: The automated detection of click fraud,” 2021. 

Dr. Denise Martinez (Electrical Engineering): She received her BS, MS and PhD in Electrical Engineering from Texas A&M University. She has been faculty at Tarleton since 2001. Her undergrad emphasis area was signal processing and controls, leading to her MS thesis in the area of image processing and error control coding, followed by her PhD dissertation in the area of control systems. She likes the mechanical/electrical engineering blend of control systems, thus enjoys working with undergraduate students on controls projects and applications of Matlab. She also loves teaching, thus another research project area is related to classroom techniques for student engagement and success.

Dr. Eric Wyers (Electrical Engineering): My research interests are in optimization over discrete engineering design spaces, autonomous calibration of complex systems through machine learning, and robust engineering design optimization.

Mr. Ethan Welborn (Computer Science): I’m currently pursuing a Master’s of Science in Computer Engineering degree, and my long-term goal is to earn a Ph.D in Computer Science. My research interests include the fields of Computer Vision, Deep Learning, Autonomous Vehicles and Unmanned Aerial Vehicles (UAVs). I am also interested in Compiler Design and Programming Language Design. I’m currently working on a vehicle detection and tracking system for estimating vehicle speeds using Mask R-CNN and homography techniques. The research project for my Master’s thesis is detecting potholes using images and video from a UAV camera.