Research

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): He received his PhD in Computer Science from the University of Southampton, UK, an MS in Advanced Computer Science from the University of Birmingham, UK, and a BS in CIS from the American College of Greece, Deree College, where he was a recipient of the Mani Scholarship. Prior to joining Tarleton State University in August 2018, Sotirios was a senior researcher at the University of Nevada, Reno, performing research in perception for autonomous vehicles. Before that, he worked on target recognition and tracking, as well as multiple-view geometry algorithms for camera-laser calibration, as a senior researcher at Athens Information Technology and a research associate at the Femto-St Institute in Besançon, France. Earlier, he was a postdoctoral research associate at the University of Nebraska at Omaha, conducting research on robot navigation funded by the Office of Naval Research (ONR), and a BK21 (Brain Korea) postdoctoral research associate at Pusan National University in Pusan, South Korea, working at the intersection of robotics and computer vision.

Sotirios’ research interests span the entire spectrum of robotics and computer vision. His focus areas include active vision, robot navigation, perception for autonomous systems (UGVs, UAVs), machine learning, deep neural networks, and parallel algorithms for high-performance computing. At TSU, his research has been funded by NASA as part of the University Nanosatellite Program (UNP). He has also received the Faculty Excellence in Scholarship Award and the Outstanding Junior Faculty Award.

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. 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.

Luis Anselmo Zarza-Lopez (Computer Science): He is a Doctorate in Telematics Engineering candidate, with extensive academic experience as an instructor and researcher at prestigious institutions such as the Universidad Tecnológica de la Mixteca. With a strong educational background, including a Master of Science in Computing Systems Engineering and a Bachelor’s in Electronics and Communications Engineering, he brings expertise in areas such as interactive media, computing engineering, and telematics. He has five publications in security protocols and genetic algorithms. His previous experience includes server installation and configuration, database management, and information systems, and he is certified in logic programming, cryptography, and quantum computing. His past projects include a program that generates security protocols using genetic algorithms, and a three-dimensional graphic simulator of computer networks.