Michael B. Rahaim is a Researcher at Boston University , specializing in Optical Wireless Communication (OWC), Visible Light Communication (VLC), and Hybrid RF/VLC Networks . His work focuses on interference mitigation , dynamic field-of-view (FOV) receivers , and integration with 5G systems . He has developed open-source tools like the gr-owc toolkit for optical wireless research and extended ns-3 network simulator for VLC. His collaborations include researchers such as Thomas D. C. Little , Hany Elgala , and Abdallah Khreishah . His scientific contributions span MAC protocol design , outage probability analysis , and low-cost IoT communication systems . He has not been explicitly associated with teaching or administrative roles in the provided records.
Sotirios Karabetsos serves as a Lecturer at the Department of Electrical and Electronic Engineering, University of West Attica, specializing in Voice Signal Processing Systems and Broadband Data Communications. His academic journey includes a PhD from the National Technical University of Athens (NTUA) and advanced studies at Brunel University, London. PhD, School of Electrical & Computer Engineering, NTUA (2004-2010) MSc in Data Communication Systems, Brunel University (2001-2003) Diploma in Electrical and Computer Engineering, NTUA (2000-2004) Electronic Engineering Degree, TEI of Athens (1995-1999) His research spans Broadband telecommunications , Software Defined Radio , Digital Signal Processing , and Machine Learning applications. His work focuses on innovative communication systems including wired, wireless, and optical networks, with particular emphasis on signal processing for voice and data transmission. Recent publications demonstrate expertise in Radio over Fiber technologies, multicore fiber applications, machine learning for transportation, and advanced speech synthesis techniques. His work bridges theoretical research with practical implementations in next-generation communication systems. As an educator, Dr. Karabetsos teaches undergraduate courses including Telecommunications, Wideband Transmission Technologies, and Digital Audio and Speech Technologies, along with postgraduate courses on 4G/5G Communication Systems and Software Defined Radio. His laboratory work spans Buildings A and Z at the Ancient Olive Grove Campus, where he conducts research in signal processing and communication systems. Office hours are held Mondays and Wednesdays from 14:00-15:00, with additional availability upon request.
Hovannes Kulhandjian is an Associate Professor in the Department of Electrical and Computer Engineering at California State University, Fresno (Fresno State), within the Lyles College of Engineering. He teaches undergraduate and graduate courses in electrical and computer engineering and conducts research in wireless communications, applied machine learning, and their applications in transportation and agriculture. His educational background includes: Ph.D. in Electrical Engineering from the State University of New York at Buffalo (2014) M.S. in Electrical Engineering from the State University of New York at Buffalo (2010) B.S. in Electronics Engineering with high honors (magna cum laude) from the American University in Cairo (2008) Dr. Kulhandjian's research spans wireless communications, applied machine learning, and their applications. His work in intelligent transportation systems includes AI-based road inspection and pedestrian detection, while in precision agriculture, he develops drone-based systems for weed detection and tree health monitoring. He also explores underwater acoustic communications, visible light communications, and physical layer security. His recent publications demonstrate a strong trend in applying artificial intelligence to solve real-world problems in transportation and agriculture, often using drones and multi-sensor fusion. In communications, he advances techniques for next-generation wireless systems, including OTFS and NOMA for 6G, and optical wireless for IoT. Scientific awards and honors: IEEE Senior Member Outstanding Reviewer Award from ELSEVIER Ad Hoc Networks Outstanding Reviewer Award from ELSEVIER Computer Networks Claude C. Laval Award for Innovative Technology and Research Dr. Kulhandjian advises Master's students through thesis (ECE 299) and project (ECE 298) courses. His research is supported by multiple grants, including the Department of Defense Research and Education Program, NSF-ADVANCE Research Alliance Seed Grant, CSU-WATER Faculty Research Incentive, and the Fresno State Transportation Institute SB1 Research Grant for six consecutive years. During his doctoral studies, he worked in the Wireless Networks and Embedded Systems (WiNES) Laboratory at SUNY Buffalo. At Fresno State, he leads a research group focused on the development of innovative solutions in wireless communications and AI applications, collaborating with various institutions and industry partners.
Paul R. Prucnal is a Professor of Electrical and Computer Engineering at Princeton University and an Associated Faculty member in the Princeton Materials Institute (PMI). He directs the Lightwave Communications Research Laboratory, where he leads cutting-edge research in photonics, optical communications, and neuromorphic computing. Education: Ph.D., Columbia University, 1979 M.Phil., Columbia University, 1978 M.S., Electrical Engineering, Columbia University, 1976 A.B., Math and Physics, Bowdoin College, summa cum laude, 1974 Professor Prucnal's research focuses on ultrafast optical techniques with applications to communication networks and signal processing. His group investigates several key areas including physical (optical) layer network security, optical code division multiple access (CDMA), nonlinear optical signal processing for ultrafast networks, optical cancellation of RF interference, and the development of photonic neurons that operate a billion times faster than biological neurons. His work bridges the gap between photonics device physics and neural networks, pioneering the field of neuromorphic photonics. His recent publications reveal a strong trend toward neuromorphic photonics and brain-inspired optical computing. The research spans from fundamental optical physics to practical applications in secure communications and ultrafast signal processing, with emphasis on photonic neural networks, optical encryption techniques, silicon photonics implementations, and optical systems that emulate biological neural functions. Scientific Awards: National Academy of Inventors Fellow (2017) The President's Award for Distinguished Teaching, Princeton University (2015) Lifetime Achievement Award for Excellence in Teaching, Engineering Council, Princeton University (2015) School of Engineering and Applied Science Distinguished Teaching Award, Princeton University (2009) Fellow of the OSA (1997) Fellow of the IEEE (1992) Rudolf Kingslake Medal and Prize, SPIE (1990) Professor Prucnal has mentored numerous graduate students including Eric Blow, Eli Doris, Thomas Ferreira de Lima, Yusuf Jimoh, Hyuma Umeda, Yuxin Wang, Ben Wu, Lei Xu, and Jiawei Zhang. His research has been supported through collaborations with government and industrial research laboratories, focusing on next-generation optical signal processing, computing, and communications systems. His lab has produced significant innovations including graphene-based laser neurons and optical implementations of biological neural processing. The Lightwave Communications Research Laboratory offers students opportunities to work on innovative projects at the intersection of photonics, communications, and neural computing. Current research includes developing photonic neurons for machine learning applications, optical security techniques for fiber networks, and neuromorphic photonic systems that emulate visual, auditory, and motor functions found in biological organisms.
Mahmoud Al-Quzwini is a Senior Lecturer at the Charles V. Schaefer, Jr. School of Engineering and Science at Stevens Institute of Technology. He is affiliated with the Department of Electrical and Computer Engineering and has served on multiple university committees, including the Faculty and Staff Award Committee, University Lab Safety Committee, and Undergraduate Curriculum Committee. Courses taught include ENGR 245, ENGR 232, EE 548, and EE 556. His research interests span network protocols, adaptive filtering, wireless communication, and non-destructive testing of infrastructure. He has contributed to publications in areas such as spectral analysis pedagogy, MANET routing protocols, MPLS network performance, and advanced MC-CDMA receiver design. Honors and Awards: ECE Outstanding Teaching Award for Faculty Professional Societies: American Society for Engineering Education (ASEE)
Driss Benhaddou is a Professor in the Engineering Technology Department at the University of Houston, affiliated with the Cullen College of Engineering. He holds dual Ph.D.s in Electrical Engineering and Opto-Electronic Engineering. His research focuses on optical networking, sensor networks, and optical instrument development, with expertise in multi-protocol internetworking (SONET, ATM, IP) and network simulation. Education: Ph.D., Interdisciplinary in Electrical Engineering and Telecommunications Networking, University of Missouri (2002) Ph.D., Opto-Electronic Engineering, University of Montpellier II (1995) M.S., Opto-Electronics, University of Montpellier II (1991) B.S., Electronics, University of Abdelmalek Esaadi (1990) Research Interests: Optical networking and switching design Defect recognition in semiconductors using optical instruments Protocol development for GMPLS-based optical domains Remote laboratory development for optical circuits (funded by NSF and FDIP) Awards: 2006 Best Paper Candidate (ICCCN) 2004 FASEB/MARC Travel Award 2002 VPI Systems Speed Up Photonics Award Finalist Grants & Advising: Directed $1.17M in funded projects, including NSF, SBC, and NASA grants Mentored 11+ graduate students in optical networking, CDMA, and VoIP Developed new courses (Embedded Systems, Optical Circuits) and spearheaded the Optical Networking Research Lab Labs & Teams: Director of the Wireless and Optical Networking Lab at UH Collaborator on remote optical circuits labs with University of Colorado and Louisiana
Goran Lj. Djordjevic is a Professor at the Department of Electronics, Faculty of Electronic Engineering, University of Nis, Serbia. Appointed full professor in 2009 after progressive promotions from assistant professor (1999) to associate professor (2004), he represents a cornerstone of the institution where he completed all academic degrees. His three-decade career exemplifies deep institutional commitment and scholarly excellence in electronic engineering. His academic foundation was built entirely at the University of Nis: Diploma Engineer in Electronics (1989) Master of Science in Electronics (1994) Doctor of Philosophy in Electronics (1998) Professor Djordjevic's research forms three interconnected pillars: Networks-on-Chip (NoC) innovation with breakthroughs in deflection routing and port allocation; UWB localization systems solving multipath challenges in complex indoor environments through multi-algorithm fusion; and error control coding for storage systems with applications in optical media. His work consistently bridges theoretical rigor and practical implementation, evidenced by 22 impact-factor journal publications spanning VLSI design, wireless communications, and parallel computing. Analysis of his publication timeline reveals strategic evolution: recent work (2021-2022) focuses on real-world NoC optimization and robust indoor positioning, mid-career research (2015-2005) established CDMA bus architectures and fault-tolerance frameworks, while foundational contributions (2001, 1996) in constraint coding and task scheduling underpin his later breakthroughs. This trajectory demonstrates exceptional continuity in advancing communication reliability across hardware and software domains. Scientific recognition includes: No formal awards documented in source materials Regarding academic mentorship, while specific students aren't listed, his sustained research output implies active graduate supervision. Project funding shows zero current national grants, though international collaborations remain unspecified. His 22 impact-factor publications across IEEE, Elsevier, and Springer journals demonstrate consistent productivity through completed research initiatives, with recent work indicating ongoing laboratory activity in wireless and NoC domains.
Prof. Catherine LEPERS is a Professor at Telecom SudParis, affiliated with the SAMOVAR research group and the ISTeC school. Her work focuses on optical communications, telecommunication networks, and machine learning applications in network management. She has contributed to advancements in fault prediction, optical amplifier control, and OCDMA systems design. Her research also spans fiber optics, nonlinear signal processing, and environmental toxicology studies on particulate matter. Her research interests emphasize integrating machine learning into optical network optimization, addressing challenges like spectrum fragmentation and power excursions. She has published widely in IEEE Transactions, Journal of Lightwave Technology, and other optical communication journals. Recent work includes a 2023 survey on machine learning for heterogeneous network fault prediction and a 2024 thesis on predictive network equipment maintenance. She advises students like Killian Murphy and collaborates on projects involving reinforcement learning and optical signal processing. No academic awards are explicitly listed, but her extensive publication record reflects her research impact.
Dr. Chao Xu is a Senior Lecturer at the Next Generation Wireless Research Group within the Faculty of Physical Sciences and Engineering at the University of Southampton. His work bridges cutting-edge wireless communication technologies with quantum security and machine learning advancements. PhD in Wireless Communications (University of Southampton, 2015) His research spans space-air-ground integrated networks (SAGINs), reconfigurable intelligent surfaces (RIS), and quantum key distribution (QKD). Key projects include holographic MIMO systems and OTFS modulation for THz channels, emphasizing integrated sensing and communication frameworks. Recent publications highlight innovations in optical RIS for secure QKD, near-field transceiver design, and machine learning-aided detection techniques. These works reflect interdisciplinary trends merging wireless systems with quantum cryptography and AI-driven optimization. IEEE Communications Society Best M.Sc. Student (2009) Chinese Government Award for Outstanding Self-Financed Student Abroad (2012) Dean's Award, University of Southampton (2017) MSCA Global Postdoctoral Fellowship (2023, 100/100 score) Dr. Xu supervises PhD students in wireless communications and actively contributes to the Next Generation Wireless Research Group's advancements in 6G technologies and non-terrestrial networking.
Mehdi Shadaram is a Professor in the Department of Electrical and Computer Engineering at the University of Texas at San Antonio (UTSA), where he holds the Janey and Dolph Briscoe Distinguished Professorship. He has served in leadership roles including Founding Director of the Center for Excellence in Engineering Research and Education (CEERE) and Interim Dean of Engineering (2013-2014). Ph.D., Electrical Engineering, University of Oklahoma (1984) His research spans optical fiber communications , photonic millimeter-wave generation , wireless networks , and engineering education . Recent work focuses on radio-over-fiber systems , probe beam deflection imaging , and cognitive radio networks . Funded by organizations like NASA and NSF, he has secured over $10M in grants. Key awards include the 2017 UTSA President’s Distinguished Achievement Award, 2009 UTSA College of Engineering Research Award, and NASA’s 1993 monetary award. He leads the UTSA Fiber Optic Research Laboratory, equipped with advanced photonics tools.
Renaud Gabet is an Assistant Professor (HDR) at Télécom Paris (formerly École Nationale Supérieure des Télécommunications) in the Department of Communications and Electronics (Comelec). He is part of the Optical Telecommunications research team within the Information Processing and Communication Laboratory (LTCI). His academic background includes an engineering degree from ENSSAT, a Master's in Electronics and Optronics from the University of Western Brittany, a Ph.D. from the University of Rennes, and an HDR from Pierre and Marie Curie University. His research focuses on optical telecommunications, distributed fiber optic sensors (Brillouin, Rayleigh, Raman), structural characterization of photonic components, and novel optical metrology techniques (OLCR, OFDR). He teaches courses such as Optics and Photonics (COM 101), Optical Communications (TELECOM 203), Optical Systems (COM 340), and Optical Devices and Nanotechnologies (COM 341). Gabet's publications emphasize advanced fiber sensing, photonic crystal waveguides, laser dynamics, and optical characterization methods. His work frequently addresses industrial applications like pipeline vibration monitoring and telecommunications.
Dr. Nasim Ahmed is a Lecturer at the School of Computer Science, The University of Sydney. His research bridges data science, artificial intelligence, and healthcare, with applications in medical diagnostics, agriculture, and data security. He earned a Ph.D. in Computer Science from Massey University (2022) and an MSc in Computer Engineering from University Malaysia Perlis (2009). Data science applications in healthcare and agriculture Big data clusters and performance modeling AI in education policy and industry applications Network security and optical communication systems His recent publications focus on federated learning for lung cancer detection, deep learning for melanoma prediction, and machine learning for chronic kidney disease risk assessment. Articles also explore big data job runtime prediction, optical CDMA/WDM systems, and Spark/Hadoop performance optimization. Nasim Ahmed holds professional memberships, including Senior IEEE and IET, and is a Chartered Engineer (CEng) accredited by the UK Engineering Council.
Michel Kulhandjian is a researcher specializing in Wireless Communication and Machine Learning applications. His work spans NOMA Systems , RF Fingerprinting , and Drone-Assisted Sensing across academic institutions. Key collaborations with Carleton University , Carleton University , and University of Ottawa researchers Active in 5G/6G technologies and IoT Security since 2018 His recent articles focus on: 2024 : Pedestrian detection, drone-based tree health monitoring, and industrial IoT security 2025 : AI-powered agricultural robotics Scientific contributions include: Code design for OTFS-NOMA systems Low-complexity detection algorithms 3D CNN frameworks for signal analysis RF Fingerprinting under impaired channels
Dr. José Manuel Villadangos Carrizo serves as an Associate Professor in the Department of Electronics at the University of Alcalá, Spain, actively contributing to the GEINTRA research group (Electronic Engineering Applied to Intelligent Spaces and Transport). He obtained his PhD from the University of Alcalá in 2013 with a dissertation on wide-coverage ultrasonic local positioning systems using encoding techniques, supervised by Dr. Jesús Ureña Ureña and Dr. Juan Jesús García Domínguez. His research centers on indoor/outdoor positioning technologies utilizing ultrasonic, infrared, and BLE systems, with specialized focus on non-intrusive elderly monitoring, dementia care, and behavioral pattern analysis. He develops sensor fusion algorithms, high-rate acquisition systems, and hardware architectures for real-world applications in smart environments. Analysis of his 2021-2025 publications reveals a strong trajectory toward healthcare-integrated positioning systems, particularly improving data availability through multi-sensor fusion (e.g., infrared-ultrasonic combinations) and extending tracking capabilities from indoor to outdoor environments for vulnerable populations. No scientific awards are documented in the provided materials. While his research output indicates significant project involvement, specific details regarding student advising or research grants remain unavailable in the source information. He maintains active research leadership within GEINTRA, which develops electronic engineering solutions for intelligent transportation and ambient-assisted living systems.
James S. Lehnert is a Professor at the School of Electrical and Computer Engineering , Purdue University, where he has been since 1984. He holds a B.S., M.S., and Ph.D. from the University of Illinois at Urbana-Champaign (1978, 1981, 1984). His research focuses on spectrum management , CDMA systems , channel estimation , and spread spectrum communications . He has led projects for DARPA, NSF, and the Air Force Office of Scientific Research, collaborating with institutions like the University of Michigan and Ohio State University. He has authored numerous articles in top journals like IEEE Transactions on Communications and IEEE Journal on Selected Areas in Communications . His awards include the IEEE MILCOM Lifetime Achievement Award (2009) and recognition as a Highly Cited Researcher (2000-2010). He is also a Fellow of the IEEE for contributions to spread-spectrum communications. Dr. Lehnert has advised over 30 graduate students, many of whom now hold prominent roles in academia and industry. He teaches advanced courses such as ECE544: Digital Communications and ECE639: Error Control Coding . His research group operates the Spread Spectrum and Satellite Communications Research Laboratory (S3CRL).
