جست‌وجوی استاد و پژوهشگر

Michael Langbergمشاهده پروفایل

استاد

• Information Theory
• Coding Theory
• Network Communication
• +۶ مورد دیگر

Michael Langberg is a Professor in the Department of Electrical Engineering at the University at Buffalo's School of Engineering and Applied Sciences. His research centers on the mathematical foundations of information, focusing on algorithmic and combinatorial challenges in communication, data representation, and storage systems. Langberg's research spans information theory, coding theory, network communication, and network coding, with significant contributions to 'Big Data' representation via geometric clustering and probabilistic methods in combinatorics. His work addresses fundamental problems in point-to-point communication, network reliability, and succinct data structures, emphasizing theoretical rigor while maintaining practical relevance for modern communication systems. Key themes include adversarial channel modeling, secure network coding, and energy-efficient communication protocols. His recent publications (2023-2025) reveal a strong trajectory in adversarial channel theory, secure network coding, and privacy-preserving data analysis. Langberg consistently bridges theoretical information theory with combinatorial optimization, particularly in characterizing capacity limits under adversarial constraints, developing computationally efficient coding schemes, and exploring differential privacy applications in group testing. His work demonstrates increasing interdisciplinary reach, connecting traditional information theory with machine learning systems like federated learning over O-RAN architectures. Scientific Awards: IEEE Fellow Langberg teaches core electrical engineering courses including EE 178 (Digital Principles), EE 439/539 (Information Theory and Coding), and EE 531 (Probability and Stochastic Processes), with consistent offerings through Spring 2026. While the provided text lacks specifics on research grants or student advising beyond course instruction, his extensive publication record indicates active leadership in theoretical communications research. No laboratory or research team affiliations are explicitly mentioned in the source material.

Elias Ezeمشاهده پروفایل

مدرس

• Cyber Security
• Networks and Network Security
• Intelligent Systems
• +۷ مورد دیگر

Dr. Elias Eze is a Lecturer at the Department of Computing and Engineering within the School of Architecture, Computing and Engineering at the University of East London. He joined UEL in July 2022 after working as a Research Fellow and Associate Lecturer at the University of Bedfordshire and an academic at Ebonyi State University in Nigeria. PhD in Computer Science (University of Bedfordshire, 2017) MSc in Computer Networking (University of Bedfordshire, 2012) BSc in Computer Science (Ebonyi State University, Nigeria, 2010) Dr. Eze specializes in Big Data Analytics , Machine Learning , Artificial Intelligence , Network Security , and Cyber Security . His research focuses on applying deep learning and data mining techniques to aquaculture, vehicular networks, and food supply chains. He is a Certified Ethical Hacker (CEH) and an associate member of the British Computer Society. His recent publications emphasize the integration of 5G-IoT connectivity with Big Data Analytics for aquaculture optimization, leveraging Neural Networks in water quality monitoring, and enhancing communication reliability in Vehicular Ad-Hoc Networks (VANETs). Notable projects include the Advancing Digital Precision Aquaculture in China (ADPAC) initiative funded by the Newton Fund, Innovate UK, and BBSRC. Dr. Eze teaches modules such as Computers and Network Security (CN6003) and Big Data Analytics (CN7031). He supervises final-year projects, master's dissertations, and doctoral students.

• Remote Laboratories
• E-Learning
• Vehicular Communications
• +۷ مورد دیگر

Unai Hernandez Jayo is a Lecturer at the University of Deusto's College of Engineering, Bilbao campus, teaching Electronics , Electrical Engineering/Circuits , and Power Electronics in industrial degrees. He serves as Director of the Master's Degree in Industrial Automation, Electronics and Control and has been accredited as Professor by ANECA. His research focuses on remote laboratories , e-learning , and vehicular communications within the DEUSTEK research group (A-rated by Basque Government). Teaches core electronics subjects in industrial engineering Active in educational technology and remote experimentation Develops scalable remote lab architectures and real-time control systems Research Interests include: Remote Laboratories E-Learning and Educational Technology Vehicular Communication Systems Wireless Sensor Networks Smart City Applications Engineering Pedagogy His publications show a strong focus on remote laboratories (especially VISIR platform), vehicular communication protocols , and smart city sensor networks . He has contributed to systematic reviews on extended remote labs and VR/AR techniques in educational experimentation. Academic Contributions : Accredited Professor by ANECA (Spanish quality agency) Holds two active 6-year research periods and one technology transfer period from CNEAI Academic Editor (Sensors journal 2022-2023)

• Security
• Cryptography
• Embedded Systems
• +۴ مورد دیگر

Jerome Lacan is a Professor at the Higher Institute of Aeronautics and Space (ISAE) and Head of the Department of Complex Systems Engineering (DISC). He leads the BLEND research group focused on blockchains for aerospace systems and contributes to the Sysco team. PhD in Computer Science from Paul Sabatier University (Toulouse, France) Accreditation to supervise research (2008) His research spans security and cryptography, with emphasis on: Blockchains for embedded systems (drones, satellites) Threshold cryptography and post-quantum cryptography Secure satellite communications (nano-satellites, authentication) Erasure codes and network coding (TETRYS protocol) His 15 most recent supervised theses (2012–2020) demonstrate expertise in cryptographic protocols, satellite communication reliability, and coding theory. Key themes include blockchain integration in aerospace, erasure coding for multimedia, and cross-layer network optimization. He has supervised 23 theses since 2008, covering topics like physical-layer security, transport protocol interactions, and high-throughput satellite systems.

• Signal Processing
• Wireless Communications
• Adaptive Filtering
• +۳ مورد دیگر

Prof. Dr. Aykut Hocanın is a Professor in the Electrical and Electronic Engineering Department at Eastern Mediterranean University, Faculty of Engineering, in Gazimağusa, Northern Cyprus. He has held various academic and administrative positions at the university since 2000, including Assistant Professor (2000), Associate Professor (2006), Professor (2012), Vice Chairman (2003-2007), Chairman (2007-2014), Dean of the Faculty of Engineering (2014-2020), and Rector of Eastern Mediterranean University (2020-2023). His educational background includes a Ph.D. in Electrical Engineering from Boğaziçi University (1994-2000), an M.Eng. in Electrical Engineering from Texas A&M University (1992-1993), and a B.S.E.E. in Electrical and Computer Engineering from Rice University (1988-1992). Prof. Hocanın's research interests span a wide range of topics in signal processing and communications. His work primarily focuses on adaptive filtering algorithms, wireless communication systems, and signal processing techniques. He has made significant contributions to the development of recursive inverse adaptive filtering algorithms, sparse system identification, and applications in echo cancellation and interference suppression. His research bridges theoretical developments with practical implementations in communication systems. Analysis of his recent publications reveals a strong focus on adaptive signal processing techniques, particularly recursive inverse adaptive filtering algorithms and their applications. His work extends to two-dimensional signal processing, impulsive noise environments, and MIMO systems. The research shows a consistent progression from fundamental algorithm development to practical applications in communication systems. His scientific achievements have been recognized through various scholarships and honors: Fahir İlkel Ph.D Scholarship, Boğaziçi University President's Honor List, Rice University CASP Scholarship from AMIDEAST He is an active member of the scientific community, serving as a reviewer for numerous prestigious journals including IEEE Transactions on Signal Processing and IEEE Transactions on Communications. Prof. Hocanın has supervised numerous graduate students, with many of his publications co-authored with PhD and Master's candidates. He has led research projects, including a TRNC Ministry of Education project on "Adaptive Filtering for Interference Cancellation." His service to the academic community extends to conference organization roles, including Technical Program Chairman for SİU 2013 and Conference co-chairman for ICSCCW 2009. He maintains active professional affiliations as a Senior Member of IEEE (with memberships in Communications Society, Signal Processing Society, and Vehicular Technology Society) and a Senior Member of ACM, demonstrating his standing in the international research community.

• Medical Physics
• Radiation Oncology
• Dosimetric Algorithms
• +۳ مورد دیگر

Premavathy Rassiah, PhD, is a Professor and Chief of Medical Physics in the Department of Radiation Oncology at the University of Utah and Huntsman Cancer Hospital (HCH). She holds a PhD in Medical Physics from the University of Texas Health Science Center at San Antonio (2005) and completed a World Health Organization fellowship at Stanford University Medical Center. She is an active member of the American Association of Physicists in Medicine, American Board of Radiology, American College of Radiology, and Children's Oncology Group. Education: PhD, University of Texas Health Sciences Center Certificate, Stanford University Certificate, Prince of Wales Hospital Certificate, Peter Mac Callum Cancer Institute MS, University Science Malaysia BS, University Science Malaysia Research Focus: Her clinical and research expertise centers on Dosimetric algorithms and Total Body Irradiation (TBI), with emphasis on precision radiation delivery, treatment safety, and technological innovations in radiotherapy. She investigates advanced techniques like stereotactic body radiation therapy (SBRT), brachytherapy protocols, and image-guided systems to optimize cancer treatment outcomes. Publications: Her recent articles (2019–2021) demonstrate a strong focus on radiation therapy safety, dosimetric accuracy, and clinical workflow optimization. Key themes include TBI techniques, brachytherapy standardization, error prevention systems, and advanced imaging technologies. Her work frequently addresses pediatric oncology applications and quality assurance methodologies. Professional Leadership: She leads initiatives in clinical safety, including developing Failure Mode and Effects Analysis (FMEA) checklists for radiation treatment and implementing novel biometric systems to prevent therapy deviations.

Gen-Huey Chenمشاهده پروفایل

استاد

• Graph Theory
• Combinatorial Optimization
• Algorithm Analysis and Design
• +۱ مورد دیگر

Gen-Huey Chen is a Distinguished Professor in the Department of Computer Science and Information Engineering at National Taiwan University, where he has served since 1987 (Associate Professor 1987-1992, Professor since 1992). He previously held leadership roles as Dean of the College of Science and Technology (2001-2005) and Department Chair (2001-2002) at National Chi Nan University. Education Ph.D. in Computer Management Decision, National Tsing Hua University, 1987 B.S. in Computer Science and Information Engineering, National Taiwan University, 1981 Research Interests Professor Chen's work centers on Graph Theory , Combinatorial Optimization , and Algorithm Analysis and Design , with significant contributions to discrete mathematics and network theory. His research bridges theoretical foundations and practical applications, particularly in structural graph problems and wireless network protocols, emphasizing efficient algorithmic solutions for complex computational challenges. Publications Trends His 2007-2009 publications reveal a cohesive research trajectory focused on graph-theoretic applications in networking. Key patterns include structural analysis of specialized graphs (chordal/circular-arc), fault tolerance in multiprocessor topologies (grids/tori), and bandwidth-optimized routing in mobile ad-hoc networks. These works consistently apply combinatorial optimization to solve real-world networking constraints while advancing theoretical graph algorithms. Advising and Grants No specific information regarding student advising or research grant funding is provided in the source material. Laboratory He directs the Discrete Algorithm Lab at National Taiwan University, which specializes in discrete algorithm development and wireless network protocol research.

Romit Roy Choudhuryمشاهده پروفایل

استاد

• Machine Learning
• Signal Processing
• Generative Models
• +۶ مورد دیگر

Romit Roy Choudhury is the Gilmore Family Endowed Professor of Electrical and Computer Engineering (ECE) at the University of Illinois at Urbana-Champaign (UIUC) and an Amazon Scholar since 2022. He earned his Ph.D. in Computer Science from UIUC in 2006 and previously held positions at Duke University, including Associate Professor (2011–2013) and Assistant Professor (2006–2011). His research spans generative models, signal processing, and wearable computing, with a focus on audio denoising, source separation, and spatial inference. Education: Ph.D. in Computer Science, University of Illinois at Urbana-Champaign, 2006. Research Interests: Generative Models, Machine Learning, Sensing, Inverse Problems, Wearable Devices, Localization, and Acoustic Sensing. His lab, Signals and Inference Research Group (SiNRG), explores innovations in audio and sensor-based systems. Publications: Over 50+ peer-reviewed articles, including impactful work on inaudible sound attacks (MobiSys 2017 Best Paper), noise cancellation via IoT (SIGCOMM 2018), and earable computing (MobiCom 2020). Awards: ACM Sigmobile Rockstar Award (2015), IEEE Fellow (2019), NSF CAREER Award (2007), and multiple best-paper recognitions. Teaching: Courses include ECE 438 (Communication Networks), ECE 434 (Real-World Algorithms for IoT), and ECE 101 (Intro to Computing). Labs/Teams: SiNRG at UIUC, collaborations with Amazon, Samsung AI, Intel, and Microsoft Research.

René Glebkeمشاهده پروفایل

پژوهشگر

• Cyber-Physical Systems
• Industrial Control Systems
• Data Communication
• +۳ مورد دیگر

René Glebke is a Researcher at RWTH Aachen University's Communication Systems Group (COMSYS), focusing on Cyber-Physical Systems (CPS). His work emphasizes reliable data communication for industrial control, critical infrastructure, and low-level packet processing. He is affiliated with projects like QuGrids (Quantum-based Energy Grids) and the Cluster of Excellence 2023 Internet of Production. Previously, he contributed to DFG SPP 1914 projects (e.g., REFLEXES, REDeFiNE). Teaching: Organized Practical Internet eXperience (PIX) Lab and seminars on Advanced Internet Technology. Awards: Best Paper (2012), Best Student Paper (2012), and a Best Paper Nomination (2021). Research Trends: Recent articles address energy grids, NILM domain bias, and in-network computing for industrial systems. Advising: Supervised 33 students across Bachelor’s/Master’s theses and 34 seminar topics. Active in lab organization (e.g., Research Focus Class on In-Network Processing). Labs/Teams: Core member of COMSYS, involved in the Internet of Production initiative.

Ibrahim Arefمشاهده پروفایل

مدرس ارشد

• Computer Vision
• Machine Learning
• System-Level Design
• +۷ مورد دیگر

Dr. Ibrahim Aref serves as a Senior Teaching Associate in the Department of Computing and Communications at Lancaster University's School of Computing and Communications, where he has been employed since 2018. Prior to joining Lancaster, he spent approximately three years with the Computer & Electronic Security Systems (CESS) research group at Northumbria University and contributed to the National Priority Research Program (NPRP) No 7-442-1-082 funded by Qatar National Research. Dr. Aref's research demonstrates a clear evolution from traditional hardware and system design toward contemporary AI and machine learning applications. His primary research interests include system-level design and verification, System-On-Chip (SoC) methodologies, high-performance computing, and embedded systems. Since 2016, his focus has significantly shifted toward computer vision and machine learning, with applications spanning medical imaging, biometric identification, and electromagnetic safety. His work bridges theoretical computer science with practical engineering applications, particularly in signal processing, electromagnetic safety, and biometric identification systems. His publication record reveals a growing emphasis on medical imaging applications and healthcare technology, with recent works on ISAR imaging techniques, mobile phone radiation suppression using metamaterials, and SAR simulation for MRI patients. Earlier publications focused on writer identification using deep learning approaches, genetic algorithms, and communication protocol design, showing his diverse research trajectory across multiple technical domains. Best Reviewer Award in ICALT-2021 As an active member of the academic community, Dr. Aref serves on the Technical Committee of the IEEE Technical Community on Learning Technology (TCLT) since March 2022. He regularly contributes as a peer reviewer for numerous international conferences including the IEEE Maghreb Meeting series (2021-2024), Communication Technologies and Cloud Computing Conferences (2021-2024), and IEEE International Conferences on Advanced Learning Technologies (2021-2024). His July 2024 presentation at the 'Natural Language Processing and Artificial Intelligence for Cyber Security' conference at Lancaster University further demonstrates his engagement with cutting-edge research topics at the intersection of AI and security.

Jean-Daniel Medjoمشاهده پروفایل

عضو هیئت علمی

• Wireless Ad Hoc Networks
• Unmanned Aerial Vehicle Networks
• LEO Satellite Networks
• +۵ مورد دیگر

Jean-Daniel Medjo is an Assistant Teaching Professor at Syracuse University , serving as the Director of the Electrical Engineering and Computer Engineering Undergraduate Program. His academic background includes a Ph.D., M.A.Sc., and B.Eng. in Electrical and Computer Engineering from Carleton University and Polytechnique Montreal. His research focuses on wireless ad hoc networks , particularly in mobile/flying networks like UAVs and LEO satellites. Key areas include routing protocols (network layer) and MAC protocols (link layer) to improve packet delivery and reduce latency. He integrates AI techniques like deep learning and reinforcement learning into network design. His publications emphasize multi-beam antenna systems and their role in optimizing ad hoc networks. Recent work includes a novel routing protocol (2023) and MAC protocols like MBA-DbMAC (2019). Earlier studies (2014–2018) explored mobility models and directional antennas in UAV networks. No awards, advising records, or grants are listed in the provided texts.

• HIV Immunology
• Viral Pathogenesis
• SARS-CoV-2/COVID-19 Research
• +۵ مورد دیگر

Dr. Otto Orlean Yang is a Professor in both the Department of Medicine and the Department of Microbiology, Immunology, and Molecular Genetics at the University of California Los Angeles (UCLA). With extensive training from Brown University (ScB in Human Biology, MD), New York University-Bellevue Hospital (Internal Medicine Residency), and Harvard University (Fellowship in Infectious Diseases and Postdoctoral work in Immunology and Virology), he has established himself as a leading researcher in viral immunology and pathogenesis. His research focuses on HIV immunology, SARS-CoV-2 pathogenesis, and immunotherapeutic approaches including chimeric antigen receptors. Dr. Yang's work spans fundamental virology, translational research, and clinical trials, with particular emphasis on understanding immune responses to viral infections and developing novel therapeutic strategies. His laboratory investigates CTL responses to HIV, viral escape mechanisms, and the development of CAR-T cell therapies for HIV cure strategies. Dr. Yang has led numerous NIH-funded research projects including R01 grants on HIV-specific chimeric antigen receptors, viral pathogenesis, and immune responses to SARS-CoV-2. His publication record spans from 1995 to the present, with over 150 publications in high-impact journals including Journal of Virology, Journal of Immunology, and Nature Nanotechnology. His recent work has focused on both HIV therapeutics and the immunopathogenesis of SARS-CoV-2 infection. As evidenced by his extensive NIH funding history and numerous clinical trials, Dr. Yang actively translates basic research findings into clinical applications. His work has contributed significantly to understanding viral immune evasion, developing novel immunotherapies, and characterizing immune responses in both HIV and SARS-CoV-2 infections. Dr. Yang serves as Principal Investigator on multiple NIH grants including "Therapeutic Anti-HIV Chimeric Antigen Receptors Via Stem Cell Delivery" (R01AI140775) and "Los Angeles CRS for the MACS/WIHS Combined Cohort Study" (U01HL146333), demonstrating his leadership in both basic and clinical HIV research.

Barry E. Mullinsمشاهده پروفایل

استاد

• Cybersecurity
• Network Security
• Digital Forensics
• +۳ مورد دیگر

Barry E. Mullins is a Professor in the Department of Electrical and Computer Engineering at the Air Force Institute of Technology (AFIT). He holds a Ph.D. in Electrical Engineering from Virginia Tech (1997), an M.S. in Computer Engineering from AFIT (1987), and a B.S. in Computer Engineering (Cum Laude) from the University of Evansville (1983). His research focuses on cybersecurity, network security, and digital forensics, with notable contributions to wireless communication security and critical infrastructure protection. He has advised numerous graduate students and authored/co-authored over 100 publications in peer-reviewed journals and conferences. Dr. Mullins has received prestigious awards, including the 2021 Dean’s Distinguished Teaching Professor and multiple best paper/poster awards. His work emphasizes practical cyber defense solutions, such as secure wireless protocols, intrusion detection systems, and advanced encryption techniques. He is actively involved in curriculum development for cyber warfare and information assurance programs, integrating real-world scenarios and military applications. His research teams have developed tools like TRAPP for tracking peer-to-peer file sharing and FPGA-based systems for malicious traffic detection. Collaborations with industry and government entities (e.g., NSA, US Cyber Command) underscore his commitment to bridging academic and operational cybersecurity needs. Dr. Mullins also leads initiatives in software-defined networking (SDN) security and blockchain applications for IoT and transportation systems. Key contributions include pioneering studies on ZigBee network vulnerabilities, secure multicast architectures for satellites, and the use of metamorphic software protections. His teaching excellence has been recognized with the Cage H. Crocker Award and AETC Educator of the Year honors. Current projects explore AI-driven network security, smart home IoT defense mechanisms, and decentralized ledger technologies for critical infrastructure.

Gerd von Cöllnمشاهده پروفایل

استاد

• Energy-Efficient Systems
• Embedded Systems
• Cyber-Physical Systems
• +۵ مورد دیگر

Prof. Gerd von Cölln is a Professor of Computer Architecture at the School of Technology, Electrical Engineering and Computer Science, University of Applied Sciences Emden/Leer. His primary focus is on energy-efficient and autonomous systems, particularly in embedded and cyber-physical systems. He leads research in energy-autonomous sensors, low-power electronics, and IoT applications. Education details are not explicitly provided in the text, but his academic role suggests advanced qualifications in electrical engineering or computer science. His research projects include Sichere Offshore-Operationen (SOOP), Energieautarke Sensorsysteme (ID3AS), and LoRaWAN-based sensors (ELVIS), demonstrating expertise in industrial automation, sensor networks, and energy harvesting. Publications emphasize sensor design, wireless communication protocols, and optimization algorithms for complex environments. While no awards are listed, his extensive project portfolio highlights contributions to applied engineering research. Advising details are unavailable, but his role implies supervision of technical projects involving students and industry partners. Prof. von Cölln collaborates on labs and teams focused on maritime automation, industrial IoT, and embedded systems, with projects addressing challenges like harsh environmental conditions and energy sustainability.

• Cryptography
• Cyber Security
• Embedded Security
• +۴ مورد دیگر

Prof. Jan Pelzl is a Professor of Computer Security at Hamm-Lippstadt University of Applied Sciences. His research focuses on cryptography, cyber security, and embedded security, with a strong emphasis on post-quantum cryptography and industrial security solutions. He leads projects addressing long-term data protection under regulations like the NIS2 Directive and explores practical implementations for critical infrastructure. Key research areas include cryptographic algorithms (ECC, RSA, hash functions), key management systems, and security engineering for embedded systems. Collaborations with industry partners such as Robert Bosch GmbH and TÜV Rheinland Akademie highlight his work on industrial security and safety standards. His publications span over two decades, with recent focus on post-quantum cryptography applications, cryptographic protocols, and embedded security architectures. Pelzl’s contributions address both theoretical advancements and real-world implementations, particularly in automotive and IoT security contexts.