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Seunghan LeeView profile

Assistant Professor

• Simulation Methodologies
• Optimization
• Stochastic Processes
• +7 more

Seunghan Lee is an Assistant Professor in the Industrial and Systems Engineering Department at Mississippi State University (MSU). He holds a Ph.D. in Systems & Industrial Engineering from the University of Arizona (2019), an M.S. in Operations Research from Georgia Tech (2015), and dual M.S. and B.S. degrees in Industrial Engineering from Seoul National University (2008 and 2006). Prior to MSU, he served as an Assistant Professor of Teaching at SUNY Buffalo. Education: Ph.D., Systems & Industrial Engineering, University of Arizona (2019) M.S., Operations Research, Georgia Institute of Technology (2015) M.S., Industrial Engineering, Seoul National University (2008) B.S., Industrial Engineering, Seoul National University (2006) Research Interests: His work focuses on simulation methodologies integrating optimization and stochastic processes, particularly for socio-economic decision support systems under uncertainty. Applications include disaster management, homeland security, smart cities, and healthcare operations. Key techniques include agent-based simulation (ABS), discrete-event simulation (DES), Bayesian optimization, and statistical computing. Awards: Best Paper Award, IISE Annual Conference (2016, 2018) Outstanding Graduate Teaching Assistant Award, University of Arizona (2019) Advising & Grants: While no student advisees are listed, his research has been supported through collaborations on projects involving disaster management frameworks, smart surveillance systems, and medical training simulations. His work often involves interdisciplinary teams addressing real-world operational challenges. Labs & Teams: Engages in collaborative projects leveraging digital twins, dynamic data-driven applications (DDDAMS), and hybrid simulation models for applications in healthcare, security, and urban planning.

• Artificial Intelligence
• Bioinformatics
• Cyberinfrastructure
• +12 more

Alex Feltus is a Professor in the Department of Genetics and Biochemistry at Clemson University's College of Science. He also serves as Core Faculty in the Biomedical Data Science and Informatics program and as a Faculty Member at the Clemson Center for Human Genetics. With a Ph.D. in Cell Biology from Vanderbilt University (2000) and a B.Sc. in Biochemistry from Auburn University (1992), Feltus has established himself as a leading researcher at the intersection of computational biology and genomics. His research spans artificial intelligence, bioinformatics, cyberinfrastructure, high-performance & cloud computing, systems biology, tumor genomics, medical genetics, crop genetics, genome assembly, systems genetics, and paleogenomics. His work focuses on revealing genomic mechanisms underlying phenotype expression, with particular emphasis on identifying biomarker systems that distinguish between biological states such as normal versus tumor tissues. Feltus's laboratory employs software engineering and computational biology techniques to make molecular discoveries in both human and plant biological systems. They develop elastic advanced compute systems for robust genomics workflows, enabling small labs to perform innovative petascale computational biology. His recent publications demonstrate a strong focus on gene expression analysis, genome assembly, Neanderthal DNA studies, plant genomics (particularly oak and Medicago), and AI applications in genetic research. Among his achievements are the development of open source software, completion of multiple NSF grants, and training of numerous undergraduate, master's, and doctoral students. He is also the co-founder of Praxis AI LLC, through which he extends his 27 years of bioscience research experience to scale computational biology skilling to thousands of learners worldwide via virtual courses, biohackathons, podcasts, and digital learning solutions. Feltus teaches several courses including Bioinformatics, Medical Bioinformatics, Advanced Medical Bioinformatics, Digital Biology, Computational Genomics, Biomedical Informatics, Next-Generation Sequence Analysis, and Perl for Bioinformatics.

Armando BarretoView profile

Professor

• Digital Signal Processing
• Biomedical Signal Processing
• Adaptive Digital Signal Processing
• +5 more

Armando Barreto is a Professor in the Department of Electrical & Computer Engineering at Florida International University (FIU). He holds a Ph.D. in Electrical Engineering from the University of Florida (1993), an M.S.E.E. from FIU (1989), and a Mechanical-Electrical Engineering degree from the National Autonomous University of Mexico (1987). His research focuses on digital signal processing with applications in biomedical systems, including EEG analysis, adaptive algorithms, neural networks, and real-time embedded systems. He also explores human-computer interaction through sensor technologies like MEMS, inertial measurement units, and multi-touch interfaces. His work addresses accessibility challenges for visually impaired users through dynamic image precompensation and assistive technologies. Key contributions include innovations in signal denoising, affective computing via pupil dynamics analysis, and multimodal data fusion for early detection of neurodegenerative diseases like Alzheimer’s. His research bridges theoretical signal processing with practical applications in healthcare, virtual reality, and wearable devices. Barreto’s publications span over three decades, demonstrating sustained leadership in sensor-based systems, medical signal processing, and computational neuroscience. He collaborates with interdisciplinary teams to advance technologies addressing clinical and accessibility challenges.

Domenico StriccoliView profile

Associate Professor

• Internet of Things
• Network Security
• Information Centric Networking
• +3 more

Dr. Domenico Striccoli is an Associate Professor in the Department of Electrical and Information Engineering at the Polytechnic University of Bari, Italy. He holds a Dr. Eng. Degree (2000) and Ph.D. in Electronic Engineering (2004) from Politecnico di Bari. His office contact is +39 080 5964225. Research focuses on advanced networking technologies: Internet of Things architectures and security Information Centric Networking paradigms Low Power Wide Area Networks optimization Nanocommunication systems Network performance modeling and evaluation Awards include Best Impact Contribution runner-up at RESTART Workshop (2024) and 2nd Best Paper at ICT-DM Conference (2023). Teaching includes Multimedia Systems and Telecommunication Signal and System for Aerospace courses.

Antonio PetrosinoView profile

Research Fellow

• Software-Defined Networking
• Satellite Communication
• NarrowBand - IoT
• +3 more

Antonio Petrosino is a Research Fellow at the Department of Electrical and Informational Engineering, Politecnico di Bari. His research focuses on Software-Defined Networking, Satellite Communication, and NarrowBand-IoT technologies. Education: Bachelor of Engineering in Computer Science and Automation (2016), Politecnico di Bari Master in Telecommunication Engineering (2020), Politecnico di Bari His work spans network optimization, security frameworks for 6G satellite deployments, and integration of UAVs in IoT-satellite systems. Recent publications highlight advancements in trust dissemination, NB-IoT over LEO satellites, and hybrid terrestrial-non-terrestrial architectures. Research Collaborations: Co-authorship with teams from Politecnico di Bari, University of Naples, and international institutions.

Jonathan H. AmsbaryView profile

Professor

• Communication
• Small Group Communication
• Organizational Communication
• +5 more

Jonathan H. Amsbary is a Professor and Director of the Graduate Program at the University of Alabama at Birmingham (UAB), where he has been a faculty member since 1988. He is affiliated with the Department of Communication Studies within the College of Arts and Sciences. Education: B.A. in Speech Communication/Psychology from the University of New Mexico M.A. in Speech Communication from Indiana University Ph.D. in Speech Communication from Indiana University Professor Amsbary specializes in applied communication and persuasion, with specific interests in how communication functions in small groups, organizations, and virtual realities. His research spans both traditional communication contexts and more recent explorations into popular culture, particularly western movies and western movie actors. He has published extensively in communication journals and co-authored multiple books, employing both quantitative and qualitative research methods in his investigations. His publication record demonstrates significant scholarly contributions across multiple domains of communication studies. His works examine topics ranging from interviewing techniques and sports communication to the rhetoric of crisis events and film studies, showing an evolving research trajectory that bridges traditional communication theory with contemporary cultural phenomena. Professor Amsbary teaches undergraduate courses in Research Methods, Public Speaking, Small Group Communication, and Interviewing. At the graduate level, he teaches Communication Models, Small Group Communication, and Organizational Communication, reflecting his commitment to developing communication skills across various contexts. Throughout his career at UAB, Professor Amsbary has witnessed the university's transformation from a commuter institution to a world-class research university. He has been instrumental in the development of academic programs, including the nationally ranked Communication Management Master's program, while maintaining the institution's commitment to excellence and diversity.

• Cryptography
• Network Security
• Distributed Systems
• +2 more

Antonio Nicolosi is an Associate Professor of Computer Science at Stevens Institute of Technology's Schaefer School of Engineering, specializing in cryptography and secure distributed systems. His NSF CAREER award-winning research explores lattice-based cryptography, non-commutative cryptographic protocols, and future internet architectures like NEBULA. Education PhD in Computer Science, New York University MS in Computer Science, Università di Catania Research Focus: Develops provably secure cryptographic systems using group-theoretic approaches, with applications in network security and privacy-preserving protocols. Honors: NSF CAREER Award (2014), EU Marie Curie Fellowship. Recent publications address pseudorandom functions, broadcast steganography, and internet architecture security. Teaches courses including Foundations of Cryptography and Secure Systems. Professional Service: Program Director for Cybersecurity Masters, editorial roles, and conference organization. Research funded by NSF, Air Force Research Lab, and DOD.

• Fluid Antenna Systems
• Reconfigurable Intelligent Surfaces
• Integrated Radio-Sensing
• +4 more

Dr. Tuan Anh Le is a Senior Lecturer in Design Engineering at Middlesex University's Faculty of Science and Technology, Department of Design Engineering & Mathematics. He holds a B.Eng. and M.Sc. in Electronics and Telecommunications from Hanoi University of Technology, and a Ph.D. from King's College London funded by the UK's EPSRC and Mobile VCE scholarship. His research focuses on developing resource allocation strategies for next-generation wireless networks using convex optimization and nature-inspired intelligence. Key areas include reconfigurable antenna systems, integrated sensing-communications, PHY-layer security, and energy-efficient 5G/6G architectures. Recent publications demonstrate strong focus on beamforming optimization techniques using metaheuristic algorithms (especially Firefly Algorithm), cognitive radio systems, and dual-function radar-communications. Work frequently appears in IEEE Transactions journals and major telecom conferences. Supervises PhD candidates in antenna design and wireless systems. Teaches modules including Digital Signal Processing, System Design, and Mobile Communications. Previously contributed to EU-funded projects on green radio technologies.

Thomas KunzView profile

Professor

• Internet of Things
• Smart Grid/Smart City
• Mobile computing systems
• +7 more

Roles & Affiliations: Professor in the Department of Systems and Computer Engineering at Carleton University, Ottawa. Holds a Dr.-Ing. from the Technical University of Darmstadt (Germany). Active in research and academic leadership, including serving on Carleton's Board of Governors (2012-15). Education: Dr.-Ing., Technical University of Darmstadt, Germany (1994) Postdoctoral experience: University of Waterloo (1994-1997) Research Focus: Internet of Things (Smart Grid/City) Mobile computing systems & wireless networks Software-defined networking (SDN) and network function virtualization (NFV) Machine learning applications in networking Adaptive mobile systems and tactical radio networks Key Achievements: World's Top 2% Most-Cited Scientists (2022, Stanford-Elsevier) Top 0.5% Global Scholars (2024, ScholarGPS) Carleton Research Achievement Awards (2012-13, 2004-05) Carleton Graduate Mentoring Award (2010) Advising & Labs: Supervised numerous graduate students (see linked list) Developed NetAnalyzer , an open-source network analysis tool

Wei XuView profile

Research Professor

• Artificial Intelligence for Science
• Explainable and Trustworthy AI
• Machine Learning
• +6 more

Wei Xu is a Research Professor in the Department of Computer Science at Stony Brook University and a Computational Scientist leading the Trustworthy Artificial Intelligence (TAI) group at Brookhaven National Laboratory's Artificial Intelligence Department. She holds a Ph.D. from Stony Brook University and M.S./B.S. degrees from Zhejiang University. Her research bridges artificial intelligence, high-performance computing, and scientific visualization, with current focus areas including explainable AI for scientific applications, quantum computing performance, and neural representations for ensemble simulations. Her work spans: AI/ML for Science : Developing trustworthy AI models for climate prediction, quantum computing, and medical diagnostics. Visual Analytics : Creating novel tools for multivariate volume visualization and quantum state representation. High-Performance Computing : Optimizing exascale workflows and performance analysis. Recent publication trends (2021-2025) demonstrate strong emphasis on explainable AI techniques for scientific domains, neural representations for data efficiency, and visualization methods for complex scientific data. Her papers frequently appear in top venues like TVCG, ICLR, and IEEE VIS. Awards & Honors: Women@Energy Showcase (2014) Best Paper Awards: PacificVis (2025), ISAV/SC20 (2020), Fully3D Workshop (2009) Spotlight Presentation at ICLR TCCML Workshop (2025) She secures funding through DOE BER/SciDAC programs and BNL initiatives (LDRD, NSLSII DSSI). As Trustworthy AI Group Lead, she oversees projects integrating AI with scientific infrastructure. She actively contributes to conferences as committee member (SC23/VIS24) and session chair (AAAI24, SC23).

Marc SteinbergView profile

Professor

• digital platforms
• platform economics
• media industries
• +12 more

Marc Steinberg is a Professor in the Department of Film Studies at Concordia University and director of The Platform Lab , a research group dedicated to studying digital platforms. His research spans platform economics, media industries, Japanese anime, transmedia storytelling, and digital culture, with a focus on the intersection of convenience, logistics, and platform capitalism. Education: PhD, Brown University MA, McGill University BA, McGill University Steinberg's work traces the historical and industrial evolution of media platforms, including the role of Japanese media mix practices in anime franchising, the rise of super apps in digital Asia, and the transformation of retail through convenience stores. He also explores the conceptual genealogy of platform capitalism, linking it to automotive and logistical systems like Toyota’s just-in-time model. Recent projects analyze how convenience functions as an aesthetic and economic driver in the platform economy, supported by grants such as the Volkswagen Foundation’s Smartness as Wealth . His research has been recognized with the ITRA-BTHA Book Prize (2014) and the Japan Society for Animation Studies Book Prize (2015). Scientific Awards: ITRA-BTHA Book Prize (Senior Prize), International Toy Research Association (2014) Japan Society for Animation Studies Book Prize (2015) Steinberg teaches courses on platform cultures, digital media, anime history, and media theory. He has co-edited volumes like Media Theory in Japan (Duke University Press, 2017) and In/Convenience: Inhabiting the Logistical Surround (Institute of Network Cultures, 2024), and has organized conferences including the Society of Animation Studies (2018) and Media Theory in Japan (2013).

• Telecommunications
• Network Optimization
• Artificial Intelligence
• +3 more

Professor Nancy Alonistioti is a faculty member at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. Her research focuses on advanced telecommunications technologies, including 5G/6G networks, AI-driven optimization, and network management systems. She leads studies in areas such as distributed learning frameworks for QoS prediction, fuzzy logic applications in emergency systems, and energy-efficient federated learning for wireless networks. Her work emphasizes network programmability, self-organizing mechanisms, and autonomic network management. Key contributions include the development of SIM+, a comprehensive information model for beyond 5G networks, and the Distinqt framework for privacy-aware learning in mobile systems. She explores applications in vehicular communications, maritime networks, and Industry 4.0 transformations through 5G capabilities. Professor Alonistioti’s research also addresses challenges like context-aware profiling, dynamic infrastructure-as-a-service paradigms, and genetic algorithm-based resource allocation in edge networks. Her publications span over two decades, reflecting a deep engagement with evolving network architectures and technologies.

• Data Communications
• Network Security
• Software-Defined Networking (SDN)
• +4 more

Dr. Martin Collier is an Associate Professor in the School of Electronic Engineering at Dublin City University and director of the Entwine Centre, focusing on IoT infrastructure. His research spans data and computer communications, network security, energy-efficient networking, and SDN/NFV. He leads projects like Horizon 2020's INPUT and FP7's ECONET, collaborating with IBM on data centre network design. His work emphasizes switch fabrics, green routers, and optical technologies. Research Interests: Switching/Routing, SDN, NFV, IoT, Energy Efficiency, Data Centre Networks. Recent Projects: INPUT (SDN/NFV personal cloud services), ECONET (energy efficiency), and IBM-funded data centre design. Laboratory activities include NetFPGA-based testing and SDN implementations. Teaching: Modules include Broadband Networks (EE552), Network Programming (EE562), and Communications Theory (EE450). Supervises final-year and MEng projects. Labs/Teams: Switching & Systems Lab (NetFPGA testbed), Entwine Centre (IoT infrastructure).

• Energy Efficient Networking
• Hardware Acceleration
• Cryptography Algorithms
• +4 more

Dr. Xiaojun Wang is an Associate Professor at the School of Electronic Engineering, Dublin City University (DCU). He holds a BEng and MEng from Beijing University of Posts and Telecommunications (BUPT) and a PhD from Staffordshire University (UK). His research focuses on energy-efficient networking, hardware acceleration for packet classification/deep inspection, and cryptography algorithms. He has been instrumental in establishing China-Ireland academic collaborations, including the China-Ireland International Conference on Information and Communications Technologies (CIICT), and coordinated a successful joint Telecommunications Engineering program with Wuhan University (2006–2012). He is also a member of DCU's Entwine Research Centre. Key roles include Head of China Affairs at DCU (2002–2007), contributing to institutional partnerships. His technical work spans green energy solutions for networks, quantum computing protocols, and hardware-software co-design for cryptographic systems. He has led projects on edge computing security, vehicular communication optimization, and blockchain-based trust frameworks. Educations: BEng in Computer & Communications, BUPT (1984) MEng in Computer Applications, BUPT (1987) PhD in Engineering, Staffordshire University (1992) Affiliations: Member of Entwine Research Centre Former Head of China Affairs, DCU His recent publications emphasize secure edge computing, quantum steganography, and 5G resource orchestration. He has pioneered energy-efficient router architectures and contributed to standards for vehicular networks and blockchain trust systems.

Dar-Jen ChangView profile

Associate Professor

• Computer Science
• Parallel Computing
• GPU Programming
• +7 more

Dar-Jen Chang is an Associate Professor in the Department of Computer Science and Engineering at the University of Louisville. He holds a B.S. in Mathematics from National Tsing Hua University (1970), an M.S. in Computer Information/Control Engineering from the University of Michigan (1982), and a Ph.D. in Mathematics from the same institution (1982). His research focuses on parallel computing, GPU programming, bioinformatics, 3D modeling, and algorithm optimization. His work spans disciplines including computer science, data mining, and biomedical applications. Chang’s research interests emphasize leveraging GPU acceleration for computational tasks such as RNA folding algorithms, hierarchical clustering, and Euclidean distance calculations. He has explored applications in 3D anatomical modeling, robotics simulation using Unity, and gaming frameworks with CUDA integration. His contributions include developing frameworks for algorithm visualization and database systems for automated process planning. His publications highlight trends in GPU-optimized algorithms, graph database analysis (e.g., Yelp and IMDb datasets), and interdisciplinary applications like medical imaging and genetic sequence prediction. He has also contributed to neural networks for fuzzy logic systems and biological sequence mining.