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Hyuck M. KwonView profile

Professor

• Wireless Mobile Communications
• Communication Systems
• Information Theory
• +6 more

Hyuck M. Kwon is a Full Professor of Electrical and Computer Engineering at Wichita State University (WSU), part of the College of Engineering. His research focuses on wireless communications, including satellite systems, smart antennas, MIMO, and CDMA. He has held academic appointments since 1985, including visiting roles at institutions like KAIST and George Mason University. Kwon has supervised numerous PhD and MS students and has been recognized with prestigious awards, including the Dwane and Velma Wallace Outstanding Educator Award. His work spans over 100 publications and grants from agencies like the Air Force and NASA. He has developed courses such as '5G Wireless Communications' and 'Information Theory'. Education: Ph.D. in Computer, Information and Control Engineering, University of Michigan (1984) MSEE, Seoul National University (1980) BSEE, Seoul National University (1978) Research Interests: Wireless communications and networks Smart antennas and MIMO systems 5G/6G technologies Signal processing for communications Anti-jamming and secure communications Grants and Awards: Over $2M in research funding from the Air Force, NASA, and industry partners Awarded multiple Air Force Summer Faculty Fellowships (2014–2016) Nominated for NAI Fellow (2017) Lab/Teams: Active in developing advanced communication systems, including satellite digital beamforming and nano-antenna research with metamaterials.

Jerome F. HajjarView profile

Professor

• Sustainable and Resilient Steel Structures
• Composite Steel/Concrete Structures
• Earthquake Engineering
• +7 more

Jerome F. Hajjar is a University Distinguished Professor and CDM Smith Professor in the Department of Civil and Environmental Engineering at Northeastern University, with an affiliation in Marine and Environmental Sciences. He holds a PhD in Structural Engineering from Cornell University (1988) and is a licensed Professional Engineer in Illinois and Minnesota. PhD, Structural Engineering, Cornell University, 1988 MS, Structural Engineering, Cornell University, 1985 BS, Engineering Mechanics, Yale University, 1982 Hajjar’s research focuses on sustainable and resilient steel/concrete composite structures , earthquake engineering , structural stability , and large-scale experimental testing . He pioneered design for deconstruction and physics-guided machine learning for structural analysis. His work addresses climate change risks through offshore wind resilience and hurricane risk assessment. His recent publications emphasize carbon reduction strategies via steel-CLT hybrids, machine learning techniques for seismic modeling, and experimental programs on composite diaphragms. Hajjar’s projects include the STReSS Laboratory , equipped with a reinforced concrete strong floor for full-scale structural testing. 2025 William H. Wisely American Civil Engineer Award 2025 SSRC Distinguished Member Award 2021 AISC Lifetime Achievement Award 2018 Robert D. Klein Lectureship 2007 ASCE Fellow Hajjar mentors PhD students, including R. Bailey Bond (2024), and leads major initiatives like the Academic Center for Reliability and Resilience of Offshore Wind (ARROW) and the Steel Diaphragm Innovation Initiative . His advocacy extends to integrating sustainability, resilience, and equity into national building codes through roles in the Structural Engineering Institute and American Society of Civil Engineers.

• Reliable Hardware Design
• Electronic Design Automation
• Edge Computing
• +4 more

Dr. Abusaleh Jabir is a University Reader at the School of Engineering, Computing and Mathematics, Oxford Brookes University. He holds a DPhil in Computing from the University of Oxford and leads the Advanced Reliable Computer Systems (ARCoS) group. His research focuses on reliable hardware design, memristive nanotechnology, edge computing, and secure authentication systems. He has over 80 peer-reviewed publications and multiple patents, including innovations in error-tolerant circuits and memristive architectures. **Education**: DPhil in Computing (University of Oxford). **Research Interests**: Reliable hardware design, electronic design automation, sensing at the edge, physical uncloneable authentication, and emerging memristor technologies. His work addresses challenges in IoT, edge computing, and cybersecurity through innovative electronic systems. **Funding & Projects**: Current projects include the Leverhulme Trust-funded MONITOR gas sensor array initiative. His research has been supported by the UK Ministry of Defence, EPSRC, and Finance South East. **Awards & Patents**: Multiple patents granted, including EU 17706875.6 (memristive logic) and GB 1914221.5 (reconfigurable memristive logic). Recognized with best paper awards. **Advising & Impact**: Supervised PhD students now leading semiconductor and automotive industries (e.g., Infineon Technologies, Continental Teves AG). Collaborates with academic and industrial partners globally. **Labs & Teams**: Leads the ARCoS group within the Artificial Intelligence, Data Analysis and Systems (AIDAS) Institute, fostering interdisciplinary innovation in secure and reliable electronics.

Ramon Ferrer CanchoView profile

Associate Professor

• Quantitative Linguistics
• Information Theory
• Network Theory
• +3 more

Ramon Ferrer Cancho is an Associate Professor at the Polytechnic University of Catalonia's Department of Computer Science, affiliated with the Barcelona School of Informatics and the LQMC research group (Quantitative, Mathematical, and Computational Linguistics). His work focuses on quantitative linguistics, information theory, and network theory, with applications in language structure, evolution, and animal communication. Education: Doctor in Computer Science, Advanced Studies Diploma in Applied Physics and Simulation. Research Interests: Dependency syntax, linguistic laws (Zipf's law, Menzerath-Altmann law), computational models of language, and cross-disciplinary studies in biology and cognitive science. He leads projects on language optimization, complexity, and data analysis. Recent work includes studies on syntactic dependency distances, ape gesture patterns, and bottlenose dolphin communication parallels. His research bridges computer science, linguistics, and biology, emphasizing universal principles in communication systems. Notable contributions include theoretical frameworks for dependency distance minimization, optimization models of language structure, and empirical analyses of primate vocal sequences.

Ahmet TekalpView profile

Professor

• Digital Image Processing
• Video Compression
• Motion-Compensated Video Filtering
• +5 more

Ahmet Tekalp is a Professor in the Department of Electrical and Computer Engineering at Koc University's College of Engineering since 2001. He holds dual citizenship in Turkey and the USA, with prior academic roles at the University of Rochester (1986-2005) and research positions at Eastman Kodak (1984-1987) and Rensselaer Polytechnic Institute (1981-1984). He chairs the Electronics and Informatics Group at TUBITAK since 2004 as a part-time position. B.S. (1980) in Electrical Engineering & Mathematics, Bogaziçi University M.S. (1982) and Ph.D. (1984) in Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute His research focuses on digital image and video processing, including video compression, motion-compensated filtering for high-resolution applications, video segmentation, object tracking, content-based video analysis, multi-camera surveillance processing, and digital content protection. He has led numerous European and U.S. grants, including FP7 STREP projects and NSF awards, emphasizing applications in sensor networks, visual databases, and medical imaging. His scholarly work spans diverse areas such as superresolution reconstruction, head gesture animation, 3DTV streaming, and reversible data hiding. He has played pivotal roles in editorial boards, including serving as Editor-in-Chief of Signal Processing: Image Communication, and has contributed to major standards bodies like ISO MPEG and ANSI NCITS. Member, Turkish Academy of Sciences (TUBA) Fellow, IEEE Fulbright Senior Scholarship (1999) TUBITAK Science Award (2004) IEEE Signal Processing Society Distinguished Lecturer (1998) He has led multiple international research collaborations and projects, including European FP6/FP7 networks and NATO programs, with substantial grant funding from NSF, NYSTAR, and industry partners like Eastman Kodak, Xerox, and Siemens.

• Fault-Tolerant Computing
• Storage Systems
• Erasure Coding
• +3 more

James S. Plank is a Professor in the Department of Electrical Engineering and Computer Science at the University of Tennessee. He holds a PhD from Princeton University (1993) and has been at UT since 1993. His research focuses on fault-tolerant computing, erasure coding, distributed systems, and neuromorphic computing. He teaches programming courses from introductory to graduate levels and has won multiple teaching awards, including seven departmental awards, the College of Arts and Sciences Senior Faculty Teaching Award, and the Chancellor’s Citation for Excellence in Teaching. Plank is a member of the IEEE Computer Society and has contributed to open-source software like JGraph and Jerasure. His recent research emphasizes neuromorphic computing systems, including projects like NeuroPong and RISP Neuroprocessor. He collaborates with industry and academia on storage systems, checkpointing, and hardware-software co-design. Plank advises numerous graduate and undergraduate students, evident in his annual summer student gallery. He has secured grants such as the NSF-funded "Ground-roaming autonomous neuromorphic targeter" (2020). His lab, Neuromorphic UT, explores applications in control systems, vision, and robotics. Plank’s contributions to erasure coding and storage reliability include seminal works like the RAID-6 Liberation Code and SD codes for mixed failure modes.

Ammar MianView profile

Associate Professor

• Statistical Signal Processing
• Machine Learning
• Riemannian Geometry
• +4 more

Ammar Mian is an Associate Professor at Université Savoie Mont Blanc, affiliated with the LISTIC lab and Polytech Annecy-Chambéry. He holds a PhD from CentraleSupélec (2016-2019) and conducted postdoctoral research at Aalto University (2019-2020). His research focuses on statistical signal processing, machine learning, and Riemannian geometry with applications in remote sensing and frugal computations. He leads the Qanat project, an experiment tracking tool for reproducible research. Research interests include covariance-based methods for SAR image analysis, robust detection algorithms for sonar and GPR systems, and optimization on Riemannian manifolds. His work emphasizes reproducibility in ML and efficient computational techniques for resource-constrained environments. Key contributions include real-time SAR time-series change detection, robust classification using second-order deep learning models, and novel methods for handling missing data in EEG signals. His recent articles (2023-2025) explore reproducibility frameworks, GPR-based object classification, and Riemannian geometry applications. No awards listed, but maintains active collaborations through LISTIC and industry partnerships. Advises students via internship programs (e.g., Federated ML energy cost analysis). Lab work involves developing open-source tools like Qanat for experiment management and reproducibility.

George N. KarystinosView profile

Professor

• Communication Theory and Systems
• Wireless Communications
• Signal Processing
• +9 more

George N. Karystinos is currently a Professor and Dean of the School of Electrical and Computer Engineering at the Technical University of Crete , Greece. He joined TUC in 2005 and was promoted to full Professor in 2019. His academic journey began with a Ph.D. in Electrical Engineering from SUNY Buffalo (2003) and a Diploma in Computer Engineering and Science from the University of Patras (1997). Specialty: Communication theory, coding theory, adaptive signal processing Key research areas: Wireless communications, signal waveform design, L1-norm principal component analysis Leadership: Dean of School of ECE (2021–present) His work focuses on noncoherent detection for RFID/IoT systems and L1-norm PCA for robust signal processing. Recent publications explore power line communication and low-complexity sequence detection . Scientific Awards: 2003 IEEE Transactions on Neural Networks Outstanding Paper Award 2001 IEEE ICT Best Paper Award 2018 IEEE MOCAST Best Student Paper Award 2015 IEEE ICASSP Best Student Paper Award 2013 IEEE ISWCS Best Paper Award 2011 IEEE RFID-TA Second Best Student Paper Award He is affiliated with the Telecommunications Laboratory at TUC and has supervised award-winning research in wireless systems and signal processing.

Fatmir MenkulasiView profile

Associate Professor

• Sustainable Structural Systems
• Concrete and Steel Structures
• Composite Materials in Civil Engineering
• +4 more

Fatmir Menkulasi is an Associate Professor in the Department of Civil and Environmental Engineering at Wayne State University's College of Engineering. His research focuses on developing sustainable structural systems for buildings and bridges, with emphasis on concrete, steel, and composite materials. Current research explores novel material applications in structural design Specializes in computational modeling and experimental studies Active in infrastructure rehabilitation and structural health monitoring Recent publications highlight advancements in UHPC (Ultra-High Performance Concrete) systems, hybrid structural configurations, and deformation analysis. His work addresses critical challenges in urban infrastructure resilience and cost-effective engineering solutions. Scientific Recognition AASHTO Region 3 High Value Research Award (2024) MDOT Top 4 Project Recognition (2022) ASCE Outstanding Reviewer (2020) Multiple Professor of the Year awards at Louisiana Tech University Menkulasi teaches advanced courses in reinforced concrete design, bridge engineering, and prestressed concrete systems at both graduate and undergraduate levels.

Maryam Mehri DehnaviView profile

Associate Professor

• High-Performance Computing
• Cloud Computing
• Machine Learning
• +3 more

Maryam Mehri Dehnavi is an Associate Professor in the Department of Computer Science at the University of Toronto and a Principal Research Scientist at NVIDIA. She holds the Canada Research Chair in Parallel and Distributed Computing and leads the ParaMathics research group. Research focuses on high-performance computing , machine learning , sparse matrix optimizations , and compiler design for heterogeneous systems. Her work develops domain-specific languages , scalable numerical libraries , and auto-vectorization techniques for cloud and GPU platforms. Recent publications address LLM compression , sparse code translation , GPU kernel synchronization , and control flow optimization . Scientific recognition: Ontario Early Researcher Award (2021), NSF CRII Grant, NSERC New Frontiers in Research Fund. Current students: Mushegh Shahinyan , Martin Phan , Maryam Haghifam , and others. Former advisees: Kazem Cheshmi (NJIT), Zachary Blanco (MIT Lincoln Lab), Yuanxi Li (Amazon).

Fangneng ZhanView profile

Research Fellow

• Computer Science
• Artificial Intelligence
• Neural Rendering
• +7 more

Currently a Research Fellow at Harvard University & MIT , Fangneng Zhan specializes in Neural Rendering and Generative AI . His research focuses on developing evolutive rendering frameworks, 3D-aware generative models, and multimodal synthesis techniques. Previously, he was a postdoctoral researcher at the Max Planck Institute for Informatics under Prof. Christian Theobalt. He earned his Ph.D. in Computer Science & Engineering from Nanyang Technological University, Singapore and a Bachelor's in Communication Engineering from the University of Electronic Science and Technology of China . His work spans 3D reconstruction, robotics applications , and lighting estimation , with significant contributions to SIGGRAPH , NeurIPS , and CVPR conferences. Recent research highlights include evolutive gauge transformations for neural fields, generalizable 3D style transfer via Gaussian splatting, and multimodal synthesis frameworks leveraging pre-trained models like CLIP and Stable Diffusion. He has co-authored Top50 Popular Paper in TPAMI 2023 and organized workshops at CVPR 2024 on generative models. Scientific Awards: Top50 Popular Paper, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2023 Collaborative Network: Mentored students at institutions like Harvard, NTU, and ETH Zurich. His projects include datasets for lighting estimation and real-time scene text detection systems.

Koushik SenView profile

Professor

• Software Engineering
• Programming Languages
• Formal Methods
• +8 more

Koushik Sen is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He holds a B.Tech from IIT Kanpur and M.S./Ph.D. from UIUC. His research focuses on Software Engineering, Programming Languages, and Formal Methods, emphasizing tools like DART, CUTE, and Jalangi for improving software reliability. He leads projects such as CORVETTE and Sky Computing Lab, and collaborates with Samsung Research America on JavaScript analysis. Sen has received prestigious awards including the Sloan Fellowship and ACM SIGSOFT Impact Award. Education: B.Tech, Indian Institute of Technology, Kanpur M.S. and Ph.D., University of Illinois at Urbana-Champaign Research Interests: Software Testing, Verification, Symbolic Execution, Security, and Quantum Computing. His work bridges automated testing (e.g., concolic testing) with machine learning for bug detection and program synthesis. Projects include Hindsight Logging for ML reproducibility and quantum circuit optimization (QFAST). Awards: NSF CAREER, IFIP Manfred Paul, ACM SIGSOFT Distinguished Paper (multiple), and Sloan Fellowship. Advising: Supervised over 30 students/postdocs, leading to faculty roles at UBC, CMU, and industry positions at Google, Facebook, and Samsung. Labs/Teams: Berkeley Center for Responsible, Decentralized Intelligence (RDI), EPIC Data Lab, and Sky Computing Lab. Active in quantum computing and hardware fuzzing (RTL-FuzzLab).

Stephanie ForrestView profile

Professor

• Cybersecurity
• Software Engineering
• Computational Immunology
• +8 more

Stephanie Forrest is a Professor of Computer Science at Arizona State University and serves as Director of the Biodesign Center for Biocomputation, Security and Society . She holds affiliations with the School of Computing and Augmented Intelligence , Global Futures Laboratory , and Santa Fe Institute External Faculty . Education: B.A. from St. John's College M.S. and Ph.D. in Computer Science from the University of Michigan Research Interests: Forrest specializes in the intersection of biology and computation , with key contributions to cybersecurity (anomaly detection, instruction-set randomization), automated software repair (evolutionary methods), and biological modeling (immune systems, SARS-CoV-2 spread). Her work bridges complex adaptive systems , AI/ML , and defense applications . Scientific Contributions: 2020 IEEE S&P Test of Time Award 2019 ICSE Most Influential Paper Award 2011 ACM/AAAI Allen Newell Award NSF Presidential Young Investigator (1991) IEEE Fellow Evolutionary Computation Pioneer award Publications & Grants: Her research appears in top venues (ICSE, IEEE S&P, PNAS) and is funded by the National Science Foundation , DARPA , Air Force Research Lab , and Santa Fe Institute . Key projects include Crispy (CRISPR-inspired DoS defense), GenProg (automated bug correction), and SIMCoV-GPU (agent-based pandemic modeling).

Sam S. RamanujanView profile

Professor

• Big Data Architecture
• Visual Analytics
• Software Engineering
• +4 more

Dr. Sam S. Ramanujan is Professor of Computer Information Systems and Analytics at the University of Central Missouri , affiliated with the Harmon College of Business and Professional Studies . He teaches advanced object-oriented programming and software engineering courses, combining over two decades of academic expertise with substantial industry experience in complex system deployment. Doctor of Philosophy in Information Systems (University of Houston, 1995) MBA in CIS and Quantitative Analysis (University of Arkansas, 1989) PGDM in Information Systems (XLRI Institute of Management Studies, 1987) Bachelor of Arts (Hons) in Economics (University of Delhi, 1985) His research spans big data architecture , visual analytics , healthcare IT , and legal aspects of technology . He has published extensively on topics including software maintenance, e-commerce trust models, and cloud-based healthcare systems, with a focus on bridging technical and legal challenges in digital environments. Dr. Ramanujan's academic work shows a consistent focus on software engineering (1995–2017), healthcare IT (2004–2017), and legal-compliance frameworks (2000–2017). His publications demonstrate interdisciplinary expertise in merging technical systems with regulatory requirements . Best Paper Award , Journal of American Academy of Business, Cambridge (2006) He has contributed to pedagogical advancements in distributed computing curricula and collaborates with scholars like S. Kesh and S. Nerur. His industry experience informs real-world applications of his research in software maintenance and offshore operations.

Jonathan S. SkinnerView profile

Professor

• Health Economics
• Economics of Aging
• Health Policy
• +7 more

Jonathan S. Skinner is a Professor at Dartmouth College, Department of Economics, and a professor at the Dartmouth Institute for Health Policy and Clinical Practice within the Geisel School of Medicine. He serves as the Aging Program Director at the National Bureau of Economic Research (NBER) and has contributed extensively to understanding healthcare productivity, technology adoption, and policy implications for aging populations. Key research areas: Health Economics, Economics of Aging, Public Policy Current projects focus on Medicare/Medicaid spending, geographic healthcare disparities, and pandemic impacts on vulnerable populations. Publications (2023–2010) reveal trends in healthcare fraud networks , racial segregation in hospital admissions , and end-of-life expenditures . His work often integrates Medicare claims data and network analysis to assess systemic inefficiencies. Recent scientific collaborations include partnerships with institutions such as the NBER and JAMA Network Open. He has analyzed regional mortality disparities and technology diffusion in clinical settings, with implications for public health strategy.