جست‌وجوی استاد و پژوهشگر

Nagi Gebraeelمشاهده پروفایل

استاد

• Predictive Analytics
• Machine Learning
• Prognostics and Health Management
• +۵ مورد دیگر

Professor Nagi Gebraeel serves as the Georgia Power Early Career Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Institute of Technology, where his research integrates predictive analytics, machine learning, and optimization for industrial IoT applications. His work focuses on real-time equipment diagnostics, prognostics, and operational decision-making in critical infrastructure systems. Education: Ph.D. in Industrial Engineering (2003), Purdue University M.S. in Industrial Engineering (1998), Purdue University Research Focus: Dr. Gebraeel develops statistical learning algorithms for IoT-enabled maintenance, repair, and operations (MRO), with emphasis on federated learning frameworks for distributed fault diagnosis and cybersecurity protection against Industrial Control System (ICS) attacks. His research spans manufacturing, power generation, and deep space habitats through NASA's HOME Space Technology Research Institute, where he pioneers self-aware habitat systems. Recent work addresses data heterogeneity in high-consequence industrial environments using causal-informed analytics. Publication Trends: His 2024-2025 publications demonstrate a strong trajectory toward distributionally robust optimization for maintenance logistics, federated learning architectures for distributed fault diagnosis, and prognostics for complex systems like offshore wind farms and industrial robots. Key themes include handling imbalanced data in fault diagnosis, state-space representations for interdependent systems, and cybersecurity integration in manufacturing networks. Awards and Recognition: NSF CAREER Award (2007) SAE Aircraft Electrical Power System Recognition Award (2008) SAE Materials Modeling and Testing Recognition Award (2006) IEEE-AUTOTESTCON Certificate (2006) Fellow of the Institute of Industrial and Systems Engineers Advising and Funding: Dr. Gebraeel mentors doctoral students including Michael Ibrahim (2025 IISE Best Student Paper winner), Heraldo Rozas (now Assistant Professor at University of Chile), Ayush Mohanty, and Nazal Mohamed. He secured a $500,000 NSF grant in August 2025 for AI-driven cybersecurity in distributed manufacturing networks and leads NASA-funded research on deep space habitat systems. His work bridges academic research with industry applications through Georgia Tech's Strategic Energy Institute collaborations. Research Infrastructure: He directs the Analytics and Prognostics Systems laboratory at Georgia Tech's Manufacturing Institute and leads the Predictive Analytics and Intelligent Systems (PAIS) research group. Previously, he served as associate director of Georgia Tech's Strategic Energy Institute (2014-2019), fostering data science applications in energy systems.

Karoline Faustمشاهده پروفایل

دانشیار

• Microbial community dynamics
• Microbial systems biology
• Bioinformatics
• +۶ مورد دیگر

Karoline Faust is an Associate Professor at KU Leuven, affiliated with the Laboratory of Molecular Bacteriology (Rega Institute) and the Faculty of Medicine . She contributes to the iSi Health and Leuven One Health institutes, and serves on senior academic councils. Her research spans microbial systems biology, focusing on community dynamics and network analysis. Education: PhD in bioinformatics (2010, KU Leuven) Affiliations: KU Leuven, ISME Journal editorial board, Belgian Society for Microbiology Her research investigates microbial community dynamics , systems biology approaches to microbiomes, and bioinformatics tool development . She specializes in modeling human gut microbiota , synthetic microbial communities , and environmental microbiomes (e.g., microplastic impacts on Daphnia microbiomes). Her work integrates metabolic modeling , network analysis , and experimental systems to understand microbial interactions. Recent publications highlight her contributions to microbial network inference , 16S rRNA sequencing protocols , microfluidics , and ecological modeling of microbiomes. She develops tools like manta , miaSim , and CoNet to analyze community structures. Teaching: Karoline co-teaches courses in microbiology, bioinformatics, and network analysis at KU Leuven, and has contributed to international workshops on microbial network inference. Scientific Engagement: She serves as Senior Editor at ISME Journal and Secretary of the Belgian Society for Microbiology .

Xiaodong Linمشاهده پروفایل

استاد

• Information Security
• Privacy-Enhancing Technologies
• Digital Forensics
• +۴ مورد دیگر

Dr. Xiaodong Lin is a Professor at the University of Guelph's School of Computer Science and an IEEE Fellow (2017) for contributions to secure vehicular communications. He leads the Blockchain Technology and Cybersecurity (BTC) lab, focusing on privacy-enhancing technologies, digital forensics, wireless network security, blockchain applications, and DeFi security. PhD, Beijing University of Posts and Telecommunications, China PhD, University of Waterloo, Canada His research bridges theoretical and applied domains in cybersecurity, particularly vehicular networks, smart grids, and decentralized systems. Recent work examines blockchain security, privacy-preserving protocols for IoT, and secure data aggregation in wireless networks. Key publication trends include secure fog computing for vehicular crowdsensing, privacy-preserving authentication in 5G, and cryptographic solutions for smart grids. Awards highlight multiple Best Paper recognitions at IEEE conferences. IEEE Fellow (2017) Best Paper Awards (IEEE INFOCOM 2018, GLOBECOM 2017, SECURECOMM 2016) Dr. Lin supervises graduate students in blockchain security, AI security, and digital forensics. His lab provides financial support to qualified students.

Shaomin Wuمشاهده پروفایل

استاد

• Machine Learning
• Business Analytics
• Risk Management
• +۵ مورد دیگر

Professor Shaomin Wu is a faculty member at the University of Kent's Kent Business School, where he holds the academic rank of Professor of Business/Applied Statistics. He earned an MSc and PhD in applied statistics and has extensive industry experience, including a five-and-a-half-year stint at a global manufacturer in Shanghai before moving to the UK in 2001. He has held roles as a postdoctoral researcher and lecturer before joining Cranfield University and later the University of Kent. His research focuses on recurrent event data analysis, machine learning, and reliability mathematics, with funding from the EPSRC and ESRC. His research projects include managing risk in warranty servicing policies, smart data analytics for local government, and sustainable supply chain demand forecasting. He teaches modules such as risk analysis, reliability engineering, and machine learning. Currently supervising PhD students in time series forecasting, explainable AI, and recurrent event data analysis, he also serves as a co-chair of international conferences, editorial board member, and external examiner for doctoral degrees. Notably, he ranks among the top 2% of global scientists by Stanford University. His work integrates machine learning with business analytics, resilience engineering, and environmental sustainability. Key contributions include IoT-driven resilience methodologies for smart grids and unmanned systems, as well as frameworks for corporate carbon disclosure and maintenance optimization under uncertainty.

Ye Zhishengمشاهده پروفایل

دانشیار

• Inventory Control
• Reliability Engineering
• Emergency Response Systems
• +۴ مورد دیگر

Ye Zhisheng is the Dean’s Chair and Associate Professor in the Department of Industrial Systems Engineering & Management at the National University of Singapore (NUS). His research focuses on reliability engineering, inventory control, emergency response systems, and statistical modeling. He holds a PhD in Industrial and Systems Engineering from NUS, along with a BEng in Material Science and Engineering and a BEco in Economics from Tsinghua University. His work emphasizes practical applications in mission-critical systems, predictive maintenance, and data-driven decision-making. Current research initiatives include optimal maintenance policies for manufacturing systems, degradation analysis of bearings, and federated learning approaches for battery lifecycle prediction. He has pioneered methods for integrating physics-informed neural networks into prognostics and health management (PHM) systems. Key technical contributions span advanced statistical methodologies like sieve estimation for survival data, phase-type distributions modeling, and condition-based maintenance optimization. His interdisciplinary approach bridges operations research, mechanical engineering, and computer science to address complex reliability challenges. Recent projects include resilient consensus-based power grid management and contamination source identification frameworks. Notable collaborations involve developing intelligent cross-domain fault diagnosis systems using transformer networks and advancing the Internet of Federated Things (IoFT) for distributed data analytics. His work has been applied in aerospace, telecommunication infrastructure, and medical emergency response systems.

• Medical Mycology
• Infectious Diseases
• Translational Research
• +۷ مورد دیگر

Olivier Lortholary is Professor of Medicine at Paris Descartes University and holds multiple significant positions in the field of medical mycology and infectious diseases. He serves as Deputy Director of the French National Reference Center for Invasive Mycoses and Antifungals, and is Head of the Necker-Pasteur Center for Infectious Diseases and Tropical Medicine at Necker Hospital in Paris. His work is closely associated with the Institut Pasteur in Paris, France, where he is actively involved in research and teaching initiatives. Dr. Lortholary's educational background includes an M.D. from the Paris 6 School of Medicine and a Ph.D. from Paris 7 University. His extensive academic career has positioned him as a leading expert in medical mycology, with particular focus on fungal infections in immunocompromised patients. His research primarily centers on translational aspects of medical mycology, with special emphasis on Cryptococcus neoformans and cryptococcal meningitis, which represents the leading opportunistic fungal infection in advanced HIV-infected patients. He also investigates new immune deficiencies that predispose individuals to invasive fungal infections, develops diagnostic and therapeutic innovations for these conditions, and conducts clinical and microbiological studies of central nervous system infections and emerging infectious diseases. Dr. Lortholary has made substantial contributions to the field, with over 590 published papers, including more than 12 invited contributions to prestigious journals such as Clinical Infectious Diseases and Lancet Infectious Diseases. His research spans epidemiology of fungal infections, antifungal susceptibility testing, and clinical management approaches across various patient populations. He plays a significant role in shaping clinical guidelines as a member of various international expert panels, including the Infectious Diseases Society of America (for cryptococcosis management), the American Society of Transplantation (for donor-derived fungal infections), and ESCMID (for Candida and other fungal infections). Additionally, he serves as the French representative on the EUCAST Antifungal Susceptibility Testing Committee. As an educator, Dr. Lortholary co-directs the Medical Mycology course at the Pasteur Institute and has developed a MOOC (Massive Open Online Course) on Medical Mycology available through FUN-MOOC, reaching a global audience of healthcare professionals and researchers.

Hui Panمشاهده پروفایل

استاد

• Networking
• Complex networks
• Mobile computing
• +۳ مورد دیگر

Hui Pan is a distinguished academic holding dual positions as Nokia Chair in Data Science and Professor of Computer Science at the University of Helsinki, and Chair Professor of Computational Media and Arts at the Hong Kong University of Science and Technology (HKUST). His research spans networking, mobile computing, augmented reality, and computational social science. He earned his Ph.D. in Computer Science from the University of Cambridge in 2007. His work bridges social networks with mobile systems, pioneering fields like mobile social networks and opportunistic forwarding algorithms. Research interests include data science, complex networks, and innovative applications of augmented reality. His recent publications focus on low-latency AR frameworks, blockchain for computation offloading, and mobile web visualization. He has received prestigious awards, including IEEE Fellow (2018), ACM Distinguished Scientist (2016), and the Nokia Chair Endowment (2017). He has supervised over 15 PhD and 12 MPhil graduates, with 13 current Ph.D. students and 2 MPhil students. His editorial roles include Associate Editorships at IEEE Transactions journals and guest editorships at top venues like IEEE JSAC and ACM Transactions. He has organized conferences such as WWW Track Chair and ExtremeCom General Chair.

Yuanzhu Chenمشاهده پروفایل

استاد

• Computer Networking
• Mobile Computing
• Complex Networks
• +۵ مورد دیگر

Yuanzhu Chen is a Professor in the School of Computing at Queen’s University, affiliated with the Faculty of Arts and Science. He previously served as Professor and Department Head at Memorial University of Newfoundland (2005–2021). His research focuses on computer networking, mobile computing, complex networks, and applied machine learning, emphasizing wireless innovation beyond traditional wired systems. He holds a PhD from Simon Fraser University (2004) and a B.Sc. from Peking University (1999). Education: PhD in Computing Science (Simon Fraser University, 2004); B.Sc. in Computer Science (Peking University, 1999). Earlier roles include Post-doctoral Researcher at Simon Fraser University (2004–2005) and leadership positions at Memorial University, including Department Head (2019–2021). Research Interests: Network Coding and Opportunistic Routing Mobile and Wireless Network Protocols Complex Network Analysis Machine Learning Applications Indoor Positioning Systems Social Network Dynamics Selected Awards: Recipient of Queen’s University President's Award for Distinguished Teaching. Lab Affiliation: Director of the Wireless Networking and Mobile Computing Lab (WineMocol). Active in collaborative projects involving smartphone sensors, community-based environmental monitoring, and stock market prediction using web data.

Kiran T. Thakurمشاهده پروفایل

دانشیار

• Neuroinfectious Diseases
• Neuroimmunology
• Global Health
• +۶ مورد دیگر

Dr. Kiran T. Thakur serves as the Herbert Irving Associate Professor of Neurology at Columbia University Irving Medical Center and practices as an inpatient neurologist at NewYork-Presbyterian/CUIMC. Her clinical expertise spans neuroinfectious diseases, neuroimmunology, emergency neurology, and global health, with active clinical and research engagements across eight countries in Africa, Southeast Asia, and the Caribbean. She holds leadership roles including Neurology Clerkship Director at Perdana University Graduate School of Medicine (Malaysia) and serves as a neurology consultant for the World Health Organization. Her educational background includes an MD from Tufts University School of Medicine (2008), internship at Johns Hopkins Hospital's Osler Medical Service, neurology residency at Harvard's Brigham & Women's Hospital (where she served as chief resident), and fellowship in neuroinfectious disease/neuroimmunology at Johns Hopkins Hospital. She is additionally pursuing a Master of Science in clinical trials at the London School of Tropical Medicine and Hygiene. Dr. Thakur's research program focuses on improving detection and management of neuroinfectious diseases in hospital settings, with particular emphasis on vulnerable populations including HIV-positive individuals and immigrants. Her work integrates clinical, translational, and implementation science approaches to address cerebral malaria, tuberculous meningitis, Zika-related complications, and SARS-CoV-2 neurological outcomes. Current projects investigate novel diagnostics for infectious meningoencephalitis, risk factors for neuroinvasive infections, and therapeutic strategies for viral encephalitis. Analysis of her 15 most recent publications reveals consistent focus on neuroinfectious disease epidemiology (particularly in resource-limited settings), diagnostic challenges in immunocompromised patients, and global health implementation strategies. Her work prominently features Zika virus complications, tuberculous meningitis management, and CNS infections in travelers, reflecting her dual expertise in tropical medicine and neuroimmunology. Scientific recognition includes: Lewis P. Rowland Teaching Award (Columbia University, 2016) CDC Nakona Citation Award (2014) Dr. Thakur directs the NIH NINDS K23-funded study on pathogen identification in neurological infections (2018-2023) and leads Columbia's post-doctoral neuroinfectious disease fellowship for physician-scientists from low/middle-income countries. Her research program receives support from the NIH, World Federation of Neurology, and American Academy of Neurology, with implementation studies conducted in collaboration with WHO, PAHO, and CDC. The Thakur Laboratory at Columbia's Neurological Institute coordinates international research networks across Malawi, Vietnam, Bangladesh, Uganda, and the Dominican Republic. Her team conducts clinical trials on antimicrobial dosing, develops diagnostic algorithms for resource-limited settings, and implements training programs to build neuroinfectious disease capacity in underserved regions, with current emphasis on SARS-CoV-2 neurological sequelae and tropical disease management.

Dmitri Perkinsمشاهده پروفایل

استاد

• Wireless Communications
• Mobile Networking
• Network Security
• +۴ مورد دیگر

Dmitri Perkins is a Professor at the Department of Computer Science and Electrical Engineering within the College of Engineering and Information Technology at the University of Maryland, Baltimore County (UMBC). He has held leadership roles including Senior Program Director at the National Science Foundation (2021-2024) and Lead Program Director for the NSF's Industry-University Cooperative Research Centers (2015-2019). His research spans wireless and mobile networking paradigms, including cognitive radio, sensor networks, and large-scale heterogeneous systems. Ph.D., Computer Engineering, Michigan State University (2002) M.S., Computer Engineering, Michigan State University (1997) B.S., Computer Science, Tuskegee University (1995) His research focuses on adaptive protocol design , spectrum management , and network security . Key areas include dynamic spectrum access , cross-layer optimization , and formal performance evaluation in wireless systems. Publications highlight innovations in cognitive radio networks , IoT protocols , and secure wireless communication . Recent publications emphasize machine learning for spectrum efficiency , edge computing in heterogeneous networks , and security frameworks for wireless systems. The 15 most recent works (2002-2018) demonstrate expertise in protocol design , network scalability , and spectrum optimization . NSF CAREER Award (2005) NSF Director's Award for Superior Accomplishment (2024) ONR Research Fellow, U.S. Naval Research Lab (2013-2014) He leads a research lab at UMBC offering RA positions in spectrum research , IoT/CPS systems , and wireless cybersecurity . Prior to UMBC, he served as Hardy Edmiston Endowed Professor at the University of Louisiana at Lafayette and held roles at the U.S. Naval Research Laboratory.

Jonathan Andrew Crowcroftمشاهده پروفایل

استاد

• Computer Networks
• Distributed Systems
• Opportunistic Communications
• +۷ مورد دیگر

Jon Crowcroft is the Marconi Professor of Communications Systems in the Department of Computer Science and Technology at the University of Cambridge, and serves as the Chair of the Programme Committee at the Alan Turing Institute. He is also a Fellow of Wolfson College, Cambridge, and a visiting professor at the Department of Computing at Imperial College London. With a career spanning over three decades in computer networking research, Professor Crowcroft has made seminal contributions to the development of the Internet and continues to be highly active in cutting-edge research areas. His educational background includes: BA in Physics from Trinity College, University of Cambridge (1979) MSc in Computing from University College London (1981) PhD from University College London (1993) Professor Crowcroft's research spans multiple domains in computer networking and distributed systems. He has worked in Internet support for multimedia communications for over 30 years, with three main focus areas: scalable multicast routing, practical approaches to traffic management, and the design of deployable end-to-end protocols. His current research focuses on opportunistic communications, social networks, and techniques to scale infrastructure-free mobile systems. He is particularly known for his 'build and learn' paradigm for research and has recently been exploring decentralized digital identification systems, smart cities, and edge computing. His work often bridges theoretical foundations with practical implementations, emphasizing privacy-preserving approaches and sustainable network architectures. Professor Crowcroft has received numerous prestigious awards recognizing his contributions to the field, including: Election as Fellow of the Royal Society (2013) ACM SIGCOMM Award (2009) ACM Fellow (2002) Fellow of the Royal Academy of Engineering IEEE Fellow (2004) Chartered Fellow of the British Computer Society Throughout his career, Professor Crowcroft has advised numerous PhD students, including Mark Handley and Pan Hui, who have themselves become influential researchers in the networking community. He has authored several influential books that have been adopted internationally in academic courses, such as 'TCP/IP & Linux Protocol Implementation,' 'Internetworking Multimedia,' and 'Open Distributed Systems.' His research has been supported by various grants and collaborations with both academic institutions and industry partners, contributing to successful startup projects and influencing Internet standards. Professor Crowcroft is actively involved in several research initiatives, including serving on the Scientific Council of IMDEA Networks Institute since 2007 and the advisory board of the Max Planck Institute for Software Systems. He is also a director of the Matrix Foundation, which develops open network protocols. His current research group focuses on privacy-preserving analytics, decentralized systems, and the future of Internet architecture.

• Experimental and Behavioral Economics
• Neuroeconomics
• Trust Behavior
• +۳ مورد دیگر

Professor Michael Naef is the Head of the Department of Economics and a Professor at Durham University's Business School. His research focuses on Experimental and Behavioral Economics and Neuroeconomics , exploring topics such as trust dynamics, cultural influences on cooperation, and neurochemical effects on decision-making. He leads the Department of Economics within a triple-accredited business school, emphasizing academic excellence and global connections. Key research interests include investigating how dopamine receptors modulate trust behavior, the origins of cooperative behavior in rice-farming cultures, and the role of testosterone in social interactions. His work combines experimental economics with neuroscience and psychology, often employing pharmacological interventions and neuroimaging techniques. Publications highlight contributions to understanding volatility in trust beliefs (2023), the neurobiological basis of social learning (2019), and testosterone's influence on competitiveness (2017). He advises PhD students Angel Li and Zekun Lin, focusing on advancing behavioral economic theory and applications. Prof. Naef's research has implications for understanding cultural economic differences, mental health impacts on decision-making, and the biological underpinnings of social preferences. His work bridges disciplines, fostering interdisciplinary collaborations in economics, neuroscience, and endocrinology.

Hesham ElSawyمشاهده پروفایل

استادیار

• Wireless Networks
• Internet of Things (IoT)
• Federated Learning
• +۳ مورد دیگر

Hesham ElSawy is an Assistant Professor in the Department of Systems and Networks at the School of Computing, Faculty of Arts and Science, Queen's University. His work focuses on advancing next-generation wireless systems, with particular emphasis on federated learning, IoT networks, and edge computing. He is affiliated with Ingenuity Labs Research Institute, Queen's University, and contributes to interdisciplinary research at the intersection of communication theory and network optimization. His research interests span stochastic geometry modeling, energy-efficient protocols for massive IoT deployments, and resilient federated learning frameworks. ElSawy explores novel paradigms in aerial wireless networks, UAV-assisted communication, and network security through percolation theory applications. Recent publications highlight his contributions to system-level analysis of parallel computing at extreme edges, UAV-enabled federated learning architectures, and energy-as-a-service models for RF-powered networks. His work emphasizes practical implementations and large-scale network validation. ElSawy holds no listed awards or grants in the provided text but maintains active collaborations through Ingenuity Labs. His research addresses critical challenges in 5G/6G networks, including latency optimization, resource allocation, and heterogeneous network integration.

• Control Technology
• Distributed Optimization
• Machine Learning
• +۴ مورد دیگر

Mikael Johansson is a Professor at Kungliga Tekniska Högskolan (KTH), specializing in Control Technology . He teaches and coordinates courses such as Distributed Optimization (FEL3311) and various advanced-level degree projects in computer science, electrical engineering, and systems engineering. His research spans Control Systems , Machine Learning , and Optimization , with a focus on asynchronous algorithms, federated learning, and applications in energy systems and construction. His work includes 15 recent publications on topics like neural networks, distributed optimization, and battery technology. Notable areas of contribution are in asynchronous learning, federated learning with privacy constraints, and quasi-Newton methods for optimization. His research bridges theoretical advancements with practical applications in urban design, healthcare, and autonomous systems.

• Internet of Things (IoT)
• Wireless Communications
• Statistical Signal Processing
• +۳ مورد دیگر

Professor Jinho Choi is a Chair and Professor in Radio Frequency at the School of Electrical and Mechanical Engineering, University of Adelaide, Australia. He holds a B.E. (magna cum laude) from Sogang University, and M.S.E. and Ph.D. degrees from KAIST. His research focuses on advancing wireless communication and sensing technologies, particularly in IoT, 5G/6G, non-terrestrial networks, and cognitive satellite systems. He authored three books and has been recognized with the 1999 EURASIP Best Paper Award, IEEE Fellowship, and inclusion in Stanford's Top 2% Scientists list since 2020. He currently serves as a Senior Editor of IEEE Wireless Communications Letters and editorial roles in multiple journals. Education: B.E. (Electronics Engineering) - Sogang University, Seoul (1989) M.S.E. (Electrical Engineering) - KAIST (1991) Ph.D. (Electrical Engineering) - KAIST (1994) Research Interests: Professor Choi's work addresses connectivity challenges in non-terrestrial networks, leveraging statistical signal processing and machine learning. Current projects include UAV-assisted LEO satellite technologies, cognitive satellite radios, and semantic communication protocols. His research aims to enhance global connectivity and efficiency in terrestrial and satellite networks. Publications: His recent work spans semantic communication, satellite quantum key distribution, federated learning optimization, and coverage diversity in mega constellations. These studies reflect trends in 6G-ready technologies, AI-driven communication systems, and hybrid satellite-terrestrial networks. Awards: 1999 Best Paper Award for Signal Processing (EURASIP) IEEE Fellow (Leadership in technical excellence) World’s Top 2% Scientists (Stanford University, 2020–present) Grants & Supervision: As a senior academic, he oversees grants in wireless innovation and has advised numerous students on advanced communication systems. His lab focuses on next-generation networks, integrating theoretical insights with practical implementations. Labs/Teams: Active in interdisciplinary teams at the University of Adelaide, collaborating on projects funded by industry and government to bridge gaps between academic research and real-world applications.