جستجوی استاد راهنمای دانشگاهی

Emily Bernhardtمشاهده پروفایل

استاد

• Ecosystem Ecology
• Biogeochemistry
• Climate Change Ecology
• +۷ مورد دیگر

Emily Bernhardt is a Professor of Ecosystem Ecology and Biogeochemistry at Duke University's School of the Environment. She leads the Duke Aquaterrestrial Biogeochemistry Lab, which focuses on tracking elemental movement in ecosystems and assessing human impacts like urbanization, agriculture, and climate change. Her work bridges aquatic and terrestrial systems, emphasizing policy-relevant science. Education: Ph.D., Cornell University (2001); B.S., University of North Carolina, Chapel Hill (1996) Research Themes: Saltwater intrusion in coastal wetlands, mercury pollution from gold mining, ecosystem metabolism, and long-term ecological monitoring Recent grants include LTER funding for Hubbard Brook research and THELORACS project collaborations. Awards include election to the National Academy of Sciences (2023) and the 2023 Duke Sustainability Champion honor. Key Projects: Exploring ghost forest expansion due to sea-level rise in North Carolina, evaluating LiDAR for tree health monitoring, and modeling carbon dynamics in rivers Labs/Teams: Collaborative efforts with the Hubbard Brook Experimental Forest and coastal wetland networks

Allison Stromمشاهده پروفایل

استادیار

• Galactic Evolution
• Astrophysics
• Stellar Feedback Mechanisms
• +۳ مورد دیگر

Allison Strom is an Assistant Professor in the Department of Physics and Astronomy at Northwestern University’s Weinberg College of Arts & Sciences. Her research focuses on galaxy formation and evolution using large-scale telescopic observations, particularly investigating baryonic processes such as accretion, stellar feedback, and outflows within dark matter halos. She holds a PhD from the California Institute of Technology (2017). Her research interests include chemical evolution of galaxies through spectroscopy, physical properties of distant galaxies (star formation rates, gas masses, electron densities), and massive stellar populations’ contributions to galactic feedback. She uses rest-UV and rest-optical spectroscopy to trace galactic chemical abundances and ionization states. Strom’s recent work emphasizes high-redshift galaxy studies, including circumgalactic medium dynamics, Lyα emission mechanisms, and ionizing radiation escape fractions. Her publications span observational surveys like CLASSY and KBSS-MOSFIRE, focusing on spectroscopic analysis and cosmological simulations. Awards: Packard Fellow (2024) Scialog Fellow (2024) Kavli Fellow (2024) Her research integrates observational data with theoretical models, addressing questions about galactic chemical enrichment, stellar feedback effects, and the interplay between galaxies and their environments. She contributes to major projects like the Keck Baryonic Structure Survey and COS Legacy Archive Spectroscopic Survey.

• Machine Learning
• 3D Computer Vision
• 3D Multimedia Signal Processing
• +۵ مورد دیگر

Professor Wanqing Li is a leading academic in machine learning and 3D computer vision at the University of Wollongong, where he serves as Director of the Advanced Multimedia Research Lab (AMRL). He holds a B.Sc. and M.Sc. from Zhejiang University and a Ph.D. from The University of Western Australia. His career includes roles at Motorola Labs (Senior/Principal Researcher) and visiting stints at Microsoft Research. His research focuses on 3D multimedia signal processing, human activity understanding, and medical image processing, with applications in aged care and health monitoring. He has published over 250 papers in top venues like TIP, CVPR, and AAAI, and his work has been recognized with awards including the Motorola CTO’s Award (2003). He currently leads the Centre for Artificial Intelligence (CAI) at UOW and is a co-founder of the Centre for Multimedia Signal Processing and Content Management. Education: B.Sc. (Zhejiang University), M.Sc. (Zhejiang University), Ph.D. (University of Western Australia). Research Interests: Machine Learning (statistical/deep learning), 3D computer vision (human motion analysis, 3D reconstruction), medical imaging, free-viewpoint video systems, and applications in healthcare. He pioneered 3D data-driven human activity understanding, now a cornerstone of modern computer vision. Awards & Recognition: Motorola CTO’s Award (2003), Australia’s top multimedia researcher (2021–2023), elected Associate Editor of IEEE Transactions on Image Processing (2022). Labs/Teams: Director of Advanced Multimedia Research Lab (AMRL), co-founder of CAI and Multimedia Signal Processing Centre.

Guoxin Suمشاهده پروفایل

مدرس ارشد

• Formal Methods
• Probabilistic Verification
• Multi-Agent Systems
• +۲ مورد دیگر

Guoxin Su is a Senior Lecturer in the School of Computing and Information Technology at the University of Wollongong. He holds a Ph.D. in Computer Science from the University of Technology Sydney (2013) and previously served as a Senior Research Fellow at the National University of Singapore. His research spans software engineering (formal methods, probabilistic verification) and artificial intelligence (multi-agent systems, reinforcement learning). Current projects focus on developing verification techniques for distributed systems and adaptive AI algorithms. Su secured multiple grants including AUD $30,000 from the Australian Department of Defence for research on multi-agent systems. He teaches courses in Systems Analysis, Software Engineering Practices, and Big Data Management. As an active researcher, he serves on program committees for AIACT and CECIT conferences and reviews for IEEE Transactions on Software Engineering and IEEE Transactions on Information Forensics and Security.

Balakrishnan Chandrasekaranمشاهده پروفایل

استادیار

• Networked Systems
• Blockchain Technology
• Cybersecurity
• +۳ مورد دیگر

Balakrishnan Chandrasekaran is an Assistant Professor in the Department of Computer Science at Vrije Universiteit Amsterdam, holding tenure-track status. He previously served as a Senior Researcher at the Max-Planck-Institut für Informatik in Saarbrücken, Germany. He earned his Ph.D. from Duke University in the United States. His research focuses on enhancing the performance and security of networked systems, with contributions spanning blockchain technology, latency reduction, and optical data center networks. Education: Ph.D. in Computer Science from Duke University (USA), followed by postdoctoral research at Max-Planck-Institut. His academic journey emphasizes both theoretical and applied networking challenges. Research Interests: Blockchain governance and transaction transparency Optimization of network congestion control (e.g., BBRv3) High-performance optical data center architectures Security implications of modern networking paradigms Recent work explores frameworks like Lighthouse for optical testbeds and analyses of blockchain transaction fairness. His publications address both foundational network principles and applied solutions for real-world systems. Teaching: Currently instructs courses on Network Security and Systems Seminar , integrating cutting-edge research into pedagogy. Labs/Teams: Leads projects in optical data center networking and blockchain security through collaborative frameworks like DEMO and VOXEL.

Edwin Renمشاهده پروفایل

دانشیار

• Internet of Things
• 4G/5G Mobile Telecommunication Networks
• Cloud Computing
• +۸ مورد دیگر

Edwin Ren is an Associate Professor in the School of Computing Sciences at the University of East Anglia (UEA), UK. His research focuses on Internet of Things (IoT), 5G/6G networks, cloud computing, and cybersecurity. He holds a PhD in Information Communication Technology from the University of Agder, Norway, and has held postdoctoral positions at National Chiao Tung University, Taiwan. Ren is a member of the Cyber Intelligence and Networks and Data Science & AI groups at UEA. **Education**: - PhD in Information Communication Technology, University of Agder, Norway (2012) - Postdoctoral Fellow at National Chiao Tung University (2012–2017) **Research Interests**: - IoT and Smart Systems - Network Function Virtualization (NFV) and SDN - Blockchain-based Security Protocols - Mobile Edge Computing and 5G/6G Architectures - Privacy-Preserving AI and Federated Learning **Key Achievements**: - Best Paper Award at IEEE MDM 2012 - Active in interdisciplinary projects like the Training DIGIT initiative (EPSRC-funded) and Smart Environments Research Facility **Grants & Collaborations**: - EPSRC-funded projects on Digital Innovation and Cyber-Physical Systems - Royal Society-supported AIoT platform research **Labs/Teams**: - Leads the Cyber Intelligence and Networks research group at UEA - Involved in the Smart Environments Research Facility, a multidisciplinary EPSRC project

• Environmental Engineering
• Hydrology
• Climate Change
• +۳ مورد دیگر

Nikolaidis Nikolaos is a Professor at the School of Chemical and Environmental Engineering at the Technical University of Crete. His research focuses on environmental systems, with emphasis on hydrological modeling, climate change impacts, and sustainable resource management in Mediterranean regions. His work integrates field observations with computational modeling to address complex environmental challenges. Research spans watershed management, soil functions, climate adaptation strategies, and socio-ecological systems. Professor Nikolaidis leads interdisciplinary initiatives and maintains the HERS Lab (Hydro-Environmental Research and Simulation), fostering collaborations across environmental science and engineering disciplines.

• Computational Intelligence
• Soft Computing Methods
• Decision Support Systems
• +۵ مورد دیگر

Jozef M. Zurada is a Professor in the Department of Computer Information Systems at the University of Louisville's College of Business. He has held visiting roles at Edith Cowan University (Australia) and the University of Alberta (Canada). His research focuses on computational intelligence, soft computing, and data analytics applications in business and manufacturing systems. He teaches Data Mining, Machine Learning, and Infrastructure Technologies. Education: DSc (Technical Sciences, Informatics) - Polish Academy of Sciences, Poland PhD (Computer Science Engineering) - University of Louisville MS (Electrical Engineering) - Technical University of Gdansk, Poland Research Interests: Dr. Zurada explores advanced computational methods to enhance decision-making in business systems, including neural networks, data stream analysis, and predictive modeling. His work bridges theoretical computer science with practical applications in real estate analytics, manufacturing optimization, and sustainable business strategies. Awards: 2011 Distinguished Research and Development Award (International Association of Assessing Officers) 1998 Faculty Excellence Award (University of Louisville) 1997 Achievement Award Nominee (Conference of Southern Graduate Schools) 1996 Outstanding Scholarship Award (University of Louisville) 1981 President's Award (University of Gdansk) Teaching & Advising: Teaches core data science courses. No student advisees explicitly listed in texts. Recent Publications Trends: Recent works emphasize big data's role in business innovation, text classification improvements using feature selection, and real-time adverse event detection in streaming data environments.

Michael Flemingمشاهده پروفایل

دانشگاهی

• Political Economy
• Critical Criminology
• Toxic Masculinity
• +۵ مورد دیگر

Dr. Michael (Mike) Fleming is an Assistant Teaching Professor in the Department of Sociology at the University of New Brunswick (Fredericton campus). He holds a PhD in Sociology with specialization in Work and Development from Memorial University of Newfoundland, alongside MA and BA degrees from UNB and St. Thomas University. His teaching focuses on public sociology/criminology and social justice, emphasizing critical approaches to power dynamics in capitalist societies. Research interests include political economy, critical criminology, toxic masculinity, policing, and corporate crime, particularly analyzing maple syrup marketing theft in Atlantic Canada. Education: PhD, Memorial University of Newfoundland (specializing in Work and Development) MA, University of New Brunswick BA (hons), St. Thomas University Research emphasizes corporate crime in Canada and resilience theories in economically dependent communities. His work has been featured in Canadian Truck News and Eastern Trucking News, and he presented at major conferences like the Canadian Sociological Association and Atlantic Canada Studies Conference. He currently serves as President of the Board of Directors for Fredericton Community Kitchens, Inc. His publications span topics like trucking industry sociology, user modeling in mixed-initiative systems, and trust mechanisms in electronic marketplaces.

Esmaeil Bahalkehمشاهده پروفایل

استادیار

• Hospital Operations Management
• Healthcare Access
• Health Services Delivery
• +۶ مورد دیگر

Esmaeil Bahalkeh serves as Assistant Professor in the Department of Health Management and Policy at the University of New Hampshire, where his NIH-funded research bridges industrial engineering and healthcare delivery systems. His work focuses on optimizing hospital operations and expanding healthcare access through advanced analytical methods. His academic credentials include: Ph.D. in Industrial Engineering from Purdue University M.S. in Industrial & Systems Engineering from Ohio University B.S. in Industrial Engineering from Sharif University Bahalkeh's research program centers on two interconnected streams: Hospital Operations Management examines resource allocation, workforce scheduling, and financial sustainability in healthcare settings, while his Healthcare Access stream investigates systemic barriers and operational solutions across emergency services, long-term care, and ambulatory settings. He employs discrete event simulation, machine learning, and data mining to model complex healthcare systems and test policy interventions. His publication trajectory from 2015-2025 reveals consistent methodological evolution from manufacturing systems theory toward healthcare-specific applications, with recent work emphasizing interpretable AI for hospital service lines and access improvement strategies in specialized clinics. Over 70% of his recent publications address operational challenges in critical care and outpatient settings. Bahalkeh teaches core courses including Healthcare Operations Management (HMP 712), Machine Learning in Healthcare (HDS 805), and Quality Improvement for nursing practitioners (NURS 933), integrating his research on data-driven decision making into both undergraduate and doctoral programs.

• Cloud Computing
• Deep Learning
• Computer Vision
• +۳ مورد دیگر

Muhammad Usman Yaseen is an Associate Lecturer at the College of Science and Engineering, University of Derby. His research focuses on cloud computing, deep learning applications in video analytics, IoT security, and healthcare informatics. He has contributed to scalable object detection systems, deep learning pipeline modeling, and cybersecurity frameworks for smart environments. His work bridges theoretical advancements with practical implementations in distributed computing systems. Research trends in his publications emphasize hybrid deep learning architectures, anomaly detection in IoT networks, and health-related predictive models. He explores topics including mental health prediction via social media analysis, SAR image enhancement, and medical imaging diagnostics for conditions like facial paralysis and brain hemorrhages. His work often addresses real-world challenges in edge-cloud integration, resource optimization, and interpretable AI systems. No scientific awards or grant details are explicitly mentioned. He collaborates with researchers in computer science and engineering disciplines, contributing to both theoretical and applied research in distributed systems and AI-driven solutions. His research outputs reflect a focus on interdisciplinary applications of machine learning across healthcare, cybersecurity, and environmental imaging domains.

Yong Seog Kimمشاهده پروفایل

استاد

• Decision Support Systems
• Data Mining
• Feature Selection
• +۶ مورد دیگر

Yong Seog Kim is a Professor in the Department of Data Analytics and Information Systems at Utah State University's Huntsman School of Business. His primary research focuses on decision support systems and the development of data mining algorithms for feature selection, clustering, and streaming data analysis, with applications in customer relationship management, e-commerce, and computational finance. Education: Ph.D., Management Information Systems, University of Iowa M.A., Computer Science, University of Iowa M.A., Economics, Yonsei University B.A., Economics, Yonsei University Research Focus: Dr. Kim's interdisciplinary work bridges data science and applied domains. He specializes in predictive modeling for business optimization, social dynamics simulation, and inclusive systems design, particularly for populations with disabilities. His methodological innovations include agent-based simulations for crowd evacuation and novel clustering techniques for high-dimensional data. Publication Trends: His recent work demonstrates a strong emphasis on practical applications of analytics in diverse sectors including agriculture, transportation safety, financial regulation, and disability services. Methodologically, his articles showcase advanced techniques in machine learning, simulation modeling, and knowledge graph construction. Recognition: Outstanding Graduate Mentor of the Year (2021) Academic Leadership: Dr. Kim mentors graduate students and leads courses in Data Mining and Visual Analytics. His work with the Analytics Solutions Center facilitates industry-academia partnerships.

Chad Mourningمشاهده پروفایل

استادیار

• Computer Graphics
• Data Visualization
• Virtual and Augmented Reality
• +۳ مورد دیگر

Chad Mourning is an Assistant Professor at the Department of Electrical Engineering and Computer Science within the Russ College of Engineering and Technology at Ohio University. He specializes in computer graphics, data visualization, virtual/augmented reality, machine learning for meteorology, and cybersecurity. His research focuses on applications such as real-time weather visualization for aviation safety, antenna pattern analysis, and machine learning-driven sensor networks. He holds patents for technologies like 'Reduction of Sensor Captured Data Streamed to an Operator' and 'Wake Turbulence Analyzer for Real-Time Visualization, Detection, and Avoidance.' His work integrates interdisciplinary approaches, combining aerospace engineering with computational methods to enhance aviation safety and cybersecurity. Patents: REDUCTION OF SENSOR CAPTURED DATA STREAMED TO AN OPERATOR (9,756,280) Wake Turbulence Analyzer for Real-Time Visualization, Detection, and Avoidance (9,709,698) Dr. Mourning's recent publications span topics such as augmented reality weather systems, NOTAM data processing via NLP, and low-cost distributed aviation weather sensors. He actively engages in educational initiatives, including cybersecurity workshops for K-12 teachers. His lab explores cutting-edge applications of quantum computing in aviation security and parallel computing for high-fidelity antenna visualization.

• Green and Sustainable Computing
• High-Performance Computing
• AI-Driven Assistive Technologies
• +۹ مورد دیگر

Dr. Ishfaq Ahmad is a Full Professor of Computer Science and Engineering at The University of Texas at Arlington (UTA) since 2002, with prior roles as Associate Professor and Director of the Multimedia Technology Research Center at the Hong Kong University of Science and Technology. He leads the Institute of Research in Security (IRIS) at UTA and has extensive industry collaboration, overseeing over $15M in research funding. His research focuses on sustainable computing, AI-driven assistive technologies, IoT, and high-performance computing. Dr. Ahmad has authored over 290 publications and holds prestigious awards including IEEE Fellow and IDES Distinguished Life Fellow. Education: PhD in Computer Science (Syracuse University, 1992), M.S. in Computer Engineering (Syracuse University, 1987), B.S. in Electrical Engineering (University of Engineering and Technology, Lahore, 1985). Research Interests: Green Computing, Exascale Systems, Assistive Technologies, Smart Grids, and STEM Education. His work emphasizes sustainability and interdisciplinary innovation, with contributions to video compression, parallel algorithms, and technology transfer. Awards & Grants: Over 40 international awards, including Google Scholar top rankings in multiple fields. Key grants include NSF-funded projects on assistive technologies and sustainable computing, along with industry partnerships like those with Adobe and Sun Microsystems. Labs & Leadership: Founded Journal of Sustainable Computing and the International Green and Sustainable Computing (IGSC) conference. Serves as Editor-in-Chief of Springer’s Discover Internet-of-Things and on editorial boards of IEEE journals.

Upendranatha Sharma Chakravarthyمشاهده پروفایل

استاد

• Big Data Analytics
• Machine Learning
• Cloud Computing
• +۷ مورد دیگر

Dr. Upendranatha Sharma Chakravarthy is a Professor in the Department of Computer Science and Engineering at The University of Texas at Arlington (UTA), where he has served since January 2000. He leads the Information Technology Laboratory (IT Lab), established in 2000, and oversees the NSF-funded Distributed and Parallel Computing Cluster. His roles include academic leadership, research mentorship, and contributions to the College of Engineering. Education: He holds a B.E. in Electrical Engineering from the Indian Institute of Science (1973), M.Tech from IIT Bombay (1975), and Ph.D. from the University of Maryland (1985). Prior to UTA, he was at the University of Florida (1989–1999) and held industry roles at Xerox and Computer Corporation of America. Research Interests focus on Big Data Analytics using AI/ML, graph mining, multilayer networks, stream data processing, and distributed systems. His work emphasizes scalability, real-time data handling, and applications in social networks, healthcare, and cybersecurity. Recent projects include MLN-geeWhiz (multilayer network analysis), CoWiz (Covid-19 visualization), and NetSplicer (scalable network algorithms). Awards include ACM Distinguished Scientist (2011), IEEE Senior Member (2011), and multiple university awards for research excellence. He organizes conferences (e.g., DEBS 2013) and teaches advanced topics in databases, data mining, and parallel computing. Grants: Active NSF funding includes NetSplicer (2020–2025) and CyberTraining (2023–2024). He has supervised 15 PhD and 85 MS students. The IT Lab collaborates with industry/government on projects like ROMAN (airborne networks) and justice-in-data initiatives. Labs/Teams: IT Lab specializes in big data science, developing tools like ModViz (data visualization) and VideoScoop (video analysis). It also promotes underrepresented STEM participation through BPC initiatives.