جست‌وجوی استاد و پژوهشگر

Franz J. Kurfessمشاهده پروفایل

استاد

• Artificial Intelligence
• Human-Computer Interaction
• Deep Learning
• +۵ مورد دیگر

Dr. Franz J. Kurfess is a Professor in the Computer Science and Software Engineering Department at California Polytechnic State University (Cal Poly, San Luis Obispo). Since 2020, he has participated in the CSU Pre-Retirement Reduction in Time-Base (PRTB) Program, teaching primarily during Fall and Winter quarters while maintaining academic advising roles. He coordinates international exchange programs for the College of Engineering and focuses on interdisciplinary research in Artificial Intelligence (AI), Human-Computer Interaction (HCI), and Deep Learning applications in agriculture, environmental science, and public safety. Education and Professional Background: No formal education details provided in the text, but his career spans over three decades in academia with a focus on computational systems and educational innovation. His teaching includes advanced courses like Human-Computer Interaction (CSC 486) and User-Centered Design (CPE/CSC 484), emphasizing practical, project-based learning with industry collaboration. Research Interests: Combines technical expertise in AI with societal applications, including wildlife population monitoring, UAV navigation systems, agricultural automation, and ethical considerations in data science. His work bridges theory and practice through collaborations with external partners, such as the 'CSU-FORWARD' diabetes initiative and shark surveillance projects. Publications Highlight: Over 50 publications since 1983, with recent focus on AI-driven solutions for environmental challenges (e.g., livestock detection via aerial imaging) and educational technology (e.g., cross-class AI project collaboration). Early work includes foundational contributions to neural networks and knowledge management systems. Awards and Recognition: No explicit awards listed, but sustained academic contributions are evident through his prolific publication record and leadership in international exchange programs. His role as a faculty advisor for student theses and senior projects underscores his commitment to mentoring. Labs and Teams: Engaged in interdisciplinary collaborations, including the School Safety Project and UAVSim open-source development. Active in curriculum design for HCI and AI courses that integrate real-world problem-solving.

• Positron spectroscopy
• Materials science
• Surface physics
• +۷ مورد دیگر

Dr. Ali R. Koymen is a Professor in the Physics Department at The University of Texas at Arlington with a distinguished career spanning several decades. His academic journey began with a BS in Physics from Hacettepe University in 1977, followed by an MS (1980) and PhD (1984) from the University of Michigan. Dr. Koymen's research focuses on positron spectroscopy, materials science, and nanotechnology, with particular expertise in surface analysis using positron annihilation techniques. His work bridges fundamental physics with practical applications in energy, healthcare, and advanced materials. Recent publications demonstrate his continued leadership in graphene research, positron physics, and machine learning applications in radiation detection. His publication record shows consistent contributions to understanding electron emission mechanisms, surface properties of novel materials, and developing advanced analytical techniques. Dr. Koymen has made significant contributions to the field of positron-induced electron spectroscopy and Doppler broadening spectroscopy for surface analysis. Among his notable achievements are multiple grants from the National Science Foundation, Robert A. Welch Foundation, and industry partners including Lockheed Martin Corporation. His research has been supported by federal, state, and private funding sources totaling millions of dollars for projects including the development of advanced positron beam systems and antimatter containment technologies. Dr. Koymen has mentored graduate students including Jack Driscoll and Vivek Khichar, serving as Dissertation Committee Chair. He continues to be an active educator, teaching Quantum Mechanics courses through Fall 2025 and maintaining a robust research program with presentations at major conferences through 2024.

Sophie Coulsonمشاهده پروفایل

استادیار

• Sea Level Change
• Ice Sheet Dynamics
• Mantle Flow
• +۵ مورد دیگر

Sophie Coulson is an Assistant Professor of Geophysics in the Department of Earth Sciences at the University of New Hampshire. She received her Ph.D. in Earth and Planetary Sciences from Harvard University and previously worked at Los Alamos National Laboratory as part of the Ice Sheet Group. Her research focuses on flow and deformation in the Earth's interior and the effect these processes have on changing sea level and ice sheet stability over diverse timescales. Dr. Coulson's research interests include: Sea Level Change Ice Sheet Dynamics Mantle Flow and Dynamic Topography Glacial Isostatic Adjustment (GIA) Paleoclimate Reconstruction Gravitational Effects on Sea Level Her recent publications demonstrate expertise across multiple domains of Earth sciences, with particular focus on detecting the 'sea level fingerprint' of ice sheet melt, 3-D crustal deformation from ice mass loss, and historical sea level changes during events like the Messinian Salinity Crisis and Viking settlements in Greenland. Her work has been published in top journals including Science, Science Advances, and PNAS. Dr. Coulson has received significant media attention for her research, with coverage in Nature, The Washington Post, CNN, and NBC News. She actively participates in major scientific conferences including PALSEA meetings and AGU Fall Meetings, where she has convened sessions on ice sheet-solid Earth interactions. As an educator, she teaches courses including ESCI 402: Earth History, ESCI 734/834: Global Geophysics, and ESCI 795/895: Topics in Sea Level Change & Geodynamics. She mentors graduate students including Grace Ertel (PhD student) working on ocean dynamics and solid-Earth deformation interactions. Dr. Coulson is committed to outreach, having led numerous workshops for girls in STEM programs across New Mexico.

Qian Liaoمشاهده پروفایل

استاد

• Environmental Fluid Mechanics
• Hydrodynamic-Biogeochemical Modeling
• Hydraulics and Hydrology
• +۲ مورد دیگر

Qian Liao is a Professor in the Department of Civil and Environmental Engineering at the University of Wisconsin-Milwaukee's College of Engineering & Applied Science. Currently on sabbatical for the Fall 2024 semester, Dr. Liao specializes in environmental fluid mechanics and aquatic system dynamics. Dr. Liao holds a PhD in Civil and Environmental Engineering from Cornell University (2004), an MS in Urban and Environmental Science from Peking University (1999), and a BS in Hydraulic and Hydropower Engineering from Tsinghua University (1996). His research focuses on: Hydrodynamic-biogeochemical interactions in aquatic systems Turbulence modeling and mixing processes Advanced flow measurement techniques including imaging-based analysis Hydraulic systems and watershed management His recent publications demonstrate strong focus on signal processing applications in sensing systems, radar technologies, and wireless communications, with particular emphasis on multi-target localization, signal authentication, and efficient computational methods.

Tian Zhaoمشاهده پروفایل

دانشیار

• Type systems
• Type inference
• Static analysis
• +۴ مورد دیگر

Tian Zhao is an Associate Professor in the Department of Computer Science at the University of Wisconsin-Milwaukee, affiliated with the College of Engineering & Mathematical Sciences. Currently on sabbatical for the Fall 2024 semester, Dr. Zhao earned a PhD from Purdue University in 2002. PhD, Purdue University, 2002 Dr. Zhao's research spans type systems, type inference, static analysis, and domain-specific programming. Their work bridges theoretical foundations with practical applications in programming languages and software engineering. Key publication trends highlight expertise in JavaScript, asynchronous programming, logical frameworks, semantic web technologies, and memory management. Articles emphasize static analysis, formal methods, and domain-specific language design.

Thomas Millerمشاهده پروفایل

استاد مدعو

• Wood Engineering
• Structural Analysis
• Seismic Performance
• +۲ مورد دیگر

Thomas Miller is an Adjunct Professor in the Wood Science & Engineering department at Oregon State University , affiliated with the College of Forestry. His work focuses on structural engineering, seismic performance, and finite element modeling of wood-based systems. Research Interests : Wood engineering, CLT diaphragms, seismic resilience, finite element analysis, sustainable construction materials. Key Contributions : 15+ publications on topics ranging from cross-laminated timber behavior to structural health monitoring of wood systems. Email : Thomas.Miller@oregonstate.edu Scientific Awards : None listed publicly.

Peter G. Jacobsمشاهده پروفایل

استاد

• Artificial Intelligence
• Medical Device Design
• Machine Learning
• +۶ مورد دیگر

Peter G. Jacobs is a Professor and James and Shirley Kuse Chair in the Department of Chemical, Biological, and Environmental Engineering at Oregon State University (OSU), and concurrently holds a Professorship in Biomedical Engineering at Oregon Health & Science University (OHSU). He directs the Artificial Intelligence for Medical Systems (AIMS) Lab, focused on AI-driven medical devices for diabetes and other conditions. His research integrates machine learning, control systems, and ubiquitous sensors to develop closed-loop systems for insulin/glucagon delivery and hypoglycemia prediction. Education: Ph.D. in Electrical Engineering (OHSU, 2010), M.S. in Electrical and Computer Engineering (University of Wisconsin-Madison, 1998), B.S. from Swarthmore College (1995). Research interests span medical device innovation, diabetes technology, exercise physiology integration, and AI in healthcare. Recent projects include the T1Dexi initiative studying exercise impacts on glycemia and the development of AI-based decision support systems like DailyDose. Awards include the 2024 Diabetes Technology Society Artificial Pancreas Award, Kuse Chair appointment, and Excellence in Teaching recognition. He has co-founded Pacific Diabetes Technologies and contributed to companies like Dexcom. Grants include a $4.2M Helmsley Charitable Trust award for app-based diabetes education and NIH-funded projects on AI meal detection algorithms. Current lab members include PhD students Gavin Young, Rahul Narayan, and Valentina Roquemen-Echeverri. Key collaborations involve OHSU's Harold Schnitzer Diabetes Center and institutions globally. The AIMS Lab also explores smart-home monitoring for fall risk assessment in multiple sclerosis patients and AI applications in obstetrics.

Tianhua Chenمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۴ مورد دیگر

Tianhua Chen is an Associate Professor (Reader) in Artificial Intelligence at the University of Huddersfield's Department of Computer Science, School of Computing and Engineering. He holds leadership roles including Course Leader for MSc Artificial Intelligence programs and Team Lead for AI in Health and Wellbeing at the Centre for Autonomous and Intelligent Systems. His research focuses on machine learning applications in mental health and clinical decision support, with over 60 peer-reviewed publications in top journals like IEEE Transactions on Fuzzy Systems and Frontiers in Psychiatry. Dr. Chen's work is supported by grants from Innovate UK, NHS, and EPSRC. Education: PhD in Computational Intelligence from Aberystwyth University (2017). Professional roles include Editorial Board memberships at Artificial Intelligence in Medicine and BMC Medical Informatics. He leads courses including MSc CMS3503 Machine Learning and MSc CMI3506 Case Study in Data Analytics and AI. Research interests span probabilistic machine learning, affective computing, and healthcare analytics with applications in wellbeing and mental health. Recent work includes AI for ADHD diagnosis, pandemic mental health analysis, and wearable device signal processing for mental state prediction. Awards include a Google Scholar h-index of 17 and an IEEE spotlight article recognition. He organizes special journal issues and serves on program committees for IJCAI, MICCAI, and IEEE conferences. Active in applied AI development, with a focus on translating techniques into real-world healthcare solutions. Labs and collaborations include the Centre for AI in Mental Health, Centre for Climate Resilient Societies, and the Resilient Societies Research Centre. Current projects address photovoltaic fault detection and smart manufacturing systems alongside health-related AI applications.

Anamika Prasadمشاهده پروفایل

دانشیار

• Biobased and bioinspired material design
• Tissue biomechanics (bone tumor, vascular tissue in plant, cardiovascular tissue)
• Nano-mechanical characterization
• +۱ مورد دیگر

Dr. Anamika Prasad is an Associate Professor in the Department of Mechanical and Materials Engineering at Florida International University's College of Engineering and Computing. Her research focuses on biobased and bioinspired materials, tissue biomechanics, nano-mechanical characterization, and biomedical devices for precision agriculture and healthcare. She leads the PrasadLab, exploring innovations at the intersection of materials science and biological systems. Education: Not explicitly listed in provided materials. Research Interests: Biobased materials and bioinspired design Tissue biomechanics (bone tumors, vascular tissues) Nano-characterization techniques Biomedical devices for healthcare and agriculture Her recent work includes developing nanopesticides for crop protection, bioinspired composites, and 3D-printed bioreactors. She has contributed to additive manufacturing advancements and sensor technologies for plant health monitoring. Notable grants include NSF CAREER and DMREF awards. Lab/Teams: PrasadLab (https://sites.google.com/view/prasadlab/home).

Sanjib Surمشاهده پروفایل

دانشیار

• Wireless systems
• Millimeter-wave networks
• Internet of Things
• +۲ مورد دیگر

Sanjib Sur is an Associate Professor in the Department of Computer Science and Engineering at the University of South Carolina's Molinaroli College of Engineering and Computing. His research focuses on wireless systems for healthcare, mobility sensing, and IoT connectivity. Research interests span: Millimeter-wave communication networks Contactless health monitoring technologies Intelligent transportation systems Edge computing for sensor networks His recent publications demonstrate strong focus on non-contact sensing for healthcare (sleep analysis, stroke rehabilitation) and smart infrastructure (traffic monitoring, outdoor networking). Technical approaches consistently integrate millimeter-wave systems with deep learning for robust environmental operation.

Mina Nouredaneshمشاهده پروفایل

استادیار

• Aging and complex age-related conditions
• Artificial Intelligence for Health
• Wearable Technologies
• +۴ مورد دیگر

Mina Nouredanesh is an Assistant Professor in the Department of Community Health Sciences at the Max Rady College of Medicine, University of Manitoba. She holds a Canada Research Chair (Tier II) in AI for Complex Health Data. Her research focuses on leveraging artificial intelligence and wearable technologies to address complex age-related conditions like Parkinson's disease, dementia, and fall risks in older adults. Dr. Nouredanesh completed a postdoctoral fellowship at McMaster University's School of Rehabilitation Science, followed by a PhD and MASc in Mechanical and Mechatronics Engineering from the University of Waterloo. She also holds a BSc in Electrical Engineering from Amirkabir University of Technology. Her research program has two main themes: predicting complex age-related conditions using multimodal health data and developing personalized technologies for their management. She has published in leading journals and presented at top-tier conferences, collaborating with researchers globally. Awards include grants from AGE-WELL, Vector Institute, and the McMaster Institute for Research on Aging. Dr. Nouredanesh is actively involved in training graduate students (Master's, PhD) and postdoctoral researchers. Her work spans AI applications in rehabilitation, medical imaging, and robotics, with a focus on translational research to improve quality of life for older adults and caregivers.

• Multi-Robot Systems
• Human-Robot Interaction
• Robot-Assisted Healthcare
• +۲ مورد دیگر

Yi Guo is Thomas E. Hattrick Chair Professor in Electrical and Computer Engineering at Stevens Institute of Technology. Her research focuses on autonomous robotics with applications in healthcare, environmental monitoring, and human-robot interaction, emphasizing multi-robot coordination and machine learning approaches. Her work integrates control theory with machine learning to develop cooperative robotic systems for complex environments. Major research thrusts include human-robot collaborative navigation, robot-assisted gait analysis, deformable object manipulation, and distributed swarm control. Recent innovations include reinforcement learning for crowd navigation and mobile platforms for elderly mobility assessment. Guo's publication portfolio demonstrates strong applications in healthcare robotics, particularly gait analysis systems combining wearable sensors with mobile robots. Her research consistently bridges fundamental robotics with practical implementations in clinical and environmental domains. As Editor-in-Chief of IEEE Robotics and Automation Magazine, she leads major conference initiatives including ICRA and IROS. She directs an active research group of 11 PhD students and maintains collaborations with healthcare institutions on assistive technologies.

• Applied Computing
• Generative AI
• Machine Learning
• +۸ مورد دیگر

Dr. Vinh Bui is a Senior Lecturer and Course Coordinator in Information Technology at the Faculty of Science and Engineering, Southern Cross University. With over 10 years in higher education, he specializes in academic leadership and has a background in both computer science and electrical engineering. He holds a MSc in Information Technology (2001) and PhD in Electrical Engineering (2008) from UNSW, and is currently completing a postgraduate certificate in tertiary teaching. His research focuses on applied computing, including generative AI, machine learning, nature-inspired algorithms, and big data analytics with applications in healthcare, tourism, and waste management. He has published over 30 peer-reviewed articles and secured $10M+ in research funding. Dr. Bui actively engages in community initiatives like the AI in Healthcare Symposium and is a certified Cisco instructor. Awarded the 2023 Southern Cross University Research Award and Outstanding Teaching Excellence Award, he supervises PhD and MPhil students in synthetic data/environment research. He has developed and coordinated over 30 IT subjects, emphasizing computational thinking, cybersecurity, and IoT programming.

• Machine Learning
• Health Informatics
• Human Computer Interaction
• +۳ مورد دیگر

Prithwi Raj Chakraborty is a Lecturer in the Department of Information Technology at Southern Cross University's Faculty of Science and Engineering. He holds a PhD in affective computing, emotion analysis, and machine learning from Queensland University of Technology (QUT). His academic career began as a Research Fellow at QUT before transitioning to SCU. Active collaborations include partnerships with Sydney University, Griffith University, QLD Health, and QCH. His research focuses on machine learning applications in health informatics, human-computer interaction, and affective computing. Education: PhD in Computer Science from Queensland University of Technology (QUT). Key research areas include cognitive load modeling, wearable sensor analytics, and mHealth solutions like the myPainPal chronic pain management app. He has published impactful work on fall risk detection for the elderly and biometric-based video analysis. Current projects involve optimizing high-performance office environments and generic viewer interest modeling. Professional affiliations include Southern Cross University's Faculty of Science and Engineering, with past experience as a Casual Academic in the School of Business and Tourism. His work bridges computational methods with real-world human behavior analysis in healthcare and workplace settings.

• Artificial Intelligence
• Data Science
• Machine Learning
• +۶ مورد دیگر

Hamid Bouchachia is a Professor of Data Science and Intelligent Systems at Bournemouth University, leading the Machine Intelligence Research Group within the Department of Computing and Informatics, Faculty of Science and Technology. He holds an Engineering degree, Master, PhD, and habilitation from reputable institutions, with a Post-Doc at the University of Alberta, Canada. Education: Engineering Degree Master’s Degree PhD in Data Science Habilitation Degree Postdoctoral Research at University of Alberta (Computer & Electrical Engineering) Research Interests: Bouchachia focuses on scalable machine learning for data streams, medical imaging with ML, smart environments (e.g., smart homes, industrial monitoring), and assistive technologies. His work emphasizes online learning, active learning, and distributed AI applications in healthcare and energy sectors. He develops algorithms for real-time pattern recognition, high-performance computing, and adaptive systems. Key Contributions: His research spans incremental learning frameworks, evolving fuzzy classifiers, and energy-efficient neural networks. Recent work includes lightweight RNN models for forecasting and deep learning for abnormal behavior detection in dementia care. Advising & Students: Supervises PhD students on topics like deep learning for healthcare, cloud migration, and smart home systems. Notable advisees include Damla Arifoglu (abnormal behavior detection) and Saad Mohamad (active learning). Labs & Teams: Heads the Machine Intelligence Research Group, collaborating on projects involving AI-driven medical imaging, smart energy systems, and ambient intelligence.