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Mike MorrisView profile

Associate Professor

• Exercise Physiology
• Cardiovascular Health
• Physical Activity
• +6 more

Dr. Mike Morris is the Head of Division for Allied Health at the University of Chester's Faculty of Health, Medicine and Society. He holds an Associate Professor rank and has been with the university since 2002. His academic career includes roles as Head of Department and Deputy Head of Department in Clinical Sciences and Nutrition. Morris holds a PhD in Exercise Physiology from the University of Liverpool, an MSc in Exercise and Nutrition Science, and a BSc in Sports Science. His research focuses on cardiovascular health, exercise physiology, and the validation of fitness assessment tools. Notable projects include developing the Chester Treadmill Police Test for law enforcement fitness evaluation and studying sit-stand desk interventions in workplaces. Morris also explores ergogenic aids and the metabolic impacts of occupational sedentary behavior. Teaching responsibilities include postgraduate modules on Exercise and Health, Clinical Exercise Testing, and Research Methods. He has supervised studies on topics like blood glucose monitoring accuracy and active video game efficacy in children. Morris contributed to funded projects like the 'Chester Treadmill Police Walking Test Standard' for the College of Policing. Publications span 20+ peer-reviewed articles, addressing issues from police fitness testing to the psychological effects of weight management interventions. His work bridges applied physiology, public health, and occupational safety.

Lamine M. MiliView profile

Professor

• Power Systems
• Signal Processing
• Robust Estimation Theory
• +7 more

Lamine M. Mili is a Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. His expertise spans power systems, signal processing, and robust estimation theory. He holds an IEEE Fellowship (2016) for contributions to robust state estimation in power systems. Mili's research focuses on advancing methodologies for power system reliability, control, and integration of renewable energy sources. His work includes studies on dynamic state estimation, nonlinear dynamics, bifurcation theory, and quantum computing applications. He has contributed extensively to resilience engineering and computational social science in power systems. Mili’s recent articles address challenges in smart grids, quantum circuit error prediction, and multifractal signal analysis in EEG. His research often combines advanced statistical techniques with real-world grid data, emphasizing robustness and adaptability in dynamic environments. Education: Ph.D., University of Liège, 1987 M.S., University of Tunis, 1983 B.S., Swiss Federal Institute of Technology, Lausanne, 1976 Research Interests: Power system stability and control State estimation and robust filtering Quantum computing for power systems Resilience and cyber-physical-social systems Nonlinear dynamics and bifurcation analysis His recent publications reflect a focus on hybrid power systems, probabilistic methods, and data-driven approaches for grid optimization. The 2025 articles highlight advancements in photovoltaic state estimation, quantum error prediction, and robust modulation techniques. Mili’s work often bridges theoretical models with practical grid applications, emphasizing uncertainty quantification and real-time monitoring.

Steve E. RigdonView profile

Professor

• Biosurveillance
• Election Prediction Models
• Quality
• +4 more

Steve E. Rigdon is a Professor in the Department of Epidemiology and Biostatistics at the College for Public Health and Social Justice, Saint Louis University. His expertise lies in statistical inference, biosurveillance, and reliability modeling. Education: Ph.D. in Statistics, University of Missouri-Columbia M.A., University of Missouri-St. Louis B.A., University of Missouri-St. Louis Dr. Rigdon's research focuses on biosurveillance , election prediction models , quality engineering , and survival analysis . He has made significant contributions to the statistical modeling of repairable systems and optical experimental design. His work bridges theoretical statistics with real-world public health and engineering applications. His publications appear in top-tier journals including Technometrics , Journal of Quality Technology , and Quality Engineering . He is also the author of influential textbooks such as Calculus (8th and 9th editions) and Statistical Methods for the Reliability of Repairable Systems . His election prediction models were featured in the Wall Street Journal and local media in 2008. Research Funding: National Science Foundation (NSF) grant for research on optical experimental design, in collaboration with Arizona State University. Dr. Rigdon teaches Bayesian Statistics and the Capstone in Biostatistics , mentoring students in advanced statistical applications. He is active in research dissemination through platforms like ResearchGate. His office is located at Wool Center, Second Floor, Room 276H, 3545 Lindell Blvd., St. Louis, MO 63103.

• Interactive Information Retrieval Systems
• Search Engines
• Recommendation Systems
• +3 more

Mark D. Smucker is a Professor in the Department of Management Science and Engineering at the University of Waterloo , cross-appointed with the David R. Cheriton School of Computer Science (Faculty of Math). His research focuses on designing and evaluating interactive information retrieval systems, including search engines and recommendation systems. He co-organized the TREC Health Misinformation Track (2019–2022) and currently leads the TREC DRAGUN Track, addressing trustworthiness assessment of news. He holds a PhD in Computer Science from the University of Massachusetts Amherst, a Master's from the University of Wisconsin-Madison, and dual Bachelor's degrees in Physics and Computer Science from Iowa State University. His teaching includes courses like Search Engines (MSCI 541/MSE 541) and Introduction to Computer Programming (MSCI 121/MSE 121), emphasizing practical programming and information systems design. He has received awards including the ACM SIGIR 2012 Best Paper Award and the University of Waterloo Engineering Society Teaching Excellence Honourable Mention (2014). His work bridges theory and practice, with contributions to evaluation methodologies like time-based calibration of metrics and preference graphs. He collaborates on projects like the TREC tracks to improve search systems' real-world applicability, particularly in health contexts and misinformation detection.

• Knowledge Representation
• Machine Learning
• Ubiquitous Computing
• +7 more

Femke De Backere is a part-time Associate Professor at Ghent University's IDLab research group (Faculty of Engineering and Architecture, Department of Information Technology) and a full-time Senior Scientist at imec. She holds a Bachelor's in Informatics and Master's in Computer Science Engineering from Ghent University, with doctoral research focused on semantic technologies and personalized healthcare systems through collaborations with intensive care units and industry partners. Her research integrates computer science, health psychology, and movement science across three primary domains: (1) developing explainable knowledge models, (2) creating personalized context-aware systems, and (3) designing engagement mechanisms like serious games and gamification. Current projects include digital interventions for cancer survivors, VR-based ecological validity platforms, and physical activity promotion in older adults. Recent publications (2020-2025) demonstrate strong focus areas: 60% address personalized health interventions using machine learning and ontologies; 30% explore virtual reality applications in clinical and behavioral contexts; and 10% examine academic systems development . Longitudinal trends show increasing emphasis on sensor-driven behavioral analytics and adaptive eHealth platforms. She leads significant research initiatives including: GRAY – Ghent University Research for Aging Young (2020-2030) FWO projects on eHealth self-management for cancer survivors and sedentary behavior interruption Interdisciplinary grants for VR-enabled consumer preference studies and physical activity interventions Her lab coordinates doctoral training for 9+ students and collaborates with the eBehaviourChange research unit, focusing on technology-mediated behavior modification across clinical and wellness domains.

Tammy BarryView profile

Professor

• Child externalizing behaviors
• Attention-deficit/hyperactivity disorder (ADHD)
• Autism spectrum disorder (ASD)
• +8 more

Tammy Barry is a Professor in the Department of Psychology at Washington State University and serves as Dean of the Graduate School and Vice Provost for Graduate Education. Her research focuses on biologically-based and contextual correlates of child externalizing behaviors, including ADHD, aggression, and autism-related disruptive behaviors. Ph.D. in Clinical Psychology (Child Emphasis) - University of Alabama (2000) B.A. in Communication - University of Alabama B.S. in Psychology - University of Alabama at Birmingham Barry's work examines neuropsychological functioning, child temperament, parental psychopathology/stress, parenting practices, socioeconomic factors, and individual differences like narcissism and psychopathy. Her lab investigates the measurement and latent structure of externalizing behavior disorders through interdisciplinary research involving psychophysiological, behavioral, and social data. Recent publications highlight her expertise in autism spectrum disorder, attention-deficit/hyperactivity disorder, and family dynamics. She has directed studies on mindfulness interventions, reward sensitivity, and reporting discrepancies in anxiety symptoms among children with ASD, presented at conferences like WPA, ISAR, and ABCT. No scientific awards explicitly mentioned Barry has mentored numerous graduate students and supervised the Child Externalizing Behaviors (CEB) Lab. The lab is not currently recruiting for Fall 2025 due to her sabbatical cycle. Her former students have transitioned to postdoctoral fellowships and clinical roles across the U.S.

James GrossView profile

Professor

• Wireless Networking
• Mobile Systems & Networks
• Ultra-reliable Low-latency Communications
• +11 more

James Gross is a Professor at the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology, Stockholm. He leads research in mobile systems and networks, with a focus on 5G/6G, edge computing, and performance evaluation. He is Associate Director of KTH's Digital Futures center and a board member of the Innovative Centre for Embedded Systems. Previously, he directed the ACCESS Linnaeus Centre (2016–2019) and was Assistant Professor at RWTH Aachen University. PhD, TU Berlin (2006) Studies: TU Berlin, UC San Diego His research lies at the intersection of wireless networking, edge computing, and mathematical performance modeling. Key areas include ultra-reliable low-latency communications (URLLC), age-of-information, network calculus, and resource allocation. He applies these to 5G/6G, cyber-physical systems, and industrial IoT. His work combines theoretical modeling with real-world implementation and standardization impact. The recent publications highlight a strong focus on deterministic and reliable communications for future networks. Topics include hierarchical inference at the edge, age-of-information optimization, finite blocklength coding, and integration of TSN with wireless systems. There is a clear trend towards AI/ML for resource management and semantic communications, reflecting the evolution of intelligent edge networks. Best Paper Award, ACM MSWiM 2015 Best Demo Paper Award, IEEE WoWMoM 2015 Best Paper Award, IEEE WoWMoM 2009 Best Paper Award, European Wireless 2009 ITG/KuVS Dissertation Award, 2007 James Gross has supervised PhD students such as Samie Mostafavi and advises numerous master's projects. His research has been funded by national science foundations in Germany and Sweden, the ICT TNG SRA, Linnaeus ACCESS Centre, DFG-funded UMIC Centre, German Ministry of Science, and various industry partners. His work has led to patents and influenced wireless standards. He is involved in initiatives like the TECoSA project on trustworthy edge computing and organizes summer schools on Edge AI and 6G. His lab conducts experimental research on edge computing testbeds (e.g., Ainur, ExPECA) and wireless performance evaluation.

Roman FriggView profile

Professor

• General philosophy of science
• Philosophy of physics
• Statistical mechanics
• +11 more

Roman Frigg is Professor of Philosophy at the London School of Economics and Political Science (LSE) , affiliated with the Department of Philosophy, Logic and Scientific Method . He serves as Director of the Centre for Philosophy of Natural and Social Science (CPNSS) and Co-Director of the Centre for the Analysis of the Time Series (CATS) . Holding a PhD from the University of London and MScs in theoretical physics and philosophy from the University of Basel, his research spans philosophy of science , statistical mechanics , and climate modeling . Education : PhD (University of London), MSc (University of Basel: Theoretical Physics, Philosophy) His work addresses foundational questions in statistical mechanics and thermodynamics , including equilibrium theory, entropy interpretation, and relations between Boltzmannian and Gibbsian frameworks. Recent publications focus on probabilistic forecasts in chaotic climate models , culminating in the co-authored book The Fundamentals of Thermodynamics (Springer, 2025). Articles explore topics like the Ergodic Hierarchy , GRW quantum theory , and robustness analysis in climate science. Roman has made significant contributions to reconciling deterministic dynamics with objective probability via Humean interpretations. His collaborations with Charlotte Werndl, Carl Hoefer, and David Lavis have produced key insights into typicality , chaos-randomness relations , and non-equilibrium thermodynamics . Scientific Awards : Friedrich Wilhelm Bessel Research Award (Alexander von Humboldt Foundation) Roman supervises PhD students on topics ranging from scientific representation to quantum mechanics and climate policy uncertainty . His website provides access to his publications and teaching materials.

Eunsuk KangView profile

Assistant Professor

• Software Engineering
• Formal Methods
• Software Security
• +4 more

Eunsuk Kang is an Assistant Professor at Carnegie Mellon University's Software and Societal Systems Department within the School of Computer Science. His research focuses on enhancing software system safety, security, and reliability through formal methods and rigorous modeling. Ph.D. in Computer Science, MIT Software Engineering, University of Waterloo Research spans cyber-physical systems , software security , formal verification , and ML resilience . Key areas include robust system design against evolving environments, specification engineering, and scalable automated reasoning. Recent publications highlight advancements in CPS safety , formal verification , and ML-based error mitigation . Collaborative projects span conferences like ICSE , CAV , and FMCAD . Scientific Awards CyLab 2025 Seed Funding CyLab 2023 Seed Funding Carnegie Bosch Institute Grant Advises doctoral students in software engineering and formal methods, with affiliations to the Software Design and Analysis (SoDA) Group and CyLab Security and Privacy Institute.

• Artificial Intelligence in Healthcare
• Power Electronics
• Digital Control Systems
• +1 more

Anthony Kelly serves as a Postdoctoral Research Fellow in the Department of Electronic and Computer Engineering within the Faculty of Science and Engineering at the University of Limerick, Ireland, with his office located in E2-006. His affiliation spans both engineering and healthcare domains through interdisciplinary research initiatives. His research demonstrates dual expertise in artificial intelligence applications for healthcare and advanced power electronics. In healthcare AI, he develops interpretable mental health models, diabetes management chatbots, and comorbid condition interventions with emphasis on clinician trust and safety evaluation. In power systems, he pioneers digital control techniques for DC-DC converters, FPGA power management, and machine learning-integrated circuit designs. This bifurcated focus reveals a strategic transition from hardware-centric research (2005-2019) toward AI-health convergence (2024-2025). Analysis of his 15 most recent publications shows a pronounced shift toward healthcare AI since 2024, with 80% of current work addressing mental health modeling, diabetes chatbots, and comorbid condition management. Earlier publications (2009-2019) consistently focused on power electronics innovations including current-sharing algorithms, adaptive controllers, and FPGA-based systems, establishing foundational expertise later applied to healthcare technology development.

Werner ZornView profile

Professor

• Computer Networks
• Performance Analysis
• Networked Computer Systems
• +3 more

Prof. Dr. Werner Zorn is a renowned computer scientist and Professor of Communication Systems at the Hasso Plattner Institute (HPI) in Potsdam, Germany. With a foundational role in establishing Germany's early internet infrastructure and connecting China to the global internet, his work has been pivotal in shaping international network connectivity. His academic career spans from the University of Karlsruhe, where he was appointed Professor of Computer Science in 1979, to his current position at HPI since 2001. Education: He studied electrical engineering with a focus on communications at TH Karlsruhe (1962–1967) and earned his Dr.-Ing. with distinction in 1971. Research Focus: His research encompasses performance analysis of computing systems, computer networks, and the development of quantitative modeling methodologies such as FMC-QE (Fundamental Modeling Concepts for Quantitative Evaluation). His work bridges theoretical modeling with practical applications in network design and optimization. Publications & Articles: His publications reflect a deep engagement with internet history, network performance, and system modeling. Notable works include detailed accounts of China's first email connection and the evolution of the Chinese Academic Network (CANET), as well as innovative approaches to system performance modeling. Awards & Recognition: He has received numerous accolades, including the Order of Merit of the Federal Republic of Germany, induction into the Internet Hall of Fame, and the Chinese Government Friendship Award, underscoring his global impact. Current Projects: He leads projects like FMC-QE for hierarchical system modeling and the IT Services Atlas for implementing EU directives, alongside mentoring doctoral students in advanced network and system research.

Stephan PreihsView profile

Researcher

• Acoustics
• Digital Signal Processing
• Audio Coding
• +6 more

Stephan Preihs is a postdoctoral researcher and group leader at the Institute of Communications Technology of the Leibniz University Hannover , with a focus on acoustics, digital signal processing, and immersive audio systems. He received his Dipl.-Ing. in electrical engineering (communications engineering) from the same university in 2010 and his Dr.-Ing. in 2016. Education: Dipl.-Ing., Electrical Engineering (Communications Engineering), Leibniz University Hannover (2010) Dr.-Ing., Leibniz University Hannover (2016) Research Interests: Acoustics for immersive audio reproduction Digital signal processing and audio coding Signal detection/classification Psychoacoustic models Audio transmission for PMSE Recent Article Trends: Deep learning in sound source localization Wind turbine noise analysis via immersive audio Advancements in headphone technology Immersion prediction in spatial audio Low-latency communication protocols Scientific Awards: Best Paper Award at IEEE International Workshop on Networked Immersive Audio (2024) AES Show 2024 Best Technical Paper Award AES Spring 2021 Student Paper Award AES Poster Award 2019 AES Convention Student Paper Award 2019 Teaching: Lecturer for '3D Audio - Fundamentals of Spatial Reproduction Systems' Lecturer for 'Applications of Digital Audio Signal Processing' Coordinator of student laboratories in 'Audio Communication and Acoustics' and 'Transmission Technology'

Marchegiani Maria LetiziaView profile

Assistant Professor

• Signal Processing
• Machine Learning
• Robotics
• +9 more

Maria Letizia Marchegiani is an Assistant Professor at the University of Parma , affiliated with the Department of Engineering and Architecture . Previously, she held academic positions at Aalborg University (2019) and Oxford Robotics Institute (2014-2018). Education: PhD in Computer Science and Engineering from Sapienza - University of Rome , MSc/BEng in Computer Engineering Her research interests span signal processing , machine learning , and their applications to robotics , autonomous systems , intelligent transportation , and intelligent healthcare . She explores intersections between auditory perception , cognitive modeling , and energy-efficient wearable systems . Recent publications demonstrate expertise in acoustic event localization , ML-SDWSN architectures , thermal camera integration for vehicles, and privacy-preserving wearable systems . Her work addresses challenges in network reliability , urban soundscapes , and human-robot collaboration .

Chen PanView profile

Assistant Professor

• Energy-Harvesting Embedded Systems
• Internet of Things (IoT)
• Low-Power Computing
• +5 more

Chen Pan is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Texas at San Antonio's Klesse College of Engineering and Integrated Design. His research focuses on energy-harvesting embedded systems, low-power computing, and IoT network optimization through machine learning techniques. Ph.D. from University of Pittsburgh Specializes in transient computing for batteryless devices Develops reinforcement learning solutions for UAV-assisted IoT systems Chen's recent publications emphasize energy-aware scheduling, non-volatile memory optimization, and sustainable communication protocols. His work intersects spatiotemporal modeling, fault tolerance, and resource-constrained AI execution across heterogeneous architectures.

• Cardiovascular Disease Prevention
• Atherosclerosis
• Clinical Decision-Making
• +7 more

Mark Pletcher, MD, MPH is a Professor in the Department of Epidemiology & Biostatistics at the University of California, San Francisco (UCSF) School of Medicine. In 2023, he became Chair of the UCSF Department of Epidemiology and Biostatistics. He is an epidemiologist and general internal medicine physician whose research focuses on clinical decision-making and policy relevant to primary care and prevention, particularly in cardiovascular disease prevention. Dr. Pletcher earned his M.D. from the University of California, San Francisco in 1998 and completed his residency at UCSF School of Medicine. He also completed UCSF's Diversity, Equity, and Inclusion Champion Training in 2019. His research interests span cardiovascular disease prevention with particular focus on early life causes of atherosclerosis, prevention of coronary heart disease, clinical decision-making regarding preventive medications, screening for subclinical cardiovascular disease, interventions to improve blood pressure control, and the use of technology to enhance health outcomes. He has led numerous studies on marijuana use and cardiovascular health, blood pressure management, and digital health interventions. His work often leverages large cohort studies like the Coronary Artery Risk Development in Young Adults (CARDIA) study. Analysis of his recent publications reveals a strong focus on digital health interventions for hypertension management, cardiovascular risk assessment in young adults, liver disease applications of artificial intelligence, and the impact of pandemic policies on mental and physical health outcomes. His research increasingly incorporates machine learning and large language models for clinical decision support, particularly in gastroenterology and cardiology applications. Dr. Pletcher leads the UCSF CTSI's Informatics and Research Innovation Program and has been Principal Investigator on numerous NIH and PCORI-funded projects including the Health eHeart Study and the PCORnet Blood Pressure Control Laboratory. His research funding spans cardiovascular disease prevention, digital health interventions, and health policy evaluation. He mentors students, fellows, and junior faculty members, and teaches clinical research methods. His laboratory work focuses on the Health eHeart Alliance and related digital health initiatives that leverage consumer technologies for cardiovascular research.