Ersin Korkmaz is an Associate Professor in the Department of Civil Engineering at Kırıkkale University , specializing in Transportation Engineering . His academic journey includes dual bachelor's degrees from Erciyes University (Electrical and Civil Engineering, 2011-2012), a master's degree in 2016, and a doctorate in 2019. Expertise in optimization algorithms (flower pollination, differential evolution, YOLO-based models) Research focuses on transportation energy demand, smart traffic systems, and UAV-based intersection analysis Developed hybrid AI control systems for signalized intersections Contributor to bibliometric studies in banking and accounting sectors His work bridges civil engineering and computational methods, with recent publications analyzing traffic safety, energy forecasting, and infrastructure optimization. Notable trends include integration of metaheuristic algorithms for transportation modeling and applications of drone imaging in urban mobility.
Dr Ze Ji is Reader of Robotics and Autonomous Systems at Cardiff University’s School of Engineering, where he leads the Robotics and Autonomous Intelligent Machines (RAIM) group and directs the Robotics and Autonomous Systems Laboratory. He is Co-Investigator and theme leader for the ERDF-funded IROHMS research centre and holds a Royal Academy of Engineering Industrial Fellowship hosted by Spirent Communications Ltd. Education PhD in Engineering, Cardiff University (2007) – EU FP6 TAI-CHI project MSc, Cardiff University BEng, Cardiff University Research Interests Dr Ji’s research centres on Robot Perception And Learning (RoPAL) , spanning: Simultaneous localisation and mapping (SLAM) Deep reinforcement learning for navigation and manipulation Human-robot collaboration & digital-twin based fatigue management Vision, tactile sensing, and smart sensing systems Unmanned surface vehicles (USVs) and UAV coordination Physics-based differentiable simulation for elastoplastic material handling Publications Trend Since 2021 Dr Ji has authored >120 peer-reviewed papers. A dominant theme is mapless navigation via hierarchical and preference-based reinforcement learning for ground, aerial and surface robots. Parallel streams investigate human-centric manufacturing (digital twins for fatigue-aware assembly), vision-based tactile sensing, defect detection on steel, and orchard robotics (green-fruit segmentation), all underpinned by deep learning and rigorous real-world validation. Scientific Awards & Fellowships Royal Academy of Engineering Industrial Fellowship EU FP6 Best Exhibit Prize, Helsinki 2006 (TAI-CHI project) Fellow of the Higher Education Academy (FHEA) Grants & Centres Principal Investigator, EPSRC-funded differentiable physics project (2025) Co-Investigator, IROHMS (ERDF/WEFO) Industrial Fellowship with Spirent Communications Ltd Laboratory & Facilities Dr Ji manages the Robotics and Autonomous Systems Laboratory , housing two KUKA LBR iiwa robots, Robotnik Vogui+, three KUKA YouBots, TurtleBots, drones, advanced 3-D vision systems, and sensors. The lab has also produced two student-built USVs (unmanned surface vehicles) for maritime research.
Hao Xu serves as an Associate Professor at the University of Nevada, Reno, holding the Ralph E. and Rose A. Hoeper Professorship. His research laboratory operates from SEM Building, Room 337D, with contact via haoxu@unr.edu. His research spans critical domains in intelligent transportation systems: Intelligent control and machine learning for cyber-physical systems Networked control systems and unmanned aircraft applications Power control, smart grid integration, and wireless sensor networks Recent publications (2023-2025) demonstrate concentrated expertise in roadside LiDAR applications, developing algorithms for vehicle/pedestrian detection, trajectory prediction, and safety analysis under challenging conditions including snow and heavy traffic. His work integrates deep learning with optimization techniques to enhance data processing robustness, particularly for vulnerable road user protection and near-miss event quantification. While no specific scientific awards beyond his named professorship were documented, his research directly addresses critical transportation safety challenges through innovative sensor applications and data analytics. Information regarding student advising, research grants, and laboratory infrastructure details was not provided in available materials, though his publication output indicates active collaboration with transportation agencies on smart infrastructure development.
Tianmin Shu is an Assistant Professor in the Department of Computer Science at Johns Hopkins University's Whiting School of Engineering, with a secondary appointment in the Department of Cognitive Science. He directs the Social Cognitive AI (SCAI) Lab and is a member of the Data Science and AI Institute. Dr. Shu's educational background includes: PhD in Statistics, University of California, Los Angeles (2019) BS in Electronic Engineering, Fudan University (2014) Dr. Shu's research pioneers machine social intelligence to build human-centered AI systems. His work integrates: Embodied AI for physical-world human-robot collaboration Neurosymbolic methods for multimodal social reasoning Computational models of human social cognition Theory of Mind frameworks for mental state inference Continual learning for adaptive social agents Recent publications (2024-2025) reveal three dominant research thrusts: (1) Multimodal Theory of Mind systems like MMToM-QA for mental state reasoning, (2) Embodied assistance frameworks such as GOMA for goal-oriented human-robot alignment, and (3) Human feedback learning methods including pragmatic feature preferences. His work increasingly bridges language models with world models while exploring neural correlates of social cognition through fMRI studies. Dr. Shu's scientific contributions have been recognized with prestigious awards: Cognitive Science Society’s 2017 Computational Modeling Prize 2020 NeurIPS Best Paper Award (Cooperative AI Workshop) 2022 IROS Workshop Excellent Paper Award 2024 ACL Outstanding Paper Award (MMToM-QA) As director of the SCAI Lab, Dr. Shu leads research on socially intelligent systems through open-source platforms including VirtualHome 2 (multi-agent household simulator) and SimWorld (photorealistic interaction simulator). His lab develops computational frameworks that enable machines to perceive social dynamics, infer intentions, and provide context-aware assistance in complex environments.
Dr. Esmée Verhulp is an Assistant Professor in the Faculty of Social and Behavioural Sciences at Utrecht University . Her research focuses on Developmental Psychology and Aggressive Behavior in Children , with a particular emphasis on Virtual Reality Therapy for behavioral disorders and Ethnic Differences in Mental Health outcomes. Current affiliations: Utrecht University (Faculty of Social and Behavioural Sciences, Psychology) Email: e.e.verhulp@uu.nl Research Interests include: studying Social Information Processing in children with behavioral issues, exploring Hostile Intent Attributions as transdiagnostic factors, and analyzing Ethnic Disparities in mental health service utilization. She also investigates the role of Self-Views (self-esteem, narcissism) in aggression development. Recent Publications highlight her work on Interactive Virtual Reality for assessing and treating aggression, meta-analytic reviews of Hostile Intent Attributions , and studies on Cultural Differences in problem recognition and care access. Her methodological approach integrates Longitudinal Studies and Randomized Controlled Trials . Other Contributions involve collaborations with researchers like Barbara Orobio de Castro and Anneke van Dijk , with a focus on Adolescent Psychiatry and Clinical Psychology .
Bin Ran serves as the Vilas Distinguished Achievement Professor and Director of the Intelligent Transportation Systems (ITS) Program within the Civil & Environmental Engineering Department at the University of Wisconsin-Madison. A globally recognized expert in Connected Autonomous Mobility (CAM), he has authored over 850 scientific articles and secured more than 200 patents across multiple jurisdictions, significantly advancing transportation engineering through innovations in vehicle-highway automation and intelligent infrastructure systems. His educational foundation includes a PhD from the University of Illinois at Chicago (1993), an MS from the University of Tokyo (1989), and a BS from Tsinghua University (1986). These qualifications underpin his leadership in transportation research and education. Ran's research program centers on Connected Autonomous Mobility (CAM), Collaborative Automated Driving Systems (CADS), and Connected and Automated Vehicle & Highway (CAVH) technologies. His work integrates dynamic transportation network modeling, smart city applications, big data analytics, and Drive GPT-enhanced traffic simulation to develop proactive safety systems and resilient infrastructure solutions. Current projects emphasize cloud-based architectures, digital twins, and cooperative vehicle control frameworks. Analysis of his 2024-2025 publications reveals dominant trends in cloud-to-vehicle control systems, risk-quantified adaptive cruise control, and federated digital twin frameworks for connected corridors. Research spans cybersecurity for connected vehicles, energy-efficient platooning, and urban traffic flow optimization—addressing both technological innovation and sustainability challenges in transportation networks. Professor Ran has received prestigious accolades including the ITE's Wilbur S. Smith Distinguished Transportation Educator Award (2018) and the Vilas Distinguished Achievement Professorship (2016). His complete award portfolio features: 2025 TRB Committee on Vehicle-Highway Automation Best Paper Award 2024 Top 0.05% Lifetime Global Highly Ranked Scholar in Transport 2020 ASCE Journal Best Paper Award 2010 Chinese National Distinguished Expert Lifetime Honor 1994 Charley Wootan Award for best transportation PhD dissertation He actively mentors graduate researchers through thesis supervision (CIV ENGR 890/990 courses) and leads major initiatives including the Transportation Research Board's Task Force on vehicle-highway automation architecture and the World Transport Convention's Faculty Committee. His grant portfolio supports international collaborations through the International Road Federation's 180-country network. As ITS Program Director, Ran oversees a research ecosystem integrating connected vehicle corridors, roadside edge computing, and V2X-enabled infrastructure. His team develops physical-virtual integration frameworks like the Digital Twin for Connected Vehicle Corridors, focusing on real-world deployment of cooperative automated driving systems across diverse environmental conditions.
Thøger Gorm Jensen serves as a Guest researcher at the Research Unit for Clinical Microbiology within the Clinical Institute at Odense University Hospital (OUH), affiliated with the University of Southern Denmark (SDU). His academic career spans clinical microbiology research with particular emphasis on bloodstream infections, bacterial genomics, and epidemiological surveillance systems. His work bridges laboratory research with practical clinical applications in hospital infection control and public health monitoring. Dr. Jensen's research interests focus on the epidemiology of bloodstream infections, particularly bacteremia in Danish populations. His work encompasses molecular characterization of pathogens, development of diagnostic pipelines like RSYD-BASIC for bacterial isolate analysis, and comparative studies of infection patterns across different populations. He has made significant contributions to understanding SARS-CoV-2 dynamics during the pandemic and continues to investigate antimicrobial resistance patterns in clinically relevant pathogens. His research integrates genomic approaches with traditional epidemiological methods to provide comprehensive insights into infection dynamics. Analysis of his recent publication trends (2021-2025) reveals a strong focus on population-based cohort studies of bloodstream infections in Denmark, with increasing emphasis on comparative international epidemiology (particularly with Singapore) and the implementation of automated surveillance systems. His work consistently addresses clinically relevant questions about pathogen identification, antimicrobial resistance patterns, and infection control measures, with practical applications in hospital settings and national public health infrastructure. Dr. Jensen has been actively involved in developing diagnostic tools and surveillance systems, including landmark corona tests during the pandemic as reported in multiple media outlets. His research has practical implications for clinical microbiology laboratories and hospital infection control protocols, with several publications focusing on how laboratories can act proactively in implementing rapid diagnostics for early clinical decision making. His collaborative network extends across Danish hospitals and international institutions, with notable involvement in the SG-DK Bacteraemia study group and contributions to nationwide surveillance initiatives. Dr. Jensen participates in significant research activities including conference presentations on bacterial whole genome sequencing implementation and PCR diagnostic optimization, demonstrating his commitment to advancing clinical microbiology practice through research.
Elizabeth Wiemers is an Assistant Professor in the Psychology Department at Bradley University's College of Liberal Arts & Sciences. Her research focuses on cognitive psychology with a particular emphasis on working memory, attentional control, and executive function. Her recent publications demonstrate expertise in areas like: Cognitive training mechanisms and transfer effects Proactive and reactive cognitive control dynamics Individual differences in attentional capacity Mind wandering and task engagement Neuropsychological assessment in clinical populations Cognitive load management in multitasking Contact: ewiemers@bradley.edu
Demet Özgür Ünlüakın is an Assistant Professor at the Faculty of Engineering and Natural Sciences , Işık Üniversitesi , specializing in Industrial Engineering . She holds a Ph.D., Master's, and Bachelor's degree in Industrial Engineering from Boğaziçi Üniversitesi. Education Ph.D. (1997-2007): Boğaziçi Üniversitesi, Fen Bilimleri Enstitüsü/Endüstri Mühendisliği Master's (1995-1997): Boğaziçi Üniversitesi, Fen Bilimleri Enstitüsü/Endüstri Mühendisliği B.S. (1991-1995): Boğaziçi Üniversitesi, Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü Her research focuses include Stochastic Processes , Decision Making , and Quality Management , particularly in the context of maintenance optimization , dynamic Bayesian networks , and multi-component systems . She has supervised several Master's theses at Işık Üniversitesi and Boğaziçi Üniversitesi. Scientific awards are not explicitly mentioned in the provided data. Advised Students ŞİMAL EKİN DEMİRAL (2024 Thesis: Opportunistic maintenance of complex systems using dynamic Bayesian networks) İPEK KIVANÇ (2020 Thesis: Maintenance optimization of multiple component systems using probabilistic graphical models) BUSENUR TÜRKALİ (2020 Thesis: Evaluation of alternative maintenance strategies on a complex system in thermal power systems) AYŞE KARACAÖRENLİ (2019 Thesis: Analysis of different maintenance policies on a multi-component system using dynamic Bayesian networks) MUSTAFA BURAK AKTEL (2018 Thesis: Maintenance policy analysis of gate systems in hydroelectric power plants) MO'TASEM ABUSHANAP (2014 Thesis: Proactive maintenance of thermal power plants under limited observations) UMUT KÜÇÜKDURMAZ (2014 Thesis: Effects of recent IVR applications on call center performance in banking sector) ELİF ANILGAN (2012 Thesis: Statistical analysis and capacity planning of a third-level neonatal unit) Her projects include ICT-enabled Bee Foraging Sites and Beekeeper Routes Optimization and Opportunistic Maintenance using Dynamic Probabilistic Networks . She teaches courses such as Engineering Statistics , Quality Planning and Control , and Stochastic Processes .
Annika Björnsdotter is a Lecturer at the School of Psychology , University of Gothenburg. She holds a PhD in Psychology (2014) and is a licensed psychologist, psychotherapist, and CBT supervisor. Her work bridges clinical practice, teaching, and research, with a focus on parent training programs, leadership development, and integrative approaches to well-being. Licensed psychologist (clinical specialization) PhD in Psychology (2014) Licensed psychotherapist and CBT supervisor Research Interests : Annika’s research explores the intersection between sexology and cognitive behavioral therapy (CBT), particularly in leadership training and proactive well-being strategies. Her 2014 doctoral work evaluated the Family Check-Up program against the iComet internet-based intervention for families with children aged 10-13 exhibiting conduct issues, contributing to psychometric standards and normative data for parent rating scales. Publications Trends : Her scholarly output spans randomized controlled trials (2024), Swedish-language leadership training frameworks (2021), and long-term evaluations of family-based interventions (2018). Articles emphasize empirical validation of therapeutic models, digital adaptation of clinical tools, and organizational behavior applications. Teaching and Supervision : Annika teaches advanced cognitive behavioral therapy courses in the psychology program and supervises student clinical work. She also instructs in the psychotherapist program and mentors theses at multiple academic levels.
Dr. Simone Schäffner serves as a Scientific Associate and Lecturer at the Chair of Pedagogy and Intervention for Language and Communication Impairments within the Institute for Special Education at the Faculty of Human Sciences, Julius-Maximilians-University Würzburg. Since January 2021, she has held dual roles as both a lecturer in the Academic Speech Therapy/Speech Therapy program at Würzburg's Vocational School for Speech Therapy and as Coordinator of the Academic Speech Therapy/Logopedics program at the university. Her educational background includes: Doctor of Philosophy (Dr. phil., summa cum laude) from RWTH Aachen University (2018) Master of Science in Teaching and Research Logopedics from RWTH Aachen University (2012) Bachelor of Science in Logopedics from RWTH Aachen University (2010) State-certified Logopedist qualification (2008) Dr. Schäffner's research centers on multimodal language processing , particularly examining how different sensory inputs affect language comprehension in children with language development disorders. Her work explores bilingual language processing in bimodal bilingual individuals and investigates the relationship between language disorders and sensory integration. A significant portion of her recent research focuses on metacognitive training approaches for improving executive functions in children, with direct applications for speech therapy interventions. She examines gesture production differences, modality switching mechanisms, and the role of modality compatibility in elementary school children's language processing. Analysis of her publication trajectory reveals a clear progression from foundational research on modality effects in language switching to applied research examining these phenomena in clinical populations. Her work increasingly bridges cognitive psychology and speech therapy, developing evidence-based interventions that translate theoretical findings into practical therapeutic approaches, particularly through metacognitive and working memory training protocols. Dr. Schäffner supervises bachelor's theses in the Academic Speech Therapy program and coordinates clinical internships at the ENT Clinic of the University Hospital Würzburg. Her teaching encompasses courses on research methodology in speech therapy, language comprehension disorders, and multilingualism. She leads several active research projects: Investigating modality-specific effects in language processing in children with language development disorder Conducting multitasking studies to examine modality effects in bimodal bilingual individuals Studying the relationship between diagnosed language disorders and sensory integration Her research takes place within the Chair of Pedagogy and Intervention for Language and Communication Impairments, which functions as part of the university's broader infrastructure for special education research and clinical practice.
Pernille Pedersen is an Associate Professor in the Department of Public Health - Department of Health Services Research at Aarhus University's Faculty of Health. She also serves as Program Manager and Senior Researcher at DEFACTUM with research output spanning from 2006 to present, including 40 publications and active projects through 2026. Her educational background includes: Training as a nurse Master of Health Science (cand.scient.san.) PhD from Aarhus University Dr. Pedersen's research focuses on rehabilitation, particularly daily life participation and return to work or education for individuals with health challenges. She employs quantitative methods to develop effective rehabilitation interventions that enhance functional ability and quality of life. Her work particularly addresses mental illness and cancer rehabilitation pathways, with expertise in employment, mental health, social inequality, and register-based research. Her recent publications (2025) demonstrate a strong focus on transdiagnostic approaches to sleep disorders, vocational rehabilitation for schizophrenia patients, workplace accommodations for pregnant healthcare workers, and social vulnerability assessment in healthcare settings. These works reflect her commitment to evidence-based rehabilitation interventions that bridge clinical practice and real-world applications. As an educator, she coordinates the 10 ECTS rehabilitation course in the Public Health Bachelor's program, emphasizing active student participation. She supervises students at all levels from Bachelor's to PhD candidates and serves as a censor for Public Health programs. Dr. Pedersen leads multiple research projects including studies on late effects after pelvic cancer and functional ability in young people with schizophrenia. She is part of the SEVERIN coordination group, co-founded Rehabilitation and Mental Illness under the Danish Psychiatric Society, and serves on the research committee of the Danish Society for Public Health. Her collaborative work spans regional departments of social medicine, occupational medicine, oncology, psychiatry, and municipal health and employment departments.
Bruce L Lambert is a Professor in Medical Social Sciences (Intervention Science) at Northwestern University's Feinberg School of Medicine and concurrently holds a Professor position at the School of Communication. His work bridges clinical medicine, health informatics, and communication science with appointments across multiple institutes including the Center for Diabetes and Metabolism, Institute for Public Health and Medicine (IPHAM), and Northwestern University Clinical and Translational Sciences Institute (NUCATS). His research focuses on medication safety systems, electronic health record (EHR) design, and health communication. Key interests include preventing drug name confusion errors, optimizing indication-based prescribing, and developing clinical decision support tools. Lambert employs psycholinguistic testing to predict real-world medication errors and investigates secure messaging networks in healthcare settings. His work demonstrates how EHR interface design directly impacts wrong-patient and wrong-drug error rates. Analysis of his recent publications reveals strong emphasis on opioid safety in emergency departments, Veterans Health Administration prescribing patterns, and multimodal approaches to medication error prevention. His scholarship consistently addresses system-level interventions rather than individual provider blame, advocating for human factors engineering solutions in healthcare technology. Lambert actively contributes to medication safety policy, having published on Tall Man lettering limitations and the need for comprehensive immune monitoring in vaccine trials. His research directly informs EHR design standards and clinical workflow improvements across multiple healthcare systems. As an educator, he integrates principles of conservative prescribing and health literacy into medical training. His work on pharmacy deserts in minority communities highlights health equity concerns in medication access. Lambert's PhD from University of Illinois at Urbana-Champaign (1992) established his foundation in communication science applied to healthcare contexts.
Simone Lenti is an Assistant Professor (Ricercatore RTDa) at the Department of Computer, Control, and Management Engineering of Sapienza University of Rome. He is an active member of the A.WA.RE research group , which specializes in visual analytics. Lenti obtained his Ph.D. in 2021 with a dissertation on visual analytics techniques for cybersecurity. His research bridges cybersecurity , visual analytics , and human-computer interaction , focusing on: Developing computational methods for vulnerability analysis (e.g., NLP for CVE relevance, smart contract taxonomies) Designing visual tools for threat detection (e.g., attack graphs, firmware fuzzing) Enhancing interpretability in data-driven systems (e.g., partial dependence analysis, process mining) Lenti's publications (2019–2025) demonstrate a consistent focus on applying visual analytics to cybersecurity challenges , with recent expansions into bioinformatics and education. Key trends include automated vulnerability management, human-centered explainability, and scalable threat modeling. Awards: IEEE VizSec 2018 Best Paper for contributions to cybersecurity visualization. He contributes to academic infrastructure through tools like easyDeclare (declarative process modeling) and BUCEPHALUS (business-centric cybersecurity analysis), emphasizing practical applications of his research.
Jan-Matthias Braun is an Associate Professor at the Maersk Mc-Kinney Moller Institute, University of Southern Denmark, specializing in Applied AI and Data Science. His research bridges artificial intelligence, robotics, and medical device engineering. Current projects focus on explainable AI integration in colon capsule endoscopy Development of real-time FPGA-based systems for colorectal diagnostics Biomechanical modeling for adaptive orthotic devices His work emphasizes cross-disciplinary applications of machine learning in healthcare, particularly for gastrointestinal disease detection and assistive robotics. Publications demonstrate expertise in deep neural networks, hardware acceleration, and smart environment control systems. Teaching responsibilities include: Advanced cybersecurity courses Deep learning applications in epilepsy detection Mentorship in capsule endoscopy image analysis
