Find Academic Supervisors

• Cognitive Psychology
• Behavioral Adaptation
• Modality Dependence
• +3 more

Linda C. Bräutigam is a Researcher in the Biological Psychology research group within the Department of Psychology at the University of Tübingen's Faculty of Science. She has been pursuing her Ph.D. in Psychology since November 2021 under the supervision of Victor Mittelstädt. Her educational background includes: Ph.D. in Psychology (since 11/2021), University of Tübingen, Advisor: Victor Mittelstädt M.Sc. in Neurobiology (10/2018-01/2021), University of Tübingen B.Sc. in Biology (10/2015-09/2018), University of Tübingen Bräutigam's research focuses on cognitive psychology, particularly behavioral adaptation and modulation, and the modality dependence of information processes. Her current projects investigate congruence effects in the Eriksen Flanker Paradigm across modalities, proactive reward manipulation in Stroop and Simon tasks, and motor control adjustments within a Slider Simon task. Her work bridges experimental psychology and neuroscience to understand how the brain processes conflicting information and adapts behavior. Her recent publications in 2024 explore behavioral adjustments in proportion congruency manipulations using visual and auditory distractors in the Eriksen flanker task, and the role of proactive reward in conflict tasks. These studies contribute to the fields of cognitive control, conflict processing, and motivational influences on performance, highlighting trends in understanding how reward structures can modulate cognitive conflict beyond general performance enhancement. Bräutigam is actively involved in the Biological Psychology research group at the University of Tübingen, where she conducts experiments on cognitive conflict and behavioral adaptation.

• Machine Learning
• Artificial Intelligence
• Cybersecurity
• +5 more

Mohamed M. Abdallah is a researcher affiliated with Hamad Bin Khalifa University in Doha, Qatar, specifically within the College of Science and Engineering . His work focuses on advanced applications of Machine Learning , Artificial Intelligence , and Cybersecurity in domains such as Smart Grids , Internet of Things , and Wireless Communication . His recent research explores Federated Learning under adversarial conditions, optimization of Multi-Agent Systems for task offloading, and Privacy-Preserving Techniques in networked environments. Key contributions include frameworks for Deep Reinforcement Learning (DRL) in Edge Computing and 6G Networks , addressing challenges in Energy Efficiency , Latency , and Data Distribution Shifts . His publications highlight collaborations with institutions like Texas A&M at Qatar and Hamad Bin Khalifa University , emphasizing solutions for Heterogeneous Networks , Blockchain Applications , and Secure Communication in IoT and critical infrastructure.

Katherine WhiteView profile

Professor

• Cognitive Psychology
• Language Production
• Aging and Cognition
• +3 more

Dr. Katherine White serves as Professor of Psychology and Director of the Cognition and Aging Lab at Rhodes College. Her research program investigates cognitive mechanisms underlying language production across the lifespan, with particular focus on how linguistic, attentional, and emotional factors influence word retrieval in younger and older adults. She holds the Winton M. Blount Professorship in Social Sciences. Her educational background includes: Ph.D. in Cognitive and Sensory Processes from the University of Florida M.S. in Psychology from the University of Florida B.A. in Psychology from Rhodes College White's research spans cognitive psychology, psycholinguistics, and aging science. She examines tip-of-the-tongue phenomena, written language production errors, and emotional influences on speech fluency through controlled experiments and naturalistic communication settings. Her work reveals how attentional control modulates emotional interference during speech, how aging affects orthographic encoding, and how semantic factors influence word retrieval failures. Current projects explore multimodal communication through gesture-speech interactions in collaboration with Pomona College. Analysis of her publication record shows consistent evolution from foundational studies on tip-of-the-tongue states and written errors toward increasingly complex investigations of emotional and multimodal aspects of language production. Recent work integrates aging, emotion, and naturalistic communication contexts, reflecting theoretical expansion from isolated laboratory paradigms to ecologically valid models of real-world language use. White actively mentors undergraduate researchers through her Cognition and Aging Lab. Lab alumni regularly present at national conferences including the Psychonomic Society and Cognitive Aging Conference. Many graduates pursue advanced degrees in psychology (clinical, neuropsychology, geropsychology) or health professions (MD, PharmD, Speech Pathology). Her training program emphasizes hands-on research experience in experimental design, data collection, and scientific communication. The Cognition and Aging Lab operates as an interdisciplinary research hub investigating language-cognition interactions across adulthood. Current projects include multimodal communication studies examining gesture's role in speech production and investigations of emotional content's impact on narrative fluency in aging populations. The lab maintains active collaborations with cognitive science programs at other institutions while serving as a training ground for future scientists.

• Human Resource Management
• HR Analytics
• Job Crafting
• +3 more

Dr. Zhonghao Wang serves as Assistant Professor of Management at the Marilyn Davies College of Business, University of Houston-Downtown, where he teaches undergraduate courses in Human Resource Management and HR Analytics across multiple semesters from 2023-2025. Education Ph.D. in Human Resources and Labor Relations, Michigan State University M.S. in Global Finance, Fordham University B.A. in English Language and Literature, Wuhan University B.S. in Finance, Wuhan University Research Focus Professor Wang investigates workplace change dynamics through two interconnected streams: (1) employee-driven adaptations including job crafting, transfer of training, and career trajectory responses; and (2) methodological innovations in survey research addressing careless/insufficient effort responding. His work bridges theoretical rigor with practical HR applications, published in premier outlets like Human Resource Management and Organizational Research Methods . Publication Trends His 2021-2025 publications reveal evolving focus from foundational job crafting (2021-2022) to contemporary workplace challenges: cannabis use impacts (2025), hybrid training transfer (2023), and advanced survey methodology (2024). The research consistently employs longitudinal designs and examines reciprocal relationships between individual behaviors and organizational contexts, with increasing emphasis on distal career outcomes. University Service Wang actively contributes through Faculty Senate Committee on Credentials and Elections (2024-2026), Parking and Transportation Committee (2023-2025), Marilyn Davies College of Business Curriculum Committee (2024-2026), and Department of Management Search and Curriculum Committees (2023-2025), demonstrating institutional commitment across all governance levels.

Martin BaumannView profile

Professor

• Human Factors
• Cognitive Psychology
• Human-Machine Interaction
• +12 more

Prof. Dr. Martin Baumann is Chair of Human Factors at Ulm University, a position he has held since February 2014. His research is centered on cognitive and behavioral aspects of human interaction with advanced technological systems, particularly in automated transportation. He leads a research group focused on human-machine systems, with strong affiliations to transportation safety and driver assistance technologies. His research interests include: Cognitive Modeling and empirical studies of human behavior in human-machine systems Attention processes, situational awareness, and cognitive distraction Design and implementation of cooperative driver assistance and automation systems Multimodal interaction and transitions between automated and manual driving modes Diagnostic reasoning and decision-making under uncertainty His scholarly work, accessible via Google Scholar, demonstrates a consistent focus on understanding and enhancing human performance in automated environments. Key trends across his recent publications include modeling driver cognition, evaluating multimodal interfaces, and improving the safety of human-automation handovers in vehicles. His work integrates cognitive psychology with engineering design to develop human-centered automation. Scientific Contributions: Developed cognitive models of driver behavior and situational understanding Pioneered research on attentional tunneling and cognitive distraction in automated driving Advanced methodologies for usability evaluation of in-vehicle technologies Influenced design principles for cooperative human-machine interaction Prof. Baumann has supervised numerous research projects and mentored early-career researchers, though specific student names are not listed. His work has been supported by national and institutional research grants related to transportation safety and human factors engineering. He previously led research groups at the German Aerospace Center (DLR) and held postdoctoral positions at Chemnitz University of Technology and BASt, reflecting a deep engagement with applied cognitive science. He is associated with the Human Factors research lab at Ulm University, which conducts empirical studies on driver behavior, cognitive load, and interface design using driving simulators, eye-tracking, and cognitive task analysis. The team focuses on holistic evaluation methods for next-generation driver assistance systems.

Nancy CarlisleView profile

Associate Professor

• Cognitive Psychology
• Visual Attention
• Working Memory
• +3 more

Nancy Carlisle is an Associate Professor in the Department of Psychology at Lehigh University, where she serves as Director of Graduate Studies. Her research focuses on the top-down control of visual attention and working memory, utilizing behavioral, eyetracking, computational modeling, and electrophysiological techniques. Ph.D. in Psychology, Vanderbilt University, 2011 B.S. in Zoology (Animal Behavior and Neurobiology), Michigan State University, 2005 B.S. in Psychology, Michigan State University, 2005 Carlisle's work investigates how attentional control templates in visual working memory guide perception by biasing selection toward goal-relevant information. She explores the interplay between working memory and attention, including how these systems suppress distractions and enhance guidance. Her interdisciplinary approach bridges cognitive psychology, neuroscience, and computational modeling. Her recent publications (2024-2022) highlight trends in attentional suppression mechanisms, EEG-based cognitive control studies, and neuroimaging applications in psychiatry (e.g., depression, autism, dementia). Collaborations with institutions like Vanderbilt, UC Davis, and University of Iceland reflect her transdisciplinary impact. As Director of Graduate Studies, she mentors graduate trainees and undergraduates in her CAM Lab, which focuses on attention-memory interactions. The lab employs behavioral, EEG, and eyetracking methods to study neural dynamics.

• Artificial Intelligence
• Biometrics
• Security Systems
• +5 more

Kingsley Nwosu is an Associate Professor in the Department of Computer Science at Norfolk State University's College of Science, Engineering and Technology. His research spans artificial intelligence, biometric systems, and security frameworks, with a focus on healthcare, campus safety, and low-resource environments. Email: kcnwosu@nsu.edu Research Themes: AI-driven emotion recognition and facial recognition systems Biometric authentication for security and privacy Blockchain applications in e-voting and data integrity Urban mobility optimization via embedded systems Public policy evaluation for social enterprises Data partitioning strategies for machine learning Publication Trends: His work since 2012 highlights interdisciplinary applications of AI and biometrics in healthcare, security, and economic development, with recent emphasis on scalable solutions for developing economies and proactive cybersecurity measures.

Valderi Reis Quietinho LeithardtView profile

Assistant Professor

• Distributed Systems
• Data Privacy
• Internet of Things
• +11 more

Valderi Reis Quietinho Leithardt is an Assistant Professor at the Department of Information Science and Technology, Iscte – University Institute of Lisbon , Portugal, where he holds a full-time position with exclusive dedication. He is an integrated researcher at ISTAR-Iscte (Research Center in Information Sciences, Technologies and Architecture) and a Senior Member of the IEEE . His academic affiliations also include collaborations with the University of Coimbra, University of Salamanca, and Fondazione Bruno Kessler. Education: Post-Doctorate , University of Salamanca, Spain (2019–2021) Post-Doctorate , University of Coimbra, Portugal (2017–2019) PhD in Computer Science , Federal University of Rio Grande do Sul, Brazil (2011–2015) Master’s in Computer Science , Pontifical Catholic University of Rio Grande do Sul, Brazil (2006–2008) Bachelor’s in Data Processing Technology , Higher Education Center of Foz do Iguaçu, Brazil (1999–2002) Research Interests: Valderi's research focuses on Distributed Systems, Data Privacy, Internet of Things (IoT), Cloud Computing, and Intelligent Systems . He explores algorithmic solutions for secure and efficient data management in heterogeneous environments, with applications in smart cities, precision agriculture, healthcare, and energy systems. His work integrates machine learning, blockchain, and federated learning to enhance privacy, security, and system performance. Publication Trends: His recent publications (2024–2025) emphasize time series forecasting, anomaly detection, JVM optimization, and privacy-preserving AI . A strong trend is observed in applying machine learning to power grid fault prediction, blockchain-based healthcare data privacy, and data quality in federated learning. His work bridges theoretical computer science with real-world applications in infrastructure, sustainability, and digital security. Scientific Contributions: Senior IEEE Member Active contributor to open science and reproducibility Involved in interdisciplinary research networks: Embedded and Distributed Systems Laboratory, COPELABS, CTS, CANDEIIA Member of professional societies: IEEE (since 2011), Brazilian Computer Society (since 2003) Academic Service and Leadership: He has held leadership roles in academic programs, including Director and Coordinator of the Master's in Computer Science and Management at Iscte (2025–2027). He actively organizes and participates in scientific events such as IEEE CIoT, DiTTEt, SBSeg, and MobiSPC, serving on organizing and scientific committees. He has coordinated workshops like WTTFC 2024 and 2025, promoting technological trends in future computing. Labs and Research Groups: He is a collaborator in several research networks, including: Embedded and Distributed Systems Laboratory (since 2016) Expert Systems and Applications Laboratory (since 2019) COPELABS – Human-Centered Computing and Cognition (since 2020) Fondazione Bruno Kessler (2021–2025) Center for Technology and Systems (CTS) (since 2023) Advanced Center for Development of Intelligent Systems and Artificial Intelligence (CANDEIIA) (since 2024)

• Cybersecurity
• Privacy Preservation
• Risk Management
• +14 more

Leandros Maglaras is a Professor in the School of Computer Science and Informatics at De Montfort University, where he conducts research in the Cyber Security Centre and Software Technology Research Laboratory. He holds a PhD from the University of Huddersfield and another from the University of Thessaly, and has served as Director of the National Cyber Security Authority of Greece (2017–2019), significantly advancing national cybersecurity preparedness. His research interests include Cybersecurity, Privacy Preservation, Risk Management, Intrusion Detection, Critical Infrastructure Protection, IoT, Blockchain, and Machine Learning . He is a Senior Member of IEEE and actively contributes to editorial boards of journals such as IEEE Access and Elsevier’s ARRAY. The analysis of his recent publications reveals a strong focus on cybersecurity in IoT and critical infrastructures , leveraging advanced techniques like federated learning, blockchain, and machine learning for intrusion detection and privacy preservation. His work spans smart agriculture, vehicular networks, healthcare, and industrial control systems, emphasizing real-world applicability and dataset development. Scientific Awards: Best Paper Award at DCOSS 2019 Maglaras has led numerous EU-funded research projects (e.g., CONCORDIA, COCKPITCI) and served on editorial boards. He has contributed to national policy, including drafting Greece’s Cyber Security Strategy and NIS Directive implementation. He mentors students and collaborates extensively, though specific advisee names are not listed. He is also involved in cyber peacekeeping initiatives and has co-edited books on cybersecurity of critical infrastructures. Labs and Research Groups: Cyber Security Centre (CSC), De Montfort University Software Technology Research Laboratory (STRL)

• Cognitive Neuroscience
• Declarative Learning
• Neural Oscillations
• +5 more

Esther De Loof is a postdoctoral researcher at Ghent University's Faculty of Engineering and Architecture, Department of Electronics and Information Systems (EA06). Her work spans cognitive neuroscience, focusing on declarative learning , reward prediction errors , and neural oscillations using EEG and computational modeling. Key Research Areas: Cognitive control, visual awareness, attentional inhibition, neural synchrony, and predictive processing Collaborators: Tom Verguts, Kate Ergo, Clio Janssens, Filip Van Opstal Publications reveal a focus on theta and alpha band dynamics in cognitive control (2016-2022), reward processing mechanisms, and the interplay between attention and memory systems. She has contributed to Nature Human Behaviour , Journal of Neuroscience , and Psychophysiology . Her methodological approach combines EEG , intracranial recordings , and computational models to investigate how the brain implements adaptive control strategies through neural oscillations and prediction error signaling.

Alla SikorskiiView profile

Professor

• Patient-Reported Outcomes
• Cancer Care
• Intervention Design
• +3 more

Alla Sikorskii is a Professor in the Department of Psychiatry at Michigan State University. Her research focuses on patient-reported outcomes, symptom management, and intervention design for individuals with cancer and chronic conditions, with a particular emphasis on caregiver dyad dynamics and adaptive clinical trial methodologies. She earned an M.S. in Mathematics from Kiev University and a Ph.D. in Statistics at MSU. Her work spans methodological innovations in sequential multiple assignment randomized trials (SMART) to improve supportive care for cancer survivors and their caregivers. Key research areas include symptom measurement, interdependent psychological distress, and optimizing healthcare utilization through evidence-based interventions. She has led studies on HIV-exposed children's neurodevelopment, caregiver burden mitigation, and the obesity paradox in colorectal cancer. Recent projects include a longitudinal study of fatty acid impacts on executive function in HIV-affected Ugandan youth and a cluster-randomized trial evaluating visual navigation aids in long-term care settings. Her work frequently integrates statistical rigor with interdisciplinary collaboration, addressing global health disparities through community-engaged approaches. Notable contributions include advancing adaptive intervention frameworks and demonstrating how symptom management reduces unscheduled healthcare visits. Current efforts focus on sustaining scalable interventions and evaluating the efficacy of complementary therapies such as reflexology and compassion training in oncology care. Dr. Sikorskii collaborates across disciplines to translate statistical methodologies into actionable clinical practices, with a focus on sustainable health equity solutions.

Paul R. MelcherView profile

Professor

• Quality Management
• Process Optimization
• Integrated Management Systems
• +9 more

Prof. Dr. Paul R. Melcher is a Professor for Actuators / Quality Management and Integrated Management Systems at the Department of Engineering and Communication, Hochschule Bonn-Rhein-Sieg (H-BRS). With a career spanning over two decades at H-BRS, he has held roles including Internship Coordinator (2000-2020), Quality Officer (2009-2020), and Appointment Officer (2018-2020). His expertise lies in Quality Management , Process Optimization , and Integrated Management Systems , with a focus on methodologies like FMEA , MITO , and ISO 9001 standardization. Research Focus : Quality management systems, process analysis (audits), workflow development, Lean Manufacturing, and digital transformation in education. Projects : Led the 2021 ADENiA project on automated detection of noise-induced sleep disturbances, and contributed to national studies on process organization in enterprises. Training : Developed DGQ-certified e-training modules for QM tools (e.g., Pareto diagrams, histograms) and served as a trainer for ISO auditor qualifications.

• Neuroscience
• Cognitive Science
• Motor Control
• +2 more

Giulia Ellena serves as a Research Fellow at the Interdepartmental Center for Mind/Brain Sciences (CIMEC) within the University of Trento, Italy, where her work bridges experimental neuroscience and cognitive psychology through advanced brain stimulation methodologies. Her research program centers on Neuroscience and Cognitive Science , with specialized expertise in Motor Control , Time Perception , and Brain Stimulation techniques. She employs transcranial magnetic stimulation (TMS) and statistical learning paradigms to investigate neural plasticity during proactive motor tasks and temporal processing, utilizing quantitative approaches to decode cognitive-motor interactions. Analysis of her recent publications reveals a cohesive research trajectory focused on non-invasive neuromodulation, particularly rTMS applications for enhancing motor learning and dissecting time perception mechanisms. Her work demonstrates strong interdisciplinary integration between psychological theory and neurophysiological measurement, with emphasis on statistical learning frameworks and causal brain-behavior relationships in human cognition. No scientific awards are documented in the available records. Current information indicates no formal student supervision or grant leadership activities have been publicly recorded at this time.

• Cognitive Ergonomics
• Electrophysiology
• Mobile EEG
• +4 more

Dr. Stefan Arnau is a Researcher at the Leibniz Institute for Work Research Dortmund (IfADo) since 2019, specializing in Experimental Ergonomics and Information Processing . His work focuses on cognitive fatigue, aging, and neurophysiological markers in applied settings. Key Techniques: Mobile EEG, eye blink analysis, ERP Collaborators: Prof. Edmund Wascher, Dr. Sarah Getzmann, Dr. Jonathan Reiser His research interests span cognitive ergonomics, neurophysiological correlates of mental load, and real-world applications of EEG technology. Recent publications emphasize aging-related cognitive decline, task-switching efficiency, and stress-induced neural changes. Analysis of his 15 most recent articles reveals a consistent focus on: Decoding cognitive states via EEG and eye blink activity Age-related differences in attentional resource allocation Neuroergonomic applications in driving and workplace environments Theta and alpha oscillations as markers of cognitive effort Machine learning for artifact removal in real-world EEG data Temporal perception under distraction He contributes to third-party funded projects and participates in the Dortmunder Vital-Studie for health assessment in occupational settings.

• Traumatic Brain Injury
• Sport-Related Concussion
• Neuropsychology
• +3 more

Dr. Spencer W. Liebel is a tenure-track Assistant Professor and Clinical Neuropsychologist in the Department of Neurology at the University of Utah School of Medicine. He holds adjunct appointments in Orthopaedics and Physical Medicine & Rehabilitation, and is a core faculty member of the Traumatic Brain Injury and Concussion Center. His clinical specialties include Cognitive Disorders, Epilepsy, Neurodegenerative Disorders, and Traumatic Brain Injury. Education: Postdoctoral Fellowship in Neuropsychology, Michigan Medicine/VA Ann Arbor Healthcare System Internship in Clinical Psychology (Neuropsychology), Clement J. Zablocki VA Medical Center Ph.D. in Clinical Psychology (Neuropsychology), University of Georgia M.S. in Psychology, University of Georgia B.S. in Psychology (Spanish minor), Brigham Young University Research Focus: Dr. Liebel's work centers on neurocognitive outcomes in traumatic brain injury (TBI) and sport-related concussion. He investigates recovery trajectories, neuropsychological assessment validation, personality factors (e.g., sensation-seeking), and optimization of return-to-play protocols using advanced statistical modeling and consortium data (NCAA-DoD CARE). His research bridges clinical neuropsychology, sports medicine, and neuroimaging. Publication Trends: Recent articles (2018–2024) emphasize concussion management in athletes, neurocognitive test validation, fMRI reproducibility in TBI, and computational approaches to rehabilitation. Common themes include longitudinal recovery analysis, military/NCAA athlete cohorts, and integration of neuroimaging with behavioral outcomes. Over 75% of publications involve multi-institutional collaborations. Awards: No scientific awards or honors were listed in the source material. Mentorship & Affiliations: Dr. Liebel actively mentors graduate students and postdoctoral fellows in neuropsychology and concussion research. He is a member of the International Neuropsychological Society and Sports Neuropsychology Society.