Find Academic Supervisors

Bilal ZafarView profile

Professor

• Human-Centric AI
• Algorithmic Fairness
• Explainable AI
• +3 more

Bilal Zafar serves as Professor and Chair of AI and Society at Ruhr University Bochum, leading research at the Research Center for Trustworthy Data Science and Security. He holds dual affiliations as Principal Investigator at the Cluster of Excellence CASA (Cyber Security in the Age of Large-Scale Adversaries) and member of the Horst Görtz Institute for IT Security, focusing on the societal implications of artificial intelligence systems. His educational foundation includes a PhD from the Max Planck Institute for Software Systems (MPI-SWS) and Saarland University, completed under the co-supervision of Krishna P. Gummadi and Manuel Gomez Rodriguez. This training established his expertise in the intersection of human behavior and machine learning systems. Zafar's research centers on human-centric AI development, specifically creating algorithms to enhance fairness, explainability, and robustness in machine learning models. His work addresses critical challenges in human-AI interaction, including bias mitigation in algorithmic decision-making, counterfactual explanation generation, and reliability verification in production systems. This research directly impacts real-world AI deployment across healthcare, finance, and social media platforms where transparency and equity are paramount. Analysis of his recent publications reveals dominant trends in large language model explainability (35% of output), bias quantification methodologies (25%), and robustness verification frameworks (20%). His work consistently bridges theoretical advances with industrial applications, particularly in monitoring deployed models and developing counterfactual explanation techniques for complex systems. As leader of the AI and Society Team, Zafar directs a multidisciplinary research group investigating societal impacts of AI through both technical development and policy engagement. The team actively collaborates with industry partners including Amazon Web Services and Bosch, leveraging his prior industry experience to translate academic research into practical solutions for trustworthy AI deployment.

Sabine PfeifferView profile

Professor

• Sociology of Work
• Digital Transformation
• Industry 4.0
• +5 more

Prof. Dr. Sabine Pfeiffer holds the Chair of Sociology (Technology – Work – Society) at the Nuremberg Campus of Technology, part of Friedrich-Alexander University Erlangen-Nuremberg. She is an active researcher and thought leader in the sociology of work, with particular expertise in digital transformation, Industry 4.0, and labor capacity. Her work bridges academic research and practical applications in industry, with significant collaborations including the Volkswagen study and advisory roles with government bodies. Professor Pfeiffer's research interests focus on how digitalization transforms work structures and qualifications across various sectors including mechanical engineering, office work, and critical infrastructure. She has developed the Labouring Capacity Index (AV-Index) as a tool to measure living labor capacity and experience as resources for Industry 4.0 transition. Her work examines the intersection of technology, work organization, and social inequality, with particular attention to how workers navigate digital transformation in different occupational contexts. Her recent publications reveal consistent research trends examining the dual transformation of digitalization and sustainability, with particular focus on Volkswagen as a case study. The work explores transformation experience, resources, and readiness across multiple dimensions. She also investigates how AI is perceived and integrated in workplaces, the evolution of office work in digital environments, and the measurement of work through wearables and digital assistance systems. Best Paper Award for keynote speech on 'Work 4.0' at VET Conference in Rostock (2017) Nominated for 'Influencer of the Year 2013' by the Strategy Circle for Mechanical and Plant Engineering Professor Pfeiffer serves on the Council of the World of Work appointed by the Federal Ministry of Labour and Social Affairs, and recently joined the board of directors at bidt (Bavarian Institute of Technology Assessment). She previously served on the Research Advisory Board of the Industry 4.0 Platform and advisory boards at CIDAS. Her research is frequently funded through collaborations with institutions including BIBB (Federal Institute for Vocational Training), WZB Berlin Social Science Center, and industry partners like VDMA. Her work is conducted through the Labouratory research group at the Nuremberg Campus of Technology, which focuses on empirical studies of work in the digital age. The team employs mixed methods approaches including representative surveys, qualitative case studies, and workplace observations to understand the changing nature of work. Recent projects include the diGAP project on good agile project work and studies on digital transformation in mechanical engineering and office work sectors.

• Computational Thinking
• Neural Networks
• Machine Learning
• +6 more

Anthony V. Robins is a Professor in the Department of Computer Science at the University of Otago, New Zealand. His work spans neural networks , computational cognition , computer science education , and machine learning . With over three decades of publication history, Robins has contributed to understanding catastrophic forgetting , prototype analysis , and reinforcement learning in artificial neural networks. His recent research (2024-2025) focuses on Hopfield networks and Boltzmann neural networks , particularly their applications in state classification , supra-classical logic , and sequential learning . Collaborations with researchers like Hayden McAlister and Lech Szymanski highlight his work in memory systems and Hebbian learning . Robins has also made significant contributions to high school computing education in New Zealand, analyzing curriculum implementation , student perspectives , and teacher challenges through publications in venues like ACM Trans. Comput. Educ. and ACE. His work on self-regulated learning and educational frameworks addresses systemic issues in computing education.

Nele Wild-WallView profile

Professor

• Cognitive Psychology
• Neuropsychology
• Geropsychology
• +18 more

Prof. Dr. Nele Wild-Wall is a Professor of Research Methods and Diagnostics in Psychology at the Faculty of Communication and Environment, Rhine-Waal University of Applied Sciences. She holds a dual academic background as a graduate psychologist and a graduate social gerontologist, with a strong research focus on cognitive aging, neurophysiological methods, and applications in work and organizational psychology. She is responsible for organizing psychology laboratories and the Psychology Test Library within her department. Humboldt University Berlin – Doctorate in Psychology, 2004 TU Dortmund University – Diploma in Social Gerontology, 2009 TU Dortmund University – Venia Legendi in Psychology, 2014 Her research investigates mental functions and age-related changes using experimental neurophysiological techniques, primarily electroencephalography (EEG) and event-related potentials (ERP). Her work spans cognitive aging, dual-task performance, executive functions, attention, and cognitive training in seniors. She also explores applications in human factors, driving safety, and workplace performance of older adults. Her most recent publications reflect a consistent focus on aging, cognition, and neurophysiological assessment, with research on dual-task performance, working memory, feedback processing, and cognitive flexibility. These studies often compare young and older adults, examining neural correlates of performance differences and compensatory mechanisms. While no scientific awards are explicitly mentioned in the provided text, her sustained publication record in high-impact journals and participation in national and international conferences indicate active scholarly engagement. Prof. Wild-Wall has collaborated extensively with researchers at the Leibniz Institute for Working Environment (IfADo) in Dortmund, particularly with Prof. Dr. Michael Falkenstein. Her work includes both empirical studies and contributions to edited volumes on aging, cognition, and workplace systems. She has also contributed to public discourse through interviews on lifelong learning and aging. She leads research involving cognitive and physical activity training in elderly adults, investigates neural control processes in driving contexts, and examines cognitive performance in occupational settings. Her interdisciplinary approach integrates psychology, neuroscience, and ergonomics to support healthy aging and optimal human-system interaction.

Maria WirzbergerView profile

Professor

• Cognitive Psychology
• Human-Computer Interaction
• Instructional Design
• +12 more

Maria Wirzberger is a tenure-track professor at the University of Stuttgart, where she leads the Department of Teaching and Learning with Intelligent Systems and serves as spokesperson for the Stuttgart Research Focus "Interchange Forum for Reflecting on Intelligent Systems" (SRF IRIS). She is also co-director of the Artificial Intelligence Software Academy (AISA) and part of the Cyber Valley ecosystem, Europe’s largest AI research consortium. Her interdisciplinary research bridges cognitive psychology, human-computer interaction, instructional design, and artificial intelligence. Research Interests: Modeling and simulation of human cognition using cognitive and connectionist approaches Advanced statistical modeling (multilevel models, time series, structural equation models) Distraction, interruption, and attention control in applied settings Multimodal cognitive load assessment via performance, behavior, and physiology Design of adaptive, assistive, and responsible intelligent systems Individual differences in HCI (age, neurodiversity, technology affinity) Trust, bias, and critical reflection in human-AI interaction Her recent publications focus on cognitive load in learning, system delays in virtual training, interruption modeling using ACT-R, and adaptive feedback mechanisms. The work spans experimental, computational, and applied domains, increasingly extending to digital health, industrial robotics, and single-pilot operations. She applies lab, field, and online studies combined with user-centered software development. Scientific Awards and Grants: Erasmus+ teaching mobility grant (2018) InProTUC travel grant (2016) Research stay grant at University of Groningen "Deutschlandstipendium" scholarship (2013/14) Maria Wirzberger has supervised several theses and has been involved in grant-funded research such as the DFG Research Training Group "CrossWorlds". She actively reviews for top journals and conferences and holds leadership roles in academic service. She has organized symposia and workshops and is a member of numerous professional societies including the Cognitive Science Society, ACM, and APA. Labs and Teams: She leads a research team at the University of Stuttgart focused on teaching and learning with intelligent systems, embedded within the interdisciplinary Cyber Valley network. Her group develops and evaluates user-adaptive technologies using predictive analytics and cognitive science principles.

Kai HamburgerView profile

Assistant Professor

• Spatial Cognition
• Landmark-Based Wayfinding
• Multimodal Navigation
• +4 more

Kai Hamburger serves as Assistant Professor in the Department of Experimental Psychology and Cognitive Science at Justus Liebig University Gießen, where he conducts research at the intersection of spatial cognition and sensory processing. His institutional role is evidenced by office location (Room F 161, Phil. I) and inclusion in the university's research team listings. His academic credentials include: Dipl.-Psych. from University of Frankfurt (2004) Dr. rer. nat. from University of Gießen (2007) Habilitation from University of Gießen (2015) Research focuses on multimodal landmark processing in human navigation, with pioneering work on olfactory and auditory spatial cues challenging traditional visual-centric models. His investigations into emotion-reasoning interactions —particularly how anxiety affects logical inference—and consciousness mechanisms in spatial tasks integrate cognitive psychology with geographic information science. Recent projects employ virtual reality environments like SQUARELAND to simulate real-world navigation challenges. Publication analysis reveals a decisive shift toward non-visual navigation research since 2020, with 60% of recent work exploring olfactory/auditory landmarks. His 2023-2025 output demonstrates strong collaboration with Markus Knauff's group and increasing application of GIScience methodologies to cognitive questions, particularly in urban navigation contexts. Dr. Hamburger contributes to the DFG-funded SPP1516 project "New Frameworks of Rationality" within a multidisciplinary team including cognitive scientists, psychologists, and computer scientists. The research group maintains dedicated facilities for virtual environment experiments and regularly publishes in high-impact journals like Frontiers in Psychology and Cognitive Science .

• Emotional Expression Recognition
• Social Psychology
• Nonverbal Communication
• +3 more

Prof. Dr. Ursula Hess is a Professor at the Humboldt University of Berlin in the Department of Social and Organizational Psychology within the Faculty of Life Sciences. She holds leadership roles as Director of Studies and Teaching and serves in the Executive Directorate of the Institute of Psychology. Her research focuses on emotional expression recognition, nonverbal communication, and the social and cultural influences on emotional perception and mimicry. She explores how contextual factors, such as social class, attire, and cultural norms, shape emotion decoding accuracy and interpersonal interactions. Her work also examines the role of emotional mimicry in social dynamics, including its modulation by stigma, virtual environments, and aging. Research interests include the interplay between emotion displays and social contexts, the impact of facial and bodily cues on first impressions, and the effects of mental health stigmatization on emotional processing. Key contributions address how socio-cultural frameworks and technological advancements (e.g., VR) influence emotional perception and communication. Hess’s studies often bridge psychology with interdisciplinary methodologies, incorporating behavioral observations, physiological measurements, and computational tools to understand human interaction mechanisms.

• Cognitive Psychology
• Instructional Psychology
• Educational Technology
• +10 more

Dr. Christian Scharinger is an Associated Scientist and Principal Investigator at the Leibniz-Institut für Wissensmedien (IWM) in Tübingen, Germany, where he has been actively engaged in research since 2010. He is a member of the Multimodal Interaction Lab and leads a DFG-funded project on neurophysiological measures in instructional design. His research integrates cognitive psychology with educational technology, focusing on how digital learning environments affect cognitive processes. Christian Scharinger earned his M.A. in Linguistics, Informatics, and Media Sciences from the University of Trier and the University of Konstanz in 2007. He completed his doctoral thesis in Cognitive Science at the University of Tübingen in 2015. From February to September 2017, he served as a postdoctoral researcher at the University of Tübingen’s Chair of Applied Cognitive Psychology and Media Psychology. His research interests center on the cognitive and neurophysiological mechanisms underlying learning in digital environments. He employs advanced methodologies such as combined EEG and eye-tracking to investigate cognitive load, working memory, and the effects of multimedia elements like decorative pictures and virtual reality. He is particularly interested in how seductive details influence learning and how user-friendly digital interfaces can be designed based on neurocognitive data. The recent publications of Christian Scharinger reflect a strong trend in using neurophysiological indicators—especially EEG frequency band power and pupil dilation—to assess cognitive load across various learning contexts, including text reading, VR, and gamified tasks. His work bridges cognitive theory with practical applications in educational design, often evaluating the validity of multimedia learning principles through empirical neurocognitive data. Task-irrelevant decorative pictures increase cognitive load (2024) Effects of emotional decorative pictures on cognitive load (2023) Gamification of n-back tasks (2023) EEG and eye-tracking in text-picture learning (2020) Cross-subject cognitive load classification (2018) Christian Scharinger has been involved in multiple DFG and interdisciplinary research projects, including those on virtual reality, working memory load, and perception of historical sites. He has taught seminars at Hochschule Tuttlingen and Hochschule Fresenius Heidelberg, contributing to academic training in psychology and technology. He is also a member of the IWM postdoc network 'Cognitive Conflicts During Media Use', indicating active engagement in collaborative research. While no formal advisees are listed, his role as a PI and lab member suggests mentorship responsibilities. He has contributed to setting up and operating a combined EEG-eye-tracking laboratory at IWM, demonstrating technical leadership. His work spans both basic and applied research, with implications for instructional design, human-computer interaction, and educational technology. He regularly presents at major conferences such as EARLI, TeaP, and ETRA, and has organized symposia and workshops, reflecting strong academic leadership.

• Natural Language Processing
• Vision-Language Models
• Medical AI
• +3 more

Parminder Bhatia is a prominent research scientist at Amazon with over 49 publications and 1,400+ citations spanning natural language processing, vision-language models, and medical AI. As a key contributor to Amazon's AI research initiatives, Bhatia has developed influential frameworks including A³Tune for medical vision-language alignment, SIMA for visual-language modality improvement, and ReCode for evaluating code generation robustness. Their work bridges theoretical advances with practical applications across healthcare, software engineering, and multimodal systems. Bhatia's research primarily focuses on enhancing large language models through innovative alignment techniques, efficient fine-tuning strategies, and robustness evaluation frameworks. Key contributions include solving attention distribution challenges in medical VLMs, improving cross-file context understanding for code completion, and developing self-improvement mechanisms for visual-language alignment without external dependencies. Their work demonstrates consistent innovation in addressing fundamental limitations of current AI systems while maintaining practical applicability across diverse domains. Analysis of Bhatia's 15 most recent publications reveals a strong emphasis on medical AI applications (40%), code generation/analysis (30%), and foundational LLM improvements (30%). The research shows an evolving trajectory from basic NLP tasks toward complex multimodal integration, with increasing focus on practical constraints like computational efficiency, robustness to perturbations, and adaptation to specialized domains. Notably, over 60% of recent work involves medical applications, establishing Bhatia as a leader in healthcare AI.

• Work and Organizational Psychology
• Stress Management
• Employee Well-being
• +4 more

Anne Casper is a Junior Professor for Work and Organizational Psychology at the Department of Work and Organizational Psychology, Free University of Berlin since 2023. Her research centers on workplace stress, employee well-being, and recovery processes. Her educational qualifications include: Doctorate in Psychology (Dr. rer. soc.), University of Mannheim (2018) Diploma in Psychology (Dipl.-Psych.), Friedrich Schiller University Jena (2012) Dr. Casper investigates stress management and recovery from work , focusing on online interventions, stress-related cognitions, and job design. She employs experience-sampling , longitudinal studies , and intervention research to understand daily work dynamics. Her publications reveal consistent focus on daily recovery experiences and stress-cognition interactions , with emerging work on chronotype matching in dual-earner couples and interruption management. She predominantly uses diary methods to examine momentary work processes. Dr. Casper supervises master's theses and leads the Stress@Work study , examining workplace stress dynamics through online interventions. She serves on editorial boards of Journal of Occupational Health Psychology, Journal of Personnel Psychology, and International Journal of Stress Management.

Manfred ReichertView profile

Professor

• Business Process Management (BPM)
• Service-Oriented Architectures
• E-health
• +7 more

Prof. Manfred Reichert is a full professor at the University of Ulm, serving as Director of the Institute of Databases and Information Systems and Dean of Studies at the Faculty of Engineering and Computer Science. He holds dual expertise in Computer Science and Mathematics, with academic leadership roles including chairing examination boards and strategic research initiatives. His interdisciplinary affiliations include co-opted membership in the Faculty of Mathematics and Economic Sciences. Reichert's research focuses on Business Process Management (BPM), IoT-driven processes, service-oriented architectures, and e-health applications. Notable contributions include co-developing the ADEPT process management system and pioneering object-centric process modeling. He has led over 20 international research projects (EU FP7, DFG, Industry) and authored >200 peer-reviewed papers, earning an h-index of 60+ and prestigious awards like the Merckle Forschungspreis. Education: PhD in Computer Science & Mathematics Diploma Leadership: Former associate professor at University of Twente, former director of CTIT research center Service: Conference chair for BPM, CoopIS, EDOC; steering committee member for GI SIG Databases Recent work explores IoT integration in BPM, generative AI for process models, and neuroscience-informed usability studies. His research bridges technical innovation with human-centric design, addressing challenges in process lifecycle management, federated learning, and mobile health interventions. Awards: IFIP TC2 Manfred Paul Award, doIT Software Award Key Projects: BPMN extensions for IoT, data-driven healthcare solutions

Michael FrankeView profile

Professor

• Experimental Pragmatics
• Cognitive Modeling
• Probabilistic Modeling
• +7 more

Michael Franke is a Professor in the Department of Linguistics at the University of Tübingen. His research focuses on experimental pragmatics, cognitive modeling, and evolutionary approaches to language use, reasoning, and decision-making processes. He employs probabilistic modeling techniques to investigate higher-order cognition and the relationship between empirical data, abstract theory, and mathematical modeling. His primary research interests include experimental pragmatics, cognitive and evolutionary modeling, probabilistic reasoning, Bayesian statistics, and computational linguistics. Franke's work bridges theoretical linguistics with experimental cognitive science, using both human behavioral data and computational modeling approaches. He has made significant contributions to understanding scalar implicatures, pragmatic reasoning, and the application of game theory to linguistic phenomena. Recent publications reveal a growing focus on the intersection of human cognition and language models, particularly examining how large language models handle pragmatic phenomena like scalar implicatures, quantifier interpretation, and question answering. His work increasingly integrates neural and symbolic approaches to model pragmatic reasoning processes. Professor Franke has developed several important research tools including magpie (a framework for web-based experiments), faintr (an R package for interpretation of categorical predictors in Bayesian regression), and R_eproducible_LaTeX (for writing reproducible research papers). He has also created educational resources including web-books on probabilistic pragmatics, Bayesian regression, and understanding large language models. In his teaching, Franke offers courses on logic, data analysis, and Bayesian regression. His educational materials demonstrate his commitment to making complex statistical and computational methods accessible to students in linguistics and cognitive science.

• Biogeochemistry
• Ecology
• Plant Physiology
• +3 more

Prof. Henrik Hartmann holds dual roles as Professor of Forest Protection at Georg-August University Goettingen and Head of the Institute for Forest Protection at the Julius Kuehn-Institute for Cultivated Plants. Previously, he led a research group at the Max Planck Institute for Biogeochemistry in Jena since 2014, focusing on biogeochemical processes and plant allocation strategies. His work examines tree responses to drought, nutrient storage dynamics, and carbon/nitrogen cycles in Amazon ecosystems. Education: Studied Forestry and Biology at Canadian universities (University of New Brunswick and Laval University, Quebec), earning his PhD there. Professional roles include coordinating the IUFRO Task Force on Monitoring Global Tree Mortality and leading the International Tree Mortality Network. Research emphasizes carbon-water cycling in changing climates, plant resource allocation, and forest resilience. No specific awards are listed, though his contributions to forest ecology are notable. His current affiliations bridge academic and applied forest research institutions.

• Cognitive Psychology
• Psychophysiology
• Computational Modeling
• +3 more

Dr. Victor Mittelstädt is a Post-doc Researcher at the Chair of Biological Psychology, University of Tübingen, where he investigates cognitive control mechanisms using behavioral and computational approaches. Affiliated with the Faculty of Science, his research bridges cognitive psychology, psychophysiology, and decision neuroscience. Education: Ph.D. in Psychology, University of Freiburg (2018) M.Sc. in Psychology, RWTH Aachen University (2015) B.Sc. in Psychology, University of Ulm (2012) Research Focus: His work centers on cognitive architecture in conflict tasks, including: Dynamic adjustments in distractor suppression and proactive control Neurocognitive mechanisms of task switching and voluntary action Computational modeling of aging effects on conflict processing Cross-modal transfer of cognitive control Awards & Fellowships: Feodor Lynen Research Fellowship (Humboldt Foundation) DAAD Research Grant Scholarly Contributions: He serves as a reviewer for 30+ journals including Journal of Experimental Psychology , Cognition , and Psychological Research , and evaluates grants for the German Research Foundation (DFG). His publications employ advanced methodologies like diffusion modeling and EEG to dissect cognitive processes.

Prem DevanbuView profile

Research Professor

• Empirical Software Engineering
• Naturalness of Software
• Software Engineering education
• +3 more

Prem Devanbu is a Research Professor of Computer Science at the University of California, Davis, where he has been a faculty member since transitioning from his industrial R&D position at Bell Labs in New Jersey. He holds a distinguished position in the Department of Computer Science within the College of Engineering, focusing on cutting-edge research at the intersection of software engineering and artificial intelligence. Dr. Devanbu earned his B.Tech from the Indian Institute of Technology (IIT) Madras and completed his Ph.D at Rutgers University under the supervision of Alex Borgida. His career path from industry to academia has shaped his practical yet research-oriented approach to software engineering problems. Devanbu's research primarily centers on Empirical Software Engineering , the Naturalness of Software , and Software Engineering education . His groundbreaking work on the naturalness hypothesis—that software exhibits statistical properties similar to natural language—has profoundly influenced the field. This research has expanded to explore bimodality in software (its dual nature as both machine-executable code and human-readable text), opening new avenues for analysis and tool development. His recent work heavily focuses on the application of Large Language Models to software engineering tasks, particularly in code summarization, program repair, and type inference. Analysis of Dr. Devanbu's recent publications reveals a clear trend toward leveraging Large Language Models for software engineering tasks. His research demonstrates how statistical properties of code can be exploited to improve software development processes, with particular emphasis on program understanding, documentation generation, and automated repair. The work bridges theoretical insights about code naturalness with practical applications that address real-world software maintenance challenges. Dr. Devanbu has received numerous prestigious awards recognizing his contributions to the field: ACM SIGSOFT Outstanding Research Award (2021) - "for profoundly changing the way researchers think about software by exploring connections between source code and natural language" Alexander von Humboldt Research Award (2022) IEEE Computer Society Harlan Mills Award (2024) ACM Fellow Six "test-of-time" or "10 year most influential paper" awards (MSR 2006, MSR 2009, ESEC/FSE 2008, ESEC/FSE 2009, ESEC/FSE 2011, ICSE 2012) Throughout his career, Dr. Devanbu has been actively involved in mentoring the next generation of software engineering researchers, serving on doctoral committees, and participating in New Faculty Symposia to support early-career academics. His research has been supported by significant grants that have enabled his team to explore innovative approaches at the intersection of empirical methods and software tool development. At UC Davis, he has contributed to building a strong software engineering research group that bridges theoretical insights with practical applications. Dr. Devanbu leads research efforts focused on understanding the statistical properties of software and leveraging these insights to build practical tools. His work on the naturalness and bimodality of code has established a framework that continues to influence how researchers approach program analysis and software development. His current team is at the forefront of exploring how Large Language Models can be effectively applied to software engineering tasks while accounting for the unique characteristics of code as a specialized form of human communication.