Find Academic Supervisors

Kaya de BarbaroView profile

Associate Professor

• Developmental Psychology
• Clinical Psychology
• Social Interactions
• +5 more

Dr. Kaya de Barbaro is an Associate Professor in the Department of Psychology at the University of Texas at Austin (College of Liberal Arts). She holds a Ph.D. from the University of California San Diego. Her research focuses on bridging computer science and developmental/clinical psychology, particularly maternal mental health and infant social-emotional development. She directs the Daily Activity Lab, which uses mobile/wearable sensors and machine learning to analyze real-world interactions, aiming to develop just-in-time interventions for new mothers. Key research areas include maternal-infant dynamics, physiological synchronization, and the impact of environmental chaos on development. She has pioneered methods for analyzing high-density data, such as Granger causality and machine learning algorithms to detect behaviors like crying and holding. Recent work emphasizes leveraging ecological momentary assessment surveys and 24-hour LENA audio recordings to understand proximal mechanisms of development. Dr. de Barbaro teaches Psychology 333D (Introduction to Developmental Psychology) and has developed curricula for both in-person and online formats. She is actively involved in training students through the Eureka program at UT Austin. Her lab collaborates on tools like chatbots for postpartum mental health and has published extensively on sensor-based methodologies in developmental science.

Tijana GajićView profile

Researcher

• Language Education
• Digital Learning Tools
• Foreign Language Acquisition
• +4 more

Tijana Gajić is a researcher at Singidunum University in Belgrade, Serbia. She holds a Ph.D. in Philology (2020), an MA in English Language and Literature (2009), and a BA in the same field (2007) from the University of Belgrade. Her work focuses on the intersection of language education, digital tools, and critical pedagogy. Doctoral Studies: Philology , University of Belgrade (2017-2020) Master Studies: English Language and Literature , University of Belgrade (2008-2009) Bachelor Studies: English Language and Literature , University of Belgrade (2003-2007) Dr. Gajić’s research explores the impact of digital technologies on language acquisition, critical thinking development, and the sociopolitical dimensions of English language learning. She has published extensively on mobile applications like Duolingo, HelloTalk, and WordUp, analyzing their efficacy in modern pedagogy. Her recent publications (2024-2025) examine digital tools’ influence on language education, critical pedagogy in Serbian classrooms, and AI-driven language learning innovations. Earlier works (2020-2016) established her expertise in tandem learning, vocabulary enhancement via apps, and affective factors in language acquisition. Notable collaborations include partnerships with researchers like N. Maenza , A. Gagić , and J. Nikolić . While no specific grants or awards are mentioned, her involvement in conferences such as Sinteza and ELTA Serbia underscores her active role in advancing language education. Her 2022 book, Nastava stranih jezika i razvoj kritičkog mišljenja u eri neoliberalizma , synthesizes her critical pedagogy framework. Current projects likely continue her focus on digital transformation in language teaching.

Adriana TapusView profile

Professor

• Robotics
• Human-Robot Interaction
• Machine Learning
• +7 more

Adriana Tapus is a Full Professor at ENSTA Paris, affiliated with Institut Polytechnique de Paris, leading the Autonomous Systems and Robotics Laboratory (SAR) within the Computer Science and Systems Engineering Unit (U2IS). She holds an HDR (Habilitation) and a PhD from EPFL, Switzerland, with postdoctoral experience at USC. Her research focuses on socially assistive robotics, human-robot interaction (HRI), and personalized therapy for individuals with physical/cognitive impairments. She directs the IP Paris Doctoral School and coordinates national/international projects like the EU-funded ENRICHME and SWEET. Education: PhD in Mobile Robotics, EPFL (2005) Habilitation (HDR), ENSTA Paris (2011) M.S. Computer Science, University Joseph Fourier Engineer, Politehnica University of Bucharest Research Interests: Tapus pioneers socially assistive robotics, integrating machine learning, human modeling, and multimodal communication (verbal/non-verbal/para-verbal). Her work addresses adaptive therapies for vulnerable populations using robotics, physiological data interpretation, and context-aware interaction. Key themes include: Human-robot cooperation and trust Emotion recognition and expression Personalized rehabilitation systems AI ethics and human-centered design Publications: Over 150 articles, with recent work exploring humor in HRI, teleoperation trust models, and cross-cultural intelligent vehicles. Notable 2025 contributions include studies on robot laughter efficacy and multimodal facial expression frameworks. Awards: 2025: 4 IROS papers accepted 2016: 25 Women in Robotics recognition 2010: Romanian Academy Award Multiple conference best paper awards (RO-MAN, ICRA, etc.) Advising & Grants: Supervised over 20 PhD students and led projects like EU Horizon 2020 ENRICHME. Current students focus on teleoperation dynamics, robot humor, and haptic interfaces. Active in editorial roles (IJSR, THRI) and conference organization (HRI General Chair 2019). Labs/Teams: Founder of RoboticsByDesign lab and co-initiator of the Hi! Paris interdisciplinary AI center. The SAR lab develops systems for healthcare, education, and human-robot collaboration.

• Learning Sciences
• Technology-Enhanced Learning
• Collaborative Learning
• +4 more

Professor Nancy W. Y. Law is a leading scholar in Learning Sciences and Technology at the University of Hong Kong's Faculty of Education . She has served as Founding Director of the Centre for Information Technology in Education (CITE) (1998-2013) and currently holds the Chair of Learning Sciences and Technology . Her career spans over 25 years of international comparative studies, policy analysis, and large-scale educational innovation. Current roles: Associate Dean (Strategic Development), HKU Key affiliations: Sciences of Learning Strategic Research Theme (co-convener) Research Expertise Her work focuses on technology-enhanced learning , digital literacy , knowledge building communities , and multilevel educational change . She pioneered network models of teacher innovation and socio-technical frameworks for sustainable pedagogical transformation, particularly in STEM education and Cyberbullying prevention . Scientific Leadership With over 25 major research grants (2000-2023) exceeding HK$50 million, she leads projects like: Learning and Assessment for Digital Citizenship Jockey Club Self-directed Learning in STEM Design-Aware Learning Analytics A Fellow of the International Society of Learning Sciences and recipient of the HKSAR Humanities and Social Sciences Prestigious Fellowship , she has supervised numerous international comparative studies including SITES 2006, ICILS 2013, and longitudinal digital citizenship research (2019-2021).

Sara BakerView profile

Professor

• Science of learning
• Executive functions
• Self-regulation in children
• +5 more

Professor Sara Baker is a Professor of Developmental Psychology and Education at the University of Cambridge's Faculty of Education and a Fellow at Darwin College, where she served as Vice Master from 2021-2024. She is also a 2022 Senior Fellow in the Science of Learning with UNESCO-IBE/IBRO. Her work bridges cognitive science and educational practice, focusing on how children develop executive functions and self-regulation skills. Baker leads the Early Years Library project, co-founded the Research Centre for Play in Education, Development and Learning (PEDAL), and is a founding member of the Global Executive Functions Initiative. Sara Baker specializes in the science of learning, with research aimed at improving children's lives by identifying factors at home and school that support their agency over learning. Her work emphasizes developing executive functions and self-regulation through playful learning approaches. She uses lab-based experiments and collaborates with educators to translate cognitive science research into educational contexts. Her research spans multiple countries including the UK, USA, Mexico, Denmark, Slovakia, South Korea, Ghana, Rwanda, Nigeria, Kenya, South Africa, and more, reflecting a strong commitment to culturally relevant and globally applicable educational practices. Analysis of Professor Baker's recent publications reveals a strong focus on executive functions, self-regulation, and playful learning across diverse cultural contexts. Her work increasingly addresses cultural adaptation of assessment tools and educational practices, particularly for Global Majority countries. There's a clear trajectory from basic cognitive research toward practical applications in educational settings, with growing emphasis on teacher training, culturally relevant assessment, and the role of play in early childhood development. Her interdisciplinary approach connects developmental psychology, educational theory, and practical classroom applications. 2022 Senior Fellow in the Science of Learning with UNESCO-IBE/IBRO Professor Baker leads the doctoral program in the Faculty of Education and serves as an Academic Project Director in the School of Humanities and Social Sciences. She is the Cambridge academic lead on the Close the Gap partnership between Cambridge and Oxford, focused on postgraduate widening participation. Her research has been funded by prestigious organizations including the Newton Trust, Cambridge Humanities Research Grant, Economic and Social Research Council, LEGO Foundation, Nuffield Foundation, and Office for Students/Research England. She actively supervises doctoral students and seeks highly motivated candidates for October 2026 entry whose research aligns with her focus areas. Professor Baker co-founded and is actively involved with the Research Centre for Play in Education, Development and Learning (PEDAL), which investigates how children's play affects their development. She leads the Early Years Library project, a curated collection of evidence-based practices for early years educators, and is a founding member of the Global Executive Functions Initiative. Her work with the Connections international professional learning network focuses on self-regulation, while the Close the Gap project addresses widening participation in postgraduate education between Oxford and Cambridge.

Claus LammView profile

Professor

• Empathy
• Prosocial Behavior
• Social Neuroscience
• +5 more

Claus Lamm is a Full Professor of Biological Psychology at the University of Vienna , where he leads the Social, Cognitive and Affective Neuroscience Unit (SCAN-Unit) . He serves as Vice Dean for Research and Advancement of Early Career Researchers at the Faculty of Psychology and holds affiliations with the Vienna Cognitive Science Hub , Environment & Climate Change Hub , and Austrian Academy of Sciences . His academic career spans international collaborations and formative research experience abroad. Scientific Focus: Lamm investigates the neural underpinnings of empathy and prosocial behavior , employing multi-modal approaches combining neuroimaging, psychopharmacology, and psychoneuroendocrinology . His work extends to comparative studies with ravens and dogs, and explores environmental social neuroscience through climate change decision-making research. Recent publications show trends in cross-cultural psychology , machine learning applications , and neurobiological pathways related to social behavior. Awards & Grants: Recipient of the APS Mentor Award for his support of early career researchers. Funded by European Research Council , Austrian Science Fund , Vienna Science and Technology Fund , and intramural grants exceeding €10 million. Key projects include "Unravelling the opioid system in empathy" and "Comparative dog-human fMRI" . Media Engagement: A prominent public science communicator, Lamm has appeared in Nature , Science Magazine , and Austrian media outlets like Ö1 Mittagsjournal and ORF2 , discussing topics from pandemic psychology to social media effects . He maintains active outreach through Science TV and educational programs .

Susanne WeisView profile

Research Professor

• Neuroimaging
• Cognitive Neuroscience
• Machine Learning in Neuroscience
• +3 more

Susanne Weis is a Research Professor and Group Leader of the 'Variability of the Brain' group at the Department of Brain and Behavior (INM-7), part of the Institute of Neuroscience and Medicine (INM) at Research Center Jülich GmbH. Her work focuses on understanding brain variability through advanced neuroimaging techniques and machine learning, with particular emphasis on sex differences, hormonal influences, and clinical applications in mental health. Her research interests include neuroimaging methodologies, machine learning applications in cognitive neuroscience, and the structural-functional relationships underlying brain variability. She investigates how factors like sex hormones and naturalistic stimuli (e.g., movies) affect brain connectivity and cognitive performance, aiming to improve diagnostic and predictive tools for disorders such as schizophrenia and Alzheimer’s disease. Publications highlight her contributions to developing datasets (e.g., SpEx), analyzing confound leakage in ML models, and exploring meta-analytic networks during naturalistic viewing. Her work bridges basic science and clinical impact, addressing challenges in interpreting neuroimaging data and advancing personalized medicine approaches. In her role as a group leader, Weis oversees research projects and collaborates with interdisciplinary teams. She is affiliated with the Helmholtz Association and contributes to the broader scientific community through her research in neuroimaging and computational neuroscience.

Frank RudziczView profile

Associate Professor

• Natural Language Processing
• Machine Learning
• Healthcare
• +12 more

Dr. Frank Rudzicz is an Associate Professor in the Faculty of Computer Science at Dalhousie University. His research lies at the intersection of artificial intelligence, natural language processing, and healthcare, with a focus on developing machine learning systems that improve clinical decision-making, patient outcomes, and accessibility in medicine. He holds a BSc from Concordia University (2004), an MEng from McGill University (2006), and a PhD from the University of Toronto (2011). His research interests include Natural Language Processing, Machine Learning, Healthcare, Speech Technologies, Explainable AI, and Fairness in ML. Dr. Rudzicz's recent publications span a wide range of topics, including Alzheimer's detection through speech analysis, surgical outcome prediction, mental health monitoring, privacy in AI, and the application of large language models in clinical settings. His work consistently emphasizes ethical AI, patient privacy, and real-world clinical integration. He has received several awards, including a Best Paper award at EMNLP 2020, a Best Student Paper award at ICASSP 2021, and the ISCA Best Student Paper award in 2013. His research has been published in top-tier journals such as Nature Scientific Reports , JAMA Network Open , IEEE Access , and Frontiers in Human Neuroscience , as well as leading conferences including NeurIPS, ACL, ICML, and Interspeech. Dr. Rudzicz supervises a dynamic research group working on AI for health, with active projects in voice-based diagnostics, ambient clinical documentation, explainable AI for surgery, and wearable-based monitoring for chronic diseases. He collaborates widely across disciplines, including with clinicians, neuroscientists, ethicists, and public health experts. He is also involved in major initiatives such as the Genetics Navigator study and Bridge2AI-Voice, aiming to build ethically sourced, diverse biomedical datasets. His lab actively explores the societal implications of AI in healthcare, including fairness, trust, and resistance to malicious fine-tuning.

• Affective Neuroscience
• Emotion Regulation
• Schizophrenia Spectrum Disorders
• +4 more

Univ-Prof. Dr. med. Malek Bajbouj serves as Director of the Institute for Affective Neuroscience and Emotion Modulation at Charité – University Medicine Berlin's Campus Benjamin Franklin (CBF), operating within the Department of Neurology, Neurosurgery and Psychiatry (CC 15). His position integrates clinical leadership with translational neuroscience research focused on severe mental illnesses. Dr. Bajbouj's research program centers on affective neuroscience and emotion dysregulation mechanisms in psychiatric disorders, particularly schizophrenia spectrum conditions and depression. He pioneers multimodal intervention approaches combining neuromodulation (tDCS), oxytocin augmentation, mindfulness therapies, and digital health tools. His work emphasizes translational biomarker development using neuroimaging, machine learning, and physiological stress parameter analysis to personalize treatment for treatment-resistant populations. Analysis of his 2023-2025 publications reveals three dominant research trajectories: (1) novel treatment combinations for negative symptoms in schizophrenia (oxytocin + mindfulness, yoga therapy); (2) real-world implementation of neuromodulation (at-home tDCS protocols, technical efficacy monitoring); and (3) global mental health responses to crises (pandemic impacts on vulnerable groups, culturally adapted refugee interventions). His methodology consistently employs rigorous randomized controlled trials with embedded biomarker studies. As director of his eponymous institute, Dr. Bajbouj leads a multidisciplinary team conducting neuroimaging studies, clinical trials, and international collaborations focused on emotion modulation pathways. The institute coordinates research across CC 15's clinical infrastructure at CBF Building V, with particular emphasis on bridging laboratory neuroscience with clinical psychiatry through the DepressionDC and OXYMIND trial frameworks.

• Artificial Intelligence
• Machine Learning
• Cognitive Robotics
• +3 more

Dr. Ulrike Kuhl is a Researcher at the University of Bielefeld, serving as Project Coordinator for the AI Academy OWL at the Research Institute for Cognition and Robotics and as Scientific Project Coordinator within the Faculty of Engineering's Machine Learning Group. Her office is located at CITEC 2-412, and she can be reached at +49 521 106-12125. Dr. Kuhl's research spans several interconnected domains at the forefront of human-centered AI development: Explainable Artificial Intelligence (XAI) frameworks and their psychological impact Cognitive learning enhanced through AI technologies Counterfactual explanation methodologies and user behavior Human-AI interaction design principles Applications of machine learning in environmental monitoring and sports analytics Analysis of Dr. Kuhl's publication trajectory reveals a consistent focus on bridging the gap between sophisticated AI systems and human understanding. Her work particularly examines how different explanation types affect user trust and decision-making, with recent publications exploring counterfactual explanations in contexts ranging from water distribution networks to educational technology. She has developed experimental frameworks like the 'Alien Zoo' methodology for systematically studying explanation usability. Dr. Kuhl actively contributes to the Center for Cognitive Interaction Technology (CITEC) at the University of Bielefeld, an interdisciplinary hub where computer scientists, engineers, and cognitive scientists collaborate on next-generation interactive technologies. Through her coordination of the AI Academy OWL initiative, she facilitates regional collaboration between academic researchers and industry partners to advance artificial intelligence applications in the Ostwestfalen-Lippe region.

Shrikanth NarayananView profile

Professor

• Human-centered signal processing
• Machine intelligence
• Affective computing
• +10 more

Shrikanth (Shri) Narayanan is University Professor and Niki & C. L. Max Nikias Chair in Engineering at the University of Southern California (USC), with appointments spanning Electrical & Computer Engineering, Computer Science, Linguistics, Psychology, Neuroscience, Pediatrics, and Otolaryngology-Head & Neck Surgery. He serves as Research Director of the Information Sciences Institute and Director of the Ming Hsieh Institute. PhD in Electrical Engineering (UCLA, 1995) Engineer and MS in Electrical Engineering (UCLA, 1992 and 1990) BE in Electrical Engineering (Anna University, India, 1988) His interdisciplinary research focuses on human-centered signal processing and machine intelligence , addressing societal challenges in health, education, defense, and media arts. Key areas include: Behavioral signal processing Affective computing Multimodal signal processing Computational speech science Biomedical applications Scientific Awards : IEEE James L. Flanagan Speech and Audio Processing Award (2025) Edward J. McCluskey Technical Achievement Award (2024) ISCA Medal for Scientific Achievement (2023) Claude Shannon-Harry Nyquist Technical Achievement Award (2023) ACM ICMI Sustained Accomplishment Award (2020) USC Distinguished Faculty Service Award With over 1,000 publications and 19 patents , his work has been commercialized through startups like Behavioral Signals Technologies and Lyssn . He leads transformative university initiatives and has served in editorial roles for top journals including Computer Speech and Language and IEEE Transactions on Affective Computing .

Jon GrudaView profile

Assistant Professor

• Organizational Behavior
• Leadership Studies
• Personality Psychology
• +4 more

Dr. Jon Gruda is an Assistant Professor and Lecturer in Organisational Behaviour at Maynooth University's School of Business. He holds a PhD in Management from emlyon Business School (France) and a joint Dr. rer. nat. in Psychology from Goethe University Frankfurt. His research focuses on relational leadership, dark leadership traits, anxiety in the workplace, and personality psychology, with a strong emphasis on integrating machine learning and AI methodologies. Gruda has been recognized with prestigious awards, including selection for the Lindau Nobel Laureates Meeting in Economic Sciences (2020). His interdisciplinary work includes predicting anxiety and personality traits via social media data analysis. He serves as an Associate Editor for journals like Personality and Individual Differences and Frontiers in Psychology . Education PhD in Management, emlyon Business School (2012–2017) Dr. rer. nat. in Psychology, Goethe University Frankfurt (2012–2017) MSc in Affective Neuroscience, Maastricht University (2018) MSc in Management Research, emlyon Business School (2012–2014) Triple MSc in Management, City University London/ESCP Europe (2010–2012) BSc in International Business & Management, University of Groningen (2007–2010) Research Interests Gruda’s work bridges leadership studies, personality psychology, and data science. Key areas include: Dark leadership traits (e.g., narcissism, Machiavellianism) and their organizational impacts Machine learning applications for detecting anxiety and personality traits via social media Cross-cultural studies on leadership perceptions and attachment orientations Impact of physiological/psychosocial factors on leadership effectiveness Publications & Projects Recent projects include predicting state-level health outcomes linked to narcissism and developing algorithms to track anxiety using Twitter data. Over 20 peer-reviewed articles since 2017 highlight his contributions to organizational behavior and computational social science. Awards 7th Lindau Nobel Laureates Meeting on Economic Sciences (2020) Benedictine University Award (Academy of Management, 2020) Wharton Global Faculty Development Program (2020) Grants & Collaborations Gruda leads projects on pro-environmental behavior and collaborates with the National Care Experience Programme on healthcare feedback analysis. Seed funding includes €301,930 for computational text analytics in healthcare. Labs & Teams Interdisciplinary research collaborations span psychology, data science, and public health, with a focus on applying machine learning to organizational challenges.

Mohammad T. AlhawaryView profile

Professor

• Arabic Second Language Acquisition
• Arabic Language Pedagogy
• Bilingualism
• +9 more

Mohammad T. Alhawary is Professor of Arabic Linguistics and Second Language Acquisition at the University of Michigan's Middle East Studies department within the College of Literature, Science, and the Arts. He serves as Director of both the MA Program in Arabic for Professional Purposes (APP) and the MA Program in Teaching Arabic as a Foreign Language (TAFL). His educational background includes a Ph.D. from Georgetown University (1999). Prior to joining the University of Michigan, he contributed to developing Arabic and Middle Eastern Studies programs at various US institutions. Professor Alhawary's research spans both theoretical and applied Arabic linguistics, with particular focus on second language acquisition processes. His work examines how factors like age, input quality, output practice, and first language transfer affect Arabic language learning. He has made significant contributions to understanding Arabic language pedagogy, curriculum design, proficiency testing, and the application of technology in language learning. His research also extends to bilingualism, multilingualism, language impairment, and Arabic medieval grammatical traditions. His publications reflect a strong trajectory in Arabic linguistics research, with recent works focusing on practical language teaching applications, reading comprehension mechanisms, code-switching patterns in digital communication, and multilingual acquisition processes. The 2023 publication 'Teaching Arabic as a Foreign Language' represents his latest contribution to language pedagogy methodology. 2019 AATA Book Award for 'Arabic Second Language Learning and Effects of Input, Transfer, and Typology' As an academic leader, Professor Alhawary serves as Executive Director of the American Association of Teachers of Arabic and edits both the Journal of Arabic Linguistics Tradition and Al-'Arabiyya journal. He continues to develop empirical research on Arabic second language acquisition to inform teaching practices both in America and globally.

• Augmented Reality
• Virtual Reality
• Human-Computer Interaction
• +3 more

Mark Billinghurst is a Professor and Director of the Australian Research Centre for Interactive and Virtual Environments at UniSA STEM, University of South Australia. His work focuses on Augmented Reality (AR), Virtual Reality (VR), and empathic computing, emphasizing remote collaboration, human-computer interaction, and inclusive design. He has authored influential books like Computer-Supported Collaboration: Theory and Practice (2024) and pioneered systems such as Empathy Glasses and gaze-tracking interfaces for collaborative tasks. Education & Affiliations: Mark Billinghurst is affiliated with the Empathic Computing Laboratory and has collaborated globally with institutions like Keio University, Nokia, and the University of Canterbury. His research spans AR applications in manufacturing, healthcare, and social interaction, with a focus on improving accessibility and user experience. Research Interests: Dr. Billinghurst’s research explores AR/VR for remote guidance, wearable technologies, and emotional interfaces. He investigates how gaze cues, multimodal feedback, and AI can enhance collaboration and empathy in virtual environments. His work bridges technical innovation with human-centric design, addressing challenges in industrial assembly, mental health, and workplace transformation. Publications & Impact: His 2016 study on gaze tracking in remote collaboration (cited over 100 times) and 2024 book on AR collaboration highlight his contributions. Recent projects include Vibe360 (group emotion analysis) and CAEVr (biofeedback-driven empathy systems). He actively contributes to conferences like IEEE VR and CHI, shaping the future of immersive technologies. Labs & Future Work: His lab develops tools like the SAR system for aircraft drilling and empathic agents (EMiRAs). Future directions include AI-driven emotional interfaces, inclusive metaverse design, and VR solutions for cognitive rehabilitation.

Jens KreitewolfView profile

Academic

• Auditory Cognition
• Speech Perception
• Neuroimaging
• +7 more

Jens Kreitewolf is a Faculty Lecturer in the Departments of Psychology and Mathematics and Statistics at McGill University. He teaches courses in statistics, research methodology, and psychophysics. His research focuses on auditory cognition, speech comprehension, and the neural mechanisms underlying voice perception. Dr. Kreitewolf holds a Ph.D. (Dr. rer. nat.) from Humboldt University of Berlin and completed postdoctoral fellowships at BRAMS and the University of Lübeck. His work combines experimental psychology, neuroimaging, and psychophysics to explore auditory processing challenges in adverse listening conditions. Key interests include how familiarity with a talker’s voice aids comprehension and the impact of hearing impairment on speech perception. Education: M.Sc. in Psychology (Ruhr University Bochum, 2009); Ph.D. in Psychology (Humboldt University of Berlin, 2014). Research Interests: Auditory scene analysis and speech-in-noise processing Voice recognition and familiarity effects Neural correlates of perceptual decision-making Circadian rhythms and perceptual sensitivity Cognitive neuroscience of auditory attention Publications highlight contributions to understanding: Risk factors for depression symptom progression Self-concept clarity in romantic evaluations Neurobiological mechanisms of working memory vulnerability Vestibular symptoms in migraine patients His interdisciplinary approach bridges psychology, statistics, and neuroscience, with applications to clinical populations and sensory processing disorders.