جست‌وجوی استاد و پژوهشگر

Stefan Ihliمشاهده پروفایل

دانشیار

• Canon Law
• Church Legal History
• Marriage Law
• +۴ مورد دیگر

Dr. Stefan Ihli serves as an Associate Professor at the Faculty of Theology at Katholische Universität Eichstätt-Ingolstadt, specializing in Canon Law and Church Legal History. His academic career spans over two decades with continuous scholarly contributions to ecclesiastical jurisprudence. His research focuses primarily on canon law, with particular emphasis on marriage law within the Catholic Church, church-state relations, ecclesiastical courts, and church labor law. His scholarly work demonstrates deep engagement with both historical and contemporary aspects of canon law, examining how legal traditions interact with modern legal systems. Professor Ihli's publication record reveals a strong trend toward analyzing the intersection of church law with civil legal systems, particularly in Germany. His work frequently addresses practical applications of canon law in contemporary contexts, including marriage validity, labor relations within religious institutions, and constitutional dimensions of church autonomy. His expertise in Bavarian church law indicates regional specialization within the broader German context. Multiple reviews of significant works in canon law (2015-2024) Substantial contributions to marriage law in Catholic canon law Analysis of church-state relations in German constitutional context Examination of labor law within ecclesiastical institutions Historical studies of church legal structures Commentary on ecclesiastical court procedures His scholarly influence extends through numerous book chapters, journal articles, and editorial contributions to major reference works in canon law. Professor Ihli has participated in significant academic collaborations, contributing to Festschriften and edited volumes that shape contemporary canon law scholarship. His institutional affiliation with Katholische Universität Eichstätt-Ingolstadt, Germany's only Catholic university, positions him at a unique intersection of theological scholarship and legal expertise within the ecclesiastical context.

Daniel E. Koditschekمشاهده پروفایل

استاد

• Dynamical Systems and Control
• Hybrid Control Systems
• Legged Locomotion
• +۷ مورد دیگر

Daniel E. Koditschek is the Alfred Fitler Moore Professor in the Department of Computer and Information Science at the University of Pennsylvania’s School of Engineering and Applied Science. He also holds primary appointments in the Department of Electrical and Systems Engineering and a research affiliation with the Department of Mechanical Engineering and Applied Mechanics. He is a leading figure in the GRASP Lab, where he leads the Kod*lab, a specialized group focused on physical interaction and locomotion in autonomous robots. His research lies at the intersection of dynamical systems theory and robotics, emphasizing legged locomotion, hybrid control systems, and bio-inspired design. Koditschek's work integrates formal mathematical modeling with empirical testing of physical robots that run, jump, climb, and manipulate objects. He actively explores how biological insights into animal mobility can inform robotic autonomy and control. His group maintains strong collaborations with biologists and emphasizes embodied intelligence in machine behavior. The recent publications reflect a strong trend in applying theoretical control frameworks—such as hybrid dynamical systems, averaging methods, and navigation functions—to practical robotic challenges in unstructured environments. Topics include terrain adaptation, energy-efficient locomotion, reactive planning, and affordance-based interaction. There is a clear focus on bridging abstract mathematical models with real-world robotic performance, particularly in legged and mobile manipulation systems. IEEE RAS Pioneer Award Heilmeier Research Award AFOSR MURI Award (2010) Daniel Koditschek has advised numerous PhD students and postdoctoral researchers, many of whom now hold faculty positions or leadership roles in robotics companies like Ghost Robotics and Boston Dynamics. His research is supported by major grants from the NSF and AFOSR, including the MURI award and REU/RET programs that engage K-12 and undergraduate educators. He has also been involved in international outreach, including activities at the Penn Wharton China Center. Koditschek leads the Kod*lab within the GRASP Lab’s PERCH facility, which houses advanced legged robots such as the Ghost Minitaur, XRHhex, Inu, Delta Hopper, and Jerboa platforms. The lab emphasizes experimental validation of control theories using custom hardware and real-world terrain challenges.

• Decision and Control
• Game Theory
• Multi-Agent Systems
• +۷ مورد دیگر

Jeff Shamma is the Department Head and Professor of Industrial and Enterprise Systems Engineering (ISE) at the University of Illinois at Urbana-Champaign, holding the Jerry S. Dobrovolny Chair. He is also courtesy Professor in Aerospace Engineering and Mechanical Science and Engineering. Formerly, he held the Julian T. Hightower Chair at Georgia Institute of Technology and faculty positions at KAUST. Dr. Shamma earned his PhD in Systems Science and Engineering from MIT (1988) and a BS in Mechanical Engineering from Georgia Tech (1983). He is a Fellow of IEEE and IFAC, recipient of the IFAC High Impact Paper Award, AACC Donald P. Eckman Award, and NSF Young Investigator Award. His research spans Decision and Control , Game Theory , and Multi-Agent Systems , focusing on human-machine networks, distributed autonomy, and adaptive robotic systems. Recent work examines crowd dynamics, risk-sensitive control, and feedback linearization for constrained optimization. Jeff has served as Editor-in-Chief of IEEE Transactions on Control of Network Systems (2020–2024) and held editorial roles in journals like Annual Reviews in Control and IEEE Transactions on Robotics . His 15 most recent publications (2024–2025) analyze learning dynamics, multi-agent optimization, and UAV-crawler systems, reflecting trends in autonomous systems, game-theoretic modeling, and industrial inspection technologies. Scientific distinctions include: Fellow of IEEE and IFAC IFAC High Impact Paper Award (2020) AACC Donald P. Eckman Award (1996) NSF Young Investigator Award (1992) Mohammed Dahleh Distinguished Lecture Award (2013) Dr. Shamma advises current PhD students Hassan Abdelraouf, Aya Hamed, and Nawaf Otaibi, with former advisees including Sarah Toonsi (2025) and Fat-hy Rajab (2025). His lab integrates theoretical research with applied projects like FalconScan, a UAV-crawler system for industrial inspection, and develops magnetic legs for curved surface UAV landing.

• Human Emotion
• Social Foundations of Emotions
• Emotional Self-Regulation
• +۳ مورد دیگر

W. Gerrod Parrott is a Professor in the Department of Psychology at Georgetown University's College. His research focuses on the nature of human emotion, including social foundations of emotions like guilt, shame, envy, and jealousy, emotional self-regulation, and historical/philosophical perspectives on emotion. He has authored four influential books and served as Editor of Cognition and Emotion (1995–1999) and President of the International Society for Research on Emotion (2008–2013). Currently, he is Editor-in-Chief of Emotion Review . Education : Ph.D. in Psychology from the University of Pennsylvania B.A. in Psychology from the University of Virginia Research Interests : Parrott explores how emotions function socially, culturally, and biologically. His work bridges psychology, sociology, and philosophy, emphasizing the role of emotion in moral judgment, interpersonal dynamics, and cultural expression. Recent studies include cross-cultural comparisons of shame, the impact of digital media on infant development, and the role of emotions in risk perception. Publications Trends : His recent articles highlight themes like moral emotions (guilt/shame), the evolution of emotion concepts across history, and the interplay between technology and emotional engagement. He critically examines cultural differences in emotional expression and their implications for psychology and policy. Editorial & Leadership Roles : Editor-in-Chief, Emotion Review Former Editor, Cognition and Emotion President, International Society for Research on Emotion Contributions to Field : Parrott’s work integrates empirical research with theoretical innovation, shaping debates on emotion’s role in cognition, morality, and culture. He advocates for interdisciplinary approaches to understanding emotion’s societal and individual impacts.

• Computer Learning
• Fuzzy Sets and Systems
• Decision Support Systems
• +۳ مورد دیگر

Prof. Sadettin Emre Alptekin is a full Professor of Industrial Engineering at Galatasaray University, Faculty of Engineering and Technology, where he also serves as Vice Dean. Since joining the university as a research assistant in 2000, he has steadily advanced through the academic ranks, becoming an Assistant Professor (2006–2010), Associate Professor (2010–2023), and finally Professor in 2023. Education: PhD (Dr), Industrial Engineering, Istanbul Technical University, Institute of Science and Technology, 2001–2006 MSc, Industrial Engineering, Galatasaray University, Faculty of Engineering and Technology, 1999–2001 BSc, Industrial Engineering, Istanbul Technical University, Faculty of Management, 1995–1999 Languages: Advanced English (C1), Upper-Intermediate French (B2), Advanced German (C1) Research Interests: Prof. Alptekin’s research focuses on Computer Learning , Fuzzy Sets and Systems , and Decision Support Systems . His work integrates artificial intelligence, machine learning, and soft-computing techniques to solve complex industrial and managerial problems in areas such as supply chain management, quality function deployment, blockchain adoption, and mental-health prediction. Publication Trends: Across more than 50 refereed publications, Prof. Alptekin has consistently explored hybrid intelligent models that combine fuzzy logic, machine learning, and multi-criteria decision-making. Recent articles emphasize deep-learning-based anomaly detection in industrial time-series data, blockchain adoption in supply chains, and machine-learning applications in subjective well-being and mental-health modeling. Scientific Awards & Honors: No specific awards or medals are listed in the provided documents. Research Leadership & Funding: Since 2008 he has been the principal investigator (executive) of 12 nationally funded projects, covering topics such as Industry 4.0 sub-system design, Internet of Things applications, artificial neural networks in organizational decision-making, big-data analytics, and strategic decision processes. Graduate Advising: He has formally supervised at least 8 master’s theses and numerous undergraduate projects. Representative thesis titles include Gaussian-process-regression-based man-hour prediction, machine-learning-driven human-behavior modeling, recommender-system design for e-commerce, thyroid-nodule diagnosis from scintigraphic images, software-effort estimation via neural networks, spreadsheet heuristics for joint-replenishment problems, cross-selling decision systems in insurance, and profitability analyses of Turkish banks under disinflation. Laboratories & Teams: While no dedicated laboratory name is disclosed, his continuous role as Vice Dean and principal investigator implies active leadership of the Industrial Engineering department’s research clusters in intelligent systems and decision support technologies.

Marcelo Mattarمشاهده پروفایل

استادیار

• Computational Neuroscience
• Decision-Making
• Reinforcement Learning
• +۳ مورد دیگر

Marcelo Mattar is an Assistant Professor of Psychology and Neural Science at New York University, leading the Mattar Lab. His research focuses on the neural computations underlying memory, decision-making, and reinforcement learning. He holds a Ph.D. in Psychology from the University of Pennsylvania and has held academic positions at NYU, UC San Diego, and postdoctoral roles at Princeton University and the University of Cambridge. His work bridges computational neuroscience and artificial intelligence, aiming to model how the brain uses internal models for planning and decision-making. Education: Ph.D. in Psychology (Computational and Cognitive Neuroscience), University of Pennsylvania, 2016 M.A. in Statistics, University of Pennsylvania, 2016 B.A. in Electronics Engineering, Instituto Tecnologico de Aeronautica, Brazil, 2010 Research Interests: The lab develops mathematical models of learning and decision-making, leveraging reinforcement learning, Bayesian statistics, and neural networks. Experiments involve human behavioral studies and neuroimaging, with collaborations in animal electrophysiology and computational psychiatry. Key Contributions: His work explores how episodic memory and hippocampal replay support flexible decision-making. Recent studies highlight parallels between human cognition and AI systems, such as language models' metacognitive abilities and brain-inspired algorithms. Awards: Newton International Fellowship, Royal Society (2018–2019) Lab Team: The lab includes postdocs, PhD students, and undergraduates from diverse fields like cognitive science, neuroscience, and computer science. Current members are listed on the lab's website. Lab Location: Meyer Hall, 6 Washington Place, New York, NY 10003.

Brad Knoxمشاهده پروفایل

دانشیار

• Reinforcement Learning
• Human-Computer Interaction
• Artificial Intelligence
• +۴ مورد دیگر

Brad Knox is a Research Associate Professor in the Department of Computer Science at the University of Texas at Austin . His work bridges machine learning, human-computer interaction, and computational cognitive science, with a focus on developing systems that learn from human feedback. Key research areas: Reinforcement Learning, Human-AI Interaction, Reward Design, Autonomous Systems Notable contributions: TAMER framework for human-guided learning, empirical studies on reward misdesign, and human preference modeling for autonomous agents Research Trends : His recent work (2023-2025) emphasizes reward alignment, safety in autonomous systems, and preference-based learning frameworks. Earlier studies (2012-2020) established foundational methods for integrating human feedback into reinforcement learning architectures and exploring behavioral signatures in decision-making. Scientific Honors : Bert Kay Dissertation Award (2013) Victor Lesser Distinguished Dissertation Award (IFAAMAS, Runner-up, 2013) NSF SBIR Grant (PI, 2016) NSF Graduate Research Fellowship (2008-2011) IEEE Intelligent Systems AI 10 to Watch (2013) Teaching & Leadership : Knox served as Principal Lecturer for MIT's Interactive Machine Learning course (2013) and held organizational roles at major conferences including Reinforcement Learning Conference (Scheduling Chair, 2025) and RLDM workshop (Co-chair, 2022).

Gunnar Blohmمشاهده پروفایل

استادیار

• Sensorimotor Neuroscience
• Clinical Medicine
• Neurology
• +۳ مورد دیگر

Gunnar Blohm is an Assistant Professor in the Department of Biomedical and Molecular Sciences at Queen's University, affiliated with the School of Medicine and Faculty of Health Sciences. His research focuses on sensorimotor neuroscience, particularly 3D sensorimotor control, eye-hand coordination, and computational modeling of neural processes. He holds a Ph.D. from Université Catholique de Louvain and has held postdoctoral positions at York University and his alma mater. Cross-appointed to the School of Computing, Department of Psychology, and Department of Mathematics and Statistics, he is also Vice-Director of the Connected Minds initiative. His research integrates behavioral experiments, brain imaging (MEG/EEG), and patient studies to understand how sensory information is transformed into goal-directed actions. Key areas include visuomotor transformations, multisensory integration, and Bayesian processes in neural computations. Blohm leads the Computational Sensorimotor Neuroscience Lab, emphasizing collaborative projects like Neuromatch Academy and contributions to open science initiatives. Affiliated with Queen's Centre for Neuroscience Studies and Ingenuity Labs, his work bridges computational approaches with clinical applications, aiming to develop frameworks for understanding brain dysfunction and clinical tools. His recent articles explore topics like saccade dynamics, pupil responses, and generative adversarial collaborations in scientific discourse.

Stephen Prattenمشاهده پروفایل

استاد

• Economics Methodology
• Social Ontology
• Critical Realism
• +۳ مورد دیگر

Stephen Pratten is a Professor of Economics and Philosophy at King's Business School, King's College London. He holds additional roles as co-editor of the Cambridge Journal of Economics and Research Associate at the Centre for Business Research (CBR). His research focuses on the methodology of economics, particularly social ontology and realist theorizing, alongside empirical studies on structural and regulatory changes in media industries. Education: PhD in Economics from the University of Cambridge Affiliations: King's College London (since 1999), CBR Research Fellow Research interests include critical realism, neoclassical economics, and the history of economic thought. He has contributed to interdisciplinary projects through the Social Ontology Research Unit, which explores social positioning theory and its applications. Recent work examines monetary theory, Deweyan pragmatism, and institutional analysis. His publications span over three decades, addressing topics from transaction cost economics to the philosophy of social institutions. He supervises PhD students and teaches on undergraduate and postgraduate programs, focusing on social science methodology and industrial organization. Despite no explicit awards listed, his extensive editorial roles and prolific publishing highlight his scholarly impact.

James W. Navaltaمشاهده پروفایل

دانشیار

• Exercise Physiology
• Outdoor Exercise Physiology
• Wearable Technology Validation
• +۳ مورد دیگر

Dr. James W. Navalta is an Associate Professor in the Department of Kinesiology and Nutrition Sciences at the University of Nevada, Las Vegas. His research focuses on physiological responses to outdoor exercise (hiking, trail running) and the validity/reliability of wearable technology. He earned his B.S. in Physical Education and Biology from Brigham Young University–Hawaii, M.S. in Kinesiology from UNLV, and Ph.D. in Exercise Physiology from Purdue University. Education: B.S. - Physical Education & Biology, Brigham Young University–Hawaii M.S. - Kinesiology, University of Nevada, Las Vegas Ph.D. - Exercise Physiology, Purdue University His research portfolio includes: Wearable technology validation for physiological measurements Comparative studies of indoor vs outdoor exercise environments Impact of gender-inclusive approaches on sports science Metabolic and cardiovascular responses to unconventional workouts Psychological benefits of nature immersion Recent publications demonstrate expertise in: Wearable device accuracy testing VO2max and lactate threshold validation Environmental influence on exercise physiology Methodological improvements in data collection Gender-inclusive research design Outdoor activity impact assessment As co-founder and executive editor of the International Journal of Exercise Science, he contributes significantly to academic discourse. He also serves on editorial boards for journals related to digital health and exercise technology.

Jagmohan S. Rajuمشاهده پروفایل

استاد

• Pricing
• Retailing
• Competitive Strategy
• +۷ مورد دیگر

Professor Jagmohan S. Raju serves as the Joseph J. Aresty Professor of Marketing at the University of Pennsylvania's Wharton School, where he also directs the Wharton Co-Sponsorship of the Indian School of Business. An internationally renowned pricing expert, he has taught extensively across Wharton's MBA, EMBA, and Executive Education programs and previously served as Vice Dean of Executive Education for six years. His academic credentials include a PhD in Business, MS in Operations Research, and MA in Economics from Stanford University, complemented by an MBA from the Indian Institute of Management Ahmedabad and a BTech in Electrical Engineering from the Indian Institute of Technology Delhi. Raju's research focuses on pricing strategy , retailing dynamics , and competitive positioning , with significant contributions to understanding private labels, coupon economics, and strategic channel management. His work bridges theoretical rigor with practical applications, frequently addressing real-world challenges in product launches and market competition through game-theoretic and empirical approaches. Recent publications reveal evolving expertise in digital-era retail challenges, particularly showrooming behavior, omnichannel competition, and the strategic implications of network neutrality. His scholarship consistently addresses the intersection of consumer psychology and corporate strategy across diverse sectors including pharmaceuticals, entertainment, and consumer goods. Fellow, INFORMS Society for Marketing Science (2017) Multiple Excellence in Teaching Awards (2012, 2011, 2009) Miller-Sherrerd MBA Core Course Teaching Award (2006) President of INFORMS Society for Marketing Science (2004) Marketing Professor of the Year at UCLA (1992) As an educator, Raju directs flagship executive programs including the General Management Program and Owner/President/CEO Program, while consulting for industry leaders like Johnson & Johnson, Medtronic, and Warner Home Video on pricing architecture and new product launches. His research grants and industry projects frequently examine category management dynamics and the strategic value of customer heterogeneity. He spearheads the Wharton-Indian School of Business partnership, fostering academic exchange and executive development initiatives that leverage his deep expertise in India's business landscape and global market dynamics.

Ka I Ipمشاهده پروفایل

استادیار

• Developmental neuroscience
• Emotion regulation
• Cross-cultural psychology
• +۸ مورد دیگر

Ka I Ip is an Assistant Professor at the Institute of Child Development , University of Minnesota. As director of the D.A.N.C.E. Lab , Dr. Ip employs multimodal methods including neuroimaging, cortisol assays, and cross-cultural experiments to study emotion regulation and developmental psychopathology. PhD in Developmental Psychology (University of Michigan) Susan Nolen-Hoeksema Postdoctoral Fellow (Yale University) Research focuses on how cultural contexts and early adversity shape emotional development, with particular attention to racial-ethnic minorities and immigrant families . His work applies findings to social policy reform and health equity initiatives. Recent publications analyze neighborhood socioeconomic impacts on brain development , discrimination effects in bilingual adolescents , and cortisol dynamics in immigrant families . Key journals include Biological Psychiatry and Developmental Psychology . APA Editor’s Choice Article (2024) Yale Health Equity Research Finalist (2022) Accepting PhD students for Fall 2026. Collaborates with teams in neuroimaging , cross-cultural research , and pediatric biomarker studies .

Matt Nassarمشاهده پروفایل

دانشیار

• Computational Neuroscience
• Cognitive Psychology
• Decision Making
• +۵ مورد دیگر

Matt Nassar is an Associate Professor of Neuroscience and Assistant Professor of Cognitive and Psychological Sciences at Brown University. He leads the Learning, Memory and Decision Lab, which is part of the Department of Neuroscience and the Robert J. & Nancy D. Carney Institute for Brain Science. His research focuses on understanding how the brain flexibly processes information to achieve complex and adaptive behaviors through computational approaches that bridge cognitive psychology and neuroscience. Education: PhD, University of Pennsylvania (2012) BA, Colgate University (2004) Nassar's research examines how different cognitive systems—learning, memory, and perception—leverage common computational principles to optimize decision-making. His work particularly focuses on how the brain balances stability and flexibility in processing information, how uncertainty is represented and utilized in learning, and how neural computations underlie complex behaviors. Through computational modeling and empirical research, he investigates how modular information-processing systems impact decisions and complex behavior in dynamic environments. His research integrates methods from cognitive psychology, neuroscience, and computational modeling to address fundamental questions about human cognition. Analysis of Nassar's recent publications (2020-2024) reveals a strong focus on computational neuroscience applied to decision-making, learning, and psychiatric conditions. His work frequently employs Bayesian modeling approaches to understand belief updating, uncertainty processing, and structure learning. Key themes include the neural basis of flexibility in learning, computational mechanisms underlying psychiatric symptoms, and age-related changes in cognitive processing. His research bridges cognitive psychology, neuroscience, and computational modeling to provide insights into both healthy cognition and disorders such as depression and schizophrenia. Scientific Contributions: Developed computational models of belief updating and learning under uncertainty Investigated neural mechanisms of stability-flexibility tradeoffs in cognition Examined age-related differences in learning and memory processes Explored computational mechanisms underlying psychiatric conditions Studied the role of noise correlations in neural learning systems Investigated how prefrontal cortex representations shape decision processes Nassar actively mentors researchers in his lab, with recent announcements highlighting postdocs joining from prestigious institutions like Max Planck UCL and Freie Universität Berlin. His lab appears to receive significant research funding, supporting multiple postdoctoral positions and research projects. Collaborations span multiple departments at Brown University, particularly with researchers in Cognitive and Psychological Sciences, Neurology, and Psychiatry. The lab has produced numerous high-impact publications in top journals including Nature Human Behaviour, Brain, and eLife. The Learning, Memory and Decision Lab, led by Nassar, is an active research group that uses computational models to understand how the brain represents and stores information for effective decision making. Recent lab announcements (as of February 2025) indicate the lab is expanding with new postdoctoral researchers joining from Harvard, Max Planck UCL, and Freie Universität Berlin, suggesting strong research momentum and funding support. The lab appears to be well-integrated within Brown's neuroscience community, with collaborations spanning multiple departments and research centers.

Yanli Linمشاهده پروفایل

استادیار

• Cognitive Neuroscience
• Mindfulness
• Emotion Regulation
• +۷ مورد دیگر

Yanli Lin is an Assistant Professor in the Department of Psychology within the College of Arts & Sciences at the University of Arkansas. She holds a Ph.D. in Clinical Psychology from Michigan State University and completed a postdoctoral fellowship in Cognitive Neuroscience at Washington University in St. Louis (2020–2024). Position: Assistant Professor Institution: University of Arkansas School: College of Arts & Sciences Department: Psychology Email: yanlil@uark.edu Her research focuses on understanding how mindfulness and contemplative practices influence attention, emotion regulation, cognition, and interpersonal behavior, with an emphasis on the mind-brain-behavior relationship. She employs cognitive neuroscience methods, including EEG and statistical modeling, to investigate neural and behavioral effects of meditation in both health promotion and clinical contexts. Her interdisciplinary approach integrates insights from psychology, neuroscience, philosophy, and religious studies. The recent publications highlight a consistent trend in studying distinct mindfulness states—particularly focused attention and open monitoring—on neural markers of emotion and cognitive control. Her work employs within-subject designs and advanced electrophysiological techniques to parse subtle differences in mindfulness-induced brain dynamics. These studies contribute to a growing understanding of how specific meditation practices can be precisely targeted for therapeutic applications. She has been recognized with several prestigious awards: NIH/NIA F32 National Research Service Award WUSTL McDonnell Center for Systems Neuroscience SGP Award Mind & Life Institute Francisco J. Varela Research Award Dr. Lin advises graduate students and leads a research laboratory focused on mindfulness and cognitive neuroscience. While specific grant details are not listed, her award history suggests active external funding. Her lab uses EEG and behavioral experimentation to explore how meditation shapes cognition and emotion, contributing to the scientific foundation for mindfulness-based interventions.

Kep Kee Lohمشاهده پروفایل

مربی ارشد

• Comparative primate neuroanatomy
• Sulcal anatomy
• Frontal cortex function
• +۴ مورد دیگر

Kep Kee Loh is a Senior Tutor in the Department of Psychology at the National University of Singapore (NUS). Currently, he also holds an NUS Overseas Postdoctoral Fellowship position at both the Montreal Neurological Institute (McGill University) and the University of Oxford. His research focuses on comparative primate neuroanatomy, examining what makes the human brain special compared to other primates through multimodal MRI techniques. Ph.D. in Neuroscience from Université Claude Bernard Lyon I (2014-2018) M.Sc. in Cognitive Neuroscience from University College London (2011-2012) B.Soc.Sci. (Hons.) in Psychology from National University of Singapore (2007-2011) Dr. Loh's research primarily investigates the anatomical organization of brains across humans and various primate species including chimpanzees, baboons, and macaques. He employs different magnetic resonance imaging techniques (anatomical, resting-state, diffusion-weighted MRI) to compare brain organization across species, with particular focus on the medial frontal cortex, sulcal anatomy, and the evolution of speech and language in the human brain. His work adopts a multimodal approach to provide an integrative view of what sets human brains apart from other primates. His recent publications demonstrate a strong focus on comparative neuroanatomy across species, with particular emphasis on primate brain evolution, frontal cortex organization, and language-related neural pathways. The research spans multiple disciplines including neuroscience, cognitive science, and evolutionary biology, with increasing attention to methodological advancements in neuroimaging techniques for cross-species comparisons. NUS Overseas Postdoctoral Fellowship (2021) Institute of Language, Communications and the Brain (ILCB) Postdoctoral Fellowship (2019) Fondation Recherche Médicale (FRM) Fin de Thèse (PhD funding) (2017) BRAIN Student Travel Award, 6th Motivation and Cognitive Control Symposium (2016) Dr. Loh has been involved in numerous collaborative research projects across international institutions, including the French Institute of Health and Medical Research (Stem Cell and Brain Research Institute), Aix-Marseille Université, and currently McGill University and the University of Oxford. His work has received significant recognition with over 1,000 citations for his 33 publications. While specific grant information isn't detailed in the provided text, his postdoctoral fellowships indicate successful competitive funding. Dr. Loh collaborates with several research groups including the Montreal Neurological Institute at McGill University and research teams at the University of Oxford. His work connects with broader initiatives like the collaborative resource platform for non-human primate neuroimaging, indicating participation in larger research networks focused on advancing primate neuroscience through shared resources and methodologies.