Thomas J. O’Dell is a Professor of Physiology and Associate Director of the Brain Research Institute at the University of California, Los Angeles (UCLA). His research focuses on synaptic plasticity mechanisms, particularly long-term potentiation (LTP) and depression (LTD), in the hippocampus. He investigates β-adrenergic signaling, NMDA receptor dynamics, and astrocyte calcium signaling in learning and memory processes. O’Dell’s work bridges molecular neurobiology with behavioral neuroscience, emphasizing how synaptic changes underlie cognitive functions. Research Interests: Neuronal plasticity mechanisms in hippocampal circuits Role of NMDA receptors in synaptic function and disease β-Adrenergic modulation of LTP Calcium signaling in astrocytes and its impact on synaptic transmission Grants & Funding: NIH R21MH115404 (Mechanisms of homeostatic plasticity) NIH R01NS060677 (Astrocyte calcium signaling in striatum) NIH R01MH060919 (NMDA receptor signaling in LTP) Labs/Teams: O’Dell leads a lab at the UCLA Brain Research Institute, collaborating on projects involving synaptic physiology, proteomics, and behavioral neuroscience.
Arslan Mazitov is a Researcher and Doctoral Assistant at the École Polytechnique Fédérale de Lausanne (EPFL) , affiliated with the School of Engineering (STI) and the Institute of Materials (IMX) . He is part of the Computational Science and Modelling Laboratory (COSMO) , focusing on computational materials science with an emphasis on van der Waals materials, optical properties, and machine learning applications. His research explores novel materials for photonics, energy storage, and nanotechnology. Mazitov's work bridges theory and experiment, employing advanced modeling techniques to predict material behavior and design innovative solutions. Key research areas include van der Waals heterostructures , optical anisotropy engineering , and AI-driven materials discovery . He has contributed to studies on semiconductors, 2D materials, and interfacial phenomena. His computational methods address challenges in predicting material stability, optical properties, and surface behavior under various conditions. Active in collaborative projects, Mazitov's work has practical implications for photonic devices, energy storage systems, and nanoscale engineering. His research emphasizes interdisciplinary approaches, combining computational modeling with experimental validation to advance material innovation.
Dr. Annemieke Apergis-Schoute is a Lecturer in Psychology (Teaching and Research) at Queen Mary University of London, affiliated with the School of Biological and Behavioural Sciences and the Centre for Brain and Behaviour. Her research focuses on obsessive-compulsive disorder (OCD), cognitive flexibility, prefrontal mechanisms, and student mental health. She holds a PhD from New York University, where her early work explored threat learning in rats and humans using fMRI. Subsequent roles at the University of Cambridge and UCL expanded her expertise into clinical OCD studies, including deep brain stimulation trials. Her research investigates how prefrontal control deficits and inflexible learning contribute to OCD and related disorders, with a focus on adolescents and young adults. Collaborations include pioneering DBS studies targeting basal ganglia regions to reduce compulsive behaviors. She also explores connections between brain function, interoception, and mental health in daily decision-making contexts. Key publications analyze reversal learning deficits in OCD under serotonergic modulation, neuroimaging markers of cognitive rigidity, and developmental trajectories of compulsivity. Her work bridges basic neuroscience with translational clinical interventions, emphasizing early intervention strategies and cognitive-behavioral approaches.
Professor Rodrigo Freitas holds the TDK Professorship in Materials Science and Engineering at MIT. His research focuses on computational materials design, bridging atomistic simulations with mesoscale microstructural analysis. He leads the Freitas Research Group, specializing in machine learning-driven modeling of materials kinetics and solidification processes. Education: B.S. and M.S. in Physics, University of Campinas, Brazil M.S. and Ph.D. in Materials Science & Engineering, UC Berkeley Research Interests: Professor Freitas investigates microstructural evolution in metals and alloys using advanced computational methods. Key areas include solidification mechanisms, interstitial atom behavior in superalloys, and machine learning applications for materials discovery. His work emphasizes bridging atomistic and mesoscale phenomena to guide industrial applications like semiconductor manufacturing and battery design. Publications Trend: Recent work emphasizes machine learning potentials for alloy modeling, short-range order analysis in high-entropy alloys, and kinetic modeling of complex chemical systems. Themes include alloy phase stability, defect dynamics, and data-driven materials discovery. Labs/Teams: Leads the Freitas Research Group at MIT, which develops novel computational tools for materials engineering.
Ram Samudrala is a Professor and Chief of the Division of Bioinformatics at the University at Buffalo Jacobs School of Medicine and Biomedical Sciences . His research focuses on multiscale computational biology , integrating protein structure prediction , drug discovery , and translational science to address medical challenges. He leads the development of the CANDO platform for therapeutic drug discovery and co-directs the Informatics Core at the Clinical and Translational Sciences Institute. PhD in Computational Biology (University of Maryland, 1997) BA in Computing Science and Genetics (Ohio Wesleyan University, 1993) Postdoctoral Fellowship in Protein Folding (Stanford University, 1997-2001) His work spans structural biology , genomics , and computational drug design , with applications in dentistry , infectious diseases , and cancer . He has received prestigious awards including the NIH Director's Pioneer Award (2010) and multiple Wiki Science Prizes . Samudrala's group collaborates globally, emphasizing in silico methods followed by in vitro and in vivo validation. Key grants include $1.22M NIH NCATS ASPIRE Reduction-to-Practice Award and $4.5M NIH/NLM BRIGHT Training Grant . 2023 Finalist, Clinical and Translational Sciences Institute Clinical Research Achievement Awards 2016 MacArthur Foundation 100&Change Top 50 2008 Alberta Heritage Foundation Visiting Scientist Award 2005 NSF CAREER Award He directs the BRIGHT Short-Term Training Program and serves on multiple editorial boards and review panels. Samudrala's group maintains a Protinfo web server for structural predictions and the Bioverse framework for systems-level analyses.
Silvia Arber holds a joint appointment as Full Professor for Neurobiology/Cell Biology at the Biozentrum, University of Basel, and serves as Senior Group Leader at the Friedrich Miescher Institute (FMI) in Basel, Switzerland. Her laboratory investigates the organization, function, and development of neuronal circuits controlling motor behavior, with a particular focus on how these circuits enable precise movement control. Arber obtained her PhD in 1996 from the Friedrich Miescher Institute under Pico Caroni, followed by postdoctoral training with Thomas Jessell at Columbia University (1996-2000), where she studied transcription factors in spinal cord neuronal differentiation. Her educational background includes Biology II studies at the Biozentrum of the University of Basel with graduation in Cell Biology (1987), a diploma thesis at the FMI (1990), and graduate work at the FMI (1992). Her research program centers on elucidating how neuronal circuits orchestrate accurate motor behavior in response to sensory cues and voluntary movement initiation. Using mouse as a model system, her laboratory employs multi-faceted approaches including advanced mouse genetics, viral technologies for transsynaptic circuit tracing, optogenetics and pharmacogenetics for functional manipulation, quantitative behavioral analysis, electrophysiology, and gene expression profiling. Her work has revealed precise synaptic interactions within dedicated motor circuit modules throughout the nervous system and how these impact function, with implications for understanding diseases causing motor deficits and spinal cord injury. Analysis of Arber's publication record shows a consistent focus on motor circuit organization, with particular emphasis on transcriptional control mechanisms, circuit connectivity mapping, and the relationship between developmental processes and functional circuit organization. Her work bridges molecular, cellular, and systems neuroscience, providing fundamental insights into how the nervous system controls movement. The Brain Prize (2022) Elected to the National Academy of Sciences of the United States (2020) Physiological Society Annual Review Prize Lecture (2019) Pradel Research Award (2018) W. Alden Spencer Award (2018) Louis-Jeantet Prize for Medicine (2017) ERC Advanced Grant (2010-2015) EMBO Member (2005) EMBO Young Investigator Award (2001) While specific students are not listed in the provided materials, Arber's laboratory has received significant research funding including an ERC Advanced Grant (2010-2015) and multiple prestigious awards supporting her research program. Her laboratory at the Biozentrum (Room 11.038) collaborates closely with the Friedrich Miescher Institute, where she serves as Senior Group Leader. The research group employs cutting-edge technologies for neural circuit analysis and has contributed fundamental insights into motor circuit organization, with implications for understanding and potentially treating movement disorders and spinal cord injuries.
Magnus Richardson is a Professor at the University of Warwick, affiliated with the Mathematics for Real-World Systems Centre for Doctoral Training (CDT), where he previously served as Director (2016–2020) and currently acts as Deputy Director. His research focuses on theoretical neuroscience, mathematical modeling of neural systems, and neurodegenerative diseases. He has led significant grants, including the UKRI-funded £5M renewal for the CDT, extending its operations until 2028. Richardson has supervised numerous doctoral students, including Alice Wang, Ivana Del Popolo, and alumni such as Dr. Emily Hill and Dr. Robert Gowers. His work bridges computational neuroscience and experimental biology, investigating topics like synaptic plasticity, adenosine signaling, and the impact of protein aggregates (e.g., tau, α-synuclein) on neuronal function. Richardson’s teaching includes modules on mathematical biology and machine learning. His GitHub repositories reflect his computational contributions, including neural modeling frameworks for integrate-and-fire neurons. Key research themes include understanding how synaptic inputs and neuromodulators influence neuronal dynamics, and developing mathematical tools to analyze neural systems under pathological conditions. Richardson’s grants and collaborations highlight his role in advancing interdisciplinary research at the intersection of mathematics, neuroscience, and computational biology.
Prof. Thomas Kuner is a Professor and Director of the Department of Functional Neuroanatomy at the University of Heidelberg's Medical Faculty. He holds a medical degree (MD) from Heidelberg (1998) and completed postdoctoral work at Duke University and the Marine Biological Laboratory. Since 2000, he has led a research group at the Max Planck Institute for Medical Research, followed by habilitation in Physiology (2003) and appointment as Professor of Anatomy and Cell Biology (2006). Research Focus: His work focuses on neuroanatomy, synaptic transmission mechanisms, and pain research. Key projects include investigations into the structural and functional properties of synapses (e.g., calyx of Held), the role of presynaptic proteins like Mover, and the molecular basis of pain signaling via the SFB 1158 consortium. His lab uses advanced imaging techniques (e.g., STED microscopy) and genetic models to study neuronal circuits and synaptic plasticity. Funding & Collaborations: Kuner's research is supported by grants from the DFG (e.g., SFB 1158), the Baden-Württemberg Foundation, and other national/international bodies. His interdisciplinary approach bridges cellular neuroscience, molecular biology, and clinical applications in pain management. Teaching & Leadership: He oversees the Institute of Anatomy and Cell Biology, contributing to graduate programs in medical education and anatomy. His team includes postdocs and technicians, with collaborations extending to imaging technology development and medical education innovation.
Professor Thierry Langer is a Full Professor of Pharmaceutical Chemistry at the University of Vienna’s Faculty of Life Sciences (Department of Pharmaceutical Sciences). He leads research in computational drug design, with a focus on pharmacophore modeling, 3D-QSAR analysis, and AI-driven molecular design. His work bridges theoretical and experimental chemistry, addressing targets like viral proteases (e.g., SARS-CoV-2), GABA receptors, and dopamine transporters. Research interests include: Pharmacophore-guided drug discovery for anti-viral and CNS therapies Development of next-generation computational tools (e.g., PharmacoMatch, QPhAR) Protein-ligand interaction modeling using neural networks and graph-based algorithms Recent studies focus on: Inhibitors for herpesvirus nuclear egress complexes, AI-optimized antivirals, and dopamine transporter inhibitors for cognitive enhancement. His lab collaborates on projects like the NeuroDeRisk initiative to de-risk neurotoxic compounds. Publications emphasize drug repurposing, metabolic pathway analysis, and scalable synthesis methods for promising drug candidates.
Prof. Dr. Ahmet ÖZMEN is a Professor at Sakarya University's Faculty of Computer and Information Sciences, Department of Software Engineering. He has held various administrative positions including Head of the Software Engineering Department (2019-2028) and Director of the Computer Research and Application Center (2019-2022). With extensive experience in academia since 1991, he has made significant contributions to computer vision, traffic monitoring systems, and sensor technologies. Sakarya University: Professor (2019-present), Associate Professor (2011-2019) Dumlupınar University: Assistant Professor (2001-2011), Research Assistant (2000-2001, 1993-1998) Istanbul Technical University: Research Assistant (1991-1993) Prof. ÖZMEN's research spans computer vision applications for traffic monitoring, indoor air quality systems, parallel computing, and sensor technologies. His work bridges theoretical computer science with practical engineering applications, particularly in developing vision-based systems for nighttime vehicle detection, traffic flow monitoring, and environmental sensing. His interdisciplinary approach combines machine learning, image processing, and embedded systems to solve real-world problems in transportation and environmental monitoring. His publication record shows a clear evolution from parallel and distributed systems in his early career to computer vision and sensor applications in recent years. The majority of his recent work focuses on traffic monitoring systems using computer vision techniques, particularly for nighttime conditions, and indoor air quality monitoring systems using sensor networks. His research demonstrates strong industry and societal relevance, with applications in smart transportation, environmental protection, and educational technology. TÜBİTAK Publication Awards (2006, 2008, 2009, 2010) Physical implementation award from TÜBİDER (2008) Microsoft Certified Professional Certificate (2005) YÖK overseas study scholarships (1993, 1998) Elginkan graduate scholarships (1990, 1991) Prof. ÖZMEN has supervised numerous graduate students across multiple institutions, with a focus on practical engineering problems. His research has been supported by various projects including TÜBİTAK projects, institutional research grants, and industry collaborations. He has led significant research initiatives in traffic monitoring systems, indoor air quality monitoring, and educational technology platforms. His administrative leadership has included directing research centers and shaping curriculum development in software engineering. His work has involved establishing research teams focused on computer vision applications, sensor network development, and educational technology. These teams have produced numerous publications, developed practical systems, and trained the next generation of computer engineers. Current research directions include advanced traffic monitoring systems using deep learning and multi-camera setups for urban planning applications.
Richard Futrell is an Associate Professor at the University of California, Irvine (UCI), affiliated with the Department of Language Science. He leads the Language Processing Group, focusing on computational models of human and machine language processing. His work bridges information theory, Bayesian cognitive modeling, and natural language processing (NLP) interpretability. University of California, Irvine Department of Language Science Language Processing Group leader His research examines how linguistic structures emerge from cognitive and communicative pressures. Key areas include dependency locality, surprisal theory in sentence processing, and efficiency-driven language evolution. He investigates how memory constraints, predictability, and information density shape syntactic and morphological patterns across languages. Recent publications analyze code-switching efficiency, syntactic priming, ERP component modeling, and agent-based language contact simulations. His work frequently employs Bayesian modeling, neural network analysis, and cross-linguistic corpora to uncover universal principles in language processing. ACL Best Paper Award (2024) Best Paper Award for Computational Modeling of Language (2023) Marr Prize for Best Student Paper (2017) He has developed datasets like SPACER for error repair analysis and contributed to phonotactic learning frameworks. His collaborations span cognitive scientists, computational linguists, and neuroscientists, advancing understanding of language production, comprehension, and structural optimization.
Ziming Zhang is an Assistant Professor in the Department of Electrical and Computer Engineering at Worcester Polytechnic Institute (WPI) , with additional affiliations in Data Science and Robotics Engineering. He previously held research roles at Mitsubishi Electric Research Laboratories (MERL) and Boston University. PhD in Computing (2013) from Oxford Brookes University , UK MS in Computing Science (2010) from Simon Fraser University , CA BS in Computer Science and Technology (2005) from Northeastern University , China Research interests span computer vision , machine learning , and their applications in point cloud processing , medical imaging , autonomous driving , and IoT . He leads the Vision, Intelligence, and System Laboratory (VISLab) at WPI. Recent publications focus on 3D reconstruction , hyperbolic learning , and robust classifiers . Awards include the R&D100 Award 2018 and NSF funding for data-efficient deep learning. PhD Students: Yecheng Lyu (co-supervised), Guojun Wu (co-supervised), Hangrui Zhang, Xuechu Yu Master's Students: Yun Yue, Yuping Shao Visiting Scholars: Fangzhou Lin His lab partners with industry and academic institutions, focusing on autonomous systems , robotics , and scientific imaging projects.
Mathias Benedek is an Associate Professor at the Institute of Psychology, Faculty of Natural Sciences, University of Graz, Austria. He directs the Creative Cognition Lab and is actively involved in several research networks, including the "Complexity of Life" profile area, the "Brain and Behavior" research network, and the "FUTURE EDUCATION" research network at the University of Graz. His research focuses on the cognitive and neural mechanisms underlying creative thinking, with particular emphasis on the role of memory processes, metacognition, and eye movement patterns during creative ideation. Dr. Benedek's work bridges psychological theory with empirical research methods including eye tracking, neuroimaging, and computational modeling of creative processes. His research has important implications for understanding how creative potential develops and how it can be assessed and nurtured in educational and professional contexts. Dr. Benedek's publication record demonstrates a consistent focus on creative cognition across multiple dimensions. His recent work has expanded into emerging areas such as human-AI collaboration for creative tasks, automated assessment of creativity using large language models, and the relationship between physical activity and creative performance. His research shows a strong trajectory toward more ecologically valid methods for studying creativity in real-world contexts, moving beyond traditional laboratory paradigms. Seraphine Puchleitner Anerkennungspreis (PhD Supervision Award), University of Graz, 2021 William-Stern-Preis, German Psychological Society, 2019 Research Prize, University of Graz, 2017 Research Prize (Publication Category), Initiative Gehirnforschung, 2016 Berlyne Award, Division 10, American Psychological Association, 2015 Dr. Benedek has demonstrated strong commitment to mentoring the next generation of researchers, as evidenced by his 2021 PhD Supervision Award. His research has been supported by multiple grants from national and international funding bodies, though specific grant details are not provided in the available information. His professional service includes leadership roles in the Initiative Gehirnforschung Steiermark since 2010 and active membership in several psychological societies across Europe and North America. Dr. Benedek leads the Creative Cognition Lab at the University of Graz, which employs a multidisciplinary approach to studying creative processes. The lab integrates methods from cognitive psychology, neuroscience, and computational modeling to investigate the mechanisms underlying creative thought. Current research projects examine the relationship between eye movements and internal cognitive processes, the development of automated assessment tools for creativity, and the application of creativity research to educational contexts.
Prof. Dr. Axel Mecklinger is a leading cognitive neuroscientist at Saarland University , specializing in the neurocognition of memory and language through spatiotemporal brain imaging (EEG/MEG/fMRI). His career spans over three decades, with significant contributions to understanding visual working memory , associative recognition , and memory development . Key research areas: Memory binding, ERP subsequent memory effects, novelty detection, and cognitive aging Major grants: DFG Research Groups, Collaborative Research Centers, and international collaborations with the Chinese Academy of Sciences Scientific leadership: Organized conferences, edited journals, and served as speaker for research training groups His recent work explores unitization in memory formation , cross-cultural differences in memory processing , and theta neurofeedback interventions . Awards include the Early Career Award of the German Psychophysiology Society (1992) and the European Federation of Psychophysiology Societies' Federation Prize (1994). Current projects investigate the neural mechanisms of semantic surprisal and memory plasticity in aging populations.
Md Sakib Hasan is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Mississippi. He holds a Ph.D. in Electrical Engineering from the University of Tennessee-Knoxville (2017). His research focuses on hardware acceleration, neuromorphic computing, and memristor-based systems. Research interests span: AI hardware accelerators and energy-efficient computing Biomimetic systems and bio-inspired electronics Hardware security through chaotic systems and PUFs Recent publications demonstrate strong emphasis on: Neuromorphic architectures for computer vision and temporal processing Biomembrane-based computing systems Chaotic cryptography and secure hardware design
