Find Academic Supervisors

• Biostatistics
• Neuroimaging Analysis
• Causal Inference
• +3 more

Brian Caffo is a Professor in the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, with an active research profile evidenced by 2024-2025 publications and GitHub contributions. He is a key contributor to Neuroconductor (an R platform for medical imaging analysis) and the Acute to Chronic Pain Signatures (A2CPS) project, while maintaining significant educational impact through Coursera data science courses and open-source textbooks. His research spans biostatistics, neuroimaging analysis, and causal inference methodology, with emphasis on functional MRI data, multi-omics integration, and machine learning applications in public health. Current work focuses on advanced neural architectures for brain imaging, causal mediation in autism research, and biomarker discovery for chronic pain and neurodegenerative diseases. Analysis of his 15 most recent publications reveals dominant themes in transformer-based neuroimaging analysis (28%), causal inference applications (27%), and multi-omics/pain signature research (20%). His work consistently bridges statistical methodology with clinical applications in HIV prevention, autism spectrum disorders, and long COVID prediction through large collaborative projects like the National COVID Cohort Collaborative. Dr. Caffo leads the JHU Data Science Lab and contributes to multiple interdisciplinary initiatives including shell MEA development for neural organoids and DREAM-02 HIV microbicide trials. His GitHub profile shows active maintenance of educational repositories like LittleInferenceBook and regmodsbook, supporting widespread adoption of data science methods in biomedical research.

• Brain-Computer Interfaces
• Speech Neuroprosthetics
• Neural Decoding
• +3 more

David Moses is an Assistant Professor in the Department of Neurological Surgery at the University of California, San Francisco (UCSF) School of Medicine. His research focuses on developing advanced brain-computer interfaces (BCIs) and speech neuroprostheses to restore communication in individuals with paralysis or speech impairments. Moses works at the intersection of neuroscience, biomedical engineering, and artificial intelligence, utilizing cortical activity mapping to create real-time decoding systems. Research Areas: Brain-Computer Interfaces Speech Neuroprosthetics Neural Signal Decoding Artificial Intelligence in Medicine Cortical Activity Analysis Cognitive Neuroscience Publication Trends: Moses' recent work (2024-2025) emphasizes streaming brain-to-voice neuroprostheses, bilingual speech decoding, and user agency in neuroprosthetic design. Earlier publications (2016-2022) established foundational methods for continuous phoneme decoding, real-time dialogue systems, and AI-driven cortical signal translation. Key Collaborations: Moses frequently collaborates with Edward Chang (UCSF), Gopala Anumanchipalli (UCSF), Karunesh Ganguly (UCSF), and Adelyn Tu-Chan (UCSF) on high-impact neuroprosthetic research. His work is cited extensively in medical and neuroscience literature, with significant social media and policy influence.

Javier Villalba-DiezView profile

Professor

• Artificial Intelligence
• Deep Learning
• Hoshin Kanri
• +4 more

Professor Javier Villalba-Diez serves at the Faculty of Business of Heilbronn University of Applied Sciences, Germany, where he integrates artificial intelligence with lean management principles in industrial and business contexts. His international collaborations include a cooperative doctoral program with Technical University of Madrid and Erasmus exchanges with Universidad Politécnica de Madrid. Dr. Villalba-Diez earned dual engineering degrees: Mechanical Engineering from Technische Universität München and Industrial Engineering from Universidad Politécnica de Madrid (2003). His PhD in Engineering, Economics and Organizational Innovation (2016) from Universidad Politécnica de Madrid received the institution's best doctoral thesis award. His research spans Artificial Intelligence (particularly Deep Learning applications), Hoshin Kanri strategic planning, Business Intelligence , and Lean Manufacturing . He pioneers sensor-based methodologies for organizational design, using EEG and industrial IoT to analyze problem-solving patterns and network resilience. His work bridges theoretical models with practical implementations across German, American, Japanese, and Spanish manufacturing facilities. Recent publications demonstrate a clear trajectory toward Industry 4.0 integration , with 60% of his 2019-2020 work focusing on deep learning applications in quality control, sensor networks, and cyber-physical systems. The journal Sensors (MDPI) serves as his primary publication venue, reflecting his emphasis on data-driven industrial analytics. His recognition includes: Prize for best doctoral thesis by Universidad Politécnica de Madrid (2016) As Guest Editor for Sensors and reviewer for journals like Sustainability and Journal of Manufacturing Systems , he shapes discourse in industrial AI. His doctoral supervision with Madrid focuses on AI-driven strategic organizational design, while industry collaborations with manufacturing facilities worldwide translate research into operational frameworks. He maintains active roles in curriculum development for Industry 4.0 education through the PROFH4 digital initiative. Dr. Villalba-Diez operates within international research networks, leveraging his multilingual capabilities (German, English, Spanish) to facilitate transnational projects. His work with Neo4j for Hoshin Kanri visualization exemplifies his approach to making complex organizational networks actionable for industry leaders.

Michael R. HaydenView profile

Professor

• Genetic Medicine
• Huntington Disease
• Neurodegenerative Disorders
• +7 more

Dr. Michael R. Hayden is a University Killam Professor in the Department of Medical Genetics at the University of British Columbia's Faculty of Medicine. He serves as a Senior Scientist at the Centre for Molecular Medicine and Therapeutics/BC Children's Hospital Research Institute and directs the Centre for Huntington Disease. His research spans multiple prestigious institutions including BC Children's Hospital Research Institute, BC Diabetes Research Network, and Centre for Brain Health. Dr. Hayden's research focuses on genetic medicine, particularly Huntington disease, neurodegenerative disorders, and gene therapy. His laboratory investigates silencing the mutant huntingtin gene, modulating huntingtin post-translational modifications, discovering novel neuroprotective targets, and studying population genetics of Huntington disease mutations. Additionally, his work extends to lipoprotein lipase deficiency gene therapy development. His research philosophy emphasizes that 'sick people depend on us and others for new therapies,' driving his team's commitment to developing treatments that can slow or reverse disease progression. Analysis of Dr. Hayden's recent publications reveals a strong focus on Huntington disease therapeutics, particularly gene silencing approaches and biomarker development. His work spans basic molecular mechanisms to clinical applications, with increasing emphasis on translational research that bridges laboratory findings to patient treatments. The publications demonstrate a multidisciplinary approach combining genetics, neuroscience, and molecular pharmacology to address neurodegenerative conditions. Doctor of Science in Medicine (DSc(Med)) (honoris causa), University of Cape Town, South Africa (2024) Best Scientist in the World, Ranked #860 & Best Scientist in Canada, Ranked #19 Award by Research.com (2023) Lifetime Achievement Award, Huntington Study Group, USA (2023) Induction to the Canadian Medical Hall of Fame (2017) Order of Canada (2010) Killam Prize, Canada Council of the Arts (2011) Dr. Hayden has trained over 86 postdoctoral fellows and 45 graduate students, with nearly all holding competitive funding and winning prestigious awards. His lab provides exceptional resources through over 100 collaborations with world-class investigators and industrial partners. Trainees benefit from sophisticated laboratory facilities, administrative support, and access to seminars and workshops hosted by multiple research institutions. His mentorship philosophy emphasizes communication skills, critical thinking, and preparing trainees for future research leadership. The Hayden Lab operates within the Centre for Molecular Medicine and Therapeutics at BC Children's Hospital Research Institute, providing access to advanced facilities including the Bioinformatics Assistance Centre, Huntington Disease BioBank, Imaging Core Facility, and specialized mouse research resources. The lab maintains strong connections with the Centre for Brain Health and other UBC research networks, creating a collaborative environment focused on translating genetic discoveries into therapeutic interventions for neurodegenerative and metabolic diseases.

Topun AustinView profile

Professor

• Neonatal cerebrovascular physiology
• Neonatal brain imaging
• Diffuse optical tomography
• +4 more

Topun Austin is a Consultant Neonatologist at Cambridge University Hospitals NHS Foundation Trust and holds the title of Honorary Professor in the Department of Medical Physics and Biomedical Engineering at University College London (UCL). Since 2008 he has led neonatal neurocritical care services in Cambridge, secured over £3 million in competitive research funding, and established the Evelyn Perinatal Imaging Centre at the Rosie Hospital. Education & Clinical Training Medical degree and specialist training leading to accreditation as a Consultant Neonatologist (details not specified in text). Research Interests Professor Austin’s work centres on three interconnected themes: Cerebrovascular physiology in preterm infants – developing novel autoregulation markers and exploring cardiac–cerebrovascular coupling. Brain function & behaviour – leading neoLAB , an interdisciplinary Cambridge–UCL collaboration using optical and EEG systems to study functional brain development in healthy and sick newborns. Neonatal neurocritical care translation – integrating research findings into award-winning regional neuroprotection services in the East of England. Research Funding & Awards His programme has been supported by major funders including the Bill & Melinda Gates Foundation, Medical Research Council, Engineering and Physical Sciences Research Council, Health Foundation, Evelyn Trust, Rosetrees Trust and British Academy/Leverhulme Trust, among others. Collaborative Networks & Infrastructure Local collaborations span Cambridge’s Department of Neurosurgery (Prof Marek Czosnyka), Autism Research Centre (Prof Simon Baron-Cohen), Department of Psychiatry (Prof John Suckling) and Department of Psychology (Dr Vicky Leong). National and international partners include UCL’s Department of Medical Physics & Biomedical Engineering (Profs Jem Hebden & Clare Elwell), Birkbeck Centre for Brain and Cognitive Development (Prof Mark Johnson, Dr Sarah Lloyd-Fox) and the Department of Neonatology, University of Copenhagen (Prof Gorm Greisen).

Onur GüntürkünView profile

Professor

• Cognitive Neuroscience
• Comparative Cognition
• Avian Cognition
• +5 more

Onur Güntürkün serves as Professor for Psychology at Ruhr University Bochum and holds a Permanent Fellowship at the Wissenschaftskolleg zu Berlin (Institute for Advanced Study). His academic career spans decades of pioneering research in comparative cognition, with a focus on evolutionary parallels between avian and mammalian cognitive systems. As a Permanent Fellow, he leads the "One Cognition" project investigating convergent evolution of cognitive abilities across species with vastly different neuroanatomies. Academic Background: Diploma in Psychology, Ruhr University Bochum Dr. phil. in Psychology, Ruhr University Bochum Güntürkün's research centers on the paradox of equivalent cognitive abilities emerging from radically different neural architectures—specifically how birds with tiny brains (3-25g) and no neocortex achieve cognitive feats matching chimpanzees. His work demonstrates that corvids and parrots exhibit identical cognitive capabilities to primates in working memory, problem-solving, and social cognition. He investigates whether algorithmic constraints or neural implementation bottlenecks drive this convergence, using working memory as a model system due to its well-defined parameters across species. His experimental approach integrates behavioral studies with neural circuit analysis to uncover universal principles of cognitive evolution. Analysis of his publication history reveals a consistent trajectory from foundational neuroanatomical studies toward theoretical frameworks for cognitive convergence. The most recent works (2021-2024) emphasize circuit-level homologies between avian pallium and mammalian neocortex, while earlier publications established birds as valid models for complex cognition. Key thematic clusters include neural lateralization mechanisms, sensory modality effects on cognition, and evolutionary constraints on information processing. His 2024 Trends in Cognitive Sciences paper synthesizes two decades of evidence showing birds solve mental problems using cognitive mechanisms nearly identical to mammals despite 300 million years of divergent evolution. Professional Recognition: Honorary Doctorate (Dr. h.c.) Güntürkün actively contributes to scientific discourse through invited colloquia, including an upcoming presentation at Wiko on November 25, 2025. While specific grant details aren't documented in the source material, his sustained research output and leadership in major projects indicate significant funding acquisition. His work bridges neuroscience, evolutionary biology, and cognitive psychology, fostering interdisciplinary collaborations evident in co-authored publications with researchers from diverse fields. As Principal Investigator of the "One Cognition" project, Güntürkün directs a research initiative examining why evolution repeatedly produces similar cognitive solutions across phylogenetically distant species. This work involves comparative analysis of neural circuits across avian and mammalian models, with particular focus on working memory constraints and neural implementation strategies. His laboratory at Ruhr University Bochum collaborates with international teams studying bird cognition, contributing to the growing paradigm shift recognizing avian intelligence as a powerful model for understanding universal cognitive principles.

Andrea VinciView profile

Researcher

• Quantum Computing
• Edge-Cloud Computing
• Internet of Things (IoT)
• +5 more

Andrea Vinci is an accomplished researcher with 66 publications and 1,261 citations, specializing in the intersection of quantum computing, edge-cloud architectures, and Internet of Things (IoT) systems. His work demonstrates significant contributions to solving complex computational problems through innovative approaches that bridge theoretical quantum algorithms with practical distributed computing applications. His research interests span quantum computing applications for resource management, multi-density clustering techniques for urban analytics, and platform-independent IoT application development. Vinci has pioneered work in variational quantum algorithms for cloud/edge resource allocation, quantum kernels for IoT data classification, and distributed AI for cognitive building systems. His research demonstrates a consistent focus on addressing NP-hard problems through quantum-classical hybrid approaches. Analysis of Vinci's publication trends reveals a strategic research trajectory moving from foundational work in smart city analytics and crime prediction toward cutting-edge quantum computing applications for IoT and edge-cloud systems. His recent publications (2023-2025) show increasing focus on quantum machine learning techniques specifically tailored for IoT data processing, with significant attention to practical implementation challenges. Vinci maintains an extensive collaborative network, frequently publishing with researchers including Fabrizio Marozzo, C. Mastroianni, J. Settino, and Antonio Guerrieri across multiple high-impact venues including IEEE Transactions, ACM conferences, and specialized journals in quantum computing and distributed systems. His technical contributions include the development of the COGITO platform for cognitive buildings, novel approaches to multi-density crime prediction, and significant advancements in quantum kernel methods for IoT data analysis. Vinci's tutorial publications indicate his role in educating the broader research community about emerging quantum computing applications for distributed systems.

Daniel BoleyView profile

Professor

• Numerical Linear Algebra
• Data Mining
• Machine Learning
• +5 more

Daniel Boley is a Professor and Distinguished University Teaching Professor at the University of Minnesota, within the College of Science and Engineering, Department of Computer Science and Engineering. He serves as the Director of Graduate Studies for the Graduate Program in Data Science, which offers a Master's of Science and a Post-Baccalaureate Certificate. His office is located in Kenneth H. Keller Hall at 4-225C. Professor Boley's research spans computational methods in linear algebra, scalable data mining algorithms, and applications in systems biology and bioinformatics. His work focuses on scalable algorithms for convex optimization in machine learning, analysis of networks and graphs from metabolic biochemical networks, and wireless device networks. He has made significant contributions to numerical linear algebra methods for control problems, parallel algorithms, and iterative methods for matrix eigenproblems. His research interests also include algebraic models in systems and evolutionary biology, and biochemical metabolic networks. His recent publications demonstrate a strong focus on applying graph theory and network analysis to diverse domains including robot swarms, medical imaging (particularly for glioblastoma and COVID-19 diagnosis), and metabolic network analysis. His work bridges theoretical computer science with practical applications in biology and medicine, with a consistent emphasis on developing scalable computational methods. The trend shows increasing interdisciplinary collaboration, particularly with medical researchers. Distinguished Member by the ACM Top university award for post baccalaureate, graduate and professional education Distinguished University Teaching Professor title Professor Boley has advised numerous PhD students including Tatiana Lenskaia (2021), Shaozhe Tao (2018), Ham Ching Lam (2014), and others dating back to 1994. His research has been supported by various grants enabling work on scalable computation of elementary pathways through metabolic networks, Markov models of viral evolution, and scalable data mining algorithms for text analysis. He has developed software tools for clustering, dot plot visualization, and educational graphics. Professor Boley directs the Graduate Program in Data Science and has been involved in projects such as the Principal Direction Divisive Partitioning (PDDP) Project. His research group develops practical implementations of theoretical advances, including the PDDP clustering algorithm, Dot.py genome viewer, and various educational graphics tools for introductory programming courses. He maintains active collaborations across disciplines, particularly in bioinformatics and medical imaging applications.

Christophe HurterView profile

Researcher

• Artificial Intelligence
• Data Visualization
• Augmented Reality
• +9 more

Christophe Hurter is a Researcher at the National School of Civil Aviation , specializing in Artificial Intelligence , Data Visualization , and Human-Computer Interaction . His work bridges Aviation Technology , Neuroscience , and Extended Reality (XR) , focusing on enhancing human performance through AI-driven systems. Affiliation: National School of Civil Aviation (Faculty Member, AI axis) Research Interests include: Explainable AI for aviation systems Neurophysiological monitoring using thermal imaging Eye tracking and cognitive processes in memory retrieval Graph and trajectory visualization for air traffic control Augmented/Virtual Reality interfaces for remote collaboration Event-based vision systems for spiking neural networks Recent article trends highlight his expertise in machine learning for medical diagnostics , XR applications in aviation , and visual analytics for human factors research . His work often addresses real-world challenges in air traffic control, piloting training, and biomedical data interpretation.

Mark C. FishmanView profile

Professor

• Cardiovascular Development
• Neurobiology
• Zebrafish Genetics
• +4 more

Mark C. Fishman, M.D., is a Professor of Stem Cell and Regenerative Biology at Harvard University and affiliated with the Harvard Stem Cell Institute. His laboratory investigates the heart-brain axis using zebrafish to map autonomic control circuits and decode the genetic/neuronal basis of vertebrate social behavior . From 2002-2016, he led Novartis Institutes for Biomedical Research, advancing 90 medicines to clinical trials, with a focus on regenerative therapies for aging disorders. Education : Yale College (A.B.), Harvard Medical School (M.D.) Academic Leadership : Former Chief of Cardiology and Director of Cardiovascular Research Center at Harvard Medical School and MGH Research spans cardiovascular development , neurogenetics , and translational medicine , with seminal work on zebrafish genetic screens in the 1990s establishing pathways for vertebrate organ formation. His lab introduced zebrafish as a model for dissecting social interaction circuits and homeostatic regulation . Current work explores how internal sensory systems shape behavior through genetic and pharmacological interventions. Recent publications highlight zebrafish studies on age-related vascular calcification (αKlotho), dopamine transporter mutations (psychiatric models), and collective behavior genetics . Articles span 1996-2025, reflecting continuous contributions to Developmental Biology , Neuroscience , and Cardiovascular Research . Awards include election to the National Academy of Medicine (20-year member), Fellow of the American Academy of Arts and Sciences , and leadership roles in biotech (Aditum Bio, Beam Therapeutics). He authored the textbook Medicine and Lab: Building a Home for Scientists , bridging architectural design with scientific innovation. Teaching includes SCRB 197/297 Frontiers in Therapeutics , examining disease elimination promises and personalized medicine through historical and modern therapeutic frameworks. His lab in Sherman Fairchild Building (Cambridge, MA) continues mentoring interdisciplinary researchers in cardiovascular-neurobiological interfaces.

• Cognitive Neuroscience
• Neuroimaging
• Autism Spectrum Disorders
• +4 more

Susan Y. Bookheimer, PhD, is Professor-in-residence in the Department of Psychiatry and Biobehavioral Sciences at the David Geffen School of Medicine, University of California, Los Angeles. From 2008 to 2024 she held the endowed Joaquin M. Fuster Chair in Cognitive Neuroscience and currently directs or co-directs several large-scale NIH consortia including the UCLA site of the Adolescent Brain Cognitive Development (ABCD) Study, the Lifespan Human Connectome Project in Aging, and newly funded initiatives on resilience to Alzheimer’s disease in centenarians. Education & Training Details of formal degrees are not provided in the source text; however, her continuous NIH funding since 1995 and leadership roles imply advanced research training in clinical neuroscience and neuroimaging. Research Focus Dr. Bookheimer’s work integrates multimodal neuroimaging (fMRI, sMRI, DTI, PET, EEG) with genetics, cognitive testing, and clinical phenotyping to understand: Typical and atypical brain development across the lifespan Neurobiological underpinnings of autism spectrum disorder and sensory phenotypes Early detection and prediction of Alzheimer’s disease and age-related cognitive decline Neuroplasticity and cognitive outcomes following epilepsy surgery Effects of environmental adversity, stress, and social support on brain networks Scientific Awards & Honors Joaquin M. Fuster Chair in Cognitive Neuroscience, UCLA (2008–2024) Principal or Co-Principal Investigator on >15 active NIH grants totaling >$100 M Over 230 peer-reviewed publications with >25,000 citations (Google Scholar metrics) Grants & Consortia Leadership Dr. Bookheimer currently leads or co-leads the following major NIH projects: U19AG073585 – Vulnerability and Resiliency in the Aging Adult Brain Connectome (AABC) U19AG073172 – Resilience/Resistance to Alzheimer’s Disease in Centenarians and Offspring (RADCO) R01AG073480 – Modulation of Hippocampal Circuitry with Focused Ultrasound in Amnestic MCI P50HD103557 – UCLA Intellectual and Developmental Disabilities Research Center U01DA050987 – ABCD-USA Consortium Research Project Site at UCLA U01AG052564 – Mapping the Human Connectome During Typical Aging U01MH109589 – Mapping the Human Connectome During Typical Development In addition, she has served as PI on prior awards including P50HD055784 (Autism Center), R01AG013308 (Alzheimer’s Risk), and P30HD004612 (IDDRC). Laboratories & Teams Dr. Bookheimer directs the UCLA Brain Mapping Center (part of the Ahmanson-Lovelace Brain Mapping Center) and co-directs imaging cores for both the UCLA IDDRC and the ABCD Study. Her multidisciplinary teams include post-doctoral fellows, graduate students, research staff, and collaborators across neurology, radiology, psychology, and genetics departments.

• Computational Neuroscience
• Cognitive Decision Making
• Social Neuroscience
• +3 more

Wako Yoshida is Professor of Clinical Neuroscience at the University of Oxford's Nuffield Department of Clinical Neuroscience, leading research at the intersection of computational neuroscience, decision theory, and social cognition. Her work focuses on neural mechanisms of belief construction during partially observable decision-making and social interactions, with particular emphasis on prefrontal cortex function. Her research interests include: Computational modeling of uncertainty resolution in cognitive decision-making Neural basis of Theory of Mind during cooperative social interactions Pain neuroscience and aversive learning mechanisms Application of hyper-scanning fMRI for group decision-making studies Brain-machine interfaces for pain control through co-adaptive learning Analysis of her 15 most recent publications (2016-2024) reveals three dominant trends: (1) Neural mechanisms of hierarchical belief inference in spatial navigation and social contexts, (2) Uncertainty processing in pain modulation involving prefrontal-periaqueductal circuits, and (3) Development of computational frameworks for brain-machine interfaces targeting chronic pain management. Her work consistently bridges machine learning concepts with human neuroimaging. Scientific awards: No awards mentioned in source material. Advising and grants: Source text provides no details about students, advisees, or grant funding. Yoshida directs the Pain and Aversive Learning research group at Oxford, collaborating with Ben Seymour and others to investigate computational and neural mechanisms underlying pain, aversion, and decision-making using fMRI, hyper-scanning, and computational modeling approaches.

Caroline Schild-PoulterView profile

Professor

• Molecular Biology
• Genetics
• DNA Repair
• +3 more

Caroline Schild-Poulter is a Professor and Scientist at the Robarts Research Institute, affiliated with the Schulich School of Medicine & Dentistry at Western University in London, Ontario, Canada. She leads research in the Molecular Medicine department, specifically within the Vascular and Brain Health Group, focusing on DNA damage response mechanisms and their implications in cancer development. Education: Undergraduate in Biology at the University of Lausanne, Switzerland (Major in Molecular Biology) Master's and PhD at the University of Lausanne (Topic: Mechanisms regulating gene expression) PhD training included a 2-year stage at the National Institutes of Health, Bethesda, USA Dr. Schild-Poulter's research program centers on DNA repair/signaling pathways activated by double-stranded DNA breaks, one of the most dangerous forms of DNA damage. Her work specifically investigates how DNA gets repaired and how apoptosis is activated when repair is not completed. Her research has significant implications for understanding cancer development, stroke, and aging processes. She has made notable contributions to understanding the roles of RanBPM in controlling apoptosis in response to DNA damage and how the DNA repair factor Ku functions to repair and signal from double-stranded DNA breaks. Analysis of her publication record shows consistent focus on DNA repair mechanisms, with recent work expanding into RNA-mediated immunity and protein degradation pathways. Scientific Awards: Natural Sciences and Engineering Research Council Canada (NSERC) Discovery Accelerator Award (DAS) Post-doctoral Fellowship, Medical Research Council of Canada and the Arthritis Society Post-doctoral Fellowship, Association pour la Recherche sur le Cancer (France) Fellowship, Centre National de la Recherche Scientifique (France) Post-doctoral Fellowship, Swiss National Science Foundation (Switzerland) Dr. Schild-Poulter has received significant research funding through competitive grants, including the prestigious NSERC Discovery Accelerator Award which supports her innovative work in DNA repair mechanisms. Her research program has led to numerous publications in high-impact journals and has contributed significantly to our understanding of genomic instability and cancer development. While specific students aren't listed in the available information, her position as a Professor suggests she mentors graduate students and postdoctoral fellows in her laboratory, contributing to the next generation of molecular biologists and cancer researchers. Dr. Schild-Poulter is a key member of the Molecular Medicine research group at Robarts Research Institute, where she maintains an active laboratory investigating DNA damage response pathways. Her work bridges basic molecular mechanisms with potential clinical applications in cancer treatment and prevention, particularly focusing on the critical balance between DNA repair and programmed cell death that prevents malignant transformation.

Daniel A. AbramsView profile

Associate Clinical Professor

• Autism Spectrum Disorders
• Cognitive Neuroscience
• Brain Imaging
• +5 more

Dr. Daniel A. Abrams is a Clinical Associate Professor in the Department of Psychiatry and Behavioral Sciences at Stanford University. His research focuses on the neurobiological basis of social communication impairments in children with autism spectrum disorders (ASD), particularly how atypical reward attribution to social stimuli like voices and faces impacts development. He employs techniques such as functional MRI, psychophysics, and cognitive assessments to identify neural markers of social and memory deficits in ASD. Dr. Abrams received his Ph.D. in Auditory Cognitive Neuroscience from Northwestern University (2008) and a B.F.A. from the University of Arizona (1994). His work has been funded by NIH, NARSAD, and the National Organization for Hearing Research Foundation. He leads the Speech and Social Neuroscience Lab at Stanford Cognitive and Systems Neuroscience Laboratory. Scientific awards include the K01 Research Scientist Development Award (NIH/NIMH, 2014-2017), NARSAD grant (2019-2021), and a 2017 CHRI Pilot Early Career Award. His recent publications highlight neural circuitry in voice processing, memory impairments linked to hyperconnectivity, and efficacy of clinic-home-school collaborative interventions for autistic adolescents. Key research trends: Autism neurodevelopment, reward/salience circuit dysfunction, social communication biomarkers, voice prosody decoding, and memory plasticity. Dr. Abrams’ full description below details his academic trajectory, grants, student collaborations, and clinical trial leadership.

• Artificial Intelligence
• Neuroscience
• Circuits and Systems Theory

Neslihan Serap Şengör is a Professor at the Department of Electronics and Communication Engineering, Istanbul Technical University . Her work bridges Artificial Intelligence , Neuroscience , and Circuits and Systems Theory . Research areas include: Neuromorphic computing with Intel Loihi Basal ganglia and motor control modeling Spiking neural networks for hardware Cognitive process simulation Projects focus on: Hardware implementation of motor learning Computational models for Parkinson's disease Cortex structure simulation on neuromorphic chips Contact: sengorn@itu.edu.tr