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Suren Jayasuriya is an Associate Professor at Arizona State University's The GAME School, with joint appointments in the School of Electrical, Computer and Energy Engineering (ECEE) and the Department of Arts, Media and Engineering (AME). He is also an Affiliate Faculty Member at the Mary Lou Fulton College for Teaching and Learning Innovation. His lab, the Imaging Lyceum, focuses on transdisciplinary research bridging computational imaging, computer vision, sensors, and STEAM education. Education Ph.D. Electrical and Computer Engineering, Cornell University (2017) M.S. Electrical and Computer Engineering, Cornell University (2015) B.S. Mathematics, University of Pittsburgh (2012) B.A. Philosophy, University of Pittsburgh (2012) Research Focus Dr. Jayasuriya's work integrates optics, computational photography, and machine learning to develop novel imaging systems. His research spans: Computational cameras and light transport analysis Atmospheric turbulence modeling and video restoration Neural volumetric reconstruction for sonar/radar STEAM education frameworks for K-12 teachers Philosophical aspects of imaging and representation His lab emphasizes interdisciplinary collaboration across engineering, arts, and humanities. Publication Trends Recent publications demonstrate strong focus on computational imaging (45%), AI/ML applications (30%), and educational technology (25%). Dominant themes include turbulence mitigation in videos, neural rendering for sonar/radar, sensor fusion, and AI curriculum development for middle schools. Work frequently appears in top venues like CVPR, SIGGRAPH, and IEEE Transactions. Awards Image Electronics Technology Excellence Award (IIEEJ, 2021) Best Demo Awards: IEEE ICCP 2019, MIRU 2018 Best Paper Award: IEEE ICCP 2014 ASEE Diversity Paper Finalist (2020) Teaching Honors: Fulton Top 5% Award (2019, 2021), ASU Game Changing Faculty (2021) Teaching & Advising Teaches graduate/undergraduate courses including Machine Vision (EEE 515), Minds and Machines (AME 400), and thesis supervision. Leads NSF-funded projects on computational imaging education and AI teacher training. Mentors students through the Imaging Lyceum lab with projects spanning optics, philosophy, and educational technology. Lab & Collaborations Directs the Imaging Lyceum, emphasizing Aristotle-inspired collaborative research. The lab works on: computational cameras, STEAM education, sensor development, and philosophical inquiries into imaging. Collaborates with Carnegie Mellon Robotics Institute and international partners. Funded by NSF, NEH, and industrial partners for projects in sonar imaging, heat resiliency sensing, and educational AI.

• Computational Imaging and Photography
• Computer Vision and Graphics
• Sensors and Mixed-signal Circuits
• +2 more

Tina Gupta will join the University of Oregon as an Assistant Professor in the Department of Psychology under the College of Arts and Sciences in Fall 2025. With expertise in clinical psychology and affective neuroscience, she focuses on adolescent emotional development and severe mental illness risk markers. Research Interests: Adolescent Development, Psychosis-risk, Resilience, Emotion Processing, Reward Processing, Early Intervention Methods: Clinical interviews, behavioral measures, facial expression coding, neuroimaging, eye-tracking, computational statistics Her work bridges clinical psychology and developmental psychopathology to identify biological and environmental factors contributing to severe mental illnesses like schizophrenia. She specifically examines disruptions in emotional processes and protective resilience mechanisms in at-risk adolescents. Dr. Gupta employs multi-modal approaches including fMRI , EMG , and longitudinal tracking to map brain-behavior relationships. Her recent publications analyze anhedonia trajectories, facial expressivity changes, and inflammation's role in adolescent mental health.

• Clinical Psychology
• Adolescent Development
• Severe Mental Illness
• +6 more

James Lacefield is a Professor in both the Department of Electrical and Computer Engineering and the Department of Medical Biophysics at Western University. He serves as Director of the School of Biomedical Engineering and maintains his research laboratory in the Amit Chakma Engineering Building. His academic appointments span multiple disciplines, reflecting the interdisciplinary nature of his work in biomedical ultrasound imaging. Dr. Lacefield earned his Ph.D. and B.S.E. in Biomedical Engineering from Duke University. His educational background established the foundation for his current research program that bridges engineering principles with medical applications. His research focuses on the physical acoustics and signal processing aspects of ultrasound imaging, with particular emphasis on quantitative vascular imaging applications. Dr. Lacefield's laboratory develops novel methods for color Doppler, power Doppler, and contrast-enhanced ultrasound imaging, with primary applications in cancer research. Current projects include optimization of high-resolution ultrasound systems for tumor vascular characterization and development of methods to quantify spatial blood flow distribution in tumors. Analysis of his recent publications reveals a strong focus on quantitative ultrasound techniques for cancer applications, with particular attention to tumor perfusion assessment using contrast-enhanced ultrasound. His work demonstrates increasing sophistication in speckle analysis methods to improve the reliability of perfusion measurements in preclinical tumor models. Associate Editor, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control Member, Council of Chairs of Bioengineering and Biomedical Engineering Member, College of Reviewers, Canadian Institutes of Health Research Dr. Lacefield maintains active collaborations with multiple research groups including the Imaging Research Laboratories at Robarts Research Institute. His professional activities include editorial work for major ultrasound journals and participation in national review panels for biomedical research funding.

• Biomedical Ultrasound Imaging
• Vascular Imaging
• Cancer Research Applications
• +5 more

Professor Isabel Dziobek is a distinguished academic at Humboldt University of Berlin, holding a W3 Professorship in Clinical Psychology of Social Interaction within the Institute of Psychology, Faculty of Life Sciences. She serves as Head of the University Outpatient Clinic for Psychotherapy and Psychodiagnostics and leads the Special Outpatient Clinic for Social Interaction. As Academic Director of the Center for Psychotherapy at Humboldt University and Principal Investigator at the German Center for Mental Health, she plays a pivotal role in shaping mental health research and clinical practice in Germany. Her educational background includes a Diploma in Psychology from Ruhr University Bochum (2000), a Dr. rer. nat. summa cum laude from University of Bielefeld (2006), and Habilitation in Psychology from Free University of Berlin (2014). She obtained her license to practice as a psychological psychotherapist in 2015. Professor Dziobek's research focuses on bio-psycho-social mechanisms of social interaction disorders across autism spectrum disorders, social anxiety disorders, and personality disorders. Her work integrates neurobiological approaches (fMRI, EEG, psychophysiology, eye-tracking, neuromodulation) with the development of diagnostic and intervention procedures including cognitive behavioral therapy, e-mental health, and social robotics. She has pioneered research on therapeutic mechanisms through focused short-term programs involving movement synchronization, social competence training, and brain stimulation augmentation. Analysis of her recent publications reveals a strong emphasis on empathy assessment in autism and personality disorders, development of innovative assessment tools like the Simulated Interaction Task for Children (Kids-SIT), and exploration of novel therapeutic approaches including psychedelic-assisted therapy. Her work increasingly incorporates participatory research methods and cross-cultural validation of assessment tools, reflecting a commitment to making research clinically relevant and accessible. 2016: Teaching Award of the Faculty of Life Sciences, Humboldt University of Berlin 2016: Antistigma-Preis der Deutschen Gesellschaft für Psychiatrie und Psychotherapie 2014: Charlotte- und Karl-Bühler-Preis, Deutsche Gesellschaft für Psychologie 2011: 2nd Place in Brain-Art Competition 2011 2007: Dissertation Award of University of Bielefeld 2007: 1st Prize at Canadian Film Festival "Picture This" Professor Dziobek serves in numerous leadership roles including Spokesperson for Charité Mental Health, Fellow of the Max Planck School of Cognition, and Board Member of Charité Mental Health. She directs the DZPG-funded research group and participates in the Cluster of Excellence Neurocure III. Her lab, the Dziobek Lab (dziobek-lab.org), focuses on developing and evaluating interventions for social interaction disorders while maintaining strong clinical connections through the University Outpatient Clinic.

• Social Interaction Disorders
• Autism Spectrum Disorders
• Social Anxiety Disorders
• +12 more

Marco Cuturi is a Research Scientist at Apple ML Research in Paris and Professor of Statistics at CREST-ENSAE, Institut Polytechnique de Paris. His work bridges machine learning , optimal transport , and optimization , with applications in time-series analysis , kernels , and multiresolution methods . He has held academic roles at Kyoto University and Princeton University, and previously worked in the financial industry. Research Interests: Optimal transport theory and computational methods Kernel design for structured data and histograms Time-series alignment and soft-DTW Entropic regularization in optimization Applications to computer vision and genomics Teaching: Cuturi has taught courses on linear optimization at Princeton, geometric methods in machine learning at Kyoto, and scientific English. He has also organized machine learning summer schools in Kyoto, Les Houches, and other international venues. Recent Trends: His 2024-2025 publications focus on entropic optimal transport solvers, disentangled representation learning via Gromov-Monge gaps, and applications to text-to-image diffusion models. Collaborative work with institutions like Google Research, MIT, and University of Tokyo highlights his interdisciplinary impact.

• Machine Learning
• Optimal Transport
• Optimization
• +4 more

Professor Stephan A. Sieber is a leading researcher in bioorganic chemistry at the Technical University of Munich (TUM), where he holds the Chair of Organic Chemistry II within the TUM School of Natural Sciences. His research program focuses on developing new drugs against multidrug-resistant bacteria through a multi-disciplinary approach that integrates synthetic chemistry, functional proteomics, microbiology, and protein biochemistry. His laboratory has made significant contributions to identifying unprecedented antibacterial targets beyond the scope of current antibiotics and exploiting these for chemical manipulation. Recent work has increasingly incorporated machine learning approaches to accelerate antibiotic discovery, with notable publications on AI-guided pipelines, drug-target interaction prediction, and high-throughput screening optimization. Sieber's research has resulted in the discovery of new active substances, some of which are currently being optimized for medical applications. His group's publications reveal a strong focus on chemical proteome mining, natural product mode of action studies, and novel antibacterial target identification. The lab has published extensively in top journals including Nature Chemistry, Nature Communications, and ACS Central Science. Inhoffen Medal (2024) Max Bergmann Medal (2023) ERC Advanced Grant (2023) Merck Future Insight Prize (2020) Klaus Grohe Prize (2020) ERC Consolidator Grant (2016) Professor Sieber leads an active research group that maintains a strong presence in the scientific community through regular publications, conference presentations, and collaborations. His laboratory website and BlueSky presence (@sieberlab.bsky.social) demonstrate ongoing research activities and engagement with the broader scientific community. He has successfully secured significant research funding including multiple ERC grants that have supported his innovative work in antibiotic discovery.

• Bioorganic Chemistry
• Antibiotic Development
• Chemical Proteomics
• +5 more

Carlos Brody is the Wilbur H. Gantz III '59 Professor of Neuroscience at Princeton University, where he leads a research group at the Princeton Neuroscience Institute. His laboratory employs a unique combination of computational, behavioral, and electrophysiological techniques to investigate the neural mechanisms underlying cognitive abilities. Dr. Brody's research focuses on understanding how the brain processes information during cognitive tasks, particularly examining short-term memory, decision-making, and time perception. His lab trains rats to perform complex cognitive tasks while recording neural activity, and develops computational models to explain the experimental findings. They have pioneered the study of 'internal signals' in neural activity that constitute 'the internal conversation of the mind,' with their key discovery being 'nTc' (Neurally-inferred Time of Commitment), a biomarker that indicates decision commitment before overt behavioral responses. Dr. Brody's laboratory has been continuously supported by HHMI (Howard Hughes Medical Institute) with renewal until 2032. They are currently conducting groundbreaking research using multiple Neuropixels probes for large-scale recordings across the brain while rats perform cognitive behaviors, representing what Dr. Brody considers the future of cognitive systems neuroscience that combines advanced recording technology, AI-based analysis, and well-controlled behavioral paradigms. Scientific Awards HHMI Investigator (renewed until 2032) Advising and Research Support Dr. Brody has mentored numerous successful researchers who have secured faculty positions and leadership roles: Marino Pagan (Nature publication, SFARI Bridge to Independence Award) Edward Nieh (faculty position at University of Virginia) Manuel Schottdorf (Nature publication) Sue Ann Koay (publications in Neuron and eLife, Group Leader at Janelia) Brian DePasquale (faculty position at Boston University) Emily Dennis (Group Leader at HHMI's Janelia) Ahmed El Hady (Group Leader at Max Planck Institute) Abby Russo (joined CTRL-Labs startup) Diksha Gupta (Best Paper Award at RLDM conference) His lab is currently supported by HHMI funding and is planning to implement next-generation Neuropixels probes in Spring 2025 to record from 6,000-12,000 neurons simultaneously across multiple brain regions. Research Team and Facilities The Brody Lab features a diverse team ranging from purely computational to purely experimental researchers. The lab emphasizes minimizing barriers between computational and experimental approaches, encouraging researchers to move freely along this spectrum based on their interests. They maintain state-of-the-art facilities for behavioral training, electrophysiological recordings, and computational analysis, with plans to implement next-generation Neuropixels recording technology in Spring 2025.

• Systems Neuroscience
• Cognitive Neuroscience
• Decision-making
• +6 more

Olga G. Troyanskaya is a Professor of Computer Science and the Lewis-Sigler Institute for Integrative Genomics at Princeton University. She serves as Deputy Director for Genomics at the Simons Center for Data Analysis, Simons Foundation, NYC. Her research focuses on computational biology, integrating diverse high-throughput genomic datasets to model molecular pathways in health and disease. Professor of Computer Science and Lewis-Sigler Institute for Integrative Genomics Deputy Director for Genomics, Simons Center for Data Analysis Research Interests: Troyanskaya’s work addresses challenges in bioinformatics, including algorithm development for gene expression analysis, regulatory network modeling, and disease mechanism interpretation. She combines computational methods with experimental validation using S. cerevisiae as a model organism. Scientific Trends: Recent publications emphasize single-cell multiomics, deep learning for transcriptional regulation, cancer immunotherapy design, and epigenomic analysis of immune responses. Key themes include computational modeling of genetic networks, disease-specific pathway analysis, and high-resolution omics frameworks. Collaborative roles in autism, Alzheimer’s, kidney disease, and cancer research Developed tools like HumanBase for data-driven predictions

• Bioinformatics
• Computational Genomics
• Machine Learning in Biology
• +6 more

Serge O. Dumoulin is a Professor of Perception, Cognition, and Neuroscience at Utrecht University and Vrije Universiteit Amsterdam. He leads the Computational Cognitive Neuroscience and Neuroimaging group at the Netherlands Institute for Neuroscience and serves as Director of the Spinoza Centre for Neuroimaging , a collaborative facility involving KNAW, AMC, VUMC, and VU Amsterdam. Education: M.Sc. in Biology (Utrecht University), Ph.D. in Neurology and Neurosurgery (McGill University) Research focuses on the intersection of perception, cognition, and neuroimaging, particularly the human visual system. He employs ultra-high field (7T) fMRI, computational modeling, and behavioral studies to explore neural mechanisms of visual perception, attention, and numerical cognition. His work has applications in clinical disorders and methodological advancements like the pRF method, used globally in 100+ institutions. Publications span neuroscience, neuroimaging, and cognitive processes, with a 2023 Advances in MRI Technology paper emphasizing gray-matter optimized fMRI. His 2018 Neuroimage article discusses systematic pRF variations, while a 2021 PNAS study links divisive normalization to visual hierarchy. Awards: Ammodo KNAW Award (2015), NWO Vidi/Vici grants, Neuroimage Editors' Choice Award (2013) Teaching includes courses at Vrije Universiteit Amsterdam on perception, neuroscience, and fMRI data analysis. He emphasizes coding (Matlab/Python) in student internships.

• Neuroscience
• Cognitive Neuroscience
• Neuroimaging
• +8 more

Dr. Naveen K. Vaidya is a full Professor at San Diego State University (SDSU) in the Department of Mathematics and Statistics . He received his PhD and M.Sc. in Applied Mathematics from York University, Canada , and M.Sc., B.Sc., and B.Ed. from Tribhuvan University, Nepal . His postdoctoral research was conducted at Los Alamos National Laboratory and Western University, Canada . Research Interests : Dr. Vaidya specializes in applied mathematics and mathematical biology , focusing on modeling infectious diseases such as HIV, SARS-CoV-2, dengue, malaria, and tuberculosis. His work spans within-host and between-host dynamics, integrating differential equations , dynamical systems , optimal control , and biostatistics . Recent projects explore climate impacts on disease spread and machine learning in public health analytics. Scientific Awards : He has received prestigious honors, including the University of Missouri Faculty Scholars (2015/2016) Susan Mann Dissertation Award (2008) NSERC Visiting Fellowships in Canadian Government Laboratories (2008/2009) Travel Support Awards from NSF and MBI (2018) Simons Foundation Collaboration Grant (2020, declined due to NSF grants) Grants and Funding : Dr. Vaidya has secured multiple grants from the National Science Foundation (2016–2021; 2020–2023), Simons Foundation , International Mathematical Union , and SDSU Start-up Funds . He also organized the AMNS-2019 conference in Nepal and led workshops on collaborative research. Labs and Teams : As principal investigator of the SDSU-DiMoLab , he leads a multidisciplinary team studying COVID-19 , HIV , and other infectious diseases. The lab trains graduate and undergraduate students and collaborates internationally, particularly with Tribhuvan University, Nepal .

• Applied Mathematics
• Mathematical Biology
• Pathogen Dynamics
• +8 more

Sarah Xiao is a Professor of Marketing and Head of Department at Durham University Business School, with a dual role as Programme Director for the Doctorate in Business Administration (DBA) at Fudan University, China. As a consumer psychologist, her work bridges technology, marketing, and behavioral analysis in retail, tourism, and digital economies. Her research spans: Behavioral Change in consumer decision-making Consumer Analytics (AI, Big Data, Machine Learning) Illicit Consumption and consumer misbehavior Neuroscience in marketing and consumer choice Mobile Commerce and Digital Marketing strategies Recent publications focus on AI-driven consumer behavior, social media revenge typologies, and predictive modeling in tourism demand forecasting. She supervises PhD students including Bai Dan, Matthew He, Coco Li, and Shujun Xiao, while collaborating with global institutions and private-sector partners. Her work has attracted significant research funding and appears in leading journals like Journal of the Academy of Marketing Science and Annals of Tourism Research .

• Behavioral Change
• Consumer Analytics
• Big Data
• +13 more

Mikael Johansson is a Professor at Kungliga Tekniska Högskolan (KTH), specializing in Control Technology . He teaches and coordinates courses such as Distributed Optimization (FEL3311) and various advanced-level degree projects in computer science, electrical engineering, and systems engineering. His research spans Control Systems , Machine Learning , and Optimization , with a focus on asynchronous algorithms, federated learning, and applications in energy systems and construction. His work includes 15 recent publications on topics like neural networks, distributed optimization, and battery technology. Notable areas of contribution are in asynchronous learning, federated learning with privacy constraints, and quasi-Newton methods for optimization. His research bridges theoretical advancements with practical applications in urban design, healthcare, and autonomous systems.

• Control Technology
• Distributed Optimization
• Machine Learning
• +4 more

Katsuhito Yasuno is a Research Scientist in the Department of Neurosurgery at Yale School of Medicine. He works within the Gunel Lab, focusing on neurogenetic research related to brain disorders, vascular conditions, and tumors. His work involves genomic analyses and molecular studies to understand the genetic basis of various neurological conditions. Education: Postdoctoral Fellow, Japan Science and Technology Corporation (2008) Postdoctoral Fellow, Japan Biological Informatics Consortium (2006) Postdoctoral Fellow, Tokai University School of Medicine (2004) PhD in Theoretical Physics, Tokyo Institute of Technology (2002) MS in Theoretical Physics, Tokyo Institute of Technology (1999) BS in Physics, Tokyo Metropolitan University (1997) Dr. Yasuno's research spans multiple areas of neurogenetics and molecular neuroscience. His primary interests include epidemiologic factors and methods related to brain tumors (particularly glioblastoma and meningioma), intracranial aneurysms, nervous system diseases and malformations, and vascular diseases. His physics background contributes to sophisticated analytical approaches in genetic research. His publication record shows consistent contributions to understanding the genetic mechanisms underlying neurological disorders, with recent work focusing on meningioma genetics, brain malformations, and vascular disorders. The research demonstrates a progression from basic genetic discovery to translational applications, with particular emphasis on molecular pathways that could serve as therapeutic targets. Dr. Yasuno collaborates extensively with leading researchers in the field, most notably with Dr. Murat Günel (28 common publications) and Dr. Kaya Bilguvar (34 common publications). His work involves both computational analysis and laboratory validation of genetic findings. As part of the Gunel Lab, Dr. Yasuno contributes to the lab's three major research interests: developmental neurogenetic disorders, neurovascular disorders, and brain tumor biology. The lab utilizes advanced genomics techniques and bioinformatic analysis for gene discovery followed by functional studies.

• Epidemiologic Factors
• Epidemiologic Methods
• Glioblastoma
• +7 more

Jacob Young, MD, is an Assistant Professor in the Department of Neurological Surgery at the University of California, San Francisco (UCSF) School of Medicine and a Principal Investigator in the UCSF Brain Tumor Center. His clinical practice focuses on neurosurgical management of adult brain tumors including gliomas, metastatic tumors, and meningiomas, utilizing advanced brain mapping techniques to preserve critical motor, language, and sensory functions during resection. Dr. Young's educational background includes a BS in Neuroscience from Duke University (2012), an MD from the University of Chicago Pritzker School of Medicine where he was elected to Alpha Omega Alpha Honor Medical Society (2017), and a neurosurgery residency at UCSF (2017-2024). His research program integrates laboratory investigations with clinical trials to address fundamental challenges in brain tumor treatment. His primary research interests center on understanding glioblastoma immune microenvironment dynamics and developing innovative therapeutic strategies. Key focus areas include: First-in-human clinical trials of novel immunotherapies Focused ultrasound-mediated blood-brain barrier disruption to enhance drug delivery Longitudinal molecular profiling of tumor evolution during treatment AI-driven tools for patient care navigation and clinical trial assessment Prospective outcomes research through the RANO resect group and NeuroPoint Alliance His work bridges fundamental tumor biology with translational applications to overcome treatment resistance. Analysis of Dr. Young's 15 most recent publications (2023-2025) reveals a strong emphasis on surgical innovation, tumor immunology, and molecular characterization. Key trends include: development of prognostic classification systems for resection extent, investigation of glioma-neuronal circuit interactions driving immunosuppression, and optimization of drug delivery strategies. His collaborative work within the RANO consortium establishes evidence-based surgical guidelines while his lab's focus on microenvironmental factors informs next-generation immunotherapies. Dr. Young has received significant recognition including: Chan-Zuckerberg Physician Scientist Fellowship (2021-2022) ASCO Young Investigator Award (2022-2023) Andrew J. Lockhart Focused Ultrasound Fellowship (2023) Multiple Harold Rosegay Teaching Awards from UCSF Howard Naffziger Award for Clinical Excellence His research is supported by NIH, NCI, Focused Ultrasound Foundation, and AANS grants. As lab director, Dr. Young mentors a diverse team including PhD candidates like Edward Valenzuela (DSCB program) and specialists in immunology and neuro-oncology. His lab participates in the RANO resect group, ENCRAM research program, and NeuroPoint Alliance to advance clinical protocols. Current projects include developing intraoperative focused ultrasound prototypes, single-cell analysis of tumor evolution, and AI tools for patient navigation through care pathways. Future work focuses on translating microenvironment discoveries into combination therapies targeting treatment resistance mechanisms.

• Neuro-oncology
• Glioblastoma
• Brain Tumor Immunology
• +6 more

Emily Cross is a Full Professor at the Department of Humanities, Social and Political Sciences at ETH Zurich, leading the Social Brain Sciences Professorship since spring 2023. She previously held professorships at Bangor University (Wales), University of Glasgow (Scotland), Macquarie University (Australia), and Western Sydney University's MARCS Institute (Australia). Her research centers on how embodied experience shapes social learning and perception across diverse contexts. Key contributions include identifying neural signatures of embodied expertise using dancers, developing embodied neuroaesthetics theory, uncovering neurocognitive foundations of visual learning across lifespans, and pioneering paradigms for human-robot social engagement. Her interdisciplinary approach bridges technology, performing/visual arts, and social sciences to explore experience-dependent plasticity at brain and behavioral levels. Recent publications (2024-2025) demonstrate intense focus on human-robot interaction dynamics, aesthetic movement perception, and context-dependent social cognition. Work increasingly examines self-disclosure mechanisms to robots, cultural influences on robot acceptance, and neural correlates of movement synchrony, reflecting her expanding influence at the neuroscience-robotics intersection. Scientific awards include: Philip Leverhulme Prize for Psychology Jacob Bronowski Award from British Science Foundation Young Talent Award from Dutch Neuroscience Society RoboHub and Insight Analytics top women in robotics listings Australia’s Superstars of STEM (2022) Cross passionately trains next-generation scientists with emphasis on research ethics. Her work attracts major funding from ERC, NIH, Fulbright Commission, ESRC, EPSRC, and UK Ministry of Defence. She serves on UNESCO’s International Bioethics Committee (co-rapporteur for neurotechnology ethics report) and as Associate Editor for International Journal of Social Robotics. She leads ETH Zurich's dynamic Social Brain Sciences group, which embraces interdisciplinarity through research paradigms bridging technology, performing/visual arts, and biological/social sciences, while maintaining active roles in editorial boards and conference committees including Intelligent Virtual Agents and Affective Computing meetings.

• Cognitive Neuroscience
• Social Neuroscience
• Embodied Cognition
• +5 more