Robert Gens is a researcher at the University of Washington , affiliated with the College of Engineering and the Department of Computer Science and Engineering . His work focuses on advancing machine learning architectures, particularly Sum-Product Networks (SPNs) , with applications in computer vision and deep learning. Education: S.B. in Electrical Engineering and Computer Science from MIT (2009) , Ph.D. in Computer Science and Engineering from the University of Washington ( 2016 ). His research integrates insights from neuroscience, graphics, and mathematics to develop algorithms capable of modeling infinite visual data as stable concepts. Key contributions include structural learning, discriminative training, and computational efficiency in SPNs. Notable publications span NIPS , ICML , and ICLR venues, with a focus on SPN optimization and compositional modeling. Trends in his work emphasize tractable probabilistic models , neural network efficiency , and cross-disciplinary algorithm design . Awards include the Google PhD Fellowship in Deep Learning and an NIPS 2012 Outstanding Student Paper Award . Current research involves Deep Symmetry Networks at the Seattle Laboratory of Robotics.
Felipe De Brigard is a Professor of Philosophy and Associate Professor of Psychology and Neuroscience at Duke University. He is an Associate of the Duke Initiative for Science & Society and Member of the Center for Cognitive Neuroscience . His research at the intersection of philosophy, psychology, and neuroscience focuses on memory-imagination interactions, counterfactual thinking, and their implications for moral cognition and identity. Harvard University Postdoctoral Fellow in Philosophy (2011-2013) Ph.D. and M.A. from University of North Carolina, Chapel Hill M.A. from Tufts University Undergraduate degree from Universidad Nacional de Colombia His work challenges traditional memory theories, proposing memory as a system for hypothetical thinking rather than mere recall. Current projects examine how episodic and semantic memory contribute to counterfactual simulations, with recent 2025 publications on memory fidelity in plausible counterfactuals and neural connectivity analysis. He uses fMRI and eye-tracking to explore autobiographical memory modification, moral cognition, and anxiety-related neural patterns. Major grants include: $1.8M Templeton Foundation grant for Summer Seminars in Neuroscience and Philosophy (2020-2025) National Institutes of Health funding for aging and memory research (2018-2025) In the Imagination and Modal Cognition Lab , he leads interdisciplinary research on memory's role in future planning, identity formation, and therapeutic applications for anxiety. His empirical approach to philosophical questions has sparked debates about neuroscience-philosophy integration, particularly regarding consciousness and moral responsibility theories.
Elizabeth Malinzak is an Associate Dean for Student Affairs at Duke University School of Medicine and an Associate Professor in the Department of Anesthesiology. She completed her B.S.E. in Bioengineering at Rice University and earned her medical degree from Duke University School of Medicine. Duke University School of Medicine (Current Affiliation) Department of Anesthesiology Duke Eye Center (Former Director of Anesthesia Services) Her research focuses on gender equity, leadership development, and medical education reform, particularly addressing confidence gaps, parental leave policies, and compensation disparities. She has conducted extensive scholarship on workforce dynamics in anesthesiology and advocates for social media engagement in academic medicine. Selected articles highlight her work on equity in medical training, pandemic-era educational challenges, and perioperative care for special populations. Her scholarship spans both clinical research and academic policy reform. She received the 2023 Distinguished Educator in Anesthesiology Award from the American Society of Anesthesiologists and Society for Education in Anesthesia. Her grant-funded work includes studying gender, race, and age confidence gaps in anesthesiology board certification processes. Dr. Malinzak mentors through initiatives like Women in Anesthesiology and has held leadership roles in national organizations, including Past President of Women in Anesthesiology and Past Chair of the American Society of Anesthesiologists' Committee on Young Physicians.
Hermann Riecke is a Professor at the Department of Engineering Sciences and Applied Mathematics within the McCormick School of Engineering at Northwestern University. Holding a PhD from the University of Bayreuth (1986), his research spans computational neuroscience and pattern formation in complex systems. His office is located in M458 Technological Institute. Research Interests Computational Neuroscience Dynamics of neuronal networks Olfactory bulb information processing Adaptive neural networks Pattern Formation Spatially extended dynamical systems Bifurcation theory with symmetry Localized structures and spatio-temporal chaos Publication Trends reveal expertise in computational neuroscience (olfactory processing, neuronal plasticity) and nonlinear dynamics (synchronization, chimera states, pattern formation). His work connects mathematical modeling with biological applications. Scientific Awards Fellow, American Physical Society Alexander von Humboldt Research Award (2005)
Albert Scherr is a Senior Professor at the Institute of Sociology at Pädagogische Hochschule Freiburg. His academic career spans decades of research and teaching in sociological theory and social work. He maintains an active role in both academic and public discourse on contemporary social issues. Professor Scherr's research interests encompass sociological theories, critical systems theory, social work theory, migration and refugee research, sociological discrimination and racism research, education research, and youth research. His work focuses on non-dogmatic theory development based on Luhmann's differentiation theory while challenging school-forming boundaries to critical theories and subject theories. He has conducted numerous empirical projects examining forms and effects of discrimination, particularly regarding refugees and Sinti and Roma communities. His recent publications reveal a strong focus on migration policy, discrimination studies, educational equality, and social work theory. Scherr examines the intersection of structural discrimination with individual coping mechanisms and empowerment strategies. His work increasingly addresses contemporary challenges like pandemic responses, border politics, and the relationship between social work and geopolitical shifts. Trust professor for Hans-Böckler Foundation Trust professor for Friedrich-Ebert Foundation Member of editorial boards for Sozial Extra, Soziale Probleme, and Zeitschrift für Flucht- und Flüchtlingsforschung Reviewer for German Research Foundation and Swiss National Fund Scherr has supervised numerous doctoral students whose work examines discrimination in immigration societies, anti-Semitism among youth, Islamophobia, educational selection processes, and the right to education for asylum-seeking minors. His approach combines theoretical rigor with practical engagement in policy evaluation projects on integration measures and youth work. He is actively involved in several research networks including the Center for Capability Research at Bielefeld University and the Freiburg Network for Migration Research.
Greg Landsberg , the Thomas J. Watson, Sr. Professor of Physics at Brown University, is a leading experimental particle physicist specializing in high-energy collider phenomenology. Since joining Brown in 1998, he has played pivotal roles in the CMS experiment at the CERN LHC, including serving as Physics Coordinator during the Higgs boson discovery and convener of key analysis groups. Brown University Faculty Member (1998-present) CERN Associate (2019-2020) Divisional Associate Editor, Phys. Rev. Lett. Advisory Board Member for international conferences Education: PhD (1994), State University of New York at Stony Brook MS (1992), State University of New York at Stony Brook Research Interests: Professor Landsberg's research focuses on experimental particle physics at energy frontiers, particularly searching for new physics phenomena beyond the Standard Model. His work includes studies of the Higgs boson, dark matter signatures, extra dimensions, and microscopic black hole production at colliders. He has made significant contributions to understanding flavor anomalies and electroweak symmetry breaking. Scientific Awards: National Science Foundation CAREER Award (2003-2008) Arthur P. Sloan Research Fellowship (2001-2005) Salomon Faculty Research Award (2000) Aditya Sambamurti Memorial Award (1997) Fellow of the American Physical Society (since 2009) Notable Contributions: As a member of the CMS collaboration, he contributed to the discovery of the Higgs boson (2012-2013) and led seminal research on its properties across multiple decay channels. His 2001 paper on black hole production at colliders has become a TOPCITE 500+ article.
Andrew Wharton is a Senior Research Associate in the Department of Physics at Lancaster University, specializing in experimental particle physics. He contributes extensively to the ATLAS experiment at CERN's Large Hadron Collider (LHC), with particular focus on B -> J/psi X decays for new physics searches and detector performance studies. Development of complex multi-dimensional fits for B decay analysis Investigation of miss-reconstructed physics background processes Performance studies of ATLAS's primary vertexing toolchain (TIDE) Design of novel seeding strategies for vertex fitting in high pile-up environments His research spans multiple high-energy physics domains, including Higgs boson studies, top quark analysis, dark matter detection, and quark-gluon plasma investigations. While working extensively on detector simulation and reconstruction algorithms, he also applies machine learning techniques to improve parameter estimation and signal identification. Wharton's recent publications demonstrate strong engagement with ATLAS collaborations across various research fronts: from testing lepton flavor universality to exploring exotic vector boson production. His work contributes significantly to both fundamental physics investigations and technical advancements in detector capabilities.
Hannah Phalen is an Assistant Professor in the Department of Psychology at the University of Wyoming , where she has been employed since 2023. She holds dual advanced degrees in Psychology and Law, with a Ph.D. (2023), J.D. (2019), and M.S. (2018) from Arizona State University, and a B.A. from the University of Colorado Colorado Springs (2015). Ph.D., Arizona State University, 2023 J.D., Arizona State University, 2019 M.S., Arizona State University, 2018 B.A., University of Colorado Colorado Springs, 2015 Dr. Phalen leads the Legal Judgments Lab , focusing on the intersection of psychology and law. Her research examines how race , gender , and emotions influence legal decision-making, particularly in visual evidence interpretation , damage awards , and juror bias . She also investigates how emotional expression (e.g., anger) affects perceptions of attorney effectiveness , with notable findings on gender disparities in legal settings. Her publications highlight trends in legal psychology , including the role of neuroimaging in pain assessment , gendered backlash , and visual evidence dynamics . She mentors graduate and undergraduate researchers, including Alexey Mazon , and accepts new graduate students for the 2026-2027 academic year. For collaboration or inquiries, contact Dr. Phalen at hphalen@uwyo.edu .
Luwen (Vivian) Huangfu serves as an Assistant Professor in the Management Information Systems Department at San Diego State University's Fowler College of Business. Holding a PhD from the University of Arizona (2019), she has published over 30 peer-reviewed articles in premier AI venues including IEEE Transactions and ACM conferences, accumulating 300+ citations. Her research bridges artificial intelligence with business analytics, public health, and transportation systems. Her educational foundation includes: PhD in Management Information Systems, University of Arizona (2019) Dr. Huangfu's research pioneers few-shot learning and generalized zero-shot recognition with applications spanning pavement distress detection , mental health intervention , and code search optimization . She develops novel architectures for multi-label image classification and document clustering using large language models, with significant contributions to weakly supervised learning and metric network design. Her work consistently addresses real-world challenges in transportation infrastructure, cybersecurity, and healthcare analytics. Recent publications (2023-2025) reveal a strategic focus on efficient deep learning for resource-constrained environments, particularly in transportation and medical imaging. She integrates spatial contextual awareness in multiple instance learning while advancing prompt-based refinement for long-tailed distributions. Her growing emphasis on LLM-driven security intelligence and social media mental health analysis demonstrates cross-domain impact. Her scientific accolades include: Corporation for Education Network Initiatives in California (CENIC) Award (2024) NIH-supported Summer Institute 2024/2025 Cohort NSF-supported University of Maryland Travel Award (2024) Department of Energy (DOE) Award (2022, 2023) NSF-DOE-Jointly-Supported Travel Award (2023) Management Information Systems Quarterly (MISQ) Scholarly Development Academy (2022) 24 total awards including multiple NIH/NSF grants and teaching fellowships As a principal investigator, she has secured funding from DOE, NIH, and NSA while serving as advisor for undergraduate and graduate research scholarships. Her service includes NSF ACCESS Program advisory, NIH/NSF grant review panels, and editorial roles for IEEE Transactions and Journal of Medical Internet Research. She actively mentors students through SDSU scholarship committees and DEI initiatives while maintaining rigorous peer-review commitments across 15+ journals and conferences.
Maja Clare Cassidy is a Senior Lecturer, ARC DECRA Fellow, and Scientia Fellow at the University of New South Wales School of Physics. Her research develops quantum computing and sensor technologies, leading the QMD lab while teaching advanced quantum physics courses. Current roles: Senior Lecturer (UNSW), Lab Director, Course Instructor Previous roles: Principal Research Manager at Microsoft Quantum (5 years), Postdoctoral Fellow at TU Delft/QuTech Education: Bachelor of Electrical Engineering (Hons. 1), UNSW (2005) Master of Science in Applied Physics, Harvard University (2010) PhD in Applied Physics, Harvard University (2012) Her research focuses on quantum computing device fabrication , topological superconductivity , microwave quantum optics , and machine learning applications in quantum system development. Key trends in her publications include Majorana qubit stability, ballistic transport in nanowires, and cryogenic CMOS integration for scalable quantum systems. Scientific Awards: RG Menzies Scholarship to Harvard (2008) She supervises 10 current and former students across physics and material science disciplines. Her grants include UNSW Scientia Fellowship (2022-2026), ARC DECRA Fellowship (DE240100590), and multiple industry collaboration grants for quantum hardware development.
Dr. Ivo Popivanov is an Assistant Professor in the Department of Cognitive Science and Psychology at New Bulgarian University. He holds a PhD in Neuroscience from KU Leuven, Belgium, and works as a Clinical Neuropsychologist specializing in cognitive impairments associated with dementia, including affiliations with the Bulgarian Society of Dementia and patient organization Living with Dementia . PhD in Neuroscience from KU Leuven, Belgium Focus on visual perception, bilingualism, and dementia-related cognition Teaches undergraduate course The Human Brain (GENB008) His research bridges Neuroscience and Neuropsychology with emphasis on visual perception mechanisms, bilingual cognitive processing, and dementia-related impairments. Recent work explores ERP correlates of language activation , face/body perception , and fMRI-based neural coding in primates. Scientific trends in his publications span biological motion processing , stimulus representation in the brain, eye-tracking analysis during face recognition, and neural selectivity in primate cortex. These studies often combine EEG , fMRI , and single-unit recordings to investigate visual and cognitive processing. Dr. Popivanov actively contributes to professional communities, including the Society for Neuroscience , Bulgarian Psychological Society , and Bulgarian Society of Dementia . His work has been cited over 600 times, reflecting impact in visual perception and neuropsychological research.
Mahsa Shoaran is a Tenure-Track Assistant Professor at EPFL (École Polytechnique Fédérale de Lausanne) jointly appointed at the Center for Neuroprosthetics and the Institute of Electrical Engineering . She is also the founding director of the Integrated Neurotechnologies Laboratory (INL) and contributes to several doctoral programs and teaching missions across EPFL’s School of Engineering (STI). Education: PhD in Electrical Engineering, EPFL (2015) M.Sc. & B.Sc., Sharif University of Technology Postdoctoral Fellow, California Institute of Technology (Caltech) (2015-2017) Former Assistant Professor, School of Electrical and Computer Engineering, Cornell University (2017-2019) Research Focus: Dr. Shoaran’s work sits at the convergence of integrated circuit design , machine learning , and neuroscience . Her group develops ultra-low-power, miniaturized system-on-chips (SoCs) capable of real-time neural recording , pathology detection , and closed-loop therapeutic intervention such as adaptive neurostimulation. Machine-learning algorithms running on-chip enable precise symptom detection in neurological and psychiatric disorders, while advanced circuit techniques guarantee energy efficiency suitable for long-term implantable or wearable neural interfaces. Scientific Awards & Grants: ERC Starting Grant 2021 Google Faculty Research Award in Machine Learning 2019 Swiss NSF Postdoctoral Fellowships NSF Award for Young Professionals – Smart & Connected Health MIT EECS Rising Star 2015 Doctoral Advising & Service: She currently supervises 14 PhD students in the Integrated Neurotechnologies Laboratory. Additionally, she serves on the PhD program committees for Electrical Engineering (EDEE), Microsystems & Microelectronics (EDMI), and contributes to the Neuro-X and SEL teaching programs. She is a Technical Program Committee member for IEEE CICC and serves on the Student Research Preview committee for ISSCC. Laboratory & Collaborative Teams: The Integrated Neurotechnologies Laboratory (INL) at EPFL Campus Biotech in Geneva hosts her interdisciplinary team of circuit designers, machine-learning researchers, and neuroscientists. The lab collaborates closely with clinicians to translate innovations into real-world neuroprosthetic and diagnostic devices.
Professor Jun Liu is a Professor of Artificial Intelligence and Director of the Artificial Intelligence Research Centre (AIRC) at the School of Computing, Ulster University. With over 270 publications and more than £18 million in research funding, he is a leading figure in artificial intelligence, particularly in trust and explainable AI systems and logic-based reasoning methods. Dr. Liu received his BSc and MSc degrees in Applied Mathematics, and PhD degree in Information Engineering from Southwest Jiaotong University, Chengdu, China, in 1993, 1996, and 1999, respectively. Prior to joining Ulster University, he held postdoctoral positions at The University of Manchester, UK (Feb. 2002 - Dec. 2004) and the Belgian Nuclear Research Centre (SCK*CEN) (Mar. 2000 - Feb. 2002). Professor Liu's research focuses on trust and explainable data-knowledge integrated AI decision models with applications in safety and risk analysis, policy decision making, security/disaster management, and healthcare; and logic and automated reasoning methods for intelligent systems, including resolution-based automated reasoning and lattice-valued logics for handling incomparability, inconsistency, and imprecision. His work spans theoretical foundations to practical applications in smart homes, healthcare, and industrial settings. His recent publications demonstrate a strong trend toward developing more trustworthy and explainable AI systems, with particular emphasis on belief rule-based approaches for handling uncertainty in decision-making. The research spans multiple domains including smart home activity recognition, medical imaging, food quality analysis, and environmental monitoring, showing the versatility and applicability of his methodologies. Ulster University best computer science paper award for 2016 IEEE Senior Member including IEEESMC and IEEECI Fellow of the UK Higher Education Academy Associate Editor of IEEE Transaction on Fuzzy Systems Current Chair of IEEE CIS Emergent Technologies Technical Committee As Director of the Artificial Intelligence Research Centre, Professor Liu has secured significant research funding as principal investigator and co-investigator. His current projects include "The use of Agentic AI in judicial decision-making" funded by EPSRC and "Adaptive Modeling Method for Deep Belief Rule Base" for smart home applications. He serves on editorial boards of multiple high-impact journals and organizes international conferences including the 23rd UK Workshop on Computational Intelligence. The Artificial Intelligence Research Centre under Professor Liu's leadership focuses on developing cutting-edge AI methodologies with practical applications. The center collaborates extensively with industry partners including BT through the BTIIC Phase 2 initiative and PwC through their Advanced Engineering and Research Centre, ensuring research has real-world impact across multiple sectors.
David Santos Velasco is an Associate Professor of Psychology at IE University's School of Human Sciences and Technology, where he has taught full-time since 2019. He earned a PhD in Social Psychology (with honors) from the Autonomous University of Madrid (UAM) and The Ohio State University, along with a Master's in Statistics and a Bachelor's in Psychology from UAM. His research focuses on attitude change, metacognitive processes, and their influence on opinions, with applications in social influence, consumer psychology, and political psychology. PhD in Social Psychology (UAM & OSU, 2018) MSc in Statistics (UAM, 2014) BSc in Psychology (UAM, 2012) His work includes research stays at The Ohio State University (under Pablo Briñol and Richard Petty) and Stanford University's Graduate School of Business. He collaborates with Intermedia Social Innovation (addressing cyberbullying) and IE Business School's Travel Club Chair (loyalty programs). His teaching philosophy emphasizes practical knowledge over theory, treating classrooms as real-world models to prepare students for dynamic professional environments. David's research spans topics like holistic-analytic thinking styles, attitude-behavior consistency, and metacognitive interventions to reduce prejudice. His published works appear in journals such as Personality and Social Psychology Bulletin and Psychology of Violence . Though no explicit scientific awards are listed, his work aligns with SDGs 3 (Good Health), 5 (Gender Equality), and 10 (Reduced Inequalities). He advises students to challenge intuitive social theories, promoting evidence-based understanding of human behavior. Outside academia, he engages in painting, sports (tennis/padel), and enjoys Stranger Things. His email contact is dsantosv@faculty.ie.edu and david.santos@uam.es .
Rachel Hayes-Harb is a Professor of Linguistics at the University of Utah and Associate Dean in the Honors College. She co-directs the Speech Acquisition Lab , focusing on experimental studies of adult second language learners’ perception, phonolexical development, and speech production. Her institutional roles include former Director of the Office of Undergraduate Research (2014–2021) and leadership in mentoring initiatives. Education: PhD in Linguistics (University of Arizona, 2003) Professional Service: Programs Committee, Linguistic Society of America (2007–2010) Her research examines how adult learners acquire new sound systems, emphasizing phonological representations , cross-language perception , and orthographic effects . She investigates pre-existing perceptual sensitivity , accent bias , and social factors in input selection , often using auditory lexical decision tasks and AXB experiments. Recent publications analyze variability in Hindi consonant perception , orthography’s role in German devoicing acquisition , and social science open science practices . Key grants include a Sound-attenuated booth (2013) and HVPT methodology (2017–2018). Awards: Student’s Choice Award (2011), Faculty Fellow Award (2009) Teaching: Courses on General Linguistics, Special Topics, Ethics, and Senior Capstone (2023–2024)
