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Rafael Ballester-RipollView profile

Assistant Professor

• Tensor Decompositions
• Sensitivity Analysis
• Uncertainty Quantification
• +3 more

Rafael Ballester-Ripoll is an Assistant Professor at IE University's School of Science & Technology, specializing in Data Science and Machine Learning. Before joining IE in 2019, he held postdoctoral positions at ETH Zurich and the University of Zurich (UZH). He earned his PhD in Computer Science from UZH (2017), and BSc/MSc degrees in Mathematics and Computer Science from the Technical University of Catalonia-UPC (2012). His research focuses on low-rank tensor decompositions, explainable AI, sensitivity analysis, and scientific visualization. Key contributions include advancements in large-scale visualization, data compression, and uncertainty quantification. Recent work (2025) explores CSR authenticity in AI-era social media, hexagonal A-Star algorithms for weather routing, and entropy coding for tensor networks. Publications span journals like Journal of Machine Learning Research, IEEE Transactions on Visualization and Computer Graphics, and SIAM/ASA Journal on Uncertainty Quantification. He actively participates in conferences such as IEEE VIS and EuroVis, and co-developed tools like tntorch and VIAN. His research trends emphasize tensor-based methods applied to interdisciplinary domains, including quantum computing, Bayesian networks, and probabilistic graphical models. Collaborative projects highlight applications in ocean engineering, film analysis, and recommender systems. Ballester-Ripoll has contributed to IE's Research Datalab initiatives, though no formal awards or grants are explicitly noted in the provided texts. His work bridges theoretical foundations with practical tools for data-driven decision making.

Jeremiah MurphyView profile

Assistant Professor

• Astrophysics
• Core-Collapse Supernovae
• Massive Stars
• +4 more

Jeremiah Murphy serves as an Assistant Professor in the Department of Physics at Florida State University, maintaining his office in 606 Keen Building with contact email jwmurphy@fsu.edu. His research mission centers on understanding core-collapse supernovae (CCSNe) and black hole formation mechanisms while fostering inclusive scientific environments. Murphy leads a dynamic research group employing dual theoretical and observational approaches to determine why some massive stars explode as supernovae while others collapse directly into black holes. This work connects to neutron stars, nucleosynthesis, gravitational waves, and neutrino physics. The group utilizes order-of-magnitude estimates, analytical models, and computational frameworks like BETHE-hydro for theoretical work, while observational studies leverage Bayesian inference applied to Hubble Space Telescope and Gaia data, with future James Webb Space Telescope campaigns planned. Analysis of his 15 most recent publications (2022–2025) reveals a dominant focus on the “Force Explosion Condition” framework for predicting stellar explodability, complemented by progenitor mass studies in galaxies like M31, M33, and NGC 6946. His output spans theoretical astrophysics, computational methods, and observational astronomy with significant emphasis on neutrino-driven convection and multidimensional effects in supernova simulations. Funding for Murphy’s research has been secured through competitive grants from the National Science Foundation, Research Corporations for Science Advancement, Space Telescope Science Institute, and Los Alamos National Laboratory. His group actively develops open scientific tools including the Phoebus framework for relativistic astrophysics simulations and stellar age inference codes, contributing to both methodology advancement and observational data analysis in the field. Murphy maintains active observational programs with space-based telescopes and computational projects advancing supernova theory, while his commitment to inclusive research environments is reflected in educational outreach publications focused on increasing diversity in astronomy at all academic levels.

Gopal GuptaView profile

Professor

• Programming Languages
• Software Engineering
• Parallel and Distributed Processing
• +4 more

Dr. Gopal Gupta is the Erik Jonsson Chair Professor of Computer Science at The University of Texas at Dallas (UT Dallas), leading the Department of Computer Science since 2009. He holds a Ph.D. from the University of North Carolina at Chapel Hill (1991) and has held academic roles since 1992, including Department Head and Associate Head at UT Dallas. His research focuses on Programming Languages, Software Engineering, Parallel Processing, Human-Computer Interaction, and Artificial Intelligence , with notable contributions in logic programming, constraint programming, and neuro-symbolic AI. He has developed influential systems such as the NEXUS parser , DAWN , and VoxBoox , and co-founded Interoperate , a startup translating legacy code into modern formats. His honors include the Junior Faculty Enhancement Award (1992) and multiple best paper awards. Gupta’s work bridges theory and application, emphasizing explainable AI, commonsense reasoning, and system assurance. Key Projects : Leader of the Condicutve Logic Programming initiative Co-developer of the E-plan system for chemical hazard response Pioneer in voice-based accessibility tools like VoxBoox Advocate for entrepreneurial ventures in academia His publications span logic-based AI, parallel computing, and software verification, with recent work in trustworthy AI, causal counterfactuals, and neuro-symbolic frameworks.

Robert HarrisonView profile

Professor

• High-Performance Computing (HPC)
• Computational Chemistry
• Quantum Chemistry
• +3 more

Robert Harrison is a Professor and Endowed Director of the Institute for Advanced Computational Science at Stony Brook University. His research focuses on scientific computing and computational chemistry methodologies for high-performance supercomputers. He holds a Ph.D. in Theoretical Chemistry from the University of Cambridge (1984). His work emphasizes advancing computational frameworks for extreme-scale systems, including projects like NWChemEx and MADNESS. He collaborates on optimizing applications for cutting-edge architectures such as ARM-based HPC clusters (e.g., Ookami) and NVIDIA GPU superchips. Harrison’s contributions span molecular modeling, quantum chemistry simulations, and HPC performance benchmarking. Key projects include developing scalable algorithms for electronic structure calculations, porting legacy codes to modern architectures, and advancing task-based programming paradigms for parallel computing. His research addresses challenges in exascale computing, energy efficiency, and the design of selective binding agents for heavy elements like lanthanides and actinides.

Dongsheng LuoView profile

Assistant Professor

• Data Mining
• Deep Learning
• Natural Language Processing
• +5 more

Dr. Dongsheng Luo is an Assistant Professor at the Knight Foundation School of Computing and Information Sciences at Florida International University (FIU). He holds a Ph.D. in Information Science and Technology from Pennsylvania State University (2022) and a B.Eng. in Computer Science and Technology from Beihang University (2017). His research focuses on developing interpretable AI tools for complex data analysis, particularly in graph mining, deep learning, and natural language processing, with applications in neuroscience, healthcare, and environmental systems. Education: 2022: Ph.D., Penn State University 2017: B.Eng., Beihang University His research interests emphasize explainable AI, robust graph neural networks, and multimodal integration. Recent work includes frameworks for medical plan generation, causal discovery, and flood forecasting. He investigates methods to enhance model reliability and transparency, such as confidence-aware explanations and fidelity evaluation. Collaborations span biomedical informatics, climate science, and IoT systems. Publications highlight contributions to graph explainability, time series analysis, and molecular modeling. His work bridges theoretical advances with practical applications in healthcare, environmental monitoring, and communication systems.

Sanne GeeraertsView profile

Assistant Professor

• Parenting
• Children and Family
• Self-Control
• +7 more

Sanne Geeraerts is an Assistant Professor in the Youth and Family department at Utrecht University, affiliated with the Social and Behavioral Sciences faculty. Her work focuses on understanding how parenting behaviors are transmitted across generations, particularly examining intergenerational dynamics and their effects on child development. She holds a doctoral degree from Utrecht University and has conducted extensive research on self-regulation in infants and preschoolers, parental interactions, and the role of household chaos and maternal sensitivity in behavioral outcomes. Her expertise includes Parenting, Children and Family dynamics, and Self-Control mechanisms, with a specific emphasis on the Dynamics of Youth (DoY). Dr. Geeraerts has contributed to theoretical frameworks for self-regulation studies and has evaluated methodologies for longitudinal investigations. She has been involved in teaching and mentoring within the Orthopedagogiek Master's program and courses like 'Socialization of Children and Adolescents.' Key awards include the CAS honorable mention (2022), Fulbright Scholarship (2017), and recognition for her Master's thesis (2014). Her research activities span peer reviewing for journals such as 'Self and Identity' and 'Journal of Applied Developmental Psychology,' and she has presented at international conferences including EARA and SRCD. She has also served as a visiting researcher at institutions like Pennsylvania State University.

Denilson BarbosaView profile

Professor

• Natural Language Processing
• Information Retrieval
• Machine Learning
• +3 more

Denilson Barbosa is a Professor of Computing Science at the University of Alberta's Faculty of Science. He holds a PhD and specializes in Natural Language Processing, Information Retrieval, and Machine Learning. His research focuses on knowledge extraction, entity recognition, and knowledge graph construction. Barbosa teaches courses like CMPUT361 (Information Retrieval) and CMPUT656 (Knowledge Graphs). He served as President of the Canadian Artificial Intelligence Association (CAIAC) from 2023 to 2024. His work includes developing tools like the NLP Workbench and contributing to open relation extraction, Wikipedia analysis, and low-resource language models. Education and Background: Barbosa's academic background aligns with his research interests in computational linguistics and AI applications. His teaching emphasizes practical skills in algorithms, data structures, and machine learning for text processing. Research Highlights: Barbosa's research spans semantic graphs, probabilistic language models, and defect prediction systems. He explores challenges in multilingual NLP, particularly for Indigenous and low-resource languages like Cree. His work often integrates machine learning with traditional IR methods to improve system efficiency and accuracy. Recent Contributions: Notable recent projects include improving Bengali/Hindi LLMs, evaluating QA systems via textual entailment, and developing Bayesian methods for crowdsourced truth discovery. His articles reflect his interdisciplinary approach, combining theory with real-world applications in education, software engineering, and social media analysis.

Maria FalikmanView profile

Teaching Professor

• Cognitive Psychology
• Visual Attention
• Cultural Evolution
• +5 more

Maria Falikman is a Teaching Professor of Psychology at HSE University in Moscow, Russia, and former Head of the School of Psychology there. She holds a Ph.D. and Dr. Habil from Lomonosov Moscow State University. Her research focuses on visual attention, cultural evolution, and digital transformations of the human mind, with contributions to cognitive psychology, psycholinguistics, and joint attention mechanisms. Falikman has authored the Psychology of Attention handbook and co-edited multiple Russian psychology readers. She has been a Visiting Scholar at Harvard University and the University of Groningen. Education: B.Sc., M.Sc., Ph.D., Lomonosov Moscow State University (Russia); Dr. Habil Her work bridges cognitive science and cultural-historical theory, exploring topics like meditation's effects on attention, predictive coding principles, and the mind-body problem. She has contributed to popular science via 30+ web lectures for Postnauka/Serious Science and appeared in documentaries on the human brain and cognitive robotics. Falikman is also a PEN International member and award-winning literary translator, having translated works of British and American authors and published poetry collections. Her recent research trends emphasize digital mediation's impact on cognition, cultural evolution, and interdisciplinary dialogues between psychology and neuroarchaeology. Key themes include gaze cueing mechanisms, attention allocation strategies, and the role of cultural tools in cognitive development. Awards: Russian National Psychological Award (2013, 2020); HSE Best Teacher Award (2019–2021) Falikman advises on autism interventions through joint attention studies and explores existential neuropsychology. She leads initiatives in neuroplasticity and acculturation mechanisms, integrating Vygotskian theory with modern digital contexts.

Colleen BoveView profile

Assistant Professor

• Marine Ecology
• Climate Change Impacts
• Coral Reef Ecology
• +3 more

Dr. Colleen Bove is an Assistant Professor in the Department of Biology at Ursinus College. She earned her B.S. in Marine Biology from the University of North Carolina at Wilmington and her Ph.D. in Ecology from the University of North Carolina at Chapel Hill. After completing postdoctoral research at Boston University, she joined Ursinus in 2023. Her research explores environmental stress impacts in aquatic ecosystems through multidisciplinary approaches including molecular analyses, aquarium experiments, field expeditions, and geospatial techniques. Current projects investigate coral microbiomes in the Caribbean, climate change effects on marine invertebrates, and microplastic pollution in Pennsylvania's Schuylkill River. Dr. Bove teaches courses including Ecology and Evolution, Global Change Ecology, Marine Biology, and Marine Invertebrate Zoology. She advocates for open science practices through public sharing of data, code, and protocols via GitHub and Zenodo.

Umang MathurView profile

Assistant Professor

• Formal Methods
• Logic in Computer Science
• Programming Languages
• +3 more

Umang Mathur is an Assistant Professor at the National University of Singapore's School of Computing, specializing in Formal Methods, Logic, and their applications to Programming Languages, Software Engineering, and Computer Systems. He received his PhD from the University of Illinois at Urbana-Champaign, where he was advised by Mahesh Viswanathan, and previously worked as a Research Scientist at Meta and a Research Fellow at the Simons Institute for the Theory of Computing. At NUS, he leads the FOCS Lab and is affiliated with PLSE@NUS. His research focuses on developing algorithmic techniques for analyzing concurrent software and exploring decidability horizons in verification, synthesis, and formal logic contexts. He has been recognized with prestigious awards including a Google PhD Fellowship, Google Research Award, and multiple ACM SIGSOFT/SIGPLAN Distinguished and Best Paper Awards (ESEC/FSE'18, ASPLOS'22, POPL'23). Scientific Awards Google PhD Fellowship Google Research Award ACM SIGSOFT Distinguished Paper Award (ESEC/FSE'18) Best Paper Award (ASPLOS'22) ACM SIGPLAN Distinguished Paper Award (POPL'23) He supervises PhD students Zhendong Ang, Tianyu Li, Huan Zhao, Grace Tan, and Zihan Zhou, along with Master’s students like Zheng Shi. His taught courses include CS4211 Formal Methods for Software Engineering, CS4269/CS5469 Foundations of Logic in Computer Science, and CS6217 Topics in Prog. Languages & Software Engineering (focusing on Automata Theory, Logic, and Games).

• Learning Sciences
• Machine Learning
• Educational Data Mining
• +10 more

Dr. Maria Cutumisu is an Associate Professor in Learning Sciences at McGill University's Faculty of Education, with affiliations at Mila Quebec AI Institute and the University of Alberta's Department of Computing Science. She leads the ALERT Lab, focusing on Assessment of Learning and Transfer in areas like Machine Learning, Educational Data Mining, and Game-Based Assessments. Her work integrates computing science and educational psychology, supported by grants from NSERC, SSHRC, and others. Education: Ph.D. and M.Sc. in Computing Science, University of Alberta Postdoctoral Training in Learning Sciences, Stanford University B.Sc. in Computer Science, University of Bucharest Research Interests: Machine Learning and Automated Feedback Systems Game-Based Assessments (e.g., RETAIN neonatal resuscitation simulator) Data Literacy and Computational Thinking Psychophysiological Learning Analytics (eye-tracking, wearables) Mindset and Feedback-seeking Behavior Awards: 2025: Teaching Recognition (McGill TLS) 2021: GSA Graduate Supervision Award (University of Alberta) 2009: Outstanding Ph.D. Research Achievement (University of Alberta) Grants & Advising: Principal Investigator on NSERC DG, SSHRC IDG grants Co-PI on CIHR, CREATE, and CanCode grants Supervises Master's and Ph.D. students at McGill Labs & Projects: ALERT Lab (McGill) RETAIN serious game for neonatal resuscitation training Callysto Computational Thinking Test (K-12 education)

Margo SeltzerView profile

Professor

• Computer Systems
• Operating Systems
• Database Systems
• +7 more

Margo Seltzer is a Professor and Co-Head of the Department of Computer Science at the University of British Columbia (UBC). She holds the Canada 150 Research Chair in Computer Systems and the Cheriton Family Chair in Computer Science. Her research focuses on computer systems, including operating systems, databases, data provenance, graph analytics, and interpretable machine learning. She is also involved in educational initiatives and has held leadership roles in academia, including serving as Dean of Computer Science and Engineering at Harvard University. Education: PhD in Computer Science from UC Berkeley (1992), AB in Applied Mathematics from Harvard (1983). Professional roles include Chief Technology Officer at Sleepycat Software and architect at Oracle Corporation. She has received prestigious awards such as the ACM Athena Lecturer Award, Killam Teaching Prize, and membership in the National Academy of Engineering. Research Interests: Systems, databases, transaction processing, provenance capture, healthcare informatics, and cybersecurity. Her work emphasizes practical applications of systems research, including optimizing storage, improving operating system performance, and enhancing data security. She has contributed to open-source projects like Berkeley DB and CamFlow provenance system. Key Contributions: Developed systems for provenance-aware storage, sparse decision trees (e.g., GOSDT), and intrusion detection (FRAPpucino). She advocates for reproducible research through tools like Encapsulator and Rclean. Her teaching and mentorship have influenced countless students and junior faculty in computer science. Awards: ACM Athena Lecturer (2023), SIGMOD Systems Award (2020), USENIX Lifetime Achievement Award (2019), and election to the American Academy of Arts and Sciences (2021). Her work bridges theoretical computer science with real-world applications, emphasizing both technical innovation and societal impact.

Benjamin KarneyView profile

Professor

• Intimate Relationships
• Marriage
• Social Psychology
• +7 more

Benjamin Karney is a Professor of Social Psychology at the University of California, Los Angeles (UCLA), where he serves as Social Area Chair in the Department of Psychology. He also holds an adjunct position as a behavioral scientist at the RAND Corporation, focusing on interpersonal relationships and marriage dynamics within diverse contexts. His educational background includes a Ph.D. from the University of California, Los Angeles. Ph.D.: University of California, Los Angeles Dr. Karney's research examines change and stability in intimate relationships, particularly during early marriage. He investigates how external stressors—including socioeconomic hardship, military deployment, and racial discrimination—impact cognitive and behavioral relationship maintenance processes. His methodology emphasizes longitudinal designs, repeated measures, multi-level modeling, and observational coding of couple interactions, with current work focusing on Latinx, Black, and White newlywed couples from low-income neighborhoods. Analysis of his recent publications (2015-2021) reveals consistent focus on contextual factors influencing relationship trajectories. Key trends include examination of socioeconomic status as both stressor and adaptive framework, racial discrimination effects on marital quality, and context-dependent communication strategies. His work increasingly integrates duocentric social network analysis and challenges deficit-based models of low-income relationships. Dr. Karney has received significant recognition for his contributions: Two-time recipient of the National Council on Family Relation’s Reuben Hill Research and Theory Award His research has been supported by major grants from the Department of Defense (military marriage studies) and the National Institute on Child Health and Human Development (low-income marriage research). As director of the Florida Project on Newlywed Marriage and Adult Development (FPNMAD), he led landmark longitudinal studies of early marriage. He served as expert consultant for the Strengthening Healthy Marriage project—a national experimental study for low-income couples sponsored by the Administration on Children and Families—and conducted Florida's statewide marriage baseline survey in 2003. Dr. Karney directs the UCLA Marriage and Close Relationships Lab, which maintains active research programs examining relationship dynamics across diverse socioeconomic and cultural contexts through multiple longitudinal studies.

• Behavioral Neuroscience
• Visual Perception
• Attention Allocation
• +3 more

James Bisley is an Assistant Professor in the Department of Neurobiology at the University of California, Los Angeles . His research focuses on the neural mechanisms underlying visual attention allocation and motion encoding, particularly in posterior parietal cortex and cortical area MT. Techniques include single unit recording, microstimulation, and behavioral task analysis under naturalistic viewing conditions. Research Themes Visual perception and attention Short-term memory of motion stimuli Parietal cortex priority mapping Sensorimotor integration in robotics Key Methods Animal behavioral task design Neural inactivation/stimulation Haptic feedback engineering

Martin PickeringView profile

Professor

• Psychology of Language
• Language Production
• Language Comprehension
• +5 more

Martin Pickering is a Professor in the School of Philosophy, Psychology and Language Sciences at the University of Edinburgh. He serves as the Director of Research for the School and is based in Room S12 of the Psychology Building at 7 George Square, Edinburgh. His contact email is martin.pickering@ed.ac.uk and phone number is 0131 650 3447. Professor Pickering is actively involved in teaching and research with a focus on language and communication processes. Professor Pickering completed his BA (1st Class) in Psychology at the University of Durham and his PhD in Cognitive Science at the University of Edinburgh. He has held academic positions at institutions in Arizona, Glasgow, and Edinburgh. Professor Pickering's research focuses on the psychology of language and communication, with particular emphasis on language production, language comprehension, dialogue processes, language and imagination, joint action, and bilingualism. His work employs various methodologies including eye-tracking, ERP, and behavioral experiments to investigate how people produce and understand language in interactive contexts. He has developed influential theories on dialogue processing and predictive mechanisms in language comprehension, with his 2004 paper 'Toward a mechanistic psychology of dialogue' and 2013 paper 'An integrated theory of language production and comprehension' being particularly significant contributions. His research has been supported by numerous grants from organizations including the Economic and Social Research Council, European Commission, and Royal Society of Edinburgh. Current projects include 'Predicting language under difficult conditions: Effects of cognitive load, noise, and hearing impairment' and 'COBRA: COnversational BRAins.' Fellow of the British Academy (FBA) Fellow of the Royal Society of Edinburgh (FRSE) Professor Pickering has supervised numerous PhD students, both as primary supervisor and assistant supervisor. Among his current students are Matias Morales Martinez, Fang Yang, and Yue Yu. His past students include prominent researchers such as Holly Branigan (now Professor at Edinburgh), Patrick Sturt (Reader at Edinburgh), and Chiara Gambi (Lecturer at Cardiff). He is open to supervising new PhD students in his areas of interest. Professor Pickering has held editorial positions for major journals including Journal of Memory and Language, Psychological Science, and Language and Cognitive Processes. He has also served on review panels for funding bodies such as ESRC and the Royal Society of Edinburgh.