جستجوی استاد راهنمای دانشگاهی

Irina Rishمشاهده پروفایل

استاد

• Machine Learning
• Neural Scaling Laws
• Emergent Behaviors in AI
• +۱۳ مورد دیگر

Irina Rish is a Full Professor at the Université de Montréal and a core academic member of Mila – Quebec Artificial Intelligence Institute, where she leads the Autonomous AI Lab. She holds a Canada Excellence Research Chair (CERC) and a CIFAR AI Chair, reflecting her leadership in foundational AI research. Her work is supported by major initiatives, including the U.S. Department of Energy’s INCITE project on Summit and Frontier supercomputers. PhD in AI, University of California, Irvine MSc in AI, University of California, Irvine MSc in Applied Mathematics, Moscow Gubkin Institute Her research focuses on machine learning, neural scaling laws, emergent behaviors in foundation models, continual learning, robustness, and neuroscience-inspired AI . She explores how AI systems can become more general, flexible, and aligned with human cognition. Her recent work investigates training dynamics in large language models, efficient pruning techniques, and the development of time-series foundation models. The analysis of her recent publications reveals a strong focus on scaling behaviors, continual adaptation, and robustness in AI systems . Her work spans theoretical understanding of training dynamics (e.g., zero-sum learning), practical optimization methods, and applications in climate modeling and mental health. She emphasizes open science, leading open-source projects and co-founding Nolano.ai to build efficient, compressed foundation models. Canada Excellence Research Chair (CERC) CIFAR AI Chair IBM Eminence & Excellence Award (2018) IBM Outstanding Innovation Award (2018) IBM Outstanding Technical Achievement Award (2017) IBM Research Accomplishment Award (2009) Irina Rish advises a large group of PhD and Master’s students across Université de Montréal, McGill, and Concordia. She leads major research grants and collaborates internationally on HPC-based AI research. She is also the co-founder and CSO of Nolano.ai, driving innovation in efficient AI systems. She leads the Autonomous AI Lab, which focuses on building large-scale foundation models, understanding neural scaling laws, and developing bio-inspired learning systems. She actively organizes reading groups on scaling, continual learning, and out-of-distribution generalization, fostering a collaborative research environment.

David B. Bensimonمشاهده پروفایل

استاد

• Biophysics
• Single-Molecule Studies
• DNA Mechanics
• +۷ مورد دیگر

David B. Bensimon is a world-leading biophysicist and Professor in the Department of Chemistry and Biochemistry at the University of California, Los Angeles, holding the prestigious Regent's Professor title since 2007. He maintains a dual academic position, serving as Directeur de Recherche at the French National Center for Scientific Research (CNRS) at the Ecole Normale Supérieure (ENS) in Paris while teaching and conducting research at UCLA for one quarter each year. His academic journey began with a Ph.D. from the University of Chicago in 1986 under Leo Kadanoff, followed by postdoctoral research at Bell Laboratories and ENS Paris. Professor Bensimon's research spans multiple frontiers in biophysics and molecular biology, with particular expertise in single-molecule studies of nucleic acids and their proteins. His laboratory pioneered the Magnetic Trap technique for manipulating individual DNA molecules, enabling groundbreaking investigations into DNA mechanics, topoisomerase interactions, and molecular combing. His recent work has expanded into optogenetics, developmental biology using zebrafish models, and cancer research, with significant contributions to understanding how single-cell oncogene activation leads to tumorigenesis. His research output shows remarkable breadth across disciplines, with recent publications spanning biophysics, developmental biology, cancer research, and genomic technology development. Bensimon's work on opto-chemical tools has particularly transformed how researchers can control biological processes with unprecedented spatiotemporal precision, especially in zebrafish models. His laboratory has developed photoactivatable versions of key molecular tools including Cas9 (OptoCas9) and cyclofen systems that allow precise control of protein activity at the single-cell level. 2007 Regent's Professor at UCLA 1997 Vinci of Excellence Award for phospholipid vesicle research 1994 Jacques Monod Prize for Molecular Combing discovery Special Prize of the French Physical Society for DNA mechanics work ICAM Fellow KITP-UCSB Representative Bensimon has made significant contributions to both basic science and translational applications, co-founding Depixus for nucleic acid sequencing and epigenetic analysis. His laboratory continues to push boundaries in single-molecule biophysics while expanding into developmental biology and cancer research, with recent work demonstrating that activation of kRas in dedifferentiated cells increases tumorigenesis probability by two orders of magnitude. His mentorship has produced notable researchers including X. Michalet, and his theoretical work extends to the philosophical unification of scientific disciplines as evidenced by his book "The Unity of Science".

Sebastian Risiمشاهده پروفایل

استاد

• Neuroevolution
• Evolutionary Robotics
• Self-Organizing AI
• +۹ مورد دیگر

Sebastian Risi is a Professor at the IT University of Copenhagen , where he directs the Creative AI Lab and co-directs the Robotics, Evolution and Art Lab (REAL) . His work bridges computational evolution, deep learning, and collective intelligence for applications in robotics, art, and video game design. His research focuses on self-organizing AI systems that grow or assemble through local interactions, inspired by biological development. Key areas include neuroevolution , neural cellular automata , and generative modeling , with applications in adaptive robotics, game content creation, and damage-resilient AI. Recent publications highlight trends in self-assembling neural architectures (NDPs) and 3D functional machine generation (Minecraft experiments). Awards include ERC Consolidator Grant (2022), Best Paper at FDG’21 , and Google Faculty Award (2019). Scientific Awards : ERC Consolidator Grant (GROW-AI), Best Paper FDG’21, Runner-Up IEEE Games’20, GECCO 2017 Competition Winner, Sapere Aude Grant, Amazon/Google Faculty Awards He advises on projects like GROW-AI (EU-funded), AI-TESTER (game testing), and C2SIM (military systems). Media coverage includes Science , Wired , and Popular Science .

Timothee Lionnetمشاهده پروفایل

دانشیار

• Single-Molecule Imaging
• Gene Expression
• Single-cell Biology
• +۵ مورد دیگر

Timothee Lionnet is an Associate Professor in the Department of Cell Biology at NYU Grossman School of Medicine. He holds a PhD from the University of Paris and completed postdoctoral training at Albert Einstein College of Medicine in Robert H Singer's lab. His research focuses on understanding how cells regulate gene expression through single-molecule imaging, bridging molecular-scale observations with cellular and tissue-level processes. Education: PhD in Paris, Postdoc at Einstein College of Medicine His work integrates live-cell imaging technologies, computational modeling, and systems genetics to investigate transcriptional dynamics, epigenetic regulation, and cellular responses to environmental cues. The Lionnet Lab develops novel tools to visualize gene activity in real time, aiming to uncover principles of robust gene expression programs and their role in diseases like cancer and viral reactivation. Recent research highlights include studies on chromatin landscape evolution in acute lymphoblastic leukemia, transcriptional stochasticity, and therapeutic resistance mechanisms in cancer cells. The lab collaborates on projects involving zinc finger design for genome editing and systems-level analysis of melanoma genetics. Lab activities emphasize interdisciplinary approaches, combining quantitative biology with clinical insights to advance regenerative medicine and cancer therapy strategies.

Natalia Díaz Rodríguezمشاهده پروفایل

استادیار

• Artificial Intelligence
• Deep Learning
• Reinforcement Learning
• +۶ مورد دیگر

Natalia Díaz Rodríguez is an Assistant Professor of Artificial Intelligence at ENSTA ParisTech, where she works in the Computer Science and Systems Engineering department within the Autonomous Systems and Robotics Lab (U2IS). She is also affiliated with the INRIA Flowers team, focusing on developmental robotics. Her research spans deep learning, reinforcement learning, continual learning, and symbolic AI, with applications in explainable AI, computer vision, and robotics for social good. Her academic background includes a double PhD in Artificial Intelligence from Abo Akademi University and the University of Granada, alongside MSc degrees in Soft Computing and Computer Engineering from the University of Granada. She contributes to interdisciplinary AI, particularly in robotics, ethics, and healthcare applications, and co-organizes workshops on continual learning. Double PhD in Artificial Intelligence (2015), Abo Akademi University and University of Granada Doctoral diploma on Innovation and Entrepreneurship (2017), EIT Digital MSc in Soft Computing and Intelligent Systems (2012), University of Granada MSc in Computer Engineering (2010), University of Granada Her recent publications focus on trustworthy AI, including bias identification, counterfactual explanations, and continual learning strategies, reflecting her commitment to ethical and robust AI systems. She also explores AI applications in structural engineering, climate visualization, and financial risk assessment, emphasizing practical deployment and interpretability.

Angelica Limمشاهده پروفایل

استادیار

• Human Robot Interaction
• Affective Computing
• Multimodal Perception and Learning
• +۶ مورد دیگر

Angelica Lim is an Assistant Professor of Professional Practice and Rajan Family Scholar in the School of Computing Science at Simon Fraser University. Her research focuses on Human Robot Interaction, Affective Computing, and Multimodal Perception with applications in healthcare and developmental robotics. She holds a PhD in Informatics from Kyoto University (2014), an M.Sc. from Kyoto University (2012), and a B.Sc. in Computing Science from SFU (2008). Her work bridges robotics and human-centered AI through projects like the ROSIE Lab, exploring emotion-aware systems, socially assistive robots, and VR programs for aging populations. Key contributions include benchmarking emotional speech recognition (BERSting), developing embodied emotion models for robots, and co-designing healthcare technologies with patient partners. Recent publications emphasize ethical AI, multimodal perception systems, and human-robot collaboration in dynamic environments. Teaching includes courses on software engineering, artificial intelligence, and introductory computer science. Her research has been applied in dementia care through VR programs, robotic companionship for older adults, and emotion-aware human-robot communication systems. Current initiatives focus on inclusive HRI design and sim2real methodologies for underrepresented data in affective computing.

Tim Oatesمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Deep Learning
• +۷ مورد دیگر

Dr. Tim Oates is a Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County . His research spans machine learning, artificial intelligence, and brain-machine interfaces, with a focus on weakly supervised methods, human-in-the-loop reinforcement learning, and grounded policy development for robotics. Ph.D., Computer Science, University of Massachusetts, Amherst, 2000 M.S., Computer Science, University of Massachusetts, Amherst, 1997 B.S., Computer Science and Electrical Engineering, 1989 Current research threads include: Developing non-invasive brain injury severity assessment via medical time series Modeling human brain development through computational frameworks Designing algorithms for autonomous robotic learning Recent publications highlight AI security mechanisms (backdoor detection via tensor decomposition, matrix factorization) Medical applications (3D artery reconstruction, skin lesion diagnosis, EEG denoising) Neuro-symbolic integration (holographic representations, language-guided reinforcement learning) Mathematical reasoning (schema-based problem solving, subitizing algorithms) Contact: oates@cs.umbc.edu | Office: 336 Information Technology and Engineering (ITE) Building

Al Barrمشاهده پروفایل

استاد

• Computer Graphics
• Predictive Modeling
• Scientific Visualization
• +۵ مورد دیگر

Alan H. Barr is a Professor of Computer Science at the California Institute of Technology (Caltech), affiliated with the Division of Engineering and Applied Science and the Computation & Neural Systems (CNS) department. He is a founding member of the Caltech Computer Graphics Group and a leader in developing mathematically rigorous methods for computer graphics and predictive modeling. His research focuses on enhancing computational modeling accuracy through approaches like interval analysis and constraint-based systems. Notable contributions include deformable models, quaternion interpolation, and cellular simulation frameworks. He has advised over 20 graduate students, many of whom became industry leaders at Pixar, Microsoft Research, and academic institutions like NYU and Brown University. Awards include the ACM SIGGRAPH Achievement Award (1988) and ACM Fellow (1995). Research Interests: Predictive modeling with error bounds Scientific visualization and MRI data analysis Biophysical systems simulation (e.g., cellular organelles) Self-assembling robotic structures for space colonization Mathematically robust computer graphics techniques Key Collaborations: Caltech Biological Imaging Center (Beckman Institute) JPL (Jet Propulsion Laboratory) New computational substrates research (quantum/DNA computing) Recent Work: Expanding into computational biology, medical imaging optimization, and high-confidence systems for managing complex computational interactions. Active in interdisciplinary projects across Caltech divisions.

Julijana Gjorgjievaمشاهده پروفایل

استاد

• Computational Neuroscience
• Theoretical Neuroscience
• Neural Circuit Development
• +۴ مورد دیگر

Prof. Julijana Gjorgjieva is a tenured W3 Professor of Computational Neuroscience at the School of Life Sciences Weihenstephan, Technical University of Munich (TUM). She leads an independent research group at the Max Planck Institute for Brain Research and is affiliated with the Bernstein Center for Computational Neuroscience. Her research focuses on the principles governing neural circuit development, balancing learning plasticity with functional stability through computational and theoretical approaches. Key interests include synaptic organization, energy-efficient neural computation, and evolutionary optimality principles. Education & Career: B.Sc. Mathematics, Harvey Mudd College (2006) M.A.St. in Applied Mathematics, University of Cambridge (2007) Ph.D. Applied Mathematics, University of Cambridge (2011) Postdoctoral Fellowships: Harvard University (2011-2014), Brandeis University (2014-2016) Max Planck Research Group Leader (2016-2022) W2/W3 Professor at TUM since 2016 Research Interests: Computational neuroscience, theoretical modeling of neural circuits, synaptic plasticity mechanisms, homeostatic regulation, and the interplay of development and evolution in shaping brain architecture. She employs mathematical frameworks to study how circuits achieve robustness while enabling adaptive learning. Awards: Heinz Maier-Leibnitz Prize (2022) Eric Kandel Young Neuroscientist Prize (2021) ERC Starting Grant (2018) Multiple postdoctoral and early-career fellowships Grants & Funding: Includes DFG Collaborative Research Center on Neural Homeostasis, HFSP grants, and EU Horizon 2020 initiatives. Active in mentoring and promoting computational neuroscience through programs like Neuromatch Academy. Labs & Collaborations: Leads a multidisciplinary lab integrating experimental and theoretical approaches. Collaborates with institutions such as the Max Planck Society and international computational neuroscience networks.

Matthias Sutterمشاهده پروفایل

استاد

• Experimental economics
• Behavioral economics
• Economics of credence goods
• +۶ مورد دیگر

Matthias Sutter serves as Director at the Max Planck Institute for Research on Collective Goods in Bonn while holding part-time professorships at the University of Cologne (10%) and University of Innsbruck (5%). His academic career spans multiple prestigious institutions including the European University Institute in Florence (2013-2014), University of Gothenburg (2007-2013, part-time), University of Cologne (2015-2017, Excellence Chair), and University of Innsbruck (2006-2017). His educational background includes a PhD in economics (1999) and habilitation (2002), both from the University of Innsbruck. Additional academic recognition includes membership in the German National Science Association (Leopoldina) and Academia Europaea. Sutter's research program centers on experimental economics, with particular focus on team decision making processes and the development of economic decision capabilities across different age groups. His work investigates how patience, risk preferences, and social behaviors evolve throughout life, and how these economic preferences impact health and economic success. He has made significant contributions to understanding credence goods markets, where information asymmetry between providers and consumers creates unique market challenges. His experimental approaches combine laboratory studies with field experiments to generate robust insights applicable to real-world economic situations. His publication record demonstrates consistent output in top-tier journals, with recent work spanning diverse topics including energy consumption during crises, workplace climate interventions, vaccination attitudes in polarized environments, and the formation of economic preferences in childhood. The interdisciplinary nature of his research connects economics with psychology, public policy, and organizational behavior, reflecting his broad scholarly impact. Major Awards and Honors: 2017 Hans Kelsen Preis of the Universität zu Köln 2016 Pater Johannes Schasching SJ Preis for dialogue between economy, ethics and religion 2015 Exeter Prize for Research in Experimental Economics 2009 Science Prize of the State of Tyrol 2008 Honorary Prizes from Stiftung Südtiroler Sparkasse and State of Vorarlberg 2004 Oberbank-Science-Prize Linz Sutter serves as Principal Investigator in the Excellence Cluster 'ECONtribute: Markets & Public Policy,' funded by the German Science Foundation (DFG). He holds editorial positions as Associate Editor of 'Management Science,' 'European Economic Review,' and 'Economics Letters,' and serves on the Editorial Boards of 'Experimental Economics' and 'Journal of the Economic Science Association.' His work extends beyond academia through popular science communication, including the best-selling book 'Die Entdeckung der Geduld' (The Discovery of Patience) exploring the importance of patience for health and economic success.

Jon Olav Vikمشاهده پروفایل

استاد

• Systems Biology
• Computational Biology
• Aquaculture
• +۷ مورد دیگر

Jon Olav Vik is a Professor at the Norwegian University of Life Sciences (NMBU), affiliated with the Department of Mathematical Sciences and Technology within the Faculty of Science and Technology. He leads the DigiSal project—"Towards the Digital Salmon: From a reactive to a pre-emptive research strategy in aquaculture"—funded under the Research Council of Norway’s Digital Life initiative. He is also a lead modeller in the GenoSysFat project, which aims to enhance omega-3 content in farmed salmon through integrated genomics and systems biology approaches. His research spans systems biology , computational physiology , genotype-phenotype modeling , and ecological dynamics . He works at the intersection of biology, mathematics, and computer programming, developing models to understand how genetics, nutrition, and environment interact in fish and ecological systems. His pedagogical focus includes biostatistics and programming in R, and he teaches courses such as STIN100, STIN300, and STAT100. The 15 most recent publications reflect a consistent focus on systems-level understanding in biology, particularly in salmon aquaculture, metabolic regulation, and genotype-phenotype relationships. These works appear in high-impact journals like Nature , Science , PLOS Computational Biology , and Journal of The Royal Society Interface , demonstrating interdisciplinary reach across computational biology, genomics, ecology, and biostatistics. Key themes include metabolic modeling, microbiome stability, lipidome remodeling, and sensitivity analysis in dynamic models. Jon Olav Vik has contributed to major collaborative efforts including the Infrastructure for Systems Biology Europe (ISBE) , where he helped develop frameworks for "modelling as a service." He has also authored book chapters and technical deliverables on systems biology and modeling practices. He actively supervises students and invites master’s thesis candidates with interests in quantitative biology. While no specific awards are listed, his leadership in national and international research projects underscores his scientific impact. His work supports both fundamental science and sustainable aquaculture innovation.

Luis Merino Cabañasمشاهده پروفایل

استاد

• Robotics
• Systems Engineering
• Automation
• +۵ مورد دیگر

Luis Merino Cabañas is a Professor at the Universidad Pablo de Olavide , affiliated with the Deporte e Informática department and leading the SRL Service Robotics Laboratory . His research focuses on robotics, systems engineering, and automation, with a specialization in human-robot interaction and path planning. Education : PhD in Systems Engineering from the Universidad de Sevilla (2007), where his thesis explored cooperative perception techniques for multiple unmanned aerial vehicles in forest fire detection. Research Trends : Recent work (2023–2025) emphasizes 3D path planning, sensor fusion (LiDAR, radar, inertial systems), neural distance fields for safe navigation, and socially aware robotics. His studies integrate AI, genetic programming, and multi-modal perception for applications in construction, healthcare, and GNSS-denied environments. Labs & Teams : He leads the SRL Service Robotics Laboratory , contributing to projects like the Skyeye team and BIM2ROS integration for construction robotics.

Balazs Vedresمشاهده پروفایل

استاد

• Network Science
• Data Science
• Sociology
• +۷ مورد دیگر

Balazs Vedres is a **Professor** at the **Central European University (CEU)**, with a joint appointment in the **Department of Network and Data Science**. His research integrates network science, data science, and social theory to explore creativity, innovation, and historical processes in collaborative networks. He holds a **PhD in Sociology from Columbia University** and an **MA in Economics from Corvinus University**. **Research Interests**: Focuses on structural dynamics in creative fields (e.g., jazz, video games, open-source software), gender inequality in collaborative platforms, historical network evolution, and the impact of social bots on human collaboration. He analyzes how network configurations like *structural folds* and *forbidden triads* drive innovation and creativity. **Awards**: Elected **Member of the European Academy of Sociology (2017)**, recognizing his contributions to sociological research. His work bridges computational methods with sociological theory, as seen in his publications in *American Journal of Sociology* and interdisciplinary journals. **Projects**: Leads initiatives like *Gendered Creative Teams: From Marginality to Success* and *Ceunet/Indra Mapping European Network Science*. His research often involves empirical studies of transnational activism, entrepreneurial networks, and digital platforms. **Labs/Teams**: Active in CEU’s **Data and Network Dynamics Studies (DNDS)** group, fostering interdisciplinary collaboration in computational social science. His work emphasizes the interplay between global economic integration and local developmental agency.

Richard Shwederمشاهده پروفایل

استاد

• Cultural Psychology
• Anthropology
• Moral Development
• +۵ مورد دیگر

Richard A. Shweder is the Harold H. Swift Distinguished Service Professor of Human Development at the University of Chicago, where he has been since 1972. He is a leading figure in cultural psychology and anthropological research, focusing on moral reasoning, cultural migration, and multiculturalism. His work critiques Western liberal assumptions, emphasizing robust cultural pluralism and the complexities of cross-cultural ethical conflicts. Shweder's research spans decades in Bhubaneswar, India, examining family practices, gender roles, and moral foundations. Education: Ph.D. in Social Anthropology from Harvard University (1972). Notable visiting roles include fellowships at the Center for Advanced Study in the Behavioral Sciences, Stanford University, and the Institute for Advanced Study in Berlin. Research interests include cultural psychology, moral pluralism, and the challenges of multiculturalism in liberal democracies. His books, such as Thinking Through Cultures and Why Do Men Barbecue? , explore how cultural contexts shape thought and emotion. He critiques global human rights campaigns, particularly regarding female genital surgeries, advocating for nuanced cultural understanding. Scientific awards include the Guggenheim Fellowship (1985), Carnegie Scholar (2002), and the Lifetime Achievement Award from the Society for Psychological Anthropology (2016). He has served as President of the Society for Psychological Anthropology and co-chaired projects on law and culture. Recent work focuses on the moral challenges of cultural migration and the limits of tolerance in Western societies. His 2020 lecture on moral absolutes and 2023 publications on gender equality in religious practices highlight ongoing debates in cultural anthropology. Shweder actively engages in public discourse through podcasts, interviews, and critiques of academic politics, such as opposing academic boycotts of Israeli institutions. His academic roles include teaching courses like Moral Psychology and Comparative Ethics and When Cultures Collide . He advises students on cultural migration and ethical pluralism, with notable contributions to encyclopedic references like The Child: An Encyclopedic Companion .

• Critical Medical Humanities
• Voice-Hearing Phenomenology
• Voice-Hearing Hermeneutics
• +۲ مورد دیگر

Professor Angela Woods serves as Professor of Medical Humanities in Durham University's Department of English Studies, with an associate appointment in the Department of Philosophy. She directs both the Institute for Medical Humanities and the £9.5m Wellcome Trust-funded Discovery Research Platform for Medical Humanities (2023-2030). Education: PhD in Literary and Cultural Studies, University of Melbourne Her research integrates three core domains: clinical-experiential-cultural analyses of voice-hearing and psychosis; narrative frameworks for understanding health; and interdisciplinary research dynamics. She pioneers work on voice-hearing phenomenology/hermeneutics, narrative mental health approaches, and critical medical humanities, emphasizing non-clinical voice experiences and spiritual dimensions. Her scholarship challenges traditional medical paradigms through literary-cultural lenses while maintaining clinical relevance. Recent publications (2020-2025) reveal sustained focus on voice-hearing across the psychosis continuum, particularly non-clinical experiences, spiritual voices, and narrative uncertainty. She employs innovative interdisciplinary methods bridging literary studies, psychology, linguistics, and clinical practice, establishing critical medical humanities as a distinct field with robust theoretical and practical applications. Professor Woods currently co-supervises four PhD students: Katharine Cheston (women's shame/stigma in complex conditions), Ariel Swyer (non-clinical voice-hearing), Georgia Poplett (postpartum psychosis narratives), and Sarah White. Her major funding includes the Wellcome Trust's £9.5m Discovery Platform award (2023-2030) and the decade-long Hearing the Voice project (2012-2022). She leads Durham's Institute for Medical Humanities and Discovery Research Platform, fostering transdisciplinary collaboration through The Polyphony digital publication and Bloomsbury book series. Previously, she co-directed Hearing the Voice and curated the world's first major voice-hearing exhibition, demonstrating commitment to public engagement and innovative knowledge dissemination.