جست‌وجوی استاد و پژوهشگر

Hugo Larochelleمشاهده پروفایل

دانشیار

• Neural Networks
• Deep Learning
• Machine Learning
• +۴ مورد دیگر

Hugo Larochelle is an Associate Professor at the Université de Montréal's Department of Computer Science and Operations Research (DIRO) within the Faculty of Arts and Sciences. His expertise spans Neural Networks, Deep Learning, and Machine Learning, with contributions to fields like Computer Vision and Natural Language Processing. A graduate of DIRO (Bacc 2004, PhD 2009), he held roles at the University of Sherbrooke (2011–2016) and co-founded Whetlab (acquired by Twitter in 2015). Currently at Google Brain, he balances academic and industrial research, leading projects like the UNIQUE initiative exploring neuroscience-AI intersections. He actively contributes to Quebec’s AI ecosystem through MILA and has received prestigious awards, including the 2019 Diplômé d'honneur. His work emphasizes ethical AI, reproducibility, and interdisciplinary applications. Education: Baccalauréat (Computer Science), Université de Montréal, 2004 Doctorat (Computer Science), Université de Montréal, 2009 Research Interests: Hugo’s work focuses on advancing deep learning techniques for real-world applications, including environmental monitoring (e.g., tree crown segmentation via drone imagery), AI ethics, and model unlearning. He explores intersections between neuroscience and AI, leveraging interdisciplinary approaches to solve complex problems. Recent efforts emphasize benchmark standardization (e.g., EEVEE/GATE) and improving model efficiency through architecture innovations like SoftMoE. Articles Trends: Recent publications highlight contributions to instance segmentation (SAM models), ethical AI (unlearning frameworks), and interdisciplinary applications (e.g., bird species modeling with remote sensing). His work bridges theoretical advancements with practical tools for industries and environmental science. Scientific Awards: 2019 Diplômé d'honneur (Université de Montréal). Advising & Grants: Supervised PhD students in topics like neural networks, code modeling, and program execution (e.g., Sara Hooker, David Bieber). Co-PI on the UNIQUE project (2019–2024, FRQNT-funded), exploring neuro-AI synergies. Recipient of CIFAR funding for ICRA research (2017–2022). Labs & Collaborations: Active contributor to MILA as an associate member. Leads interdisciplinary efforts in AI for environmental challenges and healthcare imaging optimization.

• Computer Science
• Creativity
• Artificial Intelligence
• +۳ مورد دیگر

Konstantinos (Kos) Zachos is a Research Fellow at Bayes Business School, City, University of London, and serves as Chief Technology Officer (CTO) for CebAI (National Centre for Creativity enabled by AI) and JECT.AI, a university spin-out. His primary research focuses on computer science and creativity, developing digital tools to enhance creative problem-solving across sectors including journalism, sports, healthcare, and manufacturing. He holds a PhD from City, University of London (2004–2007). Employment History: Chief Technology Officer, City, University of London (Oct 2020–present) Research Fellow, City, University of London (Oct 2007–present) Research Interests: AI-driven creativity tools Information retrieval and NLP applications Design thinking for innovation Technology adoption in non-creative industries His work emphasizes practical applications, such as JECT.AI’s AI tools for journalism and CebAI’s focus on creativity enhancement. Key Projects: Designing digital tools for elite sports coaching (e.g., C&C '22) AI systems for newsroom creativity (C&C '22, Computation + Journalism 2020) Health-and-safety tools for manufacturing (CHI '17) Mobile apps for dementia care (CHI '13) Advising & Grants: Over 15 years of academic-industry collaboration Principal investigator for CebAI (funded by Research England) Experience in EU and national research grants Labs & Teams: CebAI National Centre QUEST Research Group JECT.AI Development Team

• Geometric Measure Theory
• Optimal Transport
• Partial Differential Equations (PDEs)
• +۳ مورد دیگر

Paolo Bonicatto is an Assistant Professor in the Department of Mathematics at the University of Trento . His teaching responsibilities include courses such as Analisi matematica 2 for Industrial Engineering students, focusing on differential and integral calculus for functions of several variables and applications to physics. He also contributes to advanced programs in Mathematics at the Master's level, including Geometric Measure Theory and Optimal Transport , emphasizing problem-solving and mathematical modeling skills. His research interests span Geometric Measure Theory , Optimal Transport , and Partial Differential Equations (PDEs) , with a focus on topics like current transport, regularity theory for transport equations, and applications to material science. Recent work involves the analysis of advection-diffusion equations, homogenization of elasto-plastic evolutions, and the structure of divergence-free measures in low dimensions. His publications highlight contributions to the well-posedness of transport equations, renormalization techniques for vector fields, and the study of BMO-type norms and Poincaré inequalities. Notably, his work addresses foundational questions in calculus of variations and functional analysis, such as representations of total variation and decomposition results for vector fields. While no scientific awards or grants are explicitly listed, his academic output reflects active engagement with cutting-edge problems in mathematical analysis. He collaborates on interdisciplinary projects, bridging pure mathematics and applications in physics and engineering. No lab affiliations or student advisements are documented in the provided materials.

Aad van der Vaartمشاهده پروفایل

استاد

• High-dimensional statistics
• Nonparametric Bayesian statistics
• Statistical genetics
• +۵ مورد دیگر

Aad van der Vaart is a distinguished Professor of Statistics at Delft University of Technology (since 2021). Previously, he held Full Professorships at Leiden University (2012–2021) and Vrije Universiteit Amsterdam (1996–2012). His research focuses on foundational statistical theory and applications, including high-dimensional statistics, Bayesian methods, inverse problems, and genomics. He has made seminal contributions to nonparametric Bayesian inference, empirical processes, and semiparametric theory. Van der Vaart has authored influential textbooks such as Asymptotic Statistics (1998) and Fundamentals of Nonparametric Bayesian Inference (2017, with S. Ghosal). His work bridges theoretical rigor and practical applications, with over 34,830 citations (Google Scholar, 2023) and an H-index of 60. Key honors include the Spinoza Prize (2015, Netherlands’ highest science award), DeGroot Prize (2020), and membership in the Royal Netherlands Academy of Sciences. His academic journey includes roles such as Miller Fellow at UC Berkeley (2000), visiting positions at leading universities, and leadership in statistical societies. His research group actively explores modern challenges in statistical theory and methodology, including causal inference, adaptive estimation, and large-scale data analysis. Notable grants include an ERC Advanced Grant (2012) for Bayesian inverse problems. Collaborations span academia and industry, emphasizing interdisciplinary impact. While specific lab affiliations are not explicitly stated, his work is rooted in foundational mathematical statistics with broad applicability.

Yuhan Dingمشاهده پروفایل

عضو هیئت علمی

• Applied Mathematics
• Data Science
• Numerical Analysis
• +۳ مورد دیگر

Yuhan Ding is an Associate Teaching Professor of Applied Mathematics and Program Director of the Master of Data Science program at Illinois Institute of Technology's College of Computing. Their research focuses on numerical analysis, adaptive algorithms, and computational methods. Ding has contributed to the development of adaptive approximation techniques and integration libraries like GAIL, emphasizing guaranteed error control and algorithmic efficiency. Education details are not explicitly provided in the text, but their work aligns with advanced computational mathematics and data science education. Research interests include multivariate approximation, algorithm design, and mathematical modeling. Advising and grant details are not specified here. The GAIL library demonstrates expertise in creating robust computational tools for scientific applications.

Ziyue Liمشاهده پروفایل

استادیار

• High-dimensional Data Mining
• Statistics
• Machine Learning
• +۲ مورد دیگر

Jun. Prof. Dr. Ziyue Li is a Junior Professor in Machine Learning in Smart Markets at the Information Systems Department of WiSo Faculty, University of Cologne, Germany (2022–present). They also serve as Chief Machine Learning Scientist at EWI, Germany. Their academic career includes researcher positions at Hong Kong Science and Technology Park Corporation/SenseTime (2021–2022), Nokia Bell Labs (2019), and doctoral studies at The Hong Kong University of Science and Technology (2017–2021). Dr. Li's research focuses on high-dimensional data mining , machine learning , and smart mobility . Their work combines tensor analysis, graph modeling, and spatiotemporal prediction to solve complex problems in transportation systems and data analytics. They have developed innovative approaches for passenger flow prediction and travel pattern analysis. Their publications demonstrate a strong focus on tensor-based machine learning methods applied to mobility data. Key trends include Integration of graph theory with tensor decomposition Development of spatiotemporal prediction models Applications in urban transportation analytics Hybrid transfer learning approaches Multi-clustering methods for travel pattern analysis Data completion techniques for complex networks Scientific recognition includes Multiple INFORMS Data Mining Section awards IEEE CASE Best Conference Paper Award Hong Kong Ph.D. Fellowship Scholarship HKUST Excellent Research Award Three Minute Thesis Competition recognition

C. Chet Millerمشاهده پروفایل

استاد

• Organizational Behavior
• Strategic Management
• Cognitive Diversity
• +۵ مورد دیگر

C. Chet Miller is a Professor at the C.T. Bauer College of Business , University of Houston. He has previously held faculty roles at Baylor University and Wake Forest University, where he served as Director of the Center for Executive Education and Associate Dean for Faculty Affairs, respectively. Miller is an active member of the Academy of Management and Strategic Management Society, with editorial board roles at multiple journals. Education: BA and PhD from the University of Texas Research Interests focus on cognitive diversity in leadership, organizational control systems, strategic decision processes, and how organizations pursue seemingly impossible goals. His work bridges theoretical rigor with practical applications in organizational adaptation and leadership development. Recent Publications explore topics like stretch goals in uncertainty management, strategic dissent, and cognitive diversity among senior leaders. These works appear in top-tier journals such as Academy of Management Annals and Strategic Management Journal , reflecting his expertise in bridging organizational theory with real-world challenges. Awards and Honors include the Outstanding Young Researcher Award (Baylor) and Best Paper Awards (Academy of Management Review, Academy of Management Annals). He has received teaching recognition from Wake Forest University, University of Houston, and Duke University, where he served as a guest instructor. Professional Contributions extend to corporate organizations like ABB, Bank of America, and Krispy Kreme through executive development programs. His editorial roles and leadership in academic associations underscore his influence in organizational research and strategic management.

Pedro Alzariمشاهده پروفایل

استاد

• Structural Biology
• Molecular and Structural Biology
• Microbial Physiology
• +۱۰ مورد دیگر

Pedro Alzari is a leading researcher and Head of the Structural Microbiology Unit within the Department of Structural Biology and Chemistry at the Institut Pasteur in Paris, France. He is a Principal Investigator actively leading research on the structural biology of bacterial pathogens, with a primary focus on Mycobacterium tuberculosis and other Actinobacteria. His work is central to understanding microbial physiology, pathogenesis, and cell signaling mechanisms. His research interests lie at the intersection of structural biology, biochemistry, and microbiology. Dr. Alzari's work focuses on elucidating the three-dimensional structures and functional mechanisms of proteins involved in critical bacterial processes such as cell division, cell wall synthesis, and metabolic regulation. His group employs a wide array of techniques, including X-ray crystallography, cryo-electron microscopy (cryo-EM), and biophysical methods, to study key systems like the PknA/PknB serine/threonine kinases and the divisome-elongasome machinery in Corynebacteriales. A significant theme in his recent work is the discovery of eukaryotic-like signaling and structural systems in bacteria, such as the repurposed gephyrin-like protein in cell division. The trends in Dr. Alzari's recent publications (2023-2025) reveal a strong emphasis on integrative structural biology to solve complex problems in antimicrobial resistance and infectious disease. His work bridges fundamental science with drug discovery, particularly in developing new inhibitors for M. tuberculosis DNA gyrase and Plasmodium proteases. The research consistently involves high-resolution structural analysis (cryo-EM and crystallography) to understand enzyme mechanisms, inhibitor binding, and protein-protein interactions at the atomic level, providing a rational basis for therapeutic intervention. Dr. Alzari has secured significant funding for his research, leading major projects such as the ongoing 'PknA/PknB in mycobacterial cell division' and the completed 'MM4TB' project. He mentors a dynamic team of researchers, including PhD students, postdoctoral fellows, and research engineers, fostering the next generation of scientists in the field. His laboratory is a hub for structural microbiology, contributing to a deeper understanding of bacterial cell biology. The group's work on the divisome and elongasome in Actinobacteria has revealed crucial crosstalk between these machineries, identifying potential new targets for anti-mycobacterial drugs. The team's use of the Institut Pasteur's core facilities, such as the nanoimaging Cryo-EM core facility, underscores their commitment to cutting-edge methodology.

Matti Hämäläinenمشاهده پروفایل

استاد

• Neuroscience
• Magnetoencephalography
• Auditory Cortex
• +۴ مورد دیگر

Matti Hämäläinen is a Professor at the Department of Neuroscience and Biomedical Engineering , Aalto University. He is a leading expert in Magnetoencephalography (MEG) , with a focus on sensor design, neural connectivity, and clinical applications. His work contributes to understanding brain disorders like autism and epilepsy. Doctorate in Materiaalifysiikka, Teknillinen Korkeakoulu (1989) Diplomi-insinööri in Teknillinen Fysiikka, Teknillinen Korkeakoulu (1983) Hämäläinen's research spans MEG technology , auditory and visual cortex dynamics , and functional connectivity analysis . He develops open-source tools like MNE-Python and HNN-Core for neural data interpretation. Scientific Awards : None explicitly mentioned. He has led projects such as NIH Scalable Software for MEG/EEG and Device-Independent Real-Time MEG EEG Source Localization , with media coverage in outlets including Massachusetts General Hospital and Targeted News Service.

Philippe Snauwaertمشاهده پروفایل

پژوهشگر

• Didactics of Science
• Chemistry Education
• Semiotics in Science Education
• +۷ مورد دیگر

Philippe Snauwaert is a researcher at the Research Institute in Didactic and Education at the University of Namur (UNamur), where he has been actively involved in educational research since the 1980s. His work spans chemistry education, semiotics in science, teacher training, and student orientation to higher education. He holds a Doctor of Science degree from UNamur and continues to lead and contribute to significant research projects. Doctor of Science, University of Namur, 1992 His research interests lie at the intersection of science education and linguistic-semiotic analysis, particularly in how students interpret chemical symbols and solve stoichiometry problems. He investigates the evolution of chemical language and the use of visual tools like slowmation to teach dynamic chemical processes. His work also extends to reflective teaching practices and collaborative training for educators. The recent publications and projects highlight a strong trend toward improving science education through innovative didactic methods, teacher development, and curriculum analysis. His work increasingly integrates interdisciplinary approaches, especially in animal welfare education and educational transitions from secondary to higher education. Philippe Snauwaert has not received any explicitly mentioned scientific awards in the provided text. He has supervised or collaborated on research with several scholars and students, though specific advisees are not listed. He has been involved in multiple research grants and projects, including continuous training initiatives and university certificate programs in animal welfare. His leadership roles in projects like CUBEA and Salle des Pros demonstrate sustained engagement in educational innovation and professional development. He is actively involved in research teams such as the Department of Education and Technology and collaborates within networks focused on science didactics, including ARDiST. His work is often conducted in collaboration with researchers like Dehon J., Biemar S., Pondeville S., and Diederich C.

• Statistics
• Sports science and exercise
• Ecological applications
• +۷ مورد دیگر

Paul Wu is an Associate Professor in the School of Mathematical Sciences at Queensland University of Technology (QUT), Faculty of Science, where he also serves as an industry research fellow in the strategic partnership between the Centre for Data Science (CDS) and AIS/QAS. He leads the sports systems domain within CDS and applies statistical and machine learning models to complex systems across sports, marine science, and defence sectors. PhD, Queensland University of Technology Master of Engineering Science (Computer and Comm Engineering), Queensland University of Technology Bachelor of Engineering (Electrical and Computer Engineering), Queensland University of Technology His research focuses on Bayesian statistics, dynamic Bayesian networks, state space modelling, and simulation techniques. He works closely with domain experts to solve real-world problems in sports performance, ecological resilience, and human systems. His interdisciplinary work spans sports science , marine ecology , and defence applications . Paul’s recent publications demonstrate a strong trajectory in predictive analytics for elite sports and ecosystem modelling, particularly using Bayesian frameworks. His work on swimming performance prediction has informed national training strategies and contributed to competitive success. He has also advanced methods in clustering, model adaptation, and psychosocial risk assessment. His scientific contributions have been recognized through impactful collaborations with elite sports organizations including the Australian Institute of Sport, Swimming Australia, and the West Coast Eagles. Testimonials highlight his role in transforming data analytics in sports injury recovery and performance optimization. Applied Bayesian models in elite sports decision-making Developed predictive tools for marine ecosystem resilience Collaborated on over 30 industry and government projects Supervises research in complex sports data analytics Paul leads a dynamic research environment focused on translating statistical innovation into practical impact across diverse domains.

Lionel Pichonمشاهده پروفایل

پژوهشگر

• Electromagnetics
• Electromagnetic Compatibility
• Wireless Power Transfer
• +۴ مورد دیگر

Lionel Pichon is a leading researcher at the Laboratory of Electrical and Electronic Engineering of the University of Paris. His primary affiliations include the Department of Electrical and Electronic Engineering of Paris, where he specializes in advanced electromagnetic research. His work focuses on Electromagnetics , Electromagnetic Compatibility (EMC) , and Wireless Power Transfer , with particular emphasis on composite materials, biomedical applications, and automotive systems. Expertise in numerical methods (FDTD, FIT, DGTD) for electromagnetic simulations Pioneer in shielding effectiveness analysis for composite materials Developer of AI-driven approaches for dielectric property characterization Over 70 publications since 2017 highlight his contributions to fields like inductive power transfer systems, medical device EMC, and GPR imaging techniques. Collaborates extensively with institutions globally, including research on antenna design for implantable medical devices and electromagnetic compatibility in healthcare facilities. Current research trends emphasize machine learning integration with traditional electromagnetic analysis to optimize system performance and safety standards.

• Geotechnical Engineering
• Soil Mechanics
• Marine Sediments
• +۵ مورد دیگر

Dr. Madhu Murthy is a Lecturer in the Department of Civil, Maritime and Environmental Engineering within the Faculty of Engineering and Physical Sciences at the University of Southampton. His research focuses on advanced geotechnical investigations using cutting-edge imaging technologies and experimental methods to address complex engineering challenges in transportation infrastructure and marine environments. Research Interests Dr. Murthy's research spans multiple domains within geotechnical engineering, with particular expertise in: Advanced characterization of soil and granular materials using X-ray micro-computed tomography Mechanical behavior of railway ballast and development of sustainable reuse strategies Marine sediment mechanics and methane hydrate formation processes Unsaturated soil mechanics and water retention characteristics Gas migration phenomena in porous media His work integrates experimental techniques with computational analysis to provide fundamental insights into material behavior under various loading and environmental conditions. Dr. Murthy has established collaborations with international research teams and industry partners to address pressing infrastructure and energy challenges. Publication Trends Dr. Murthy's recent publications demonstrate a strong focus on applying advanced imaging techniques, particularly X-ray computed tomography, to solve complex geotechnical problems. His research spans from fundamental soil mechanics investigations to practical railway engineering applications. A notable trend is the integration of synchrotron imaging with geomechanical testing to visualize and quantify material behavior at the micro-scale. His work on methane hydrates bridges geotechnical engineering with energy resource exploration, while his railway ballast research addresses sustainability challenges in transportation infrastructure. Academic Supervision Dr. Murthy currently supervises PhD students working on cutting-edge geotechnical research topics: Rashid Salum Abeid: Investigating railway ballast behavior under various loading conditions Komeil Valipourian: Researching advanced geotechnical characterization methods His supervisory approach emphasizes both theoretical understanding and practical application, preparing students for successful careers in academia and industry.

• Digestive Oncology
• Colorectal Cancer
• Crohn's Disease
• +۵ مورد دیگر

André D'Hoore is a Professor at the Faculty of Medicine , KU Leuven , and affiliated with the LKI - KU Leuven Cancer Institute . He serves as a member of the Council of the Faculty of Medicine and the Department of Oncology, focusing on Digestive Oncology and surgical strategies for gastrointestinal diseases. Academic Rank: Professor Department: Oncology Key Affiliations: Digestive Oncology Unit, KU Leuven Cancer Institute His research spans digestive oncology , Crohn's disease , and colorectal cancer , emphasizing organ-preserving strategies , precision medicine , and innovative surgical techniques . Recent projects include studies on immunotherapy in colorectal cancer and anastomotic configurations to prevent Crohn's recurrence. Scientific awards: None explicitly mentioned. Teaching activities include courses in digestive diseases , gastrointestinal care , and problem-solving in surgery . He supervises PhD students like Bislenghi, G. and collaborates on clinical trials in inflammatory bowel disease and transplantation .

• Psychometrics
• Organizational Psychology
• Item Response Theory
• +۷ مورد دیگر

Hanyi Min is an Assistant Professor at the University of Illinois Urbana-Champaign with dual appointments in the School of Labor and Employment Relations and the Department of Psychology. Her research integrates psychometrics, organizational psychology, and machine learning to address critical challenges in human resources and employment relations. Her primary research focuses on item response theory, measurement invariance across demographic variables, and machine learning applications for personnel selection. Key interests include employee turnover prediction, work passion validation, political diversity in organizations, and age-related measurement issues. She develops advanced psychometric techniques like item-focused trees to ensure fair assessment across diverse populations while leveraging recommender systems for workforce analytics. Recent publications reveal a strong trend toward hybrid methodologies combining classical psychometrics with machine learning to solve practical HR problems. Her work emphasizes predictive validity in personnel selection, context-specific measurement invariance, and the socio-political dimensions of workplace diversity. Current research bridges psychological theory with computational approaches to improve organizational decision-making.