جست‌وجوی استاد و پژوهشگر

Paul G Dupuisمشاهده پروفایل

استاد

• Probability Theory
• Stochastic Processes
• Control Theory
• +۴ مورد دیگر

Paul G Dupuis is the IBM Professor of Applied Mathematics at Brown University. His research focuses on applications of probability theory, stochastic processes, control theory, and numerical methods. He holds affiliations with the American Mathematical Society, Society for Industrial and Applied Mathematics (SIAM), and the Institute for Mathematical Statistics (IMS). His work emphasizes large deviation theory, Markov chain approximations, Monte Carlo simulation, and partial differential equations. Education: Ph.D. in Applied Mathematics from Brown University (1985), M.S. from Northwestern University (1982), and B.S. from Brown University (1981). Research Interests: Control of deterministic and stochastic processes, differential games, numerical methods, operations research, and stochastic processes. His contributions include foundational work on large deviation theory, risk-sensitive control, and queueing networks. Awards: Elected SIAM Fellow (2010), Fellow of the Institute for Mathematical Statistics (2011), IBM Professor of Applied Mathematics (2012), and AMS Fellow (2014). Previously held an NSF Postdoctoral Fellowship (1985-1988). Grants: Current funding from the Army Research Office and National Science Foundation. Key collaborations include work on stochastic approximation, constrained diffusions, and reflected Brownian motion. Teaching: Courses include Operations Research: Probabilistic Models, Information Theory, and Advanced topics in Probability and Stochastic Control.

Matteo Magnaniمشاهده پروفایل

استاد

• Network Science
• Social Network Analysis
• Computational Social Science
• +۱۰ مورد دیگر

Matteo Magnani is a Professor in the Division of Computing Science at the Department of Information Technology, Uppsala University. He leads the Uppsala University Information Laboratory and is a founding member of the Uppsala University Computational Social Science Lab. His research spans network science, artificial intelligence, data science, and computational social science, with a focus on social data mining and multilayer networks. PhD in Computer Science, University of Bologna, 2006 Graduated with honours in Information Sciences, University of Bologna, 2002 Studies in Computer Science at University of Marne la Vallée and Imperial College London Matteo Magnani's research interests include social network analysis, multilayer and probabilistic networks, community detection, visual analytics, and the application of AI to digital media and climate communication. His work bridges computer science and social sciences, particularly in analyzing online discourse and digital intermediaries. He has contributed significantly to the understanding of network structures, uncertainty in networks, and the ethical dimensions of algorithmic analysis. His recent publications highlight trends in fairness in community detection, visual saliency in network layouts, emotional reactions to climate visuals online, and deep learning applications in social media. Topics frequently involve YouTube, Twitter, and online public debates, using advanced network and machine learning methods. Rotary Prize for best student of the Science Faculty Best Paper Award Funniest Presentation Award Best Poster Award Pedagogical Prize from UTN Distinguished University Teacher (Sweden) Docent title (Sweden) Magnani has supervised numerous students and collaborated widely, particularly with Luca Rossi, Alexandra Segerberg, and Davide Vega. He has secured funding from major sources including VR, H2020, STINT, and MIUR. He leads active research labs focused on information systems and computational social science, fostering interdisciplinary collaboration and innovation in network-based research.

Suliana Manleyمشاهده پروفایل

استاد

• Super-resolution Microscopy
• Single-molecule Biophysics
• Protein Assembly
• +۵ مورد دیگر

Suliana Manley is a Full Professor at the École Polytechnique Fédérale de Lausanne (EPFL) , affiliated with the School of Basic Sciences and the Laboratory of Experimental Biophysics . She also holds teaching and research roles in EPFL's School of Life Sciences and Swiss Plasma Center , focusing on interdisciplinary biophysical studies. Education : PhD in Physics (2004), Harvard University Bachelor's in Physics & Mathematics (1997), Rice University Manley's research centers on super-resolution fluorescence imaging , single-molecule tracking , and quantitative biophysics . Key themes include: Understanding protein assembly dynamics at cellular membranes Elucidating viral assembly mechanisms (e.g., HIV-Gag) Developing 3D imaging algorithms and high-density data reconstruction tools like PALMsiever and FALCON Quantifying nanoscale organization in systems like telomeres and centrioles Her work bridges optical physics , computational image analysis , and cellular biology , with notable Nature and PNAS publications. Collaborations span bioengineering , genetics , and medical research . Scientific Awards : Featured in Nature Methods Research Highlights (3x) Very Important Paper and Cover Article (ChemBioChem, 2012) Postdoctoral Fellow, NIH and MIT Advising & Collaborations : Current PhD students in biophysics, cellular biology, and bioengineering Former students: Anna Archetti, Aleksandr Benke, Andrea Callegari, and others Co-founder of tools for high-density super-resolution microscopy and live-cell imaging Labs & Teams : Leads the Laboratory of Experimental Biophysics at EPFL, integrating physics-based methods into biological questions. The lab focuses on quantitative imaging , computational modeling , and software development for nanoscale analysis.

George Cantwellمشاهده پروفایل

استادیار

• Network Science
• Complex Systems
• Statistical Inference
• +۴ مورد دیگر

Dr. George Cantwell is an Assistant Professor in the Department of Engineering at the University of Cambridge, affiliated with Cambridge Infectious Diseases. He specializes in computational methods for inference problems, particularly in disease spreading across networks. Education: PhD in Physics from the University of Michigan; postdoctoral fellowship at the Santa Fe Institute His research focuses on network science , complex systems , and statistical inference , with an emphasis on computational approaches. His work spans theoretical and applied domains, including: Message passing algorithms for heterogeneous networks Bias correction in social network analysis (friendship paradox) Statistical inference of network structure from noisy data Modeling judicial voting behavior through network interactions Computational cognitive neuroscience of category learning Recent publications highlight interdisciplinary applications in epidemiology, physics, and cognitive science. He actively mentors students in networks, complex systems, and statistical inference.

David Al-Attarمشاهده پروفایل

استاد

• Theoretical geophysics
• Computational geophysics
• Continuum mechanics
• +۷ مورد دیگر

David Al-Attar is a Professor at the University of Cambridge's Department of Earth Sciences, actively involved in theoretical and computational geophysics research. He serves as a supervisor within the Cambridge NERC Doctoral Landscape Awards (Training Partnerships) program, particularly in the CREATES initiative focusing on climate and environmental science. Education: While specific educational details aren't provided in the text, his extensive publication record and professorial position at Cambridge indicate advanced training in geophysics and applied mathematics. Research Interests: Professor Al-Attar's work spans several interconnected areas within geophysics. His primary focus includes theoretical and computational problems in geophysics, with particular emphasis on continuum mechanics as applied to Earth systems. He develops new physical and mathematical theories for understanding Earth processes, including rigorous function space methods for inverse problems and uncertainty quantification. His sea level change research aims to constrain ice sheet evolution during the last glacial period to better understand modern contributions to sea level rise. Additionally, he investigates solid Earth dynamics including seismic free oscillations, body tides, and Earth rotation, contributing to our understanding of deep Earth structure and mantle dynamics. Research Themes: His publications demonstrate expertise in adjoint methods, glacial isostatic adjustment, mantle viscosity, planetary seismology, and computational methods for geophysical problems. Recent work emphasizes 3-D Earth modeling, sensitivity analysis, and the integration of satellite observations with theoretical models. Current Projects: Potential projects for students include inverse problems related to deglacial sea level change with focus on uncertainty quantification, modern sea level monitoring using satellite data, and solid Earth dynamics particularly regarding outer core viscosity in tidal and rotational dynamics. Contact: He can be reached at da380@cam.ac.uk for research inquiries and collaboration opportunities.

• Sustainable Machining Processes
• Tool Wear Monitoring
• Surface Roughness Optimization
• +۳ مورد دیگر

Doç. Dr. Muhammed Aras is an Associate Professor in the Department of Mechanical Engineering at Baskent University (Başkent Üniversitesi), with a research focus on sustainable machining processes, tool wear monitoring, and surface roughness optimization. His work spans advanced manufacturing technologies, energy storage systems, and biomedical device design. PhD in Manufacturing Engineering (2018), Gazi Üniversitesi MSc in Mechanical Education (2013), Gazi Üniversitesi BSc in Mechanical Engineering (2010), Tabriz Islamic Azad University Research interests include sustainable machining (dry/hard turning, cooling-lubrication strategies), tool wear analysis (CBN, ceramic and coated inserts), and surface integrity optimization using AI-based methods (firefly algorithm, TOPSIS, Grey Relational Analysis). His 15 most recent articles (2017-2024) examine topics like: Surface roughness prediction in dry hard turning Energy storage technology viability assessments Cutting parameter optimization for various steels Acoustic/vibration monitoring in machining He has received scientific awards including the Teşvik Ödülü (Encouragement Award, 2015). His patent on an automatic orthognathic surgery articulator and book chapters on tool monitoring systems demonstrate his multidisciplinary impact.

Maher Maaloufمشاهده پروفایل

دانشیار

• Machine Learning
• Data Mining
• Multivariate Statistics
• +۳ مورد دیگر

Dr. Maher Maalouf serves as an Associate Professor in the Department of Industrial and Systems Engineering at Khalifa University, where he has been a faculty member since 2011. He holds a PhD in Industrial Engineering from the University of Oklahoma and teaches core courses including Six Sigma Methodology and Applications (ISYE 445), Business Analytics (ESMA 610), and Advanced Business Analytics (ESMA 711). His academic credentials include: PhD in Industrial Engineering, University of Oklahoma (USA) MSc in Industrial Engineering, University of Oklahoma (USA) BBA in Management Information Systems, University of Oklahoma (USA) Dr. Maalouf's research integrates advanced analytical methodologies with industrial applications, focusing on classification and regression algorithms in machine learning, statistical process optimization through Lean Six Sigma frameworks, and operational excellence implementations. His work bridges theoretical data science with practical business process improvement across manufacturing and service sectors. He maintains active research supervision through the Socio-Technical Systems Lab, currently mentoring PhD students Toheeb Olajide Salahudeen and Kehinde Ganiyu Ismaila alongside Research Associate Assia Chadly. No scientific awards were documented in the source material.

Istvan Albertمشاهده پروفایل

استاد پژوهشی

• Bioinformatics
• Genomics
• Computational Biology
• +۵ مورد دیگر

Istvan Albert is a Research Professor of Bioinformatics at Pennsylvania State University , affiliated with the Department of Biochemistry and Molecular Biology . He leads the Bioinformatics Consulting Center and teaches BMMB 852: Applied Bioinformatics . Research Interests: Specializing in bioinformatics, large-scale biological data analysis, microarray and sequence analysis, scientific programming, algorithm development, and database-driven web development. His work spans gene ontology visualization , RNA-Seq analysis , and coronavirus research . Software Development: Created GeneScape for gene function visualization and bio for bioinformatics workflows. Maintains the Biostar Handbook series and the Biostars Q&A Forum , a leading bioinformatics resource.

Mohamed F. Mokbelمشاهده پروفایل

استاد

• Database Systems
• Spatial Data
• GIS (Geographic Information Systems)
• +۳ مورد دیگر

Mohamed F. Mokbel is a Distinguished McKnight University Professor in the Department of Computer Science and Engineering at the University of Minnesota - Twin Cities , where he also serves as the Director of Graduate Studies. He is recognized as an IEEE Fellow and ACM Distinguished Member for his contributions to spatially- and privacy-aware systems. His research focuses on database systems , spatial data management , and GIS (Geographic Information Systems) , with significant work in spatiotemporal data, location-based services, and machine learning for spatial applications. His most recent publications address scalable BERT-based trajectory imputation , spatial logistic regression frameworks , and spatiotemporal big data decay techniques . Key Awards: Distinguished McKnight University Professor (2023) ACM SIGSPATIAL 10-Year Impact Award (2022) IEEE Fellow (2020) ACM Distinguished Member (2017) NSF CAREER Award (2010) Selected Conference Papers: Recathon (2015, IEEE MDM Best Paper) ST-Hadoop (2017, SSTD Best Paper) KAMEL (2023, ACM SIGMOD Demo) Academic Service: Editor-in-Chief, ACM Transactions on Spatial Algorithms and Systems (2024–) General Co-Chair, ACM SIGSPATIAL 2025 Past Chair, ACM SIGSPATIAL (2014–2017)

Luca Sebastianiمشاهده پروفایل

استاد

• Plant Physiology
• Molecular Plant Stress Responses
• Nutraceuticals in Plants
• +۳ مورد دیگر

Luca Sebastiani is a Full Professor in Horticultural Sciences (AGR/03) at Scuola Superiore Sant'Anna in Pisa, Italy, since 2014. He currently coordinates the PhD Course in AgroBioSciences and has previously served as Director of the Institute of Life Sciences (2016-2021). His academic career includes roles as Associate Professor (2002-2014) and Assistant Professor (1998-2002) at the same institution. PhD in Plant Biology from Scuola Superiore Sant'Anna (1996) MSc in Agricultural Sciences from University of Pisa (cum laude, 1991) Postdoctoral research in agricultural biotechnology (1996-1998) Research Interests: Focus on plant-environment interactions, particularly abiotic and biotic stress responses in crops. Key areas include: Physiological and molecular responses to climate change stressors Nutraceutical enhancement of food crops Plant germplasm conservation using molecular markers Agriculture 4.0 integrating AI, IoT, and robotics Phytoremediation using poplar and Brassica species Scientific Contributions: His work bridges molecular mechanisms (aquaporin function, heavy metal transport) with ecosystem-level applications (precision irrigation, contaminant phytoremediation). Recent publications emphasize genome sequencing, stress tolerance modeling, and nutraceutical food development. ISHS Medal for SapFlow Workshop organization (2011) Giovanni Spitali Foundation Award for PhD dissertation (1998) Collaborations: Extensive international collaborations with institutions like Beijing Forestry University, Comenius University, and Purdue University. Currently supervises projects in plant phenotyping, omics technologies, and sustainable crop management.

Elena Katokمشاهده پروفایل

استاد

• Behavioral Operations Management
• Behavioral Market Design
• Auctions
• +۶ مورد دیگر

Elena Katok is a Professor of Supply Chain Management at the University of Texas at Dallas, Naveen Jindal School of Management. She serves as Co-Director of the Center and Laboratory for Behavioral Operations and Economics (LBOE) and holds editorial positions as Department Editor for Management Science (Operations Department) and Associate Editor for Manufacturing and Service Operations Management. Her research focuses on Behavioral Operations Management (BOM), Behavioral Market Design, and Auctions, with particular emphasis on using laboratory experiments to understand human behavior in operational contexts. Her work bridges the gap between traditional analytical operations models and actual human decision-making in supply chain and procurement settings. The analysis of her recent publications reveals a consistent research trajectory examining how psychological and behavioral factors influence operational decisions. Her work spans auction design, contract theory, trust mechanisms, and behavioral aspects of supply chain coordination. A notable pattern is her focus on the intersection of behavioral economics and traditional operations management problems, particularly how fairness concerns, risk perception, and trust impact procurement and supply chain decisions. Professor Katok has developed and implemented numerous classroom games to teach supply chain management concepts, demonstrating her commitment to translating research into practical pedagogy. She has created simulation tools through the SoPHIE platform to enhance experiential learning in operations management courses. Her teaching portfolio includes OPRE 6371: Purchasing, Sourcing and Contract Management for SCM MS and MBA students, OPRE 7309: Behavioral Operations Management at the PhD level, and OPRE/MECO 6355: Deal Making Strategies. She has also authored several case studies including eBay sniping, Winter Gear, Sears Logistics, Spectrum, and General Hospital to facilitate hands-on learning. As co-editor of The Handbook of Behavioral Operations published by Wiley, she has helped establish Behavioral Operations Management as a significant subfield that incorporates insights from psychology and behavioral economics to study how individuals make decisions in operational contexts.

Sara Chatfieldمشاهده پروفایل

دانشیار

• American Politics
• American Political Development
• Gender and Politics
• +۴ مورد دیگر

Sara Chatfield is an Associate Professor of Political Science at the University of Denver's College of Arts, Humanities and Social Sciences, with additional affiliations in Gender and Women's Studies. Her work bridges American political development, gender politics, and methodological innovation in political science research. Dr. Chatfield earned her Ph.D. and MA in Political Science from the University of California, Berkeley (2014 and 2007 respectively), and her BA in Politics from Oberlin College (2006). Her research focuses on American political development with particular emphasis on gender and politics, public law, and political behavior. American Political Development Gender and Politics Women's Rights History Public Law Political Behavior Methodology and Causal Inference Her recent publications demonstrate a consistent focus on how gender shapes political institutions and processes across historical and contemporary contexts. Early work examined 19th century married women's economic rights reform, while more recent research investigates contemporary issues like bathroom access politics and gender disparities in political campaign staffing. Her scholarship often employs innovative methodological approaches to historical questions, bridging qualitative and quantitative traditions in political science. Dr. Chatfield teaches courses on American politics and law, including Constitutional Law I, Judicial Politics, and a freshman seminar on the politics of bathrooms. Her book In Her Own Name: The Politics of Women's Rights Before Suffrage (Columbia University Press, 2023) and her Cambridge Element The Politics of Bathroom Access and Exclusion in the United States (2024) represent significant contributions to understanding how gender shapes political institutions across historical periods.

• Active Galactic Nuclei
• Black Holes
• Galaxy Formation and Evolution

Professor David Alexander is a distinguished academic at Durham University's Department of Physics, where he serves as Professor and Chair of Board of Examiners. His responsibilities include Head of Section for Astronomy and Director of Postgraduate Research, demonstrating his significant leadership role within the department. Alexander is also responsible for teaching the Stars Lecturer component of the Level 2 Stars and Galaxies course. His primary research interests focus on Active Galactic Nuclei, black holes, and galaxy formation and evolution, representing core areas in modern astrophysics. Alexander's work spans observational and theoretical aspects of high-energy astrophysics, with particular emphasis on understanding the connections between supermassive black holes and their host galaxies across cosmic time. His research leverages data from major international facilities including NuSTAR, ALMA, DESI, and XMM-Newton, conducting multi-wavelength studies that combine X-ray, infrared, optical, and radio observations. Analysis of his most recent publications reveals a strong focus on AGN demographics, obscuration mechanisms, quasar environments, and the role of AGN in galaxy evolution. His work frequently explores the connection between AGN activity and galaxy properties, with particular attention to the cosmic evolution of these relationships. Recent papers demonstrate increasing emphasis on large-scale surveys and statistical approaches to understanding AGN populations. Leverhulme Research Fellowship (2000-2012) Philip Leverhulme Prize (2000-2008) Royal Society University Research Fellowship (2000-2003) Thomson Reuters ESI highly cited researcher over 2002-2012 Professor Alexander has been instrumental in numerous major survey projects including the NuSTAR extragalactic surveys, DESI quasar studies, and the VST ATLAS Quasar Survey. His collaborative work spans international teams and leverages cutting-edge observational facilities across the electromagnetic spectrum. His research group focuses on understanding the physical processes that govern AGN activity and their connection to galaxy evolution, with particular emphasis on obscured AGN populations and their role in the cosmic black hole growth history.

Ravid Shwartz-Zivمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Neural Networks
• +۷ مورد دیگر

Ravid Shwartz-Ziv is an Assistant Professor and Faculty Fellow at NYU's Center for Data Science, with a dual role as Senior Research Scientist at Wand AI. His research bridges theoretical foundations and practical applications in artificial intelligence, focusing on Large Language Models (LLMs), information theory, and neural network interpretability. Ph.D. in Computational Neuroscience, Hebrew University of Jerusalem (2021) B.Sc. in Computer Science and Computational Biology, Hebrew University of Jerusalem (2014) His research spans: Developing min-p sampling for LLM text generation Preventing representation collapse in Transformers Creating contamination-free LLM benchmarks like LiveBench Advancing information-theoretic frameworks for neural networks Exploring representation learning and model adaptation Recent publications demonstrate expertise in LLM efficiency, self-supervised learning, and multi-agent systems. Notable awards include the Google PhD Fellowship, Moore-Sloan Fellowship, and multiple best paper recognitions. He has led research initiatives at Intel and Google AI, focusing on neural network compression, XGBoost comparisons for tabular data, and innovative benchmarking frameworks.

• Geomechanics
• Rock Deformation
• Subsidence Modeling
• +۴ مورد دیگر

Dr. Peter Fokker is a Researcher at Utrecht University's Faculty of Geosciences, specifically within the Department of Earth Sciences and the Experimental Rock Deformation/HPT group. He is affiliated with the Research Programme in Earth Sciences Utrecht (DES/IVAU) and has been actively publishing in geomechanics, subsidence modeling, and induced seismicity for over three decades. His work primarily focuses on the application of geomechanical principles to understand and model subsurface processes related to resource extraction and geothermal energy. Dr. Fokker's research interests span several interconnected domains in geomechanics and subsurface engineering. His primary focus is on experimental rock deformation , studying how rocks behave under various stress conditions. He has made significant contributions to subsidence modeling , particularly in the context of gas field depletion in the Netherlands. His work on induced seismicity has helped understand the relationship between subsurface operations and seismic events. Additional interests include geothermal energy systems , reservoir engineering , and the application of data assimilation techniques to improve subsurface characterization. His research often bridges theoretical models with practical applications in energy resource management. An analysis of Dr. Fokker's recent publications (2020-2025) reveals a strong focus on practical applications of geomechanics to real-world challenges. His work increasingly integrates InSAR technology and data assimilation methods to monitor and model subsidence processes. There's a clear emphasis on geothermal energy applications , reflecting growing interest in sustainable energy solutions. His research also demonstrates a sophisticated approach to modeling complex reservoir behaviors across multiple scales, from laboratory experiments to field-scale operations. The interdisciplinary nature of his work is evident in collaborations spanning geology, engineering, and environmental science. Dr. Fokker has supervised multiple research projects and students throughout his career, as indicated by the "Supervised Work (4)" reference in his profile. His research has been supported by various grants focused on subsidence modeling, geomechanics of energy resources, and induced seismicity. He has been involved in significant collaborative efforts, including the Dutch National Scientific Research Program on Land Subsidence. Dr. Fokker is part of the Experimental Rock Deformation/HPT group at Utrecht University, which conducts laboratory experiments and develops theoretical models to understand rock behavior under various conditions. His work contributes to the broader research ecosystem focused on sustainable resource management and understanding subsurface processes, with particular relevance to the Dutch context of gas extraction and land subsidence.