جستجوی استاد راهنمای دانشگاهی

Marya Besharovمشاهده پروفایل

استاد

• Leadership
• Social Impact
• Hybrid Organizations
• +۷ مورد دیگر

Marya Besharov is a Professor of Organisations and Impact at Saïd Business School, University of Oxford, and Academic Director of the Skoll Centre for Social Entrepreneurship. She holds a BA, MA, and PhD from Harvard University, alongside an MBA from Stanford University. Her work focuses on leadership, social impact, and hybrid organizations, advising global entities on balancing social and financial priorities. Education: PhD in Organizational Behavior, Harvard University MA in Sociology, Harvard University BA in Social Studies, Harvard University MBA, Stanford University Research Interests: Dr. Besharov’s research explores how organizations navigate competing goals, particularly in hybrid models like social enterprises. She investigates organizational identity, institutional logics, and leadership frameworks for systemic change. Her findings appear in Administrative Science Quarterly , Harvard Business Review , and Stanford Social Innovation Review . Engagement & Teaching: She leads executive education programs and workshops on leadership and systems change through the Skoll Centre. Her teaching emphasizes contingency-based frameworks for managing organizational complexity. Labs & Initiatives: Academic Director of the Skoll Centre for Social Entrepreneurship, a global hub for social impact education and research.

Ronald Parrمشاهده پروفایل

استاد

• Reinforcement Learning
• Markov Decision Processes
• Artificial Intelligence
• +۳ مورد دیگر

Ronald Parr is a Professor of Computer Science in the Department of Computer Science at Duke University's Pratt School of Engineering. He has been at Duke since 2000, progressing from Assistant Professor to Associate Professor with tenure, and ultimately to Full Professor. From 2014 to 2017, he served as Department Chair and delivered graduation speeches in 2015, 2016, and 2017. Dr. Parr received his Ph.D. in Computer Science from the University of California, Berkeley in 1998, with a dissertation titled "Hierarchical Control and Learning in Markov Decision Processes" under advisor Stuart Russell. He earned his A.B. in Philosophy, cum laude, from Princeton University in 1990. His primary research focuses on methods for solving large stochastic planning problems using Markov Decision Processes and approximate dynamic programming techniques. His work spans reinforcement learning, value function approximation, game theory, sensing, and robotics. Dr. Parr's research has been consistently funded by major agencies including NSF, DARPA, and ARO, with recent projects focusing on feature encoding for reinforcement learning, neurosymbolic hierarchical reinforcement learning, and reasoning in large, structured, uncertain domains. His publication record demonstrates consistent contributions to top venues including NeurIPS, ICML, and AAAI, with work that bridges theoretical foundations and practical applications. Dr. Parr has received numerous honors including being elected as an AAAI Fellow in 2023, receiving an AAAI Outstanding Paper Honorable Mention in 2013, winning the IJCAI-JAIR Best Paper Award in 2007, receiving an NSF CAREER award in 2006, and being named an Alfred P. Sloan Fellow in 2003. He has advised ten graduate students to completion across various research areas within AI and robotics. His research has been supported by over $1.5 million in direct funding to his lab, with additional collaborative funding from multiple NSF, DARPA, and ARO grants. Dr. Parr has served extensively on program committees for major AI conferences including ICML, NeurIPS, AAAI, and UAI, and has held leadership roles such as Program Co-Chair and General Chair for UAI. Dr. Parr maintains an active research group focused on reinforcement learning and sequential decision making, with ongoing projects in neurosymbolic AI, hierarchical reinforcement learning, and interpretable machine learning models, continuing to bridge theoretical foundations with practical applications in robotics and AI systems.

Daniel M. Kaneمشاهده پروفایل

استاد

• Number Theory
• Combinatorics
• Complexity Theory
• +۳ مورد دیگر

Daniel M. Kane is a Professor at the University of California, San Diego (UCSD), holding a joint appointment in the Department of Mathematics and the Department of Computer Science and Engineering (CSE). His research spans mathematics and theoretical computer science, with a focus on number theory, combinatorics, complexity theory, and computational statistics. He earned a Ph.D. in Mathematics from Harvard University (2011) and dual BS degrees in Mathematics with Computer Science and Physics from MIT (2007). Prior to UCSD, he was a postdoctoral researcher at Stanford University (2011–2014) on an NSF fellowship. His research interests include robust statistics, machine learning, polynomial threshold functions, and algorithmic methods for high-dimensional data. Notable achievements include co-authoring the book Algorithmic High-Dimensional Robust Statistics (Cambridge University Press, 2023) and receiving the Best Paper Award at the Conference on Computational Complexity (2013), as well as gold medals at the International Mathematical Olympiad (2002 and 2003). Current teaching includes courses such as Math 96 (Putnam Seminar), Math 154 (Graph Theory), CSE 101 (Algorithms), and CSE 203A (Randomized Algorithms). He has consulted for companies like CASPER Labs and AIble, and his work extends to cryptographic protocols, including quantum money schemes based on quaternion algebras. Key contributions include breakthroughs in robust mean estimation, list-decodable learning, and the development of efficient algorithms for statistical problems. His research often bridges foundational theory with practical applications in machine learning and data analysis.

David Landriaultمشاهده پروفایل

استاد

• Actuarial Science
• Quantitative Risk Management
• Applied Probability
• +۴ مورد دیگر

David Landriault is a Professor in the Department of Statistics and Actuarial Science at the University of Waterloo, Canada, and a Canada Research Chair in Risk Theory. His research focuses on Actuarial Science, Quantitative Risk Management, Applied Probability, and Stochastic Processes, particularly in ruin theory, drawdown analysis, and stochastic control for insurance and finance applications. Education: PhD in Mathematics (2005), MSc in Mathematics (2003), BSc in Actuarial Science (2002) from Laval University. Affiliations: University of Waterloo (postdoctoral fellowship, 2006); Canada Research Chair in Risk Theory. Research Interests Risk and Ruin Theory Stochastic Control in Insurance and Finance Drawdown and Occupation Time Analysis Regime-Switching Models Reinsurance Design and Optimization Time-Dependent Risk Models Scientific Awards Fellow of the Canadian Institute of Actuaries (F.C.I.A.), 2009 Fellow of the Society of Actuaries (F.S.A.), 2006

• Early Childhood Education
• Art Education
• Play-Based Learning
• +۵ مورد دیگر

Felicity McArdle is a Professor in the Department of Early Childhood Education within the Faculty of Education at Queensland University of Technology. With a distinguished career spanning over two decades, her work centers on reimagining early childhood pedagogy through critical lenses of social justice, art education, and play-based learning. Her research has significantly influenced Australian early childhood policy and practice. McArdle's research interests demonstrate a consistent commitment to transformative education. She critically examines how art and play function as vehicles for social justice, challenging neoliberal discourses in early childhood education. Her work on refugee children's artistic expression and anti-bias curriculum development reveals her dedication to equity-oriented pedagogy. Through collaborative drawing methodologies and visual research approaches, she has pioneered innovative ways of understanding children's perspectives. Her publication trends reveal a sophisticated evolution from foundational work on visual arts in education (2001-2010) toward increasingly critical examinations of power, policy, and social justice (2011-2021). The consistent citation impact of her work—particularly her 2002 paper 'Early Childhood Art Education: A Palimpsest' with over 13,000 citations—demonstrates her field-defining contributions to reconceptualizing art education as critical praxis. McArdle has held significant editorial roles including co-editing the influential 2013 volume 'Young Children, Pedagogy and the Arts' and serving on the editorial board of Australian Journal of Early Childhood. Her collaborations with leading scholars like Susan Grieshaber, Jennifer Sumsion, and Linda Knight have produced seminal work on intentional teaching and play-based learning. Her research methodology expertise centers on visual and arts-based approaches, particularly collaborative drawing techniques that engage children as active research participants. This methodological innovation reflects her commitment to ethical research practices that honor children's agency while generating meaningful insights about early childhood experiences.

Monika Henzingerمشاهده پروفایل

استاد

• Algorithms
• Data Structures
• Dynamic Algorithms
• +۳ مورد دیگر

Monika Henzinger is Professor at the Institute of Science and Technology Austria (ISTA), heading the research group of Theory and Applications of Algorithms. She also serves as Vice President for Technology Transfer at ISTA since 2024. Previously, she held professorships at the University of Vienna (2009-2023) and EPFL, Switzerland (2005-2009), was Director of Research at Google (1999-2005), and served as Assistant Professor at Cornell University. Professor Henzinger's research centers on efficient algorithms and data structures with three main thrusts. First, she investigates dynamic settings where program inputs are repeatedly updated, seeking solutions faster than restarting computations. Second, she develops privacy-preserving algorithms that add minimal noise to protect input data while maintaining efficiency. Third, she translates theoretically optimal algorithms into practical implementations for dynamically changing inputs. Her work consistently addresses resource conservation in data processing, particularly computing time and memory space, while exploring the theoretical limits of possible savings. Henzinger's recent publications (2024-2025) reveal strong trends in dynamic algorithms, differential privacy, and graph theory. Her research consistently bridges theoretical computer science with practical applications, focusing on algorithms that adapt to changing inputs while preserving computational efficiency and data privacy. She has made significant contributions to problems like dynamic matching, minimum cut computation, and privacy-preserving data analysis across various domains. Professor Henzinger has received numerous prestigious awards and honors: Wittgenstein Award (2021) Two ERC Advanced Grants (2014, 2021) Carus Medal of the German Academy of Sciences Leopoldina (2019) SIGIR Test of Time Award Fellow of the Association of Computing Machinery (2016) Member of the Austrian Academy of Sciences (2017) CAREER Development Award of the National Science Foundation Best paper Award at the Symposium on Discrete Algorithms (2024) Professor Henzinger currently advises PhD students Bardiya Aryanfard, Antoine El-Hayek, and Roodabeh Safavi Hemami, along with postdocs Anamay Chaturvedi and Niklas Hahn. Her research is supported by multiple significant grants including an ERC Advanced Grant for 'Design and Evaluation of Modern, Fully Dynamic Data Structures,' the FWF Wittgenstein Prize, and the WEAVE Project on 'Static and dynamic hierarchical graph decompositions.' She also serves as Principal Investigator for the FWF project 'Fast algorithms for a reactive network layer,' providing substantial funding for her innovative work in algorithms and data structures. Professor Henzinger leads the Theory and Applications of Algorithms research group at ISTA, which focuses on developing practical algorithms for dynamic environments. Her team investigates resource conservation in data processing, specializing in dynamic algorithms that efficiently handle changing inputs, privacy-preserving algorithms that minimize noise while protecting data, and translating theoretical algorithms into practical implementations. The group maintains a strong presence in theoretical computer science through regular publications in top conferences and journals, and collaborates extensively with institutions worldwide to advance algorithmic research.

Karsten Borgwardtمشاهده پروفایل

استاد

• Machine Learning
• Systems Biology
• Bioinformatics
• +۳ مورد دیگر

Karsten Borgwardt is a Professor and Director of the Department of Machine Learning and Systems Biology at the Max Planck Institute of Biochemistry. He holds a PhD in Computer Science (2007) from LMU Munich and has held academic positions at ETH Zürich, Universität Tübingen, and the Max Planck Institutes in Tübingen. His research focuses on machine learning applications in biology and medicine, including biomarker discovery, personalized medicine, and systems biology. Education: PhD in Computer Science (2007), LMU Munich M.Sc. in Biology (2003), University of Oxford Diplom (M.Sc. equivalent) in Computer Science (2004), LMU Munich Research Interests: Development of machine learning algorithms for large biomedical datasets Pattern recognition in genomic and clinical data Applications in sepsis biomarkers, antimicrobial resistance prediction, and personalized medicine Grants & Projects: Scientific Coordinator of Marie Curie Networks (2013-2022) Swiss National Science Foundation Starting Grant (2014) Personalized Swiss Sepsis Study (CHF 5.3M, 2018) Awards: Krupp Award (2013), Golden Owl Teaching Award (2017), multiple 'Top 40 under 40' recognitions (2014-2016). Labs: Leads the Machine Learning and Systems Biology Department at MPI, collaborating with 22+ labs in sepsis research and international networks.

• Discourse Analysis
• Computational Linguistics
• Natural Language Processing
• +۳ مورد دیگر

Maite Taboada is a Distinguished Professor in the Department of Linguistics at Simon Fraser University (SFU), directing the Discourse Processing Lab. She is also an Associate Member of the Cognitive Science Program and School of Computing Science, and affiliated with the Digital Democracies Institute and Visual and Interactive Computing Institute. Her research bridges discourse analysis and computational linguistics, focusing on mechanisms of coherence, discourse parsing, and sentiment analysis. Key projects include analyzing online news comments (SOCC corpus), detecting misinformation (MisInfoText), and monitoring gender representation in media (Gender Gap Tracker/Radar de Parité). Notable research interests span toxic language detection, constructive dialogue systems, and interdisciplinary work between social sciences and engineering. She has led projects funded by SFU and collaborated with organizations like Informed Opinion. Her awards include Fellowship in the Royal Society of Canada. Key contributions include developing the SFU Opinion and Comments Corpus, systems for comment moderation, and frameworks for gender bias analysis using topic modeling. Her work integrates theoretical discourse analysis with applied computational methods, addressing societal challenges like media bias and misinformation.

• Nonlinear partial differential equations
• Singularity formation
• Mathematical analysis
• +۲ مورد دیگر

Manuel Del Pino is Professor at the University of Bath's Department of Mathematical Sciences and Royal Society Professor specializing in nonlinear partial differential equations. His research focuses on singularity formation, geometric evolution equations, and asymptotic analysis in fluid dynamics and mathematical physics. His investigations encompass blow-up phenomena in heat equations, vortex dynamics in Euler flows, and minimal surface theory. Current projects examine infinite-time singularity formation in parabolic equations and asymptotic properties of vortex configurations. Del Pino has received the Royal Society Professorship and leads multiple grants including 'Asymptotic patterns in nonlinear evolution problems' (EPSRC). He maintains collaborations with researchers globally through projects on singularity formation in PDEs.

Costanza Beltramiمشاهده پروفایل

مدرس ارشد

• Gothic Art
• Gothic Architecture
• Late Medieval Architecture
• +۷ مورد دیگر

Costanza Beltrami is a Senior Lecturer at Stockholm University in the Department of Culture and Aesthetics. She is a dedicated art historian with a focus on Gothic art and architecture of the late fifteenth and early sixteenth centuries, particularly in the Spanish region of Castile and its international connections. Her research interests include architectural drawings, collaboration, transculturation, and temporality in architecture. Dr. Beltrami teaches courses on Medieval and Renaissance art and architecture from Cordoba to Florence. Her academic background includes studying Art History at the Courtauld Institute of Art in London and working at the University of Oxford/St Catherine's College before joining Stockholm University. Her research has focused on late-Gothic architecture, including a monumental drawing of a tower from Rouen cathedral and ornament prints as artists' models. She is Reviews Editor for the Journal of the British Archaeological Association and has completed her PhD thesis on Juan Guas (active 1453–1496), the leading architect of late fifteenth-century Spain. She is currently working on a book project about collaboration, artistic identity, and the geographies of exchange in late-Gothic Castile. Her co-edited volume "Art, Travel and Exchange between Iberia and Global Geographies, 11400–1550" challenges traditional narratives about Iberian art history and emphasizes multi-directional cultural exchange. Dr. Beltrami's recent research includes editing a special issue on portable drawings and paper in Medieval and Gothic architecture. Her work explores how architectural practices in Castile demonstrate fascinating questions regarding migrant networks, cultural contact, the meanings of architecture, and the role of art in debates on national identity from the 15th century to the present.

• Psycholinguistics
• Discourse Pragmatics
• Perspective-Taking
• +۷ مورد دیگر

William S. Horton (Sid) is an Associate Professor in the Department of Psychology at Northwestern University , where he has taught since 2005 and directed the Cognition and Communication Lab (Cresap 108). Starting in September 2025, he will serve as Chair of the Department of Linguistics . His research focuses on socio-cognitive mechanisms in language use, particularly discourse pragmatics , perspective-taking , and non-literal language processing . Education: B.S. in Psychology/German from Duke University (1991), M.A. and Ph.D. in Cognitive Psychology from University of Chicago (1994/1999) Previous roles: Postdoctoral research at SUNY-Stony Brook, Cognitive Aging at Georgia Tech Research trends from his 20+ years of publications include common ground , memory processes , figurative language , and age-related communication changes . His work increasingly incorporates computational text analysis and real-time digital communication studies. Awards : Fellow, Society for Text and Discourse Students : Supervised Ph.D. theses on conversational alignment, common ground activation, and digital communication. Undergraduate honors projects explore inhibitory deficits, speech internalization, and perspective-taking in bilingualism. Cognition and Communication Lab investigates language processing in spoken/written contexts using experimental methods and computational models.

• Causal Inference
• Experimental Design
• Statistical Methods
• +۳ مورد دیگر

Peter Aronow is a Professor at Yale School of Public Health , with appointments in the Department of Statistics and Data Science , Economics Department , and the Institute for Social and Policy Studies . His interdisciplinary work bridges political science, biostatistics, and epidemiology. Professor of Public Health (Biostatistics) Secondary appointments in Political Science and Economics Associate Professor in the Institute for Social and Policy Studies Dr. Aronow specializes in causal inference and statistical methodology, particularly in non-traditional field research contexts. His research encompasses: Design-based approaches to causal inference Complex experimental designs Social network analysis Survey methodology with incomplete data His recent publications focus on spatial experiments under unknown interference, bias correction in RCTs, and temporal validity challenges. While no formal awards are listed, his work is cited across disciplines including: Political Analysis Econometrics Biostatistical Modeling Observational Study Design

Matthias Winterمشاهده پروفایل

مدرس ارشد

• Mathematical Biology
• Pattern Formation
• Reaction-Diffusion Systems
• +۷ مورد دیگر

Dr. Matthias Winter is a Senior Lecturer in the Department of Mathematics at Brunel University's College of Engineering, Design and Physical Sciences. He has been affiliated with Brunel since 2005, following academic positions at the University of Stuttgart (1996-2005) and postdoctoral fellowships at the Institute for Advanced Study in Princeton (1993-94) and Heriot-Watt University in Edinburgh (1994-96). His educational background includes a PhD from Stuttgart University in 1993 and a Habilitation from the same institution in 2003. Dr. Winter's research focuses on mathematical biology, particularly pattern formation in biological systems through reaction-diffusion equations. His work examines spike solutions, pattern formation mechanisms, and the mathematical analysis of biological phenomena. He has made significant contributions to understanding stable spike clusters in various contexts including the Gierer-Meinhardt system. His research spans Mathematical Biology, Pattern Formation, Reaction-Diffusion Systems, Nonlinear Partial Differential Equations, and several related mathematical disciplines. His recent publications (2023-2025) demonstrate continued activity across diverse applications including cancer modeling, ecological systems, climate modeling, and fundamental mathematical analysis of reaction-diffusion phenomena, showing his ability to apply sophisticated mathematical techniques to real-world biological problems. Editorial Board, ISRN Mathematical Analysis, since 2010 Academic Appeals Committee, since 2013 Level One Coordinator for Mathematics, since 2013 Course Director MSc Programme Computational Mathematics with Modelling Mathematics, 2008-2010 Dr. Winter teaches various mathematics courses including Mathematics and Statistics for Economists, Vector Calculus, and Group Projects in Mathematics, with a teaching portfolio spanning from foundational courses to specialized topics related to his research interests.

• Affective Computing
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Dr A. I. Shihab is a Senior Lecturer at Kingston University's Faculty of Engineering, Computing and the Environment, Department of Networks and Digital Media. He teaches programming languages (C++/Java), data structures, web development, and AI/machine learning. His research focuses on affective computing and machine learning applications including: Acoustic event detection in sports environments Audio signal analysis for tennis match modeling Multi-camera visual surveillance systems Medical imaging analysis using fuzzy clustering techniques Publications demonstrate expertise in combining audio/video modalities for sports analytics (tennis rallies, court-shots) and developing Markov models for sound event sequence analysis. Contact: a.shihab@kingston.ac.uk

Quek Su Yingمشاهده پروفایل

دانشیار

• Materials Science
• Condensed Matter Physics
• Theoretical Physics
• +۵ مورد دیگر

Associate Professor Quek Su Ying is affiliated with the Department of Physics at the National University of Singapore (NUS) and serves as Assistant Dean (Special Duties). Her research focuses on theoretical and computational approaches to understanding the electronic, vibrational, and transport properties of emerging materials, particularly 2D and organic systems. Affiliations : Institute of High Performance Computing, Centre for Advanced 2D Materials, NUS Research Interests : First principles calculations (mean field and many-electron perturbation theory), interface science, electronic energy level alignment, and transport in emerging materials. Her work includes studies of exciton condensation, quantum emitters, and valleytronic control via magnetic fields. Article Trends : Recent publications highlight investigations into 2D materials, organic-inorganic interfaces, and quantum phenomena. Topics include exciton dynamics, defect engineering, charge density waves, and spin-dependent transport, employing advanced ab initio methods like GW theory. Scientific Awards : Singapore NRF Fellowship Advising & Collaborations : Her group develops state-of-the-art computational methods and collaborates with experimental teams. Notable affiliations include Google Scholar Profile and partnerships with institutions like the Institute of High Performance Computing. Labs & Teams : Associated with the Centre for Advanced 2D Materials at NUS, which supports interdisciplinary research on graphene and related 2D systems. Her work bridges theoretical modeling and experimental validation.