جستجوی استاد راهنمای دانشگاهی

Matias D. Cattaneoمشاهده پروفایل

استاد

• Mathematical statistics
• Econometrics
• Data science
• +۷ مورد دیگر

Matias D. Cattaneo is a Professor in the Department of Operations Research and Financial Engineering at Princeton University , with affiliated roles in the School of Public and International Affairs , Economics Department , Latin American Studies Program , Data-Driven Social Science , AI at Princeton , and Center for Statistics and Machine Learning . He serves as an Amazon Scholar and collaborates with global organizations. Education : Ph.D. in Economics (2008) and M.A. in Statistics (2005) from UC Berkeley, Master in Economics (2003) from Universidad Torcuato Di Tella, Licentiate in Economics (2000) from Universidad de Buenos Aires. Research focuses on interdisciplinary challenges in social, behavioral, and biomedical sciences, combining econometrics, statistics, data science, and causal inference. His methodological work includes regression discontinuity designs, synthetic control methods, and local polynomial estimation, with applications to decision-making under uncertainty. Scientific recognition : Elected Fellow of the American Statistical Association Elected Fellow of the Institute of Mathematical Statistics Elected Fellow of the International Association for Applied Econometrics Elected Member of the International Statistical Institute Software contributions include R packages rdhte , scpi , and lpcde , freely available on GitHub. His GitHub activity includes 344 contributions in the last year, with active repositories on regression discontinuity and synthetic control methods.

Sahani Pathirajaمشاهده پروفایل

مدرس

• Data Science
• Bayesian Inference
• Stochastic Analysis
• +۷ مورد دیگر

Dr. Sahani Pathiraja is a Lecturer (tenure track assistant professor) at UNSW Sydney , specializing in Data Science . Her research bridges mathematical and statistical foundations with practical applications in environmental and biomedical sciences. Research Focus : Sequential Bayesian inference, Monte Carlo methods, stochastic analysis of non-linear filtering, uncertainty quantification, and real-time parameter estimation. Current Projects : Co-investigator in the ARC Industrial Transformation Training Centre: Data Analytics for Resources and Environment (DARE) and the Next Generation Graduate Program (NGGP) in Sports Data Science and AI . Research Supervision : Dr. Pathiraja supervises PhD students in areas including: Bayesian inference Stochastic differential equations Data assimilation Non-linear filtering Scientific Collaborations : Her work intersects with environmental science, biomedical applications, and machine learning. Projects include stochastic hydrology, SDEs, and operator learning for environmental systems. Contact Information : Email: s.pathiraja@unsw.edu.au Phone: +61 2 8065 0836 Office: Room 2070, Level 2, The Red Centre, UNSW Sydney

• Computational Biology
• Molecular Biology
• Systems Biology
• +۵ مورد دیگر

Robert Charles Brewster is an Associate Professor in the Department of Systems Biology at UMass Chan Medical School, with additional appointments in the Department of Microbiology and multiple graduate programs at the T.H. Chan School of Medicine and Morningside Graduate School of Biomedical Sciences. T.H. Chan School of Medicine, Department of Microbiology T.H. Chan School of Medicine, Department of Systems Biology Morningside Graduate School of Biomedical Sciences, Biophysical Chemical and Computational Biology Morningside Graduate School of Biomedical Sciences, Interdisciplinary Graduate Program Morningside Graduate School of Biomedical Sciences, Postbaccalaureate Research Education Program Morningside Graduate School of Biomedical Sciences, Systems Computational and Quantitative Biology Brewster holds a BS in Physics from the University of Massachusetts Amherst and a PhD in Physical Chemistry from the University of California, Los Angeles. His research focuses on the quantitative aspects of gene expression regulation, particularly in bacterial systems. His work primarily investigates transcription factors, promoter architecture, and the mechanisms of gene regulation in Escherichia coli, with a strong emphasis on quantitative and systems biology approaches. Brewster's research combines experimental and computational methods to understand how transcription factors control gene expression at the molecular level, with recent work focusing on transcription factor function, promoter activity regulation, and the quantification of regulatory properties in bacterial systems. Analysis of his recent publications reveals a strong trend toward quantitative systems biology approaches to understand transcriptional regulation, with a particular emphasis on Escherichia coli as a model system. His work spans multiple subfields including transcription factor mechanics, promoter architecture effects, gene expression timing, and the quantification of regulatory properties through synthetic biology approaches. Brewster has collaborated extensively with researchers including Phillips R, Garcia HG, Weinert FM, and others, indicating strong interdisciplinary connections between physics, chemistry, and biology in his research program. His laboratory appears to focus on the quantitative aspects of gene regulation, using both experimental and theoretical approaches to understand the fundamental principles governing transcriptional control in living systems.

Sadegh Talebiمشاهده پروفایل

استادیار

• Reinforcement Learning
• Markov Decision Processes
• Online Learning
• +۲ مورد دیگر

Sadegh Talebi is a Tenure Track Assistant Professor in the Machine Learning Section at the Department of Computer Science, University of Copenhagen . His research focuses on theoretical aspects of reinforcement learning, Markov decision processes, online learning, stochastic multi-armed bandit problems, and resource allocation in networks. Education BSc in Electrical Engineering (minor: Electronics) from Iran University of Science and Technology (IUST) (2004) MSc in Electrical Engineering (minor: Communication Systems) from Sharif University of Technology (2006) PhD in Electrical Engineering from the Department of Automatic Control at KTH Royal Institute of Technology (supervised by Alexandre Proutiere and Mikael Johansson) Research Specializes in theoretical foundations of reinforcement learning and online learning Key contributions in stochastic optimization, MDPs, and bandit algorithms Collaborates on applications in resource allocation and quantum computing Publications include high-impact work on offline RL, differentially private exploration, and scalable MDP solutions in journals like Neural Processing Letters and conferences such as NeurIPS and UAI.

• Numerical Analysis
• Stochastic Partial Differential Equations
• Computational Physics
• +۱۲ مورد دیگر

Prof. Dr. Lubomir Banas is a full-time Professor at the Faculty of Mathematics , University of Bielefeld. His research focuses on numerical analysis of stochastic partial differential equations (SPDEs) , particularly in micromagnetism, phase field models, and stochastic games. He leads Subproject B03 in the SFB 1283 project 'Taming Uncertainty and Profiting from Randomness and Low Regularity in Analysis, Stochastics and Their Applications.' Research Interests: Numerical methods for SPDEs and singular-degenerate PDEs Adaptive finite element techniques and a posteriori estimates Phase field models (Cahn-Hilliard, obstacle potentials) Stochastic games with asymmetric information Computational micromagnetism and magnetostriction Self-organized criticality and nonlinear stochastic flows Recent work includes: 2025: Numerical approximation of biharmonic wave maps and stochastic games 2024: Sharp interface limits for stochastic Cahn-Hilliard equations 2023: Singular-degenerate SPDEs and a posteriori estimates 2022: Stochastic total variation flow and Hamilton-Jacobi-Bellman equations 2021: Nematic electrolytes and homogenization of two-phase flows He serves on examination boards for Bachelor's and Master's programs in Mathematics and Mathematical Physics, and supervises graduate students within the Bielefeld Graduate School in Theoretical Sciences . His publications (over 30) address convergence analysis, error estimation, and computational modeling in applied mathematics.

• Neural Engineering
• Global Health
• Infectious Diseases
• +۷ مورد دیگر

Dr. Steven Schiff is the Harvey and Kate Cushing Professor of Neurosurgery and Professor of Epidemiology at Yale University, serving as Vice Chair for Global Health in the Department of Neurosurgery. He is affiliated with multiple Yale institutions including the Yale Institute for Global Health, Yale Program for Biomedical Ethics, Yale Interdepartmental Program in Neuroscience, and the Yale Center for Brain and Mind Health. Dr. Schiff's educational background includes an MD and PhD in Physiology from Duke University, followed by General Surgery Internship, Neurosurgery Residency, and Pediatric Neurosurgery Fellowship at Children's Hospital of Philadelphia. His training established the foundation for his dual expertise in clinical neurosurgery and biomedical engineering. Dr. Schiff is a pioneer in neural control engineering and sustainable health engineering with a strong focus on global health applications. His research spans neural engineering, infectious disease modeling, hydrocephalus treatment in low-resource settings, and the development of low-cost medical imaging technologies. He has made significant contributions to understanding neonatal infections in Africa, particularly the discovery of Neonatal Paenibacilliosis. His work on Predictive Personalized Public Health (P3H) integrates engineering principles with public health practice. His recent publications demonstrate a strong focus on applying AI and engineering solutions to global health challenges, particularly in neurosurgery and infectious disease. Key themes include the development of low-field MRI technology for resource-limited settings, understanding Paenibacillus infections causing hydrocephalus in African infants, and applying computational modeling to infectious disease dynamics. NIH Director's Pioneer Award (2015) NIH Director's Transformative Award (2018) Fellow of American Association for the Advancement of Science (2012) Fellow of American Epilepsy Society (2016) Honorary African Name: Musaazi, Fumbe Clan (2018) Dr. Schiff leads the Center for Global Neurosurgery at Yale University, building on his previous work founding the Center for Neural Engineering at Penn State. His NIH-funded research has enabled significant advances in understanding and treating infant infections in the developing world. He serves on multiple editorial boards including the Journal of Computational Neuroscience and Journal of Neural Engineering, and has contributed to FDA scientific committees. His work bridges engineering, neuroscience, and global public health to address critical healthcare disparities worldwide.

Daniel J. Stilwellمشاهده پروفایل

استاد

• Autonomous Underwater Vehicles (AUVs)
• Marine Robotics
• Control Systems
• +۷ مورد دیگر

Daniel J. Stilwell is a Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Polytechnic Institute and State University (Virginia Tech), and Co-Director of the Center for Marine Autonomy and Robotics. He holds affiliations including the Seale Coastal Observatory Faculty Fellow role. His research focuses on autonomous underwater vehicles (AUVs), marine robotics, control systems, and sensor networks. He earned his Ph.D. in Electrical Engineering from Johns Hopkins University (1999), M.S. from Virginia Tech (1993), and B.S. in Computer Engineering from the University of Massachusetts (1991). His notable contributions include advancements in AUV control, underwater acoustic communication, multi-agent systems, and sensor network optimization. Key projects include the "Unconventional Marine Platforms" funded by the Office of Naval Research and collaborative subsea mapping initiatives. His work bridges theoretical control systems with practical robotic applications in marine environments. Dr. Stilwell has received prestigious awards such as the NSF CAREER Award and ONR Young Investigator Program Award. His research emphasizes robust control strategies, adaptive systems, and decentralized learning algorithms. He leads efforts in experimental validation of AUV control systems and underwater sensor networks, contributing to both academic and military applications.

Xi Chenمشاهده پروفایل

دانشیار

• Operations Research
• Stochastic modeling and simulation
• Applied probability and statistics
• +۵ مورد دیگر

Xi Chen is an Associate Professor in the Grado Department of Industrial & Systems Engineering at Virginia Tech. He holds a Ph.D. in Industrial Engineering and Management Sciences from Northwestern University, an M.S. in Industrial Engineering & Systems Engineering from NC State, and a B.Sc. in Automation from Huazhong University of Science & Technology. His research focuses on stochastic modeling, simulation optimization, and power electronics, particularly in high-frequency converter design using GaN devices. Key research interests include planar transformer optimization, EMI reduction in power systems, and GaN-based high-efficiency converters. His work spans applications in adapters, PFC converters, and high-density power modules. Notable contributions include ultra-high efficiency 140W PD3.1 adapters and LLC modules using GaN power ICs. Education: Ph.D., Industrial Engineering & Management Sciences, Northwestern University M.S., Industrial Engineering & Systems Engineering, NC State B.Sc., Automation, Huazhong University of Science & Technology Awards: 2013 Nemhauser Dissertation Prize Student Scholarship Award (Spring Research Conference) Arthur P. Hurter Award for Academic Excellence Professional Activities: INFORMS Simulation Society ACM SIGSIM Society for Industrial and Applied Mathematics Recent Courses: ISE 5414: Random Process ISE 5424: Simulation Labs/Teams: Active in power electronics research with a focus on GaN devices and high-frequency converter design.

Rudie P.J. Kunnenمشاهده پروفایل

دانشیار

• Turbulent Flow
• Multiphase Flow
• Heat Transfer
• +۷ مورد دیگر

Rudie P.J. Kunnen is an Associate Professor at the Faculty of Applied Physics and Science Education , Eindhoven University of Technology, leading the Turbulent and Multiphase Flows group. His research focuses on heat, mass, and particulate transport in turbulent flows, with applications in geophysics and industry. Active in UN Sustainable Development Goals related to environmental protection Collaborator in projects like Active Contamination Control for Equipment and SubstrateS Research Interests : Turbulent flow dynamics, rotating convection, vortex structures, thermophoresis, plasma-liquid interactions, and geostrophic turbulence. His work combines experimental and numerical approaches (e.g., direct numerical simulation, particle image velocimetry). Scientific Awards : NWO Vici Prize (2024) Advising and Collaborations : Supervised multiple BSc and MSc theses at TU/e. Collaborates with researchers like F. Toschi and H.J.H. Clercx on turbulence projects.

David Castañónمشاهده پروفایل

استاد

• Stochastic Control
• Estimation Theory
• Game Theory
• +۶ مورد دیگر

David Castañón is a Professor of Electrical and Computer Engineering (ECE) and Systems Engineering (SE) at Boston University. He holds a PhD from MIT (1976) and has held leadership roles including Department Chair of BU ECE (2010-2014) and President of the IEEE Control Systems Society (2008). His research focuses on stochastic control, optimization, game theory, and distributed computing, with applications in sensor management, inverse problems, and autonomous systems. Education: PhD, Massachusetts Institute of Technology (1976). Key affiliations include the Center for Information and Systems Engineering, the Rafik B. Hariri Institute for Computing, and the ALERT Department of Homeland Security Center of Excellence. He teaches courses such as EC702 Recursive Estimation and EC719 Statistical Learning Theory. Research interests span stochastic control, estimation theory, optimization algorithms, and multi-agent systems. Notable contributions include work on sensor management, cooperative operations, and inverse problem solutions for medical and security imaging. His work often integrates theoretical frameworks with practical applications in autonomous systems and distributed computing. Scientific achievements include IEEE Fellow status (2006), CSS Distinguished Member Award, and leadership roles in major conferences like the IEEE Conference on Decision and Control (2007 as General Chair). He has also served on the Air Force Advisory Board and the IEEE Society Review Committee. Grants and lab affiliations include the NSF Engineering Research Center for Subsurface Sensing (2001-2013) and the SENTRY DHS Center of Excellence (2021-present). His interdisciplinary collaborations bridge robotics, medical imaging, and security systems.

Joseph D. Blackburnمشاهده پروفایل

استاد

• Operations Management
• Supply Chain Management
• Time-based Competition
• +۳ مورد دیگر

Joseph D. Blackburn is a Professor and former Acting Dean at Vanderbilt University's Owen Graduate School of Management. His expertise spans Operations Management, focusing on time-based competition, sustainable supply chains, and inventory systems. He holds a Ph.D. in Operations Research from Stanford University (1971), an M.S. in Chemical Engineering from the University of Wisconsin (1964), and a B.S. in Chemical Engineering from Vanderbilt (1963). Prior to academia, he worked as a Chemical Engineer at Eastman Kodak. Research Interests: Blackburn is globally recognized for pioneering work on time-based competition in manufacturing and sustainable supply chain strategies. His work integrates operational efficiency with environmental and economic sustainability, addressing challenges such as inventory optimization, remanufacturing policies, and perishable product management. Awards: Founder’s Medalist (Vanderbilt), Fellow of the Production and Operations Management Society, Jo Van Nunen Prize (2016). Leadership: Served as President of the Production and Operations Management Society and on editorial boards of top journals like Production and Operations Management . Publications include seminal works in Management Science , Journal of Operations Management , and Decision Sciences , emphasizing practical applications of operations research in real-world supply chain challenges.

Aleksandar Mijatovicمشاهده پروفایل

استاد

• Probability
• Stochastic Processes
• Mathematical Finance
• +۵ مورد دیگر

Aleksandar Mijatović is a Professor of Probability at the Department of Statistics, University of Warwick, and Deputy Head of Department for Research. He was previously Chair in Probability at King's College London and Reader in Probability at Imperial College London. His research focuses on probability theory, stochastic processes, mathematical finance, numerical stochastics, and data science. He holds a Ph.D. in low-dimensional topology from Trinity College Cambridge and worked as a quantitative analyst in foreign exchange derivatives before academia. Research interests include stochastic analysis of processes with jumps, simulation methods (e.g., Monte Carlo), stochastic control, and applications in finance. He is a Fellow of the Alan Turing Institute and maintains a YouTube channel, Prob-AM, explaining his research. His work often bridges theoretical probability with practical applications in finance and data science. Key publications explore topics like reflected Brownian motion, Lévy processes, branching processes, and stochastic gradient descent. Collaborations with institutions like King’s College London and Imperial College London highlight his academic networks. His contributions span theoretical advancements and computational methodologies, with applications in risk management, option pricing, and algorithm development.

• Economics
• Game Theory
• Behavioral Economics
• +۳ مورد دیگر

Faruk Gul is the Susan Dod Brown Professor of Economics at Princeton University. His research focuses on decision theory, game theory, and behavioral economics, with a particular emphasis on topics such as preference dynamics, self-control models, and the integration of uncertainty into economic frameworks. He has collaborated extensively with Wolfgang Pesendorfer on foundational work in these areas. Gul's work explores the implications of ambiguous preferences, strategic interactions under uncertainty, and the design of economic mechanisms. His contributions include seminal studies on coarse competitive equilibrium, calibrated uncertainty, and the theory of random evolving lotteries. His research has been supported by grants from the National Science Foundation (SES-0010394, SES-0820101, SES-0550540, SES-0236882, SES-9911177). In policy-related areas, his work addresses strategic redistricting, partisan politics, and information warfare in economic systems. He has also contributed to foundational debates in economic methodology, including critiques of traditional rationality assumptions and the case for 'mindless economics.' Gul's articles span topics such as interdependent preferences, competitive equilibrium models, and the analysis of harmful addiction from an economic perspective. His interdisciplinary approach bridges microeconomic theory, decision science, and political economy.

Marc Rousselمشاهده پروفایل

استاد

• Biochemical Systems Analysis
• Mathematical Biology
• Chemical Kinetics
• +۳ مورد دیگر

Marc Roussel is a Professor in the Department of Chemistry and Biochemistry at the University of Lethbridge, affiliated with the Alberta RNA Research and Training Institute. His research focuses on mathematical modeling of biochemical systems, enzyme kinetics, and systems biology. He has authored multiple books, including Foundations of Chemical Kinetics and A Life Scientist's Guide to Physical Chemistry . His work bridges mathematics and biology, emphasizing dynamical systems, delay differential equations, and model reduction techniques. He has received the 2024 Distinguished Teaching Award from the University of Lethbridge. Key research areas include biochemical networks, gene expression dynamics, and metabolic modeling. Roussel collaborates with experimentalists to study complex biological phenomena such as circadian rhythms, somite formation, and enzyme mechanisms. His contributions span theoretical frameworks, computational methods, and interdisciplinary applications in systems biology.

Michael Choiمشاهده پروفایل

استادیار

• Markov Chains
• Stochastic Algorithms
• Statistical Physics
• +۶ مورد دیگر

Michael Choi is an Assistant Professor in the Department of Statistics and Data Science at the National University of Singapore (NUS), affiliated with the Institute of Operations Research and Analytics (IORA). Previously, he held a joint appointment with Yale-NUS College (2022–2025) and worked at the School of Data Science (SDS) at the Chinese University of Hong Kong, Shenzhen. He earned his PhD from Cornell University’s School of Operations Research and Information Engineering (ORIE), advised by Prof. Pierre Patie, and holds an undergraduate degree in Actuarial Science from the University of Hong Kong. His research focuses on Markov chains and processes, stochastic algorithms (e.g., MCMC, simulated annealing, Langevin dynamics), and their applications in statistical physics, optimization, Bayesian statistics, information theory, game theory, and theoretical computer science. He explores interdisciplinary connections with quantum computation, control theory, and computational chemistry. Choi actively contributes to the academic community, serving as an Associate Editor of Statistics and Computing since August 2023. He has presented at numerous international conferences and workshops, including the IMS APRM 2026 (Hong Kong), INFORMS International Meeting 2025 (Singapore), and BayesComp 2025 (Singapore). His work bridges theoretical foundations with practical computational methods in stochastic systems.