جست‌وجوی استاد و پژوهشگر

Harald Van Heerdeمشاهده پروفایل

استاد پژوهشی

• Marketing Management
• Branding and Brand Equity
• Econometrics
• +۸ مورد دیگر

Harald Van Heerde is a Research Professor of Marketing at the University of New South Wales, Sydney, within the UNSW Business School's Department of Marketing. He holds roles as Editor of the Journal of Marketing and Executive Vice-Chairman/Program Director of the Marketing Science Hub at AiMark. His academic career includes positions at Maastricht University, the University of Waikato, Tilburg University, and Massey University. Education: Ph.D. in Economics (Cum Laude), University of Groningen, the Netherlands (1999) M.Sc. in Econometrics (Cum Laude), University of Groningen, the Netherlands (1995) Research Interests: Harald focuses on applying econometric models and large datasets to address critical marketing challenges. His work explores marketing mix effectiveness , brand equity , digital marketing strategies , consumer behavior in crises , and cross-industry applications such as retailing, healthcare, and entertainment. Methodologically, he emphasizes dynamic models, endogeneity correction, optimization techniques, and text mining. Articles Trends: Recent publications highlight analysis of inflation's impact on consumer spending , mobile app engagement , brand recovery post-crisis , and econometric frameworks in marketing decision-making. His work bridges theoretical advancements with practical business implications, particularly in stochastic cost industries and global market dynamics. Awards & Fellowships: 2024: AMA Fellow & Shelby/Hunt Best Paper Award 2021: Churchill Award (Lifetime Contributions) 2004–2023: 10+ paper awards including MSI/Root, Paul Green, and multiple long-term impact recognitions Advising & Grants: Currently supervising doctoral candidates Ayesha Hossain (Human Branding) and Ada Choi (consumer financial decision-making). Supervised 12 completed theses across branding, retailing, and digital marketing. Secured over AU$2 million in grants including ARC Discovery, MSI, and the Marsden Fund. His grants examine topics like brand crisis management, price war dynamics, and mobile marketing ROI. Labs & Teams: Leads the Marketing Science Hub at AiMark, a nonprofit connecting academics with household panel data. Consults for global firms including Unilever, Edeka, and AZTEC. His work emphasizes collaborative data-driven research with industry partners.

Yuning Jiangمشاهده پروفایل

استاد مهمان

• Optimal Control
• Model Predictive Control
• Power Systems
• +۴ مورد دیگر

Yuning Jiang is a Visiting Professor at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Automatic Control Laboratory (LA3) within the School of Engineering (STI). He teaches the doctoral course Optimal Control for Dynamic Systems and contributes to research in distributed optimization, model predictive control (MPC), and smart grid technologies. His work bridges theoretical advancements in control systems with practical applications in power networks and autonomous systems. Current research emphasizes scalable solutions for AC optimal power flow, real-time MPC for embedded systems, and robust optimization under uncertainty. His research interests span Optimal Control , Power Systems , Smart Grids , and Federated Learning . Notable contributions include distributed algorithms for large-scale power systems and privacy-preserving co-simulation frameworks. Recent publications focus on microservice deployment in satellite-terrestrial networks and real-time pricing mechanisms for vehicle-to-grid (V2G) integration. Yuning holds a position in the EDEE-ENS unit under EPFL’s Academic Affairs division (VPA-AVP-DLE), reflecting his role in academic administration and teaching infrastructure. His lab, the Automatic Control Laboratory, focuses on cutting-edge research in control theory and its interdisciplinary applications.

Yunan Yangمشاهده پروفایل

استادیار

• Applied Mathematics
• Inverse Problems
• Optimal Transportation
• +۳ مورد دیگر

Yunan Yang is the Goenka Family Assistant Professor in Mathematics at Cornell University, within the Department of Mathematics, College of Arts and Sciences. He holds a Ph.D. from the University of Texas at Austin (2018), supervised by Prof. Björn Engquist. Previously, he was a Courant Instructor at NYU (2018–2021), Simons-Berkeley Research Fellow (2021), and Advanced Fellow at ETH Zürich (2022–2023). His research focuses on computational mathematics, including inverse problems, optimal transport, machine learning, and nonconvex optimization. Notable contributions include applications of optimal transport to seismic inversion and PDE-constrained optimization. He has advised numerous students, including undergraduates and Ph.D. candidates at Cornell and other institutions. Yang teaches courses such as MATH 6220 (Applied Functional Analysis) and has published extensively in journals like SIAM Journal on Scientific Computing and Communications on Pure and Applied Mathematics. His work bridges theoretical foundations with practical applications in geophysics and computational science.

Grzegorz A. Rempalaمشاهده پروفایل

استاد

• Complex Stochastic Systems Theory
• Molecular Biosystems Modeling
• Mathematical and Statistical Methods in Epidemiology
• +۴ مورد دیگر

Professor Grzegorz A. Rempala is a faculty member in the Department of Biostatistics at The Ohio State University's College of Public Health. He holds a DSc Habilitatus from Warsaw Technical University, a PhD in Applied Mathematics from the University of Warsaw, and a PhD in Mathematical Statistics from Bowling Green State University. Rempala co-founded the OSU Healmod Initiative, focusing on modeling complex systems in public health. His research interests include complex stochastic systems, molecular biosystems modeling, and mathematical/statistical methods in epidemiology and genomics. Dr. Rempala's expertise spans applied probability theory, mathematical biology, and probability & stochastic processes. Despite his extensive academic contributions, specific awards, grants, or student advisees are not detailed in the provided information. His work is associated with interdisciplinary initiatives such as the Healmod Initiative, leveraging mathematical frameworks to address public health challenges.

Miroslav Krsticمشاهده پروفایل

استاد

• Control Theory
• Nonlinear Systems
• Adaptive Control
• +۵ مورد دیگر

Miroslav Krstic is a Distinguished Professor of Mechanical and Aerospace Engineering at the University of California, San Diego (UCSD), and serves as Senior Associate Vice Chancellor for Research overseeing 17 research institutes, postdoctoral affairs, and shared facilities. He leads the Center for Control Systems and Dynamics and the Naval Innovation, Science, and Engineering Center (NISEC). Education: PhD (1994) and MS (1992) from University of California, Santa Barbara, under advisor Petar Kokotovic. BSc (1989) from University of Belgrade, Yugoslavia. Research Interests: Pioneered methods in control theory including PDE backstepping, extremum seeking, nonlinear adaptive control, and delay compensation. Focuses on applications in chip manufacturing, aircraft carriers, particle accelerators, Mars rovers, and traffic congestion. Integrates machine learning with control design for PDE systems. Awards: Over 30 major honors including the Bellman Award, Reid Prize, Oldenburger Medal, Bode Lecture Prize, and Fellowships from AAAS, SIAM, ASME, IEEE, and IFAC. Recognized as the world's top control theorist by ScholarGPS. Service & Grants: Editor-in-Chief of IEEE Transactions on Automatic Control and Systems & Control Letters . Directed over $100M in research funding annually. Advised 30+ PhD students and postdocs, many in industry leadership roles. Industry Impact: Technologies deployed in EUV lithography (Cymer/ASML), US Navy aircraft carrier arresting gear (General Atomics), and NASA's Mars Curiosity Rover laser system. Contributions to fusion control, battery estimation, and combustion optimization.

• Nonlinear Circuits and Systems
• Electrical Engineering
• Circuits and Systems Design
• +۳ مورد دیگر

Orla Feely is the President of University College Dublin (UCD), having previously served as Vice-President for Research, Innovation and Impact (2014–2023). She holds a BE from UCD and MS/PhD degrees from UC Berkeley, where her thesis won the DJ Sakrison Memorial Prize. Her research focuses on nonlinear circuits and systems, supported by grants from Science Foundation Ireland and the Wellcome Trust. She is a Fellow of IEEE, Engineers Ireland, and the Royal Irish Academy, and has held leadership roles in organizations like CESAER and the Irish Research Council. Education: BE, University College Dublin MS, University of California, Berkeley PhD, University of California, Berkeley Research interests include nonlinear circuits, systems dynamics, and MEMS technology. Key grants include funding for gravitational turbulence studies (Wellcome Trust, 2024–2026) and nonlinear effects in communications circuits (SFI, 2003–2012). Awards include the IEEE Fellow distinction for contributions to nonlinear discrete-time circuits and systems. Professional activities include chairing the IEEE Technical Committee on Nonlinear Circuits and Systems, serving on the Higher Education Authority Board, and judging panels for the BT Young Scientist and Queen Elizabeth Prize for Engineering.

Babak Moaveniمشاهده پروفایل

استاد

• Structural Health Monitoring
• Bayesian Inference
• Earthquake Engineering
• +۷ مورد دیگر

Babak Moaveni is a Professor in the Department of Civil and Environmental Engineering at Tufts University, serving as the Associate Chair since September 2024. He also holds a joint appointment as a Professor in Electrical and Computer Engineering. His research focuses on structural health monitoring, Bayesian inference, earthquake engineering, and offshore wind energy systems. Moaveni earned his Ph.D. in Structural Engineering from the University of California San Diego (2007), following an M.S. (2001) and B.S. (1999) from Sharif University of Technology in Tehran, Iran. His research interests span probabilistic system identification, signal processing, uncertainty quantification, and verification/validation of computational models. Notable grants include leadership in the PIRE project on offshore wind energy digital twins and the Coastal Virginia Offshore Wind Pilot Project. He has supervised multiple Ph.D. and M.S. students, with current advisees including Mehdi Akhlaghi and Nasim Partovi-Mehr. Moaveni has received the Best Presentation Award at the 2022 EDGE Symposium and serves on editorial boards for journals like Structural Health Monitoring and Frontiers in Built Environment . His lab, the Structural Health Monitoring Lab, specializes in infrastructure management and offshore wind energy systems. Key professional activities include membership in the American Society of Civil Engineers (ASCE) and roles on Tufts' Tenure and Promotion Committee. His teaching includes courses on structural health monitoring, numerical methods, and structural reliability.

Sarath Chandar ANBIL PARTHIPANمشاهده پروفایل

دانشیار

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

Sarath Chandar is an Associate Professor at Polytechnique Montréal and Core Faculty Member at Mila, the Quebec AI Institute. He holds a Canada CIFAR AI Chair and Canada Research Chair in Lifelong Machine Learning. His research focuses on developing interactive learning algorithms for continual and lifelong learning, with expertise in deep learning, reinforcement learning, and natural language processing. Education: Ph.D. in Computer Science, University of Montreal (advisor: Yoshua Bengio) M.S. in Computer Science, Indian Institute of Technology Madras (advisor: Balaraman Ravindran) Research Themes: Continual Learning and Lifelong Learning Deep Reinforcement Learning Optimization for Deep Networks Natural Language Processing AI for Scientific Discovery Notable Contributions: Founder of the Conference on Lifelong Learning Agents (CoLLAs) Developed Chandar Research Lab (CRL), focusing on adaptive learning algorithms Contributions to model-based reinforcement learning and bias mitigation in AI systems Awards & Grants: Canada CIFAR AI Chair Canada Research Chair Tier 2 MITACS-funded projects on reinforcement learning applications Lab & Collaboration: CRL collaborates with academic/industrial partners (e.g., IBM, Samsung) Hosts annual symposium showcasing research in AI, optimization, and multi-agent systems

Anders Sejr Hansenمشاهده پروفایل

استادیار

• 3D Genome Structure
• Gene Expression Regulation
• Chromatin Dynamics
• +۵ مورد دیگر

Anders Sejr Hansen is an Assistant Professor of Biological Engineering at MIT, leading the Hansen Lab focused on understanding 3D genome structure and its functional implications. He holds a PhD from Harvard University and completed postdoctoral training at UC Berkeley. His research integrates advanced imaging, genomics, and computational methods to study chromatin dynamics, enhancer-promoter interactions, and their roles in gene regulation across health and disease. Education: Bachelor's/Master's in Chemistry, University of Oxford (2010) PhD in Chemistry and Chemical Biology, Harvard University (2015) Postdoctoral Research, UC Berkeley (2015–2020) Research Interests: His work spans molecular mechanisms of genome organization, development of novel microscopy techniques (e.g., MINFLUX, expansion microscopy), and computational models for 3D genomics. Key areas include chromatin dynamics, loop extrusion by cohesin/condensin, and the impact of 3D structure on gene expression in cancer and aging. Awards: NIH K99 Pathway to Independence Award (2019) NIH Director’s New Innovator Award (2020) Pew-Stewart Scholar for Cancer Research (2021) NSF CAREER Award (2024) NIH Director’s Transformative Research Award (2024) Advising & Grants: Hansen mentors PhD students and postdocs, including notable advisees Viraat Goel and Domenic Narducci. His lab has secured major grants from NIH, NSF, and private foundations, supporting interdisciplinary projects in imaging, genomics, and synthetic biology. Labs/Teams: The Hansen Lab at MIT collaborates with institutions globally, advancing technologies like Region Capture Micro-C (RCMC) and deep learning models (e.g., Cleopatra) for high-resolution genome mapping. The lab also explores synthetic biology approaches to engineer genome structures.

• Machine Learning
• Coding Theory
• Optimization
• +۵ مورد دیگر

Arya Mazumdar is a tenured Professor of Data Science and Computer Science at the Halıcıoğlu Data Science Institute (HDSI) , part of the School of Computing, Information and Data Sciences at the University of California San Diego (UCSD). He also holds affiliations with the Computer Science and Engineering and Electrical and Computer Engineering departments at UCSD. Previously, he was an Assistant and Associate Professor at the University of Massachusetts Amherst (2015–2021), and held a postdoctoral position at MIT (2011–2012). He is an IEEE Distinguished Lecturer (2023–2024) and recipient of the NSF CAREER Award (2015–2020). Education : PhD in 2011 from the University of Maryland, College Park (advisor: Alexander Barg) Postdoctoral scholar at MIT (2011–2012, advisor: Greg Wornell) Internships at IBM Almaden (2010) and HP Labs (2008) Research Interests : Focus on algorithmic and statistical aspects of machine learning, error-correcting codes, optimization, signal processing, and distributed systems. Key areas include clustering algorithms, compressed sensing, federated learning, and information-theoretic foundations of data science. He has contributed to theoretical guarantees for learning mixtures, distributed optimization, and robust coding schemes. Recent Articles Trends : Recent work emphasizes distributed optimization (e.g., vqSGD, Byzantine-resilient algorithms), sparse recovery in high-dimensional models, and theoretical foundations of learning (e.g., support recovery, parameter estimation). His research bridges information theory and machine learning, with applications in storage systems and large-scale data processing. Awards & Roles : 2020 EURASIP JASP Best Paper Award Co-PI and co-leader of the NSF AI Institute for Learning-Enabled Optimization at Scale Editorships: IEEE Transactions on Information Theory and Foundations and Trends in Communications Grants & Labs : Leads the EnCORE Institute as UCSD Site Lead, focusing on theoretical perspectives of large language models and computational-statistical gaps. Active in organizing workshops on topics like LLMs, clustering, and distributed optimization. His research is funded by NSF and industry collaborations. Teaching : Courses include Algorithms for Data Science , Probability and Statistics for Data Science , and Coding Theory , emphasizing foundational theory and scalable methods.

John Dalsgaard Sørensenمشاهده پروفایل

استاد

• Wind Turbines
• Structural Safety
• Risk Analysis
• +۵ مورد دیگر

John Dalsgaard Sørensen is a Professor and Head of Research Group at the Department of the Built Environment, Aalborg University, within the Faculty of Engineering and Science. He leads the Risk, Resilience, Safety, and Sustainability of Systems Research Group and is affiliated with the Danish Centre for Risk and Safety Management. His research focuses on structural safety, wind turbine reliability, probabilistic design, and risk assessment of infrastructure systems. He has supervised 13 PhD students and contributed to over 600 publications. Key research areas include wind turbine structural integrity, fatigue analysis of offshore and onshore structures, probabilistic design standards (e.g., Eurocodes), and risk-based decision-making for infrastructure. He leads projects like Windscanner (remote sensing for wind measurements) and MANTIS (cyber-physical maintenance systems). Collaborations span academia and industry, addressing challenges in energy systems, civil infrastructure, and safety engineering. His work emphasizes practical applications of advanced modeling techniques, such as Bayesian networks and stochastic simulations, to enhance reliability and reduce operational costs. He is actively involved in standardization efforts for structural design and serves on boards like Energi- og MiljøData Fonden. Recent activities include presenting at international conferences and advising on media debates related to structural safety.

Francesco Caravennaمشاهده پروفایل

استاد

• Probability Theory
• Mathematical Statistics
• Stochastic Processes
• +۲ مورد دیگر

Francesco Caravenna is a Full Professor at the Department of Mathematics and Applications of the University of Milan-Bicocca. His research focuses on Probability Theory and Mathematical Statistics, particularly in stochastic processes, disordered systems, and scaling limits. Editorial Roles: Associate Editor for The Annals of Applied Probability (2019) and Annales de l'Institut Henri Poincaré-Probabilités et Statistiques (2018). His recent work includes studies on the critical 2D stochastic heat flow, directed polymers, and the interplay between disorder and criticality. Publications emphasize rigorous mathematical analysis of stochastic partial differential equations, Gaussian multiplicative chaos, and universal scaling properties. He has received grants from MIUR and the Italian-French University (UniTO) for projects like Random Walks and Polymers (2019) and Large Scale Random Structures (2016). Scientific Awards: Fubini Award (2011), Mario Boella High School, with the Polymath Project and Subalpine Mathesis Association. His contributions span stochastic analysis, disordered systems, and interdisciplinary applications in statistical mechanics and financial modeling. Key themes include pathwise analysis, multiscale behavior, and critical phenomena in random systems.

Nicole Megowمشاهده پروفایل

استاد

• Combinatorial optimization
• Discrete optimization
• Mathematical optimization
• +۱۱ مورد دیگر

Nicole Megow is a Professor holding the chair for Combinatorial Optimization in the Faculty of Mathematics and Computer Science at the University of Bremen since 2016. She is affiliated with several research clusters including Humans on Mars Initiative, Minds, Media, Machines, and Dynamics in Logistics. Her academic journey includes positions at TU Berlin, Max Planck Institute for Informatics, TU Darmstadt, and TU Munich. Professor Megow's research focuses on mathematical optimization, algorithm design and analysis, and operations research. Her specific interests span combinatorial and discrete optimization, efficient algorithms, scheduling theory, resource allocation, packing problems, network design, routing, and uncertainty models including online, stochastic, robust, and explorable approaches. Her work bridges theoretical foundations with practical applications in logistics and decision-making systems. Her recent publications demonstrate a strong trend toward integrating prediction models with traditional optimization frameworks, particularly in scheduling and matching problems. She has made significant contributions to understanding the role of uncertainty in optimization problems, developing algorithms that work effectively with incomplete or uncertain information. Her work spans multiple prestigious venues including Mathematical Programming, Algorithmica, SODA, STACS, and NeurIPS. Dissertation Award by the German Operations Research Society (2007) Berlin Science Award for Young Researchers (2013) Heinz Maier-Leibnitz Prize (2013) Listed among Germany's top 40 researchers below 40 (Capital, 2014, 2015) Professor Megow actively supervises PhD students and postdocs, including Max Stahlberg, Joes Biburger, Sarah Morell, Bart Zondervan, Zhenwei Liu, and Alexander Lindermayr. She serves on numerous program committees for major conferences including SODA, IPCO, and STOC, and holds editorial positions for several prestigious journals. Her current research projects include Optimization under Explorable Uncertainty (DFG funded), How robots learn how to use structure (seed grant from MMM research cluster), and Scheduling Invasive Multicore Programs Under Uncertainty (within TCRC 89).

Endre Süliمشاهده پروفایل

استاد

• Numerical Analysis of Partial Differential Equations
• Finite Element Methods
• Computational Modeling of Fracture
• +۴ مورد دیگر

Endre Süli is Professor of Numerical Analysis at the University of Oxford, where he has maintained a distinguished academic career since 1985. He currently serves as Fellow and Tutor in Mathematics at Worcester College and Supernumerary Fellow at Linacre College. His progression at Oxford includes University Lecturer in Numerical Analysis (1985-1996), Reader in Numerical Analysis (1996-1999), and Professor of Numerical Analysis (1999-present). Süli completed his B.Sc. in Mathematics at the University of Belgrade (1974-1978), followed by an M.Sc. in Mathematics (1978-1980). As a British Council Visiting Student, he studied at Reading University and Oxford University in 1983/84, earned his Ph.D. from the University of Belgrade in 1985, and received his M.A. from Oxford University in the same year. Professor Süli's research centers on numerical analysis of nonlinear partial differential equations with applications across multiple scientific domains. His work spans free-discontinuity problems and computational modeling of fracture; finite element methods; Navier-Stokes-Fokker-Planck systems; adaptive algorithms with a-posteriori error control; implicitly constituted material models; and discontinuous finite element methods. His research bridges theoretical mathematics with practical computational approaches for complex physical phenomena. Recent publications (2024-2025) demonstrate Süli's continued leadership in numerical analysis, with focus areas including fractional calculus, stochastic PDEs, and advanced finite element techniques. His work shows strong interdisciplinary connections between mathematical analysis, fluid dynamics, and materials science, addressing challenging problems in polymeric fluids, porous media, and capillary flow modeling. Professor Süli's distinguished career has been recognized with numerous prestigious honors: Invited Speaker at the International Congress of Mathematicians, Madrid (2006) Fellow of the Institute of Mathematics and its Applications (2007) Foreign Member of the Serbian National Academy of Sciences and Arts (2009) Fellow of the European Academy of Sciences (2010) IMA Service Award (2011) SIAM Fellow (2016) Member of the Academia Europaea (2020) London Mathematical Society Naylor Prize and Lectureship (2021) Fellow of the Royal Society (2021) As an educator, Süli has received the Oxford University Teaching Excellence Award (2009) and the Mathematical Institute Teaching Award (2013). He has supervised numerous PhD students and postdoctoral researchers throughout his career, though specific names aren't documented in the available materials. His research has been supported by various grants enabling work on computational methods for partial differential equations. Süli maintains active service to the mathematical community through editorial boards and professional organizations. Professor Süli is affiliated with the Numerical Analysis research group and the Oxford Centre for Nonlinear PDE at the Mathematical Institute. These research centers provide a collaborative environment for theoretical and applied work on partial differential equations. His research often involves interdisciplinary collaborations with physicists, engineers, and computational scientists to develop and analyze numerical methods for complex physical phenomena.

• Information Systems
• Sustainable Energy Markets
• Smart Grids
• +۱۰ مورد دیگر

Wolf Ketter is a Full Professor of Next Generation Information Systems at the Department of Technology and Operations Management, Rotterdam School of Management, Erasmus University, and Chaired Professor of Information Systems at the University of Cologne. He serves as Director of the Institute of Energy Economics (EWI) in Cologne and leads the Erasmus Centre for Future Energy Business in Rotterdam. He is a leading figure in designing sustainable smart markets using advanced computing and simulation techniques. His research focuses on Information Systems , Machine Learning , Energy Economics , and Sustainable Smart Markets . He pioneered the use of Competitive Benchmarking through simulation platforms like Power TAC to tackle complex sustainability challenges. His work bridges computer science, economics, and business to design intelligent systems for energy, transportation, and resource allocation. The recent articles highlight a strong trend toward real-time decision-making in sustainable systems—such as electric bus operations, shared electric vehicles, traffic signal control via reinforcement learning, and local energy markets. These reflect his focus on AI-driven optimization , smart market design , and urban sustainability . Scientific Awards: INFORMS ISS Design Science Award (2012) Runner-up for Best European IS Research Paper (2013) ERIM Top Article Award (2013) ERIM Impact Award (2014) He has supervised over 10 PhD students and secured significant research impact through grants and collaborative projects. His editorial roles include serving on the boards of Information Systems Research and MIS Quarterly , the top journals in the IS field. He has chaired over 20 international conferences and workshops, advancing global discourse in trading agents and sustainable systems. Wolf Ketter founded and leads the Learning Agents Group at Erasmus University and chairs the annual Erasmus Energy Forum . His labs and teams focus on building simulation environments and AI agents to model and improve real-world sustainable markets, particularly in energy and mobility.