جست‌وجوی استاد و پژوهشگر

LU Wen Fengمشاهده پروفایل

دانشیار مدعو

• Additive Manufacturing
• Robotics
• Smart Manufacturing
• +۴ مورد دیگر

LU Wen Feng is an Adjunct Associate Professor in the Department of Mechanical Engineering at the National University of Singapore (NUS), affiliated with the College of Design and Engineering. His research focuses on advanced manufacturing technologies, including additive manufacturing, robotics, and AI-driven systems. He explores sustainable design methodologies, smart manufacturing innovations, and bioprinting applications. Key areas include optimizing material processes, enhancing mechanical properties of printed materials, and developing autonomous robotic solutions for industrial tasks. Contact: mpelwf@nus.edu.sg , located at E3-02-07. Research Interests : His work bridges AI and manufacturing, emphasizing Knowledge graph integration for additive manufacturing, Autonomous robotic systems in industrial settings, Bioprinting for tissue repair with smart bioinks, Topology optimization for lightweight and sustainable structures, Material characterization and process engineering for 3D-printed composites. Recent Article Trends : LU Wen Feng's 2025 articles highlight advancements in AI-augmented manufacturing systems (e.g., MaViLa, AutoMEX) and sustainable design workflows. His 2024 studies address material anisotropy, corrosion behavior, and topology optimization strategies for lattice structures. These trends reflect his interdisciplinary approach to solving challenges in additive manufacturing, robotics, and biomedical applications. Awards : No scientific awards explicitly mentioned. Advising & Grants : No current graduate students or grants listed. His research likely integrates industry-academia collaborations given the focus on applied manufacturing technologies. Labs/Teams : Not explicitly detailed, but his work suggests involvement in advanced manufacturing labs and AI-robotics teams at NUS.

Alexander Vladimirskyمشاهده پروفایل

استاد

• Numerical Analysis
• Applied Mathematics
• Nonlinear PDEs
• +۵ مورد دیگر

Roles & Affiliations: Professor of Mathematics at Cornell University, Department of Mathematics. Member of graduate programs in Mathematics, Applied Mathematics, Operations Research and Information Engineering, Theoretical & Applied Mechanics, and Computational Science & Engineering. Co-organizer of the Scientific Computing and Numerics (SCAN) Seminar and founder of the Cornell Mathematical Contest in Modeling. Education: Ph.D. in Applied Mathematics from University of California, Berkeley (2001); B.A. in Applied Mathematics (with high honors) from University of California, Berkeley (1995). Research Interests: Focuses on numerical analysis, nonlinear PDEs, control theory, and dynamical systems. Explores applications in optimal control, front propagation, anisotropy, bifurcation theory, and mathematical biology. Develops methods for invariant manifold approximation, Eikonal equations, and stochastic systems. Recent work includes studies on cancer therapy optimization, surveillance evasion, and pedestrian flow modeling. Teaching: Teaches courses like Introduction to Partial Differential Equations, Differential Games, Numerical Analysis, and Mathematical Modeling. Recent courses include Math 4280 (Spring 2025) and Math 3610 (Fall 2024). Labs/Teams: Active in interdisciplinary collaborations, including work on computational biology, robotics path planning, and mathematical contest problem-solving initiatives.

Julia Kempeمشاهده پروفایل

استاد

• Data Science
• Machine Learning
• Quantum Computing
• +۳ مورد دیگر

Julia Kempe is a Silver Professor of Computer Science, Mathematics, and Data Science at New York University (NYU), holding joint appointments at the Courant Institute and the Center for Data Science (CDS). She serves as Director of the CDS and is on research leave at the CSD, ENS, Paris (2023–24). Her expertise spans interdisciplinary research in quantum computing, machine learning, and data science. She holds PhDs in Mathematics (UC Berkeley, 2001) and Computer Science (École Nationale Supérieure des Télécommunications, Paris, 2001), alongside advanced degrees in theoretical physics and mathematics from prestigious institutions in France and Austria. Research Interests: Data Science, Machine Learning (theoretical foundations and applications to physics), and past contributions to quantum computing. She focuses on robustness in machine learning models, adversarial examples, and interdisciplinary applications of physics-informed AI. Awards and Honors: Knight of the National Order of Merit (France, 2010), Femme en Or de la Recherche (France, 2010), ERC Starting Grant (2007, top-ranked in Europe), and numerous academic fellowships. She is a member of Academia Europaea (2018) and a Fellow of the Asia-Pacific Artificial Intelligence Association (2022). Grants and Leadership: Principal investigator of NSF NRT grants for CDS PhD programs, co-PI on NASA TCAN grants, and leader in NYU’s Senior Leadership Team. She designed NYU’s Data Science undergraduate programs and expanded interdisciplinary collaborations in machine learning and quantum computing. Labs and Teams: Directs the CDS, collaborates with the Courant Institute, and leads research initiatives in Paris. Her work bridges theoretical computer science, physics, and applied data science, emphasizing interdisciplinary innovation.

Douglas A. Loyمشاهده پروفایل

استاد

• Sol-gel chemistry
• Tetrazine polymer chemistry
• Energy-storage materials
• +۶ مورد دیگر

Douglas A. Loy is a full Professor at the University of Arizona with joint appointments in the Department of Materials Science and Engineering and the Department of Chemistry and Biochemistry, and additional affiliations with the BIO5 Institute and the School of Mining and Mineral Resources. A fifth-generation Arizonan, he earned his BS in Chemistry from the University of Arizona (1983), MS in Chemistry from Northern Arizona University (1986), and PhD in Organic Chemistry from the University of California, Irvine (1991). Before returning to academia he spent 14 years at Sandia National Laboratories and then led the Polymer and Nanomaterials Synthesis Team at Los Alamos National Laboratory. Research Interests Sol-gel & polysilsesquioxane chemistry: fundamental studies and unconventional routes to hybrid organic-inorganic materials. Tetrazine polymer chemistry: synthesis, click modification, and application in antioxidant foams and UV-stable sunscreens. 3-D printing of glasses & ceramics: additive manufacturing of micro-optics, multi-refractive-index glass objects, and transparent devices using silica and silsesquioxane resins. Energy & biomaterials: new materials for energy storage, polymer-ceramic bone scaffolds, and smart packaging films. Across more than 70 recent publications (2012-2025), the dominant themes are advanced additive manufacturing of specialty glasses and ceramics, design of photochemically stable sunscreen systems, and development of multifunctional polymer-ceramic composites for biomedical and energy applications. The work integrates molecular-level organic synthesis with macro-scale materials processing, enabling applications ranging from holographic micro-optics to lunar in-situ resource utilization. Scientific Awards & Recognition While specific honors are not listed in the provided text, Loy is described as a “distinguished member of technical staff” at Sandia National Laboratories, indicating prior recognition for his research achievements. Funding & Collaborative Teams At the University of Arizona his group pursues federally and industrially funded projects spanning NSF, DOE, and NASA programs, particularly in advanced manufacturing and energy materials. He collaborates closely with the BIO5 Institute for biomedical applications and with the School of Mining and Mineral Resources for resource-based materials research. No explicit student lists are included in the text. Laboratory & Facilities Loy’s laboratories are located in Mines and Metallurgy 338B at the University of Arizona, equipped for sol-gel synthesis, polymer processing, and state-of-the-art 3-D printing instrumentation including multi-photon lithography systems for micro-optics fabrication.

• Microfluidics
• Catalyst Particle Research
• Organ-on-Chip Platforms
• +۳ مورد دیگر

Mathieu Odijk is a Full Professor at the University of Twente's Faculty of Science and Technology, leading the Integrated Devices and Systems department. His research focuses on microfluidic systems, catalysis, and organ-on-chip platforms, with contributions to UN Sustainable Development Goals through advanced material characterization and biomedical engineering. He has authored over 120 publications and holds an h-index of 27 with 1,820 citations. Expertise: Microfluidics, catalyst particle diagnostics, SERS substrates, organ-on-chip systems, and spectroscopic techniques. Collaborations include Weckhuysen (catalysis), van den Berg (microfluidics), and Meirer (materials science). Key projects: Modular organ-on-chip platforms (STARTER), droplet-based catalyst screening, and real-time reaction monitoring via ATR-IR systems. His research combines nanotechnology and chemical engineering to develop tools for sustainable energy, environmental remediation, and biomedical applications. Recent work includes microreactors for catalyst particle analysis, light-driven urea oxidation for wearable kidney devices, and standardized platforms for organ-on-chip research.

• Conflict
• Group-based Antipathy
• Right-wing Extremism
• +۱۲ مورد دیگر

Prof. Dr. Andreas Zick is a leading scholar at Bielefeld University, serving as Scientific Director of the Institute for Interdisciplinary Conflict and Violence Research (IKG) and Professor for Socialization and Conflict Research at the Faculty of Education. He also co-leads the ConflictA initiative since 2023 and contributes to migration education through the Faculty of Education. 2008: Professor for Socialization and Conflict Research, Bielefeld University 2013: Director of IKG 2023: Scientific Head of ConflictA His research focuses on intergroup conflicts , group-based antipathy , right-wing extremism , radicalization , and socialization processes . He investigates spatial dimensions of radicalization, societal integration challenges, and prejudice dynamics through comparative studies. Recent publications analyze radicalization spaces (2024-2025) using spatial sociology, democratic conflict perceptions (2025), and cross-cultural prosocial behavior during pandemics. Key methods include ethnography, longitudinal surveys, and multi-perspective comparative analysis. Scientific contributions recognized by: Communicator Award (2016) Nevitt Sanford Lifetime Award (2022) Active in public policy as member of the Federal Agency for Civic Education's advisory board and Federal Commissioner's Antiracism Expert Council. Leads major projects on radicalization prevention and spatial conflict dynamics with national/international partners.

Joachim Weickertمشاهده پروفایل

استاد

• Image Processing
• Computer Vision
• Mathematical Modeling
• +۴ مورد دیگر

Joachim Weickert is a Professor of Mathematics and Computer Science at Saarland University where he heads the Mathematical Image Analysis Group since 2001. He received his diploma and Ph.D. in mathematics from the University of Kaiserslautern (1991, 1996), and a habilitation degree in computer science from the University of Mannheim (2001). Prior to his current position, he worked as a research assistant at the University of Kaiserslautern, as a post-doctoral researcher at the universities of Utrecht and Copenhagen, and as an assistant professor at the University of Mannheim. His research focuses on image processing, computer vision, and scientific computing, with special emphasis on techniques based on partial differential equations, variational principles, wavelets, morphological and nonlocal methods, as well as neuroexplicit approaches. He has developed mathematical models and efficient numerical algorithms for image restoration, enhancement, segmentation, compression, optic flow computation, stereo reconstruction, shape from shading, and signal processing methods for tensor fields. These ideas have been successfully applied in industry, biomedical image analysis, and other fields. Analysis of his recent publications reveals a strong trend toward combining traditional PDE-based methods with modern deep learning approaches, particularly in the areas of image inpainting and compression. His work increasingly explores the connections between numerical algorithms for partial differential equations and neural network architectures, demonstrating how mathematical foundations can inform cutting-edge AI techniques while maintaining strong theoretical guarantees. Gottfried Wilhelm Leibniz Prize (2010), considered the most important research award in Germany ERC Advanced Grant (2017) for "Inpainting-based Compression of Visual Data" Elected member of Academia Europaea - The Academy of Europe Jan Koenderink Prize for Fundamental Contributions in Computer Vision (2014) Multiple DAGM Prizes and Best Paper Awards throughout his career AAIA Fellow (2021) and Highly Ranked Scholar (2024) distinctions Professor Weickert has supervised over 250 bachelor's and master's theses and initiated the Master Programme in Visual Computing at Saarland University, the first of its kind in Germany taught in English. He has established numerous interdisciplinary collaborations with colleagues from medicine, bioinformatics, pharmacy, physics, mechatronics, and mechanical engineering. As Principal Investigator for Visual Computing within the Multimodal Computing and Interaction Cluster of Excellence, and former dean of the Faculty of Mathematics and Computer Science (2008-2010), he has played a significant leadership role in advancing visual computing research and education. He heads the Mathematical Image Analysis Group, which has been at the forefront of developing mathematical methods for image analysis. The group maintains strong connections with both theoretical mathematics and practical applications, bridging the gap between fundamental research and real-world implementation across various domains including medical imaging, industrial inspection, and multimedia processing.

Balazs Trencsenyiمشاهده پروفایل

استاد

• Intellectual History
• Political Thought
• Comparative History
• +۱۲ مورد دیگر

Balázs Trencsenyi is Professor in the Department of Historical Studies at Central European University (CEU) and serves as Director of the CEU Institute for Advanced Study in Budapest. He is also Co-Director of Pasts Inc., Center for Historical Studies, and a Member of the 'Democracy in History' Working Group at the CEU Democracy Institute. His academic leadership includes directing the Erasmus Mundus+ Program 'History in the Public Sphere' (2019–2023) and heading the History Department (2017–2020). His educational background includes a PhD in Comparative History from CEU (2004), an MA in Nationalism Studies from CEU (1998), and an MA in Philosophy from Eötvös Loránd University (1997). Trencsenyi is a leading scholar in the intellectual and political history of East Central Europe, with a focus on transnational and comparative approaches. His research examines political modernity, crisis discourses, nationalism, national characterology, anti-modernism, and the conceptual history of identity and temporality. He has directed major collaborative projects such as the ERC-funded 'Negotiating Modernity' and 'European Regions and Boundaries: A Conceptual History.' His influential publications include the multi-volume A History of Modern Political Thought in East Central Europe (Oxford University Press) and Intellectuals and the Crisis of Politics in the Interwar Period and Beyond (2025). His recent articles reflect sustained engagement with crisis discourses, authoritarian regime-building, transnational intellectual history, and the politics of memory in East Central Europe. Themes across his work include the fragility of democracy, the legacy of state socialism, and the interplay between nationalism and modernity. CEU Community Service Excellence Award (2023) Fellow of Wissenschaftskolleg zu Berlin (2020) Member of Academia Europaea (2011) ERC Starting Grant (2008–2013) Trencsenyi has supervised numerous doctoral students in political thought, nationalism, and intellectual history. He has led research clusters such as 'Crises of Democratization' under the CIVICA project and co-organizes the 'Invisible University for Ukraine' initiative. He is Editor of East Central Europe (Brill) and has served on editorial boards and peer-review panels for major academic institutions and journals. His teaching covers comparative history, political modernity, crisis discourses, and counter-cultural movements under socialism.

Reinhard Heckelمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Computational Imaging
• +۵ مورد دیگر

Reinhard Heckel is a Tenured Associate Professor (equivalent to Professor) of Machine Learning at the Department of Computer Engineering, Technical University of Munich (TUM), and Adjunct Faculty in Electrical and Computer Engineering at Rice University. He was previously an Assistant Professor at Rice (2017–2019), a postdoc in the Berkeley Artificial Intelligence Research (BAIR) Lab at UC Berkeley, and a researcher at IBM Research Zurich. Education: PhD, 2014 – ETH Zurich Visiting PhD student – Department of Statistics, Stanford University Research Interests: His work centers on machine learning and information processing with three major thrusts: (1) developing algorithms and theoretical foundations for deep learning, especially for accelerated magnetic resonance imaging ; (2) establishing rigorous mathematical and empirical underpinnings for modern machine-learning systems; and (3) leveraging DNA as a digital information-storage medium , including error-correction coding and system design for DNA-based storage. Across more than 100 peer-reviewed papers since 2017, Heckel’s research exhibits a strong interdisciplinary blend of computational imaging , machine-learning theory , and molecular data storage . Recent 2024–2025 publications show intensive focus on robust MRI reconstruction using diffusion priors, evaluation of bias in large web-text corpora, and state-of-the-art error-correcting codes for DNA storage channels. A forthcoming book, Deep Learning for Computational Imaging (Oxford University Press), consolidates his contributions to the field. Outreach & Media: Keynote and panel talks at DLD, TUM, and major ML conferences Op-eds in Frankfurter Allgemeine on ChatGPT and DNA storage Science features on Netflix, BBC, and German television (Galileo, “Gut zu Wissen”) Research Environment: At TUM he leads a group investigating theoretical and applied aspects of deep learning, compressed sensing, and coding for DNA storage. Open-source repositories on GitHub (e.g., dna_data_storage , supplement_deep_decoder ) provide code and data supplements accompanying his publications.

Katrin Tentمشاهده پروفایل

استاد

• Model theory
• Group theory
• Geometry
• +۴ مورد دیگر

Professor Katrin Tent is a distinguished mathematician specializing in mathematical logic at the University of Münster, where she holds a professorship in the Faculty of Mathematics and Computer Science within the Institute for Mathematical Logic and Foundations Research. She is an active researcher in Mathematics Münster, an investigator in CRC 1442 Geometry: Deformations and Rigidity, and contributes to multiple research projects including Topics in Mathematics Münster T3: Models and universes, T4: Groups and actions, and T8: Random discrete structures and their limits. PhD in Linguistics, Christian-Albrechts-Universität zu Kiel (1988) Diplom in Mathematics, Christian-Albrechts-Universität zu Kiel (1989) PhD in Mathematics, University of Notre Dame (1994) Habilitation, "Model theory of groups and BN-pairs" (2000) Professor Tent's research bridges model theory, group theory, and geometry, with particular focus on finite Morley rank structures, BN-pairs, and sharply multiply transitive groups. Her work often combines methods from these areas to prove unexpected results, either constructing groups or incidence geometries with surprising model theoretic properties or using model theory to construct new and interesting geometries or groups. Her recent publications reveal a consistent trajectory connecting model theory with group-theoretic structures. She has made significant contributions to understanding sharply 2- and 3-transitive groups, finite Morley rank geometries, and the model theory of generalized polygons. Her work demonstrates how model-theoretic techniques can solve deep problems in group theory and geometry, particularly through the study of BN-pairs and incidence structures. DFG Research Fellowship (1996-1998) Bayerischer Habilitationsförderpreis (1998-2001) Heisenberg-Stipendium (2001-2004) ERC Consolidator Grants expert panel (2016, 2018) Elected to DFG Senate (2019) Professor Tent leads an active research group with current members including Marco Amelio, Dr. Benjamin Brück, Anna Cascioli, Lukas Jonuska, Silke Meissner, Zahra Mohammadi Khangheshlaghi, and Dr. Sam Shepherd. Her former research group members include Dr. Simon Andre, Dr. Isabel Müller, and Dr. Tim Clausen, among others. Her supervisory work spans both theoretical foundations and specific applications in geometric group theory and model theory. Her research group operates within the Institute for Mathematical Logic and Foundations Research at the University of Münster, collaborating closely with other researchers in the Mathematics Münster cluster. The group participates in various projects including CRC 1442 - C04: Group theoretic aspects of negative curvature, contributing to the vibrant mathematical research environment at one of Germany's leading mathematics institutions.

Joseph Dumplerمشاهده پروفایل

مدرس

• Food Engineering
• Dairy Science and Technology
• Sustainable Food Processing
• +۴ مورد دیگر

Dr. Joseph Dumpler is a Lecturer at the Department of Health Sciences and Technology at ETH Zürich, specializing in Sustainable Food Processing. He holds a PhD in Dairy Science and Technology from the Technical University of Munich, Weihenstephan, with a focus on UHT treatment of concentrated milk. His work emphasizes advancing food processing technologies, particularly in protein refinement, non-thermal methods, and membrane filtration. Educations: PhD in Dairy Science and Technology, Technical University of Munich, Weihenstephan (2017) MSc Food Engineering, Technical University of Munich, Weihenstephan His research interests include Natural Deep Eutectic Solvents (NADES) for plant protein extraction, microwave vacuum drying of dairy products, and membrane filtration optimization for microalgae and dairy systems. He has pioneered methods to refine rapeseed and pea proteins while minimizing antinutrients, and his work on microfiltration of milk products addresses emerging microbial risks. Key contributions span kinetic modeling of heat-induced protein aggregation, sustainable food processing , and non-thermal concentration techniques . His articles reflect a focus on bridging lab-scale innovations with industrial applications. Awards: J.T.M. Wouters Young Scientist Award Julius Maggi Research Award (2018) Best PhD Thesis Award from the Association of Dairy, Food and Biotechnologists (Weihenstephan) Dr. Dumpler collaborates with industry partners to translate research into scalable processes, such as NADES-based protein extraction and microwave drying systems. His current role at ETH Zürich’s Sustainable Food Processing Lab (Prof. Mathys) focuses on plant-based meat analogs and novel protein refining concepts .

• Contact Mechanics
• Tribology
• Advanced Manufacturing
• +۵ مورد دیگر

Hongtao Zhu is an Associate Professor at the University of Wollongong (UOW), Australia, affiliated with the School of Mechanical, Materials, Mechatronic and Biomedical Engineering. He holds a PhD from Northeastern University (China) and has held academic positions at UOW since 2002, progressing from Research Fellow (2002–2013) to Senior Lecturer/Lecturer (2013–2022) before becoming an Associate Professor in 2022. His research focuses on Contact Mechanics , Tribology , Advanced Manufacturing , and Computational Material Science . Notable contributions include studies on rail-wheel contact systems, high-entropy alloys, and friction reduction in manufacturing processes. He has authored/co-authored over 230 publications with an H-index of 38 (Scopus) and secured $2.2M in industry grants. Zhu leads the 'Wheel and Rail Contact System' research group, collaborating with major railway industries. He has supervised 22 PhD students (6 as principal supervisor) and currently oversees 5 PhD candidates. His professional roles include editorial board memberships for journals like Advances in Materials Science and Engineering and service as an assessor for funding bodies in Australia, Chile, Poland, and the Czech Republic. Key achievements include securing 5 ARC Discovery Projects, 3 ARC Linkage Projects, and industry collaborations with organizations like Sydney Trains and Comsteel. His work addresses critical challenges in rail infrastructure durability, material optimization, and sustainable manufacturing.

Vazira Fazila-Yacoobali Zamindarمشاهده پروفایل

دانشیار

• Anti-colonialism
• borders
• contemporary art
• +۷ مورد دیگر

Vazira Fazila-Yacoobali Zamindar serves as Associate Professor of History at Brown University, specializing in modern South Asia, decolonization, and visual archives. Her interdisciplinary work bridges historical scholarship with contemporary art and public engagement, notably through her acclaimed book The Long Partition and the Making of Modern South Asia (2007). Her educational background includes a PhD from Columbia University (2003), MA from the University of Michigan Ann Arbor (1997), and BA from Wellesley College (1992). As Director of Brown's South Asian Studies Program (2012-2016), she co-organized the Brown-Harvard Pakistani Film Festivals and founded the Theory from the South reading group. Zamindar's research critically examines decolonization, displacement, and statelessness through visual and oral histories. Current projects include a graphic novel collaboration with Sarnath Banerjee on Gandhi and Abdul Ghaffar Khan (supported by the Salomon Research Grant) and the Anticolonial solo exhibition at Karachi's Canvas Gallery (2023), exploring anticolonial resistance on the Indo-Afghan border. Her publications reveal evolving interdisciplinary trends: early works focus on Partition refugees and borders, while recent scholarship (2020-2023) emphasizes repair, statelessness architectures, and secularism in South Asian art. Recurring themes include border politics, visual culture, and decolonial methodologies across historical and contemporary contexts. Scientific recognition includes: National Endowment for the Humanities Fellowship (2009-10) Fulbright Research Scholar (2008-9) Richard B. Salomon Faculty Research Award (2022-23) Visiting Fellow at FU Berlin's Center for Affective Societies (2020-21) She actively engages public scholarship through collaborations with Primary Source, RISD Museum, Lahore Museum, and media appearances on BBC Radio's Museum of Lost Objects . Her teaching portfolio includes courses like Resisting Empire: Gandhi and the Making of Modern South Asia and Art History from the South , reflecting commitment to decolonial pedagogy. Zamindar co-leads the Decolonial Initiative on Migration of Objects and People and continues developing her graphic novel project while expanding the Art History from the South series through collaborations with scholars like Tapati Guha-Thakurta.

Lenya Ryzhikمشاهده پروفایل

استاد

• Partial Differential Equations
• Analysis
• Applied Mathematics
• +۵ مورد دیگر

Lenya Ryzhik is a Professor in the Department of Mathematics at Stanford University, specializing in analysis and partial differential equations with applications in various physical contexts. His research spans stochastic processes, wave propagation, and front dynamics in random media, with significant contributions to understanding reaction-diffusion systems and their applications in mathematical biology and physics. Professor Ryzhik's research interests focus on the mathematical analysis of partial differential equations arising in physical systems. His work particularly emphasizes stochastic PDEs, wave propagation in random media, front propagation in reaction-diffusion systems, and homogenization theory. He investigates how randomness and complex structures affect wave propagation, front speeds, and transport phenomena, with applications ranging from combustion theory to population dynamics and quantum mechanics. The publication record demonstrates a consistent focus on understanding propagation phenomena in complex environments. Ryzhik's research shows a progression from classical PDE analysis toward increasingly sophisticated stochastic frameworks, particularly examining high-dimensional systems and random media. His recent work has focused on KPZ fluctuations, random heat equations, and non-local reaction-diffusion models, revealing deep connections between probability theory and partial differential equations. Alfred P. Sloan Research Fellowship (2002-2004) AFOSR NSSEFF Fellowship (2010-2015) Ryzhik has advised graduate students including Alexandra Stavrianidi, and has secured substantial research funding throughout his career. His grant history includes multiple NSF awards (DMS-9971742, DMS-0203537, DMS-0604687, DMS-0908507, DMS-1311903), ONR funding (N00014-02-1-0089, N00014-04-1-0224), and FRG support for collaborative research on nonlinear evolution problems. He co-organized a Summer School and Workshop on 'Recent Advances in PDEs and Fluids' at Stanford in 2013. Ryzhik maintains an active research group collaborating with leading mathematicians worldwide, particularly with researchers at institutions like NYU, Chicago, and various European universities. His work frequently involves interdisciplinary collaborations bridging mathematics with physics and biology.

Edouard Boujoمشاهده پروفایل

مدرس

• Fluid Dynamics
• Flow Stability
• Flow Control
• +۷ مورد دیگر

Dr. Edouard Boujo is a Scientist and Lecturer at the Swiss Federal Institute of Technology Lausanne (EPFL) , affiliated with the School of Engineering (STI) and working in the Institute of Mechanical Engineering (IGM) and Laboratory of Fluid Mechanics and Instabilities (LFMI) . He also teaches in the SGM-ENS department of the School of Engineering. Scientist at EPFL STI IGM LFMI Lecturer at EPFL STI-SGM SGM-ENS His research focuses on Fluid Dynamics with expertise in Flow Stability , Flow Control , Aeroacoustics , Thermoacoustics , Fluid-Structure Interaction , and Coating Flow Dynamics . He employs advanced mathematical modeling and computational methods to study complex fluid behaviors. Recent publications highlight his work on stochastic modeling of fluid instabilities, adjoint-based optimization of flow systems, and nonlinear dynamics of coating flows. His 15 most recent papers cover topics ranging from symmetry-breaking bifurcations to spin coating optimization and noise-induced transitions in fluid systems. Dr. Boujo actively collaborates with institutions across Europe and New Zealand, mentoring PhD student Atharva Lagwankar . He has received research funding from the Swiss National Science Foundation for two PhD theses and contributes to major fluid dynamics conferences like the European Fluid Dynamics Conference and APS Division of Fluid Dynamics meetings. His laboratory work at LFMI involves experimental and computational studies of fluid instabilities, with applications in aerospace, mechanical engineering, and industrial coating processes. He develops adjoint-based control methods for optimizing flow systems and reducing drag in various fluid configurations.