Find Academic Supervisors

Cesare FranchiniView profile

Professor

• Quantum Materials
• Computational Physics
• First Principles Methods
• +7 more

Cesare Franchini is a full Professor at the University of Vienna's Faculty of Physics, leading the Computational Materials Physics research group. His work focuses on theoretical understanding and computational modeling of quantum materials using first principles methods, particularly VASP. He maintains an active research program with numerous postdocs, PhD students, and collaborations across multiple institutions including the University of Bologna. Professor Franchini's research centers on quantum materials with many interacting degrees of freedom (lattice, spin, and electron orbital) that enable novel electronic and magnetic phases. His specific interests include metal-insulator transitions, polaron physics (electron-phonon interactions), non-collinear spin orderings, topological Dirac/Weyl phases, multiferroism, and superconductivity. He has increasingly incorporated machine learning data-driven tools and diagrammatic Monte Carlo techniques into his computational approaches. Analysis of his recent publications (2024-2025) reveals a strong focus on polaron physics across multiple material systems, with significant work on hematite, titanium dioxide, and quantum paraelectrics like KTaO3. His research increasingly integrates machine learning with traditional first-principles methods, particularly for studying hydrogen diffusion, surface science phenomena, and electronic structure calculations. There's also substantial work on single-atom catalysis and the application of advanced computational techniques to understand fundamental charge transport mechanisms in energy materials. Professor Franchini actively supervises numerous PhD students and postdocs, including Andrea Angeletti, Viktor Birschitzky, Lorenzo Celiberti, and several others working on diverse aspects of computational materials physics. He leads or participates in major research projects including TACO (Taming Complexity in Materials Modeling), DCAFM (Doctoral College Advanced Functional Materials), and the recently launched Spin-orbit entangled anharmonic polarons project. His group maintains strong collaborations with experimentalists at Charles University, Technical University of Vienna, and other international institutions.

Bonadonna CostanzaView profile

Professor

• Volcanic Ash Dispersal
• Volcanic Risk Assessment
• Physical Volcanology
• +2 more

Costanza Bonadonna is a Full Professor at the University of Geneva (since 2019), specializing in volcanic hazards and Earth sciences. She holds a PhD supported by the European Commission (1998–2000) and has held academic positions across institutions including the University of South Florida and University of Hawaii. Her research focuses on volcanic ash dispersal modeling, risk assessment, and physical volcanology, with notable contributions to understanding tephra deposits and eruption dynamics. Bonadonna has received prestigious awards such as the 2020 AGU Volcanology presidency and the International Galileo Galilei Award. She leads the CERG-C (Centre for Environmental Risk Studies) and has organized major international workshops on volcanic risk and ash dispersal. Her work integrates numerical modeling, field investigations, and geophysical observations to enhance volcanic hazard forecasting and community resilience strategies. Research Grants: 2019–2023: SNSF Probabilistic volcanic risk framework 2018–2021: H2020 NEWTON-g and EUROVOLC networks 2017–2020: SNSF Gravitational instabilities in volcanic clouds Awards: 2020 President elect of AGU Volcanology Division Galileo Galilei Award (2020) Outstanding Woman in Science (2004, GSA) She has advised numerous international projects and collaborates with global institutions through initiatives like MeMoVolc and NEMOH. Her research bridges geophysical observations with computational models to address multi-hazard scenarios and improve disaster preparedness.

Süli EndreView profile

Professor

• Free-discontinuity problems
• Computational modelling of fracture
• Quasi-continuum methods
• +10 more

Endre Süli is a Professor of Numerical Analysis at the University of Oxford, affiliated with Worcester College and Linacre College. He has held various academic roles since 1985, including Fellowships and Tutorships in Mathematics. University Education: B.Sc. in Mathematics, University of Belgrade (1974-1978) M.Sc. in Mathematics, University of Belgrade (1978-1980) Ph.D. in Mathematics, University of Belgrade (1985) M.A., University of Oxford (1985) British Council Visiting Student, Reading University and University of Oxford (1983/84) Süli's research focuses on numerical methods for partial differential equations (PDEs), with expertise in finite element methods, adaptive algorithms, error control, and computational modeling of fractures and non-Newtonian fluids. His work bridges mathematical theory and practical applications in fluid dynamics and material science. His recent publications emphasize finite element approximations, nonlinear PDEs, and stochastic models for polymer dynamics. Themes include multiscale methods, tensor-sparsity for high-dimensional problems, and compressible flow simulations. Scientific Awards: Fellow of the Royal Society (2021) London Mathematical Society Naylor Prize and Lectureship (2021) Pro Urbe Prize, City of Subotica (2021) SIAM Fellow (2016) Member, Academia Europaea (2020) Foreign Member, Serbian National Academy of Sciences and Arts (2009) IMA Service Award (2011) Fellow, European Academy of Sciences (EurASc) (2010) Fellow, Institute of Mathematics and its Applications (2007) London Mathematical Society/New Zealand Mathematical Society Forder Lecturer (2015) Professor Hospitus, Charles University, Prague (2012) Distinguished Visiting Chair Professor, Shanghai Jiao Tong University (2013) Invited Speaker, International Congress of Mathematicians, Madrid (2006) Süli has supervised numerous research projects and held visiting appointments globally. His contributions to numerical analysis span foundational work on error estimation, nonlinear stability, and advanced computational frameworks for complex physical systems.

Endre SüliView profile

Professor

• Numerical Analysis of Partial Differential Equations
• Finite Element Methods
• Computational Modeling of Fracture
• +4 more

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.

• Analog and mixed-signal integrated circuit design
• Computer-aided design (CAD) of electronic circuits
• Design automation (EDA)
• +5 more

Georges Gielen is Full Professor in the Department of Electrical Engineering (ESAT) at KU Leuven, Belgium, and part-time Research Director at imec. He has held multiple leadership roles including Chair of ESAT Department (2012-2013, 2020-2024) and Vice-Rector for Science, Engineering & Technology (2013-2017). His academic career spans over 30 years at KU Leuven, progressing from Assistant to Full Professor. His research focuses on analog and mixed-signal integrated circuit design automation , with expertise in CAD tools, design optimization, sensor interfaces, and neuromorphic systems. His work bridges hardware design with machine learning, particularly in hardware-efficient AI implementations and biomedical applications. He has pioneered techniques for automated analog circuit sizing, topology synthesis, and reliability-aware design in nanometer CMOS. Gielen has received numerous accolades including the IEEE CAS Mac Van Valkenburg Award (2015), IEEE CAS Charles Desoer Award (2020), and EDAA Achievement Award (2021). He holds an ERC Advanced Grant AnalogCreate and is an IEEE Fellow since 2002. As a prolific scholar, he has chaired major conferences including DATE (2006), ICCAD (2007), and ESSCIRC (2017). He has graduated over 55 PhD students through the MICAS research group at KU Leuven, currently supervising 13 doctoral candidates. His research team collaborates extensively with imec and industry partners on cutting-edge projects in carbon-aware AI accelerators, uncertainty-aware design, and neuromorphic sensor interfaces.

Johannes BrandstetterView profile

Associate Professor

• Machine Learning
• Deep Learning
• Geometric Deep Learning
• +5 more

Johannes Brandstetter is an Associate Professor at the Institute for Machine Learning at Johannes Kepler University Linz (JKU) where he leads the "AI for data-driven simulations" research group. He is also Co-founder and Chief Scientist at Emmi AI, bridging academic research with industrial applications in AI-driven physics simulation. Brandstetter earned his PhD after working at CERN's CMS experiment on Higgs boson physics. In 2018, he transitioned to machine learning, joining Sepp Hochreiter's research group in Linz. From 2021-2023, he worked at the Amsterdam Machine Learning Lab under Max Welling and Microsoft Research, developing expertise in Geometric Deep Learning and neural surrogates for partial differential equations. He returned to JKU in October 2023 to establish his own research group. His research spans Machine Learning, Deep Learning, and Physics-Informed Machine Learning with focus areas including Neural PDE solvers, Computational Fluid Dynamics, and Climate Modeling. Brandstetter believes AI is poised to revolutionize industrial-scale simulations, potentially saving thousands of compute hours across engineering domains. His work integrates computer vision, numerical simulation, and engineering components to advance data-driven approaches. Recent publications reveal a strong trend toward foundation models for scientific applications, particularly in atmospheric modeling (Aurora), geometric deep learning, and neural surrogates for complex physical systems. His interdisciplinary work spans computer vision, climate science, computational physics, and engineering, demonstrating the versatility of his research approach. Principal Investigator for "AlKa-DL: Alpine karst spring discharge prediction" (FWF-funded, 2024-2027) Principal Investigator for Cluster of Excellence "Bilateral Artificial Intelligence" (FWF-funded, 2024-2029) Co-PI for "Fast, efficient and flexible CFD simulation through generative AI" (FFG-funded, 2025-2026) As an educator and researcher, Brandstetter actively engages with the scientific community through invited talks at major conferences including presentations on "Closing the Gap Between Scientific Foundation Models and Real-World Applications" (March 2025) and "Scientific Machine Learning for Science and Engineering" (February 2025).

• Sanitary Engineering
• Wastewater Treatment
• Constructed Wetlands
• +7 more

Priv.Doz.DI Dr.nat.techn. Günter Langergraber is a Professor and Head of the Institute of Sanitary Engineering and Water Pollution Control at the University of Natural Resources and Life Sciences, Vienna (BOKU). He also serves as Deputy Head of the Department of Landscape, Water and Infrastructure since 2025. With expertise in nature-based solutions , constructed wetlands , and resource-oriented sanitation systems , his work integrates modelling and simulation with practical applications for wastewater treatment and urban sustainability. Habilitation in Sanitary Engineering (2012), BOKU PhD in Natural Sciences (2001), BOKU His research focuses on developing advanced wastewater treatment technologies using constructed wetlands , biochar systems , and smart sensors . Key areas include urban water circularity , stormwater management , and climate resilience through nature-based infrastructure . He leads major EU-funded projects like ProCleanLakes and UniNEtZ , emphasizing the role of sustainable sanitation in achieving SDG 6 . Recent publications analyze: Design optimization of vertical flow wetlands using numerical models Implementation frameworks for circular cities via nature-based solutions Hydrological dynamics in Mediterranean and tropical wetland systems Soil water balance quantification via stable isotopes Scientific accolades include IWA Fellow (2014) and the IWA Project Innovation Award (2011) . He has supervised 478 publications and 56 projects, including EU Horizon 2020 initiatives and Austrian Science Fund (FWF) programs. As a keynote speaker at international conferences, he advocates for renaturalized urban water systems and decentralized sanitation . Langergraber contributes to technical guidelines (e.g., DWA-A 272) and policy reports for Austrian ministries. His work bridges academic research , industry collaboration , and public engagement through media appearances and training programs for wastewater plant operators.

Sylvain LefebvreView profile

Researcher

• Computer Graphics
• Texture Synthesis
• Additive Manufacturing
• +4 more

Sylvain Lefebvre is a permanent researcher at INRIA (Institut National de Recherche en Informatique et en Automatique) in France, where he leads the MFX research team since 2018. Previously, he was part of the ALICE group at INRIA Nancy (2009-2018) and the REVES team in Sophia Antipolis (2006-2009). His career includes a postdoctoral position at Microsoft Research Seattle (2005) following his PhD at INRIA Rhones-Alpes under Fabrice Neyret. His educational background includes a PhD in Computer Graphics from Université Joseph Fourier (Grenoble) in 2005, preceded by a Master in Computer Graphics from INP Grenoble in 2001. His habilitation thesis focused on Runtime Texture Synthesis. Lefebvre's research centers on simplifying content creation for highly detailed patterns, structures, and shapes with applications spanning Computer Graphics to additive manufacturing. He develops fast, controllable by-example synthesis approaches that generate content while enforcing user-specified constraints. His work addresses computational challenges through novel data structures and algorithms optimized for GPUs and FPGAs, including his Silice programming language. The ERC-funded ShapeForge project (2012-2017) advanced shape generation for 3D printing, leading to the IceSL software for digital modeling and fabrication. Analysis of his 15 most recent publications reveals a strong focus on additive manufacturing optimization, with recurring themes in structural integrity, material efficiency, and geometric algorithms. His work bridges computer graphics theory with practical fabrication constraints, particularly in microstructure design, slicing techniques, and mechanical metamaterials. The interdisciplinary nature spans computer science, materials engineering, and robotics. EUROGRAPHICS Young Researcher Award (2010) ERC Starting Grant for ShapeForge project (2012) Lefebvre has advised over 25 PhD students and interns including Marco Freire, Thibault Tricard, and Jimmy Etienne. His ShapeForge project received significant ERC funding, supporting research in computational fabrication. He serves on numerous program committees including SIGGRAPH, Eurographics, and SIGGRAPH Asia, reflecting his leadership in the computer graphics community. As leader of the MFX team since 2018, Lefebvre directs research in computational fabrication, focusing on IceSL software development for 3D printing workflows. The team integrates computer graphics techniques with manufacturing constraints, developing tools that simplify complex object design and fabrication while addressing real-world challenges in material usage and structural integrity.

Ajay Vikram SinghView profile

Associate Professor

• Combustion and Reacting flows
• Experimental Combustion and Fluid Dynamics
• Computational Fluid Dynamics
• +19 more

Dr. Ajay V. Singh is an Associate Professor in the Department of Aerospace Engineering at the Indian Institute of Technology Kanpur, India. He leads the Combustion and Propulsion Laboratory and has established himself as a leading researcher in combustion science and propulsion technology in India. His work on detonation physics has positioned IIT Kanpur at the forefront of this field with the unveiling of "India's First Detonation Tube Research Facility". Dr. Singh's educational background includes: PhD in Mechanical Engineering from University of Maryland, College Park (2015) M.Tech in Aerospace Engineering from Indian Institute of Technology Kanpur (2008) B.Tech in Mechanical Engineering from U.P. Technical University, Lucknow (2006) His research spans fundamental and applied aspects of combustion science with particular focus on high-speed propulsion systems, detonation cycle engines, gas turbine combustion, soot formation and oxidation, flame-synthesized functional nanoparticles, and fire dynamics. His innovative work bridges theoretical understanding with practical applications in aerospace propulsion, energy systems, and fire safety engineering. The media has widely covered his research, with features in India Today, Times of India, Hindustan Times, and Republic Bharat. Dr. Singh's publication record shows a clear trend toward increasingly sophisticated detonation research and fire dynamics studies, with recent work focusing on turbulent wind-driven flames, detonation inhibition mechanisms, and alternative fuel combustion. His articles consistently address challenges in high-speed propulsion and fire safety, demonstrating both theoretical depth and practical relevance. His scientific contributions have been recognized with numerous prestigious awards including the Distinguished Paper Award from the Combustion Institute (the only faculty member in India to receive this honor), a nomination for the Silver Combustion Medal, multiple Best Paper Awards, and the Exemplary Performance in Teaching Award. As an educator and mentor, Dr. Singh has guided numerous PhD and Master's students through their research. His Combustion and Propulsion Laboratory is supported by multiple research grants from agencies including ISRO, ARDB, SERB, and ANRF. He has developed specialized courses including "Explosion and Detonation Physics," which is the first of its kind at IIT Kanpur. Dr. Singh's laboratory serves as a hub for cutting-edge research in combustion science, featuring India's first Detonation Tube Research Facility and advanced experimental setups for studying flame dynamics, soot formation, and detonation physics. His international collaborations include institutions such as Stanford University, University of Maryland, Peking University, and Beijing Institute of Technology.

• Computational Mathematics
• Numerical Analysis
• Finite Element Methods
• +3 more

Prof. Joachim Schöberl is a faculty member at TU Wien's Faculty of Mathematics and Geoinformation, leading the Scientific Computing and Modelling research group. His academic career includes roles as a university professor (Univ.Prof.) with engineering and technical doctorates (Dipl.-Ing., Dr.techn.). Research focuses on advanced numerical methods, including finite element methods, computational fluid dynamics, and partial differential equations. He has pioneered high-order schemes for fluid-structure interaction, shell mechanics, and electromagnetic simulations. Notable contributions include the NGSolve finite element library and innovative approaches to curvature approximation in discrete geometry. Recent work emphasizes nonlinear elasticity modeling, fractional diffusion problems, and shape optimization for biomembranes. His team collaborates on projects like metascreen upscaling, micromorphic continuum models, and eddy current simulations in laminated materials. Prof. Schöberl advises PhD students researching mixed finite element methods, fractional operators, and computational mechanics. His lab develops open-source tools for high-performance scientific computing.

Marie FargeView profile

Professor

• Wavelets
• Turbulence
• Computational Fluid Dynamics
• +4 more

Marie Farge is a distinguished French mathematician and physicist currently serving as Directrice de Recherche 1ère classe at the French National Center for Scientific Research (CNRS) since 2008. She maintains strong affiliations with École Normale Supérieure in Paris where she has been based since 1981, and teaches at multiple institutions including Institut des Etudes Politiques (IEP) in Paris since 2011. Her extensive academic career includes visiting positions at prestigious institutions worldwide including Cambridge University, Harvard University, and the Max Planck Institute. Dr. Farge's research focuses on the intersection of mathematics and physics, with particular emphasis on wavelets , turbulence , and computational fluid dynamics . Her pioneering work has established wavelet analysis as a fundamental tool for studying turbulent flows and extracting coherent structures. She has developed the Coherent Vortex Simulation (CVS) method, which has become influential in turbulence modeling. Her research spans theoretical mathematics, numerical methods, and practical applications in fluid dynamics and plasma physics. Analysis of her publication record reveals a consistent focus on applying wavelet transforms to fluid dynamics problems, with increasing sophistication in handling three-dimensional turbulence and plasma phenomena. Her work demonstrates a progression from theoretical foundations of wavelet analysis to practical computational methods for complex fluid systems. The interdisciplinary nature of her research bridges mathematics, physics, and engineering applications. Prix Poncelet from the French Academy of Sciences (1993) American Physical Society Gallery of Fluid Motion award (1990) Seymour Cray Award for Scientific Computing (1988) Ministry of Foreign Affairs of Japan Award (1985) Fulbright Fellowship at Harvard University (1981) ESRO Award (1971) Elected member of Academia Europaea (2005) Grand Prix du CNRS 'La Recherche en Action' (1989) As an educator, Dr. Farge has taught extensively across France and internationally at institutions including Stanford University, Cambridge University, and numerous European and Asian universities. She has served on the editorial boards of major journals including the Journal of Applied and Computational Harmonic Analysis since 1993 and has been active in the Ethics Committee of CNRS since 2007. Her teaching spans wavelet theory, computational physics, turbulence, and signal processing, reflecting the breadth of her expertise. Dr. Farge maintains active research collaborations worldwide, evidenced by her numerous visiting positions at leading research centers including the Center for Turbulence Research at Stanford University, the Newton Institute in Cambridge, and the Institute for Advanced Study in Princeton. Her work continues to influence both theoretical developments in wavelet analysis and practical applications in fluid dynamics and related fields.

• Environmental Engineering
• Water Resource Management
• Urban Hydrology
• +3 more

Thomas Ertl is a Professor at the University of Natural Resources and Life Sciences, Vienna (BOKU), leading the Institute of Sanitary Engineering and Water Pollution Control. His research focuses on urban water systems, emphasizing sustainable drainage, climate change adaptation, and nature-based solutions. He has coordinated 55 projects, including international initiatives in Albania and Austria, addressing stormwater management, wastewater heat recovery, and sewer infrastructure resilience. Key Projects : Analysing re-activated watercourses for urban resilience (2024–2028) Resilient rainwater management in Austria (2024–2028) Assessing pollutant emissions in Albania (2024–2027) Research Themes : Building Information Modeling (BIM) in wastewater systems Uncertainty analysis under climate change Stormwater pollution and heat island mitigation Awards : 2018: Goldene Ehrennadel des ÖWAV 1993: Best student award at AGIT 93 His recent publications highlight multidisciplinary approaches to wastewater energy recovery, spatial compatibility of nature-based solutions, and prioritization of stormwater management sites. He has supervised numerous theses and contributed to media discussions on urban climate resilience, including articles in Austrian outlets like futurezone.at and Der Kurier.

• Nonlinear Partial Differential Equations
• Mathematical Physics
• Semiconductor Theory
• +7 more

Ansgar Jüngel is a Full Professor for Analysis of Nonlinear Partial Differential Equations (PDEs) at the Technische Universität Wien (TU Vienna), affiliated with the E101-Institute for Analysis and Scientific Computing. His academic journey includes roles at universities in Berlin, Konstanz, Mainz, and Vienna since 1991. He specializes in mathematical analysis of cross-diffusion systems, entropy methods, semiconductor models, and quantum fluid dynamics. Notable achievements include an ERC Advanced Grant (2021) and the Tsungming-Tu Award (2011). Research focuses on nonlinear PDEs with applications in physics, engineering, and biology, emphasizing rigorous existence theory, numerical methods, and entropy-based approaches. Recent projects include 'Emerging network structures and neuromorphic applications' and 'Taming complexity in partial differential systems.' His teaching includes courses on partial differential equations, calculus of variations, and computational finance. Publications span over 200 works, with key contributions on cross-diffusion models, quantum hydrodynamics, and energy-transport systems. He has supervised numerous PhD students and collaborates internationally on topics like semiconductor simulations and stochastic interacting particle systems. Grants include an FWF Special Research Programme and ERC funding.

Otto FelixView profile

Professor

• Micromagnetics
• Coarsening
• Stochastic Homogenization
• +3 more

Felix Otto is a Professor and Director at the Max Planck Institute for Mathematics in the Sciences (Leipzig, Germany) since 2010. Previously, he held Full Professorships at the University of Bonn (1999–2010) and the University of California, Santa Barbara (1998–1999). His research focuses on applied mathematics, including micromagnetics, coarsening dynamics, stochastic homogenization, and hydrodynamic limits. He has received prestigious awards such as the Gottfried Wilhelm Leibniz Prize (2006) and the Max Planck Research Prize (2001). Education: 1993 PhD in Mathematics (advisor S. Luckhaus), University of Bonn 1990 Diploma in Mathematics (advisor G. Dziuk), University of Bonn Research interests emphasize the interplay between analysis, probability, and physics, particularly in understanding complex systems through rigorous mathematical methods. His work on gradient flows and optimal transport has led to foundational contributions in applied mathematics. Awards: Collatz Prize (2007) Membership in Berlin-Brandenburg Academy (2014) Leopoldina Academy (2008) Professional activities include roles as Editor of Archive for Rational Mechanics and Analysis and advisory roles at institutions like the Weierstrass Institute and Fondation Mathématique Jacques Hadamard.

Christoph DellagoView profile

Professor

• Computational Physics
• Statistical Mechanics
• Molecular Dynamics Simulations
• +5 more

Christoph Dellago is a full Professor of Computational Physics at the Faculty of Physics of the University of Vienna, where he has been a faculty member since 2003. He currently serves as Director of the Erwin Schrödinger Institute for Mathematics and Physics, Head of the Computational and Soft Matter Physics Group, and Project lead of EuroCC Austria - National Competence Centre for Supercomputing. Previously, he served as Dean of the Faculty of Physics (2009-2012) and Coordinator of the Doctoral College Advanced Functional Materials (DCAFM). Full Professor, Faculty of Physics, University of Vienna (2003-present) Director, Erwin Schrödinger Institute for Mathematics and Physics (2017-present) Head, Computational Physics and Soft Matter Group (2024-present) Coordinator, Doctoral College Advanced Functional Materials (DCAFM) Austrian Representative, Council of CECAM Dellago received his PhD in Physics from the University of Vienna in 1996, followed by postdoctoral research at UC Berkeley as a Schrödinger Fellow of the Austrian Science Foundation. His research focuses on developing computational methods to study rare events in condensed matter systems, particularly transition path sampling methodology for simulating nucleation, chemical reactions, and biomolecular reorganizations. He has pioneered the application of machine learning to molecular structure recognition and potential energy surfaces. Recent work examines self-assembly of nanocrystals, biopolymer folding, aqueous interfaces, phase separation in alloys, thermo-polarization, cavitation, and freezing phenomena. Analysis of Dellago's recent publications (2023-2025) reveals a strong emphasis on machine learning applications in computational physics, particularly neural network potentials for simulating water interfaces, crystal defects, and phase transitions. His work bridges traditional statistical mechanics with modern computational techniques, creating powerful tools for studying complex dynamical processes that occur on timescales far beyond conventional molecular dynamics simulations. The publications demonstrate increasing integration of machine learning with rare event sampling methods, reflecting the cutting-edge direction of computational statistical mechanics. Förderpreis der Stiftung Futura zur Förderung junger Südtiroler im Ausland (1997) The Raymond and Beverly Sackler Prize in the Physical Sciences (2005) UNIVIE Teaching Award of the University of Vienna (2014) Dellago leads an active research group with multiple PhD students and postdocs, focusing on computational statistical mechanics. His group develops trajectory-based sampling methods and machine learning approaches for molecular simulation. He has secured significant funding through EuroCC Austria and various research platforms including the Research Platform Accelerating Photoreaction Discovery and the Research Platform Erwin Schrödinger International Institute for Mathematics and Physics. His research has been supported by numerous grants enabling advanced computational infrastructure for high-performance simulations. The Dellago Group operates within the Computational and Soft Matter Physics division at the University of Vienna, with strong connections to the Research Network Data Science. The group collaborates extensively with international research institutions and maintains close ties with the Erwin Schrödinger Institute, which Dellago directs. Their research environment combines theoretical physics, computational chemistry, and machine learning expertise to tackle fundamental questions in condensed matter physics and soft matter systems.