Rupert Klein is a Professor at Freie Universität Berlin in the Department of Mathematics and Computer Science , specializing in Geophysical Fluid Dynamics . His research spans atmospheric dynamics, numerical methods, and gas dynamics of combustion. Research Interests : Geophysical Fluid Dynamics and Atmospheric Modeling Multiscale Asymptotic Analysis Wave Propagation and Turbulence Combustion and Pressure Gain Combustion Climate Dynamics and Data Assimilation Scientific Awards : DRS Award for Excellent Supervision (2014) ECMWF Fellowship (renewed 2017) His recent work includes multiscale models for atmospheric flows, vortex dynamics, and combustion processes. Key collaborations involve DFG SPP 1276, CRC 1029 (TurbIn), and CRC 1114 (SCCS) projects. He contributes to numerical methods for low-Mach-number flows and geophysical simulations.
Thorsten Schmidt is Professor of Mathematical Stochastics at the University of Freiburg, succeeding Prof. Ernst Eberlein in the summer semester of 2015. He also serves as Senior Financial Engineer at MathFinance. Previously, he held professorships at Chemnitz University of Technology (2008-2015), Technical University Munich (2008), and University of Leipzig (2004 onwards). From 2017-2019, he was a Research Fellow at the Freiburg Institute for Advanced Studies (FRIAS) in a joint research group with the University of Strasbourg and USIAS on the topic of Linking Finance and Insurance. His research focuses primarily on financial and actuarial mathematics, stochastic processes, and statistics, with recent work on machine learning methods and their applications in financial mathematics and AI regulation. In Freiburg, his goal with his young team is to tackle complex challenges with improved mathematical models and apply these methodologies to various fields. Key Research Areas: Financial mathematics and credit risks Pricing and hedging of derivative financial products Statistics of stochastic processes Energy markets and nonlinear filter theory Machine learning applications in finance and insurance His recent publications show a strong trend toward integrating machine learning with traditional mathematical finance, particularly in risk management, insurance-finance arbitrage, and robust financial modeling. His work increasingly addresses ethical considerations in AI applications within finance, reflecting his broader interest in responsible AI development. Notable Awards: IDA Award Finance (2015) FRIAS-USIAS Research Fellow (2017/2018) IDA Award Machine Learning and AI (2020) MAPFRE Research Grant (2020) Luis Bachelier Fellow (2021) As Editor-in-Chief of Statistics and Risk Modeling and Associate Editor for Mathematical Finance and International Journal of Theoretical and Applied Finance, Schmidt plays a significant role in academic publishing. He leads the CRC 'Small Data' research center with Harald Binder, focusing on medical problems where disease progression must be estimated with few data points per patient. His LeanAI project, funded by the Vector Foundation, explores the connection between machine learning and theorem-proving software LEAN, aiming to develop AI that can translate between mathematics and formal proof systems. His laboratory work centers around the application of stochastic methods combined with machine learning to solve problems in finance and insurance where data is limited ('Small Data' initiative), with significant funding from DFG (€12 million for CRC Small Data) and the Carl Zeiss Foundation.
Fernando Corinto is a Research Fellow at the Department of Electronics and Telecommunications (DET) , Polytechnic University of Turin , and a member of the SmartData@PoliTO Big Data and Data Science Laboratory. He holds a European Doctorate in Electronics and Communications Engineering (2005) and was a Marie Curie Fellow (2004) at University College Dublin, focusing on cardiac fibrillation modeling and chaotic systems. Education : Laurea (2001) and Ph.D. (2005) in Electronics and Communications Engineering from Politecnico di Torino His research spans nonlinear dynamical systems , memristor devices , and complex network modeling , with over 50 publications. Key projects include RECOMMEND (2024–2027) and COSMO (2020–2024), where he served as Scientific Director . His recent work involves memristor-based neuromorphic systems and nonlinear circuit applications in biomedical and industrial contexts. He supervises PhD students Rosanna Cavazzana and Davide Rossetti and teaches Nonlinear Systems for Engineering (Mathematical Engineering) and Memristor-based Neuromorphic Systems (Electrical Engineering). His scientific contributions include the Flux-Charge Analysis Method and Bifurcations without Parameters in memristor circuits. He holds a national/international patent for skin ulcer classification algorithms and has led commercial research projects in biomedical and packaging systems.
Robin Neumayer is an Assistant Professor in the Department of Mathematical Sciences at Carnegie Mellon University. Her research focuses on the intersection of calculus of variations, partial differential equations (PDE), and geometric analysis, with a particular emphasis on stability and regularity in geometric inequalities. Education: Ph.D. in Mathematics, University of Texas at Austin, supervised by Alessio Figalli and Francesco Maggi. Her work explores problems related to Sobolev inequalities, isoperimetric problems, scalar curvature, and free boundary phenomena. Recent publications highlight collaborations with leading researchers and address topics such as quantitative stability, anisotropic geometries, and nonlinear PDE. Scientific Awards and Fellowships: NSF Grant DMS-2155054 (2022-2025) RTG Postdoctoral Fellow at Northwestern University (2017-18, 2019-21) Institute for Advanced Study member (2018-19) She teaches courses such as Introduction to Differential Equations and maintains active research collaborations with institutions like the Center for Nonlinear Analysis.
Elliot Hawkes is an Associate Professor in the Department of Mechanical Engineering at the University of California, Santa Barbara (UCSB). His research bridges design, mechanics, and non-traditional materials to develop robust, adaptable, human-safe robots for uncertain environments. He leads the Hawkes Lab, focusing on bio-inspired microstructured adhesives, nonlinear compliant mechanisms, soft actuators, exoskeletons, and growing robots. PhD from Stanford University, 2015 Postdoctoral Scholar at Stanford's CHARM Lab, 2015-2016 Assistant Professor at UCSB since 2016 Current projects include: Material-like robotic collectives with spatiotemporal control Variable friction shoe for locomotor therapy High-force soft actuators for industrial applications Vine-inspired robots for search and rescue Growing robots for biomedical and environmental use Recent publications in Science and Nature highlight breakthroughs in soft robotics and human-safe actuation. His team has received multiple NSF GRFP awards and a UCSB Regents Fellowship. The lab holds patents in adhesive gripping, soft actuation, and reconfigurable robotics.
Federico Bosia is Associate Professor at the Department of Applied Science and Technology (DISAT) of Politecnico di Torino, teaching Physics I in Aerospace Engineering. His research focuses on bioinspired materials, elastic wave control, fracture mechanics, and metamaterials, with applications in acoustic engineering and sustainable infrastructure. Current research projects include RAVEN (2024-2028) for atmospheric sensors and AMPHYBIA (2023-2025) on advanced metamaterials. He coordinates the COST Action European Network Bioadhesion (2016-2021) and participates in the Unite! University Alliance (2022-2028). His work spans mechanical and acoustical properties of condensed matter (ERC PE3_2), mechanical engineering (PE8_7), and metamaterials engineering (PE11_13). Recent publications highlight innovations in gradient-index phononic crystals, tunable waveguides, and vibration mitigation systems. Scientific awards include Open Badges Learning to Teach (L2T) and Mentoring Polito Project (M2P) , both issued by Politecnico di Torino in 2023. He supervises PhD students Eloi Perez Compte, Fabio Nistri, and Paolo Han Beoletto, and serves as Associate Editor for Frontiers in Materials since 2017. As Scientific Director , he leads projects like SILENCE (2021-2022) for MRI noise cancellation and BOHEME (2020-2023) under H2020. His lab, the Nonlinear Elasticity and Metamaterials Laboratory (DISAT) , explores nonlinear elasticity and soft matter applications.
Ismail Ben Ayed is an Associate Professor at École de technologie supérieure (ETS) in Montreal, Canada, holding the ETS Research Chair on Artificial Intelligence in Medical Imaging. His research bridges computer vision, optimization, and medical image analysis to develop advanced algorithms for clinical applications, with particular focus on cardiac and neurological imaging. His research program centers on medical image segmentation using novel optimization techniques, graph-based methods, and deep learning models. He pioneers approaches for handling volumetric bias, shape compactness, and distribution matching in MRI and cardiac imaging, directly addressing clinical challenges in spine labeling, ventricle segmentation, and tumor detection. His work emphasizes mathematical rigor combined with practical medical relevance. Analysis of his 15 most recent publications (2014-2017) reveals dominant themes in medical image segmentation (80% of works), particularly for cardiac MRI (35%) and neurological applications (25%). Key methodological contributions include distributed optimization frameworks (20%), advanced graph cut techniques (30%), and deep learning architectures (25%), published consistently in top-tier venues including CVPR, MICCAI, and TPAMI. His scientific recognition includes: MICCAI travel award (2017) Outstanding Reviewer Award at CVPR (2015) GE innovation award (2010) He actively mentors researchers as evidenced by his recruitment of PhD students and postdocs, with research supported by the ETS Research Chair and multiple patents. His service includes chairing MICCAI 2017/2015 and IPTA 2017, plus continuous program committee roles at CVPR, ICCV, and MICCAI since 2011. Leading the ETS Research Chair on AI in Medical Imaging, he directs a collaborative team working on clinical translation of computer vision techniques. Current projects focus on cardiac motion analysis, brain tumor segmentation, and spine labeling systems with direct applications in radiology workflows.
Prof. Dr. Michael Horn-von Hoegen is a full professor in the Faculty of Physics at the University of Duisburg-Essen , Germany. His research focuses on ultrafast structural dynamics , surface physics , and 2D materials , particularly using electron diffraction and plasmonic imaging techniques. He leads the Horn-von Hoegen Group , which plays a central role in the Collaborative Research Center CRC 1242 Non-Equilibrium Dynamics of Condensed Matter in the Time Domain , where his team investigates driven phase transitions and phonon systems with sub-femtosecond temporal resolution. Location: Office Window MF260, Faculty of Physics, Lotharstr. 1-21, 47057 Duisburg Contact: Tel. +49 (203) 379 1439 | Fax +49 (203) 379 1555 His research spans ultrafast electron diffraction of photo-induced phase transitions in atomic wires and topological materials , with recent breakthroughs on Kibble-Zurek dynamics in the Si(001) surface and chiral plasmon polaritons . The group’s 15 most recent publications (2025-2022) address phenomena such as negative thermal expansion in 2D materials , electron-phonon coupling in Pb/Si heterostructures , and quantum pathway analysis in Bismuth films . These works are categorized under disciplines like Condensed Matter Physics , Nanooptics , and Ultrafast Dynamics , with subfields including Ising Model Transitions , Plasmon Focusing , and Time-Resolved Diffraction . Prof. Horn-von Hoegen serves as DFG Liaison Officer for the University of Duisburg-Essen, providing guidance on Deutsche Forschungsgemeinschaft (DFG) proposals . His group has mentored notable researchers including Dr. Simon Sindermann (postdoc at IBM), Dr. Anja Hanisch-Blicharski (Leopoldina Fellow), Dr. Hichem Hattab (Leopoldina Fellowship), and Dr. Marin Petrovic (Humboldt Fellow). The group’s laboratory facilities include advanced ultrafast electron diffraction and photoemission microscopy systems, enabling studies of atomic-scale processes such as molecular dynamics simulations of laser-excited surfaces and domain wall motion in Si(553)-Au systems .
Sanjeev Kulkarni is the William R. Kenan, Jr. Professor of Electrical and Computer Engineering and Operations Research & Financial Engineering at Princeton University. He is associated with the Department of Philosophy and has held significant administrative roles including Dean of the Graduate School (2014-2017), Director of the Keller Center (2011-2014), and Master of Butler College (2004-2012). His research spans Statistics , Machine Learning , Applied Probability , Information Theory , and Signal Processing , with applications to Wireless Networks , Econometrics , and Control Systems . He has co-authored over 100 publications and supervised numerous PhD and Master’s students.
Mikael Gidlund is a Full Professor of Computer Engineering at Mid Sweden University in Sundsvall and holds an adjunct professorship at Beijing Jiaotong University, China. He serves as head of the Computer Engineering subject and program manager for the international MSc program in Computer Engineering. His academic journey includes a Ph.D. in Electrical Engineering from Mid Sweden University (2005), followed by roles at ABB Corporate Research (2008-2014) where he led wireless technologies research. Dr. Gidlund's research spans Wireless Communication, Industrial IoT, 5G/6G Networks, and Network Security . His group focuses on AI/ML for beyond-5G wireless communication, time-critical industrial applications, and IoT security. Current research themes include Future Wireless Networks (5G/6G) using AI/ML, Time-and mission-critical wireless communication, Industrial IoT, and IoT Security. His work demonstrates strong interdisciplinary connections between wireless systems, industrial automation, and security. His publication portfolio includes over 200 scientific articles and 20+ patents. Recent publications show a clear trend toward AI/ML integration in wireless systems, NOMA techniques, RIS technologies, and security solutions for industrial applications. The research output demonstrates strong international collaboration across six continents. Best Paper Award at IEEE International Conference on Industrial IT (2014) Co-author of IEEE Sweden VT-COM-IT Joint Chapter Best Student Journal Paper Award (2022) Dr. Gidlund actively mentors 6 current PhD students and has supervised 16 former PhD students who now hold positions at institutions including Ericsson, Lund University, Aalborg University, and Mid Sweden University. His research is supported by multiple active projects including IRS TransTech, NIIT, ENSURE 6G, and TRUST. He collaborates with institutions worldwide including City University of Hong Kong, Iowa State University, Kyung Hee University, and KTH Royal Institute of Technology. His research group maintains strong industry connections through projects with ABB, Ericsson, and other industrial partners, focusing on practical implementations of wireless technologies for industrial automation and critical infrastructure.
Marco Pirola is a Full Professor at the Department of Electronics and Telecommunications (DET) of the Polytechnic University of Turin, Italy. He is a member of the Interdepartmental Center 'CleanWaterCenter@PoliTo' and actively contributes to research in high-frequency electronics and microwave engineering. His work focuses on power amplifiers, device characterization, and advanced microwave circuit design. Research Interests: Microwave power devices, GaN technology, 5G/mm-Wave applications, space communications, and smart pipeline monitoring systems. Awards: IEEE Fellow (since 2019), IEEE Senior Member. Recent Publications address topics like Ka-band MMIC amplifiers for SAR systems, broadband Doherty amplifiers using GaN, and harmonic analysis of current-mode power stages. His projects include STARGATE (European GaAs power architectures) and Millimetre-Wave GaN Radar for UAV detection. Teaching: He leads courses on 'Radio Frequency Integrated Circuits' and 'Advanced Devices for High Frequency Applications' at the Polytechnic University of Turin. Supervised PhD students include Wenjun Zhang and Abbas Nasri, who worked on III-V HEMT circuits and GaN power amplifiers.
Christopher Rycroft is a Professor and Associate Chair in the Department of Mathematics at the University of Wisconsin–Madison. He leads the Rycroft Group, which focuses on mathematical modeling and scientific computation for interdisciplinary applications in science and engineering. Prior to joining UW-Madison in summer 2022, he was a professor at Harvard University's School of Engineering and Applied Sciences from 2014-2022, and before that a Morrey Assistant Professor at UC Berkeley from 2010-2013. Professor Rycroft's research spans three main areas: numerical methods for material mechanics, data-driven discovery, and computational geometry. His group develops new computational methods while working directly with domain scientists. Key achievements include the development of the reference map technique for fluid-structure interaction, Voro++ software library for Voronoi tessellation, and novel approaches to understanding crumpling physics. His work combines traditional analysis and modeling with machine learning methods to extract scientific insights from complex data. The Rycroft Group's publication record demonstrates a strong trajectory of interdisciplinary research bridging mathematics, physics, materials science, and biology. Recent work has focused on fluid-structure interaction, computational geometry applications, mechanical metamaterials, and biological fluid dynamics. The group develops both theoretical frameworks and practical software tools that have found applications across diverse scientific domains from materials science to virology. Everett Mendelsohn Award for Excellence in Mentorship (2021) Professor Rycroft has advised numerous PhD and master's students who have gone on to postdoctoral positions at institutions including MIT, EPFL, and Cornell. His teaching includes advanced scientific computing courses that have quadrupled in enrollment during his tenure. He has secured research funding supporting his group's work on computational methods and interdisciplinary applications. The Rycroft Group consists of graduate students, postdocs, and collaborators with diverse backgrounds in applied mathematics, physics, engineering, and computer science. The group maintains active collaborations with researchers across multiple institutions and participates in centers such as the Harvard Quantitative Biology Initiative.
Boris Buffoni is a Senior Lecturer at École Polytechnique Fédérale de Lausanne (EPFL) in the School of Basic Sciences, Institute of Mathematics, specifically within the Chair of Partial Differential Equations. He maintains his office at MA C2 605 (MA Building), Station 8, 1015 Lausanne, Switzerland, and can be contacted at boris.buffoni@epfl.ch or +41 21 693 49 87. His academic role spans both teaching responsibilities across multiple mathematics programs and active research in theoretical and applied mathematics. Dr. Buffoni's research program centers on the calculus of variations applied to Lagrangian and Hamiltonian systems, with significant contributions to optimal transportation in Lagrangian dynamics and hydrodynamics. His work explores semi-global minimization methods for quasi-linear elliptic variational problems and the variational approach to capillary-gravity water waves and their energetic stability. Additional research foci include local bifurcation and center-manifold theory for elliptic PDEs, the configurations of infinite elastic cylinders under compression or traction, and the analytic theory of global bifurcation with applications to gravity waves and their secondary bifurcations. The trajectory of his recent publications reveals a deepening focus on three-dimensional water wave phenomena, particularly steady rotational flows, gravity-capillary solitary waves, and advanced mathematical techniques for analyzing these complex systems. His 2025 publications demonstrate continued innovation in applying Kato's approach to locally coercive problems and developing the theoretical foundations of global bifurcation. The consistent application of variational methods and bifurcation theory across his work represents a unifying theme in addressing challenging problems in fluid dynamics and nonlinear partial differential equations. Dr. Buffoni has received research support including an EPSRC grant (GR/L41059) for work on 'Multibump localised solutions for spatially homogeneous partial differential equations,' reflecting the significance of his contributions to the field. His teaching portfolio at EPFL includes foundational courses such as Analysis II, Functional Analysis I, and Partial Differential Equations of Evolution, where he imparts knowledge of differential and integral calculus of real functions of several variables, linear functional analysis, and fundamental techniques for solving evolution equations.
Dr. Andrea K. Rorrer is a full-time Professor at the University of Utah's College of Education, Department of Educational Leadership and Policy, and serves as Director of the Utah Education Policy Center (UEPC). With 35 years of education experience, she has held roles as a teacher, principal, policy analyst, and researcher. Her academic career at the University of Utah includes promotions from Assistant Professor (2002-2009) to Associate Professor (2009-2014) and Professor since 2014, alongside serving as Associate Dean for Research from 2014-2023. PhD in Educational Leadership & Policy, University of Texas at Austin (2001) MS in Educational Leadership & Policy, University of Virginia (1995) Dr. Rorrer's research focuses on the intersection of educational leadership, policy implementation, and systemic change with equity as a central theme across early childhood, K-12, and higher education. Her work examines leadership preparation programs, charter school effectiveness, policy mediation, and institutional factors affecting educational outcomes. Recent publications highlight: Leadership preparation program features influencing career intentions (2025) Personalized learning software's impact on teacher-student dynamics (2024) Turnaround reform frameworks (2018) Charter school mobility patterns (2019) Homeschool policy analysis (2012) Scientific recognition includes: UCEA Master Professor Award (2020) College of Education Research Award AERA Dissertation Award (2001) Culbertson Award for early-career contributions Mentorship has been central to her career, with 35 doctoral chairs and 44 committee memberships since 2002. Current teaching activities include Thesis Research and Ed.D. Capstone Project courses.
Pouya Bashivan is an Assistant Professor in the Department of Physiology at McGill University's Faculty of Medicine. His research focuses on developing computational models to explain and regulate neural responses during visual tasks requiring memory, combining machine learning, neuroscience, and cognitive science. Education : Ph.D. in Computer Engineering (2016), Postdocs in Machine Learning (2020) and Computational Neuroscience (2016-2020) His lab investigates: Topographical neural networks for visual cortex simulation Massively-multitask models for prefrontal cortex Saccade-driven visual exploration models Predictive hippocampus models for episodic memory Recent publications explore adversarial robustness, memory-augmented networks, and brain-state decoding. Current projects emphasize causal models, brain-AI alignment, and translating computational neuroscience into therapeutic applications. The lab is located in the McIntyre Medical Sciences Building, Room 1117, Montreal, Quebec.
