Victor Becerra is a Professor of Power Systems Engineering at the University of Portsmouth, affiliated with the School of Electrical and Mechanical Engineering within the Faculty of Technology. He is also associated with the Centre for Environmental and Renewable Energy Solutions and the Agile Centre For Equitable Sustainability. His research focuses on advanced control systems, renewable energy integration, smart grids, battery management, and nuclear power plant control. He actively supervises PhD students in topics like optimal control of battery systems and microgrid optimization. His academic work spans over 193 publications, with recent contributions emphasizing techno-economic analysis of green hydrogen, modular energy storage solutions, and optimal control strategies for batteries and nuclear reactors. His research often addresses real-world applications such as grid flexibility at ports, peer-to-peer energy trading platforms, and drone-based inspection of offshore wind turbines. Becerra's expertise includes developing control algorithms for marine structures, sodium-cooled reactors, and unmanned aerial vehicles. He has contributed to books on solar energy engineering and applications, highlighting interdisciplinary approaches to sustainability challenges. His work integrates theoretical models with practical implementations, such as energy management systems for compressed air and advanced BMS for drones. Key themes in his research include renewable energy systems optimization, fault-tolerant control mechanisms, and adaptive control strategies for dynamic environments. He collaborates internationally, addressing global energy challenges through innovative control methodologies and sustainable technologies.
Celia Reina is an Associate Professor in the Department of Mechanical Engineering and Applied Mechanics at the University of Pennsylvania’s School of Engineering and Applied Science (SEAS). Her research focuses on multiscale modeling of materials, bridging statistical mechanics, thermodynamics, and machine learning. She develops novel frameworks for predicting non-equilibrium material behavior using data-driven methods and uncertainty quantification. Her work emphasizes integrating computational tools like neural networks (Stat-PINNs, VONNs) with physical principles to model dissipative systems, phase transitions, and mesoscale dynamics. Key areas include coarse-graining techniques, epistemic uncertainty analysis, and predictive modeling of complex materials under dynamic loading. Recent publications highlight advancements in stochastic systems, resonant metamaterials, and the derivation of thermodynamic models from particle-level fluctuations. She leads efforts in experimental-simulation co-design to enhance predictive capabilities in materials science.
Professor Vakur B. Erturk is a distinguished faculty member in the Department of Electrical and Electronics Engineering at Bilkent University's Faculty of Engineering. With a PhD from The Ohio-State University (2000), his academic journey spans over two decades of impactful research and teaching. His research focuses on advanced computational electromagnetics, specializing in closed-form Green's function representations, conformal antenna design, structural health monitoring systems, and metamaterial applications. His work bridges theoretical electromagnetics with practical engineering solutions, particularly in wireless sensing and high-frequency electromagnetic analysis. Professor Erturk's publication record demonstrates consistent innovation, with recent work emphasizing efficient computational methods like the multilevel fast multipole algorithm (MLFMA) for multiscale electromagnetic problems. His research shows strong continuity in antenna theory while expanding into metamaterial-inspired sensors and structural monitoring systems. Best master thesis award (1996) He actively mentors graduate students, with over 30 PhD and MSc graduates who have contributed significantly to fields including computational electromagnetics, antenna design, and wireless sensor development. His research group maintains strong collaborations with institutions like Middle East Technical University and researchers in metamaterials and structural health monitoring. Professor Erturk teaches core courses including Microwave Engineering, Antenna Engineering, and Computational Methods in Electromagnetics, shaping the next generation of electrical engineers through rigorous theoretical and practical instruction.
Julia Chuzhoy is the Manuel Blum Professor at the Toyota Technological Institute at Chicago (TTIC) and holds a part-time Professor appointment in the Department of Computer Science at the University of Chicago . She completed her Ph.D. at the Technion under the supervision of Seffi Naor , followed by postdoctoral positions at MIT , University of Pennsylvania , and the Institute for Advanced Study . She also served as a Weizmann Institute Weston Visiting Professor in 2018-2019. Her research in theoretical computer science focuses on graph-related optimization problems , including approximation algorithms, dynamic algorithms, fast graph algorithms, and hardness of approximation. She has received major funding through NSF grants (CCF-1318242, CCF-1616584, CCF-2006464, CCF-2402283) and the NSF HDR TRIPODS award (2216899). Her recent publications highlight advancements in approximation algorithms (e.g., maximum bipartite matching), dynamic graph algorithms (e.g., decremental shortest paths), and structural graph theory (e.g., excluded grid theorem). These works span both algorithmic improvements and theoretical lower bounds. Scientific recognition includes NSF Career Award (2013) Alfred P. Sloan Research Fellowship (2011) She has advised numerous TTIC and University of Chicago Ph.D. students, including Rachit Nimavat , Zihan Tan , and Parinya Chalermsook (now faculty at Aalto University ).
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.
Jacopo De Simoi is a Professor in the Department of Mathematics at the University of Toronto, holding appointments at both the St. George and Mississauga campuses. His research focuses on dynamical systems, particularly hyperbolic dynamics, billiards, and rigidity phenomena. He has held roles at institutions like Université Paris Diderot and the University of Maryland, College Park, and currently teaches courses such as Game Theory and Real Analysis. His work explores the interplay between deterministic systems and stochastic processes, with contributions to topics like Fermi acceleration and KAM theory. Education: Ph.D. in Mathematics from the University of Maryland (2009), Diploma di Licenza in Physics from Scuola Normale Superiore (2005), and M.Sc./B.Sc. in Physics from Università di Pisa. Research interests include stochastic properties of dynamical systems, conservative dynamics, and the ergodic theory of billiards. He has published extensively on spectral rigidity, entropy rigidity, and applications of renormalization group techniques. His recent work addresses inverse problems in billiard geometry and the statistical behavior of fast-slow systems. Teaching includes undergraduate and graduate courses in analysis, calculus, and dynamical systems. Collaborations span institutions globally, and he serves on editorial boards for journals like Communications in Mathematical Physics.
Christian A Parkinson is an Assistant Professor at Michigan State University , affiliated with the Departments of Mathematics and Computational Mathematics, Science and Engineering. His research spans mathematical modeling, computational methods, and interdisciplinary applications in epidemiology, control theory, and differential geometry. Research Interests : Mathematical epidemiology, path planning algorithms, reaction-diffusion systems, stochastic modeling, differential geometry, and network science. Email : chparkin@msu.edu His recent publications focus on: Hamilton-Jacobi equations for optimal path planning in multi-agent systems Reaction-diffusion models for epidemics with human behavior Differential geometry approaches to hyperbolic surfaces Network models for disease-opinion coevolution Environmental crime modeling using level sets He teaches MTH 890: Readings in Mathematics , emphasizing advanced computational and theoretical frameworks.
Susan T. Lepri is a Professor in the Department of Climate and Space Sciences and Engineering at the University of Michigan's College of Engineering, where she serves as Director of the Space Physics Research Laboratory. Her work focuses on heliospheric physics, utilizing spacecraft data from missions like ACE, WIND, and Solar Orbiter to investigate solar wind origins and coronal mass ejections. Her educational background includes: Ph.D. in Atmospheric and Space Sciences, University of Michigan M.S. in Atmospheric and Space Sciences, University of Michigan B.S. in Physics, Astronomy and Astrophysics, University of Michigan Lepri's research centers on tracing charged particles in the heliosphere using heavy ion measurements to study solar wind sources, coronal mass ejection physics, and particle acceleration mechanisms. She develops space-based ion mass spectrometers for missions including the European Space Agency's Solar Orbiter (Heavy Ion Sensor) and the Interstellar Mapping and Acceleration Probe. Her work integrates statistical analysis of solar wind composition with magnetohydrodynamic model validation to unravel plasma behavior in space environments. Analysis of her 15 most recent publications (2015-2017) reveals consistent focus on solar wind composition dynamics, particularly charge state evolution and elemental fractionation. Key themes include magnetic reconnection signatures in slow solar wind formation, anomalous composition in depleted interplanetary coronal mass ejections, and solar wind charge exchange contributions to X-ray backgrounds. Her instrumentation work bridges observational gaps in inner heliospheric measurements. Major recognitions include: 2018 Claudia Joan Alexander Trailblazer Award (University of Michigan) 2012-2013 Kenneth M. Reese Outstanding Research Scientist Award 2008 JGR-Space Physics Excellence in Refereeing Citation NASA Graduate Fellowship (2001-2003) Lepri actively mentors through outreach programs including K-12 initiatives with the Michigan Space Grant Consortium and Detroit Area Pre-College Engineering Program. She has coordinated Rochester Adams High School STEAM fairs and elementary science outreach while developing educational content like MConnex videos. Her research is supported by NASA grants enabling instrument development for Solar Orbiter and IMAP missions, with collaborations spanning international space agencies and academic institutions. As Director of the Space Physics Research Laboratory, she leads teams developing next-generation space instrumentation, particularly ion mass spectrometers for heliospheric exploration. Current projects include the Heavy Ion Sensor for Solar Orbiter (measuring inner heliospheric composition) and innovative sensors for IMAP, advancing capabilities to trace solar wind sources and particle acceleration mechanisms.
Dr. Ian Abel is an Associate Research Scientist at the Institute for Research in Electronics & Applied Physics (IREAP) at the University of Maryland, where he has been since 2018. His expertise spans fusion energy, plasma physics, and computational modeling. Abel holds a B.A. in Mathematics (2006) and M.S. in Applied Mathematics (2007) from the University of Cambridge, followed by a Ph.D. in Theoretical Physics from the University of Oxford (2012). His research focuses on magnetically confined fusion systems, particularly edge dynamics in tokamaks and innovative centrifugal mirror concepts. He has contributed to the development of gyrokinetic simulation tools like the GX code and the MaNTA transport model. Abel’s work also explores machine learning applications in plasma turbulence analysis and centrifugal mirror fusion reactor design for space propulsion. His research leverages advanced numerical methods, including GPU-native algorithms and adjoint-based optimization techniques for plasma equilibria. Key projects include the Centrifugal Mirror Fusion Experiment (CMFX), where he investigates plasma confinement and transport phenomena. His publications emphasize interdisciplinary approaches, integrating computational fluid dynamics, statistical physics, and high-performance computing to address challenges in fusion energy and plasma dynamics. While no specific awards are listed, his contributions to gyrokinetic turbulence modeling and centrifugal confinement systems are central to current fusion research.
Zachary Tatlock is an Associate Professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington, where he leads the Programming Languages & Software Engineering Group (PLSE) and the SAMPL Group. His research spans programming languages, formal verification, compilers, and computational fabrication. He is also an Amazon Scholar with AWS's Automated Reasoning Group and previously advised OctoML. Tatlock's work bridges theoretical foundations with practical systems, focusing on making it easier to write tricky code while ensuring correctness through rigorous proofs and measurements. PhD in Computer Science & Engineering, University of California, San Diego (2014) Thesis: Reducing the Costs of Proof Assistant Based Formal Verification Advisor: Sorin Lerner BS in Computer Science (Honors) and Mathematics, Purdue University (2007) Professor Tatlock's research focuses on the intersection of programming languages, formal methods, and systems. His work in compilers and formal verification aims to make it easier to write tricky code while ensuring correctness through rigorous proofs. He explores computational fabrication techniques that bridge digital design with physical manufacturing. His recent work on equality saturation (via the egg framework) has transformed program optimization and synthesis. Tatlock also investigates floating-point numerics, distributed systems verification, and hardware/software co-design, always seeking to balance theoretical rigor with practical implementation. Tatlock's recent publications demonstrate a strong focus on equality saturation techniques (egg framework), computational fabrication, and verified systems. His work increasingly integrates machine learning with program analysis and synthesis. There's a clear trajectory toward more practical applications of formal methods in real-world systems, particularly in numerical computing and fabrication. His research group has made significant contributions to e-graph technology, floating-point accuracy, and the verification of distributed systems. Distinguished Paper Award for Rewrite Rule Inference Using Equality Saturation (OOPSLA 2021) Spotlight Paper Award for Dynamic Tensor Rematerialization (ICLR 2021) Distinguished Paper Award for egg: Fast and Extensible Equality Saturation (POPL 2021) Faculty Appreciation for Career Education & Training (FACET) Award (2020) NSF CAREER Award: Verifying Distributed System Implementations (2017) Distinguished Paper Award for Automatically Improving Accuracy for Floating Point Expressions (PLDI 2015) Distinguished Teaching Award Nomination (2015) Professor Tatlock has advised numerous doctoral, master's, and undergraduate students who have gone on to prominent positions in academia and industry, including faculty positions at the University of Utah and Brown University, and leadership roles at companies like OctoML and Certora. His research is supported by significant funding from NSF, DARPA, DOE, and industry partners, totaling millions of dollars. Current grants include projects on computer-aided reasoning, formal verification, computational fabrication, and machine learning systems. He has served on numerous program committees and organized workshops including FPTalks, EGRAPHS, and PNW PLSE. As co-leader of the Programming Languages & Software Engineering (PLSE) research group and affiliate of the SAMPL Group at the University of Washington, Tatlock has developed influential tools including egg (an equality saturation toolkit), Carpentry Compiler, and Odyssey. His group actively collaborates with industry partners including Amazon Web Services, where he serves as an Amazon Scholar. The group has made significant contributions to equality saturation, floating-point accuracy, program synthesis, and computational fabrication, with applications ranging from compiler optimization to 3D printing.
Bhuvana Srinivasan is a Professor in the Department of Aeronautics and Astronautics at the University of Washington, directing the PLASMAWISE Laboratory. Previously, she held the rank of Associate Professor and served as Director of the Plasma Dynamics Computational Laboratory at Virginia Tech, supported by the Crofton Faculty Fellowship. Her research focuses on fusion energy, plasma-based propulsion, and computational plasma physics, with an emphasis on plasma-material interactions and instabilities across diverse plasma regimes. She has authored over 30 peer-reviewed publications and secured grants from the NSF, DOE, and AFOSR. Education: Ph.D. in Aeronautics and Astronautics, University of Washington (specializing in computational plasma physics) M.S. in Aeronautics and Astronautics, University of Washington B.S. in Aerospace Engineering and Mechanical Engineering, Illinois Institute of Technology Research Interests: Her work spans fusion energy concepts, plasma propulsion systems, high-energy-density plasma instabilities, and ionospheric dynamics. Key areas include plasma-surface interactions in fusion devices, magnetic field effects on plasma mixing, and algorithm development for fluid-kinetic models. She emphasizes high-fidelity multi-fluid simulations using discontinuous Galerkin methods. Awards & Recognition: NSF CAREER Award (2019-2024) Crofton Faculty Fellow (Virginia Tech, 2021-2023) Dean’s Outstanding Assistant Professor (Virginia Tech, 2017) Amelia Earhart Fellowship (Zonta International, 2007-2009) Advocacy & Leadership: She chairs DEI initiatives in academic departments and serves on national committees including the DOE Fusion Energy Sciences Advisory Committee and the APS Division of Plasma Physics Executive Board. Her work bridges computational plasma physics with societal impact, including fusion energy democratization and space exploration propulsion systems.
Michael Carley is a Senior Lecturer in the Department of Mechanical Engineering at the University of Bath. His research focuses on acoustics, aeroacoustics, boundary element methods (BEM), and numerical methods. He actively contributes to teaching aircraft stability and control, acoustics, and fluid dynamics. He is willing to supervise doctoral students in acoustics, vortex methods, and BEM applications. Dr. Carley has secured significant research funding, including EU Horizon 2020 grants for noise reduction in aviation and a Leverhulme Trust project on motorcycle helmet noise. His work spans collaborations in civil aviation, computational acoustics, and fluid dynamics modeling. Key research areas include rotor noise suppression, numerical methods for acoustic simulations, and metamaterial applications. He has published extensively on BEM advancements and noise shielding techniques. His projects emphasize practical engineering solutions, such as developing noise reduction technologies for eVTOL aircraft and optimizing acoustic metasurface designs. Grants: AERIALIST (EU Horizon 2020, 2017–2020): Focused on aircraft noise alleviation using metamaterials. Motorcycle Helmet Noise (Leverhulme Trust, 2010–2011): Investigated noise reduction strategies. Peer Review: Active reviewer for the Journal of the Acoustical Society of America (JASA Express Letters) and UK Research and Innovation (UKRI EPSRC).
Anna-Karin Tornberg is a Professor in Numerical Analysis at the Department of Mathematics, KTH Royal Institute of Technology. She holds positions as Vice Chair of the Department of Mathematics and previously served as Head of the Numerical Analysis division (2011–2023). Her research focuses on numerical methods for PDEs, particularly boundary integral methods for fluid flows involving particles and drops. She is active in the Linne FLOW Centre and Swedish e-Science Research Center (SeRC). Key roles include membership in the Royal Swedish Academy of Engineering Sciences (IVA), Royal Academy of Sciences, and receipt of awards like the Göran Gustafsson Prize (Mathematics, 2014). She has advised numerous PhD students and postdocs, including current supervisees Anna Broms, David Krantz, and Emanuel Ström. Her work spans theoretical, computational, and applied fluid dynamics with emphasis on microfluidics and high-accuracy numerical techniques. Education includes a PhD in Numerical Analysis from KTH (2000) followed by postdoctoral positions at NYU’s Courant Institute. Promoted to Full Professor at KTH in 2012. Service roles include membership in KTH’s University Board, Faculty Council, and editorial roles at Advances in Computational Mathematics and BIT Numerical Mathematics . Active in international conferences, delivering plenary/invited lectures at ICIAM, ECM, and ICM. Research group projects include development of fast numerical methods for microfluidics and molecular dynamics simulations. Current openings for PhD candidates in numerical methods for non-elliptic PDEs in time-dependent domains. Her lab collaborates on high-performance computing and fluid-structure interaction problems.
Tobias Neckel is an Associate Professor at the Institute for Informatics at the Technical University of Munich (TUM), where he leads research projects and coordinates academic programs. He has been the project team leader of the IGGSE Project ExaNIML since 2018, main coordinator of the Ferienakademie since 2014, and Program Coordinator of the Bavarian Graduate School of Computational Engineering (BGCE) since 2009. Diploma in Technomathematik from TU München (2005) Dr. rer. nat. in Informatics from TU München (2009) Neckel's research focuses on Uncertainty Quantification, Random Differential Equations, and High Performance Computing. His work develops efficient numerical algorithms using hierarchic and adaptive methods such as octrees/spacetrees and sparse grids, with applications in fluid-structure interactions and incompressible fluid flow simulation. His research bridges theoretical mathematics with practical computational science, emphasizing robust and efficient implementations. His recent publications demonstrate a strong trajectory in multi-fidelity modeling, uncertainty quantification, and high-performance computing. Neckel has made significant contributions to scalable hierarchical approximation methods, dynamic resource management in HPC, and the application of machine learning techniques to computational science problems. His work spans diverse application domains including plasma physics, hydrology, and computational engineering. Lehrfonds prize of the TUM (2014) Ernst Otto Fischer prize of the TUM (2011) Promotionspreis des Bunds der Freunde der TU München (2009) Neckel has supervised numerous graduate students and has been actively involved in curriculum development and teaching innovation. His book "Bits and Bugs: A Scientific and Historical Review of Software Failures in Computational Science" (2019) represents a significant contribution to understanding software reliability in scientific computing. He has organized minisymposia at major conferences including SIAM CSE and SIAM UQ, and serves on program committees for various computational science conferences. As coordinator of the Ferienakademie and the BGCE, Neckel plays a central role in advanced computational engineering education in Bavaria. His research group develops software for exascale computing and contributes to the Transregional Collaborative Research Centre 89 on Invasive Computing. Neckel also maintains international collaborations, with research stays at institutions including the Australian National University and Tokyo Institute of Technology.
Prof. Wim Desmet is a full professor at the Faculty of Engineering Science and head of the Department of Mechanical Engineering at KU Leuven . His research focuses on advanced modeling techniques for mechanical systems, including: noise and vibration control in automotive and industrial systems computational acoustics and interval field uncertainty modeling metamaterials for broadband vibroacoustic performance AI-driven diagnostic systems in renewable energy and manufacturing Current research projects address challenges in electric vehicle drivetrains, wind turbine monitoring, and multi-physical digital twin development. He actively contributes to academic governance as: Managing Director of KU Leuven Head of Subdivision HIST Chair of multiple executive committees Member of 15+ academic and administrative councils
