Navid Bayati is an Associate Professor at the University of Southern Denmark, affiliated with the Institute of Mechanical and Electrical Engineering and the Centre for Industrial Electronics. He leads the Control and Protection of Smart Grids (CAP-SG) group and focuses on renewable/hybrid power systems, microgrid protection, and grid code compliance. Education: Ph.D. in Power Systems & Microgrid Protection (2020, Aalborg University); M.Sc. in Power Systems (2017, Amirkabir University of Technology) His research spans renewable energy integration , transient analysis , grid interconnection , and digital twin applications . Recent work includes machine learning for carbon emission prediction, fault localization in DC microgrids, and supercapacitor resilience in hybrid systems. Collaborations include projects like IEA Wind Task 50 and RePoSys , addressing grid renovation, life cycle assessment, and digital twin resilience. His teaching portfolio covers power electronics , energy management , and microgrid control .
Katya Krupchyk is a Professor in the Department of Mathematics at the University of California, Irvine (UCI). Her research focuses on inverse problems, partial differential equations (PDEs), microlocal analysis, and spectral theory. She holds a position in the Analysis and Partial Differential Equations group at UCI. Her work often involves collaborations with leading institutions and researchers globally, addressing challenges in mathematical physics, geometric inverse problems, and nonlinear analysis. Dr. Krupchyk teaches advanced courses in real analysis, functional analysis, and partial differential equations. She has contributed to editorial boards for journals such as Journal of Spectral Theory , SIAM Journal on Mathematical Analysis , and Inverse Problems and Imaging . Her research spans theoretical and applied aspects of inverse problems, including studies on fractional operators, magnetic Schrödinger equations, and anisotropic media. Recent work emphasizes high-frequency analysis, nonlinear perturbations, and reconstruction algorithms for geometric inverse problems.
Giulia Semeghini is an Assistant Professor of Applied Physics at Harvard University's School of Engineering and Applied Sciences (SEAS) . Her research focuses on experimental investigations of highly-entangled phases of matter and quantum information processing using programmable atom arrays. The Semeghini Lab, part of the Harvard Quantum Initiative (HQI) and the Center for Ultracold Atoms (CUA), explores intersections between condensed matter physics, high-energy physics, and quantum chemistry. Key achievements include assembling an ultra-high vacuum chamber for atom arrays in 2024 and relocating to the Goel building (HQI's new home) in April 2024. The lab actively recruits students and researchers for open positions at all levels. Research themes span quantum simulation, topological qubits, entanglement engineering, and scalable quantum architectures. Publications emphasize quantum gate implementations, hybrid atom systems, and variational Monte Carlo enhancements. No scientific awards are explicitly listed, but contributions to quantum hardware and algorithms are notable. The lab collaborates widely, aiming to bridge theory and experiment in quantum technologies.
Indranil Chowdhury is an Assistant Professor in the Department of Mathematics and Statistics at the Indian Institute of Technology Kanpur. He holds a Ph.D. from Tata Institute of Fundamental Research, Centre for Applicable Mathematics in Bengaluru (2017) and has previously served as a Postdoctoral Researcher at University of Zagreb, Croatia (2020-2022) and Norwegian University of Science and Technology, Trondheim, Norway (2018-2020). Ph.D: Tata Institute of Fundamental Research, Centre for Applicable Mathematics, Bengaluru, India (2017) PG: Tata Institute of Fundamental Research, Centre for Applicable Mathematics, Bengaluru, India (2012) UG: St. Xavier's College, Kolkata, India (2010) Dr. Chowdhury's research focuses on the theory and numerical analysis of partial differential equations, with particular expertise in nonlocal and fractional order problems and fully nonlinear equations. His work bridges theoretical mathematics with practical applications in areas such as mean field games, optimal control, and mathematical modeling. His research program demonstrates a consistent trajectory of advancing the mathematical understanding of complex nonlocal phenomena through rigorous analytical techniques and innovative numerical methods. His publication record reveals a strong focus on fractional calculus, nonlocal diffusion processes, and mean field games. The research shows progression from foundational work on fractional Poincaré inequalities to increasingly sophisticated studies of fully nonlinear mean field games with both local and nonlocal diffusions. His recent work (2023-2025) demonstrates continued innovation in the field, particularly in addressing strongly degenerate cases and establishing precise error bounds for numerical approximations. Dr. Chowdhury maintains an active research program with consistent publication output in high-impact journals such as Foundations of Computational Mathematics, SIAM Journal on Numerical Analysis, and Discrete and Continuous Dynamical Systems. His collaborative work with researchers across international institutions reflects the global significance of his contributions to the field of nonlocal partial differential equations.
Cheong Sang-Wook is a Distinguished Professor at Rutgers University , holding the Henry Rutgers Professor and Board of Governors Professor titles. He serves as Director of the Center for Quantum Materials Synthesis (cQMS) , focusing on advanced materials synthesis and characterization. Key research themes: Quantum Materials , Multiferroics , Topological Defects , and Ferroelectricity . His work spans condensed matter physics , with breakthroughs in magnetoelectric coupling , chiral materials , and quantum spin liquids . Recent publications highlight innovations in polar domain imaging , altermagnetic synthesis , and topological photon emergence , reflecting his leadership in quantum materials and multiferroic oxides . Collaborations include institutions like NJIT and Ho-Am Foundation . Notable awards: James C. McGroddy Prize , KBS Overseas Compatriots Award , and Ho-Am Prize . Recognized as Highly Cited Researcher (2014, 2016, 2018, 2024), with former students like Namjung Hur and Yew San Hor advancing in academia.
Maria Dolores Blanco Rojas is a Full Professor and Deputy Director of the Systems and Automatic Engineering Department at Universidad Carlos III de Madrid (UC3M). Her research focuses on robotics and biomedical engineering, particularly in the development of soft robotic exoskeletons, shape memory alloy (SMA) actuators, and rehabilitation technologies. She leads the Robotics Lab and has contributed to over 100 peer-reviewed articles. Affiliations : UC3M, Robotics Lab, Systems Engineering and Automation Department Education : Not explicitly stated in text Her research interests include: Soft Robotics : Design of wearable exoskeletons for pediatric and post-stroke patients Materials Science : SMA-based actuators for medical and robotic applications Control Systems : Adaptive control algorithms for rehabilitation devices Biomedical Engineering : Integration of sEMG signals for gesture classification in assistive technologies Recent articles explore topics like hyperparameter optimization for machine learning models, SMA actuator efficiency, and eye-hand coordination assessment systems. Projects include the development of pediatric rehabilitation robots (Discover2Walk) and soft exoskeletons for ankle and wrist mobility. Grants/Projects : SRAR (2024–2027): Soft robotics for ankle rehabilitation STRIDE-UC3M (2022–2024): Pediatric exoskeleton validation Advising : Supervised theses on SMA actuators, soft exoskeletons, and rehabilitation systems Her lab develops novel sensors and actuators, including a silver-coated polyamide sensor and multi-wire SMA actuators for high-displacement applications. Collaborations include Airbus and TechnoFusión facilities.
Professor Martijn de Sterke is a Professor in the Department of Physics at the University of Sydney and a member of the Sydney Nano Institute. He holds a MEng in Applied Physics from Delft University of Technology (1982) and a PhD in Optics from the University of Rochester (1987). His postdoctoral work at the University of Toronto (1988–1990) preceded his faculty appointment at the University of Sydney, where he has contributed significantly to the field of nonlinear optics. His research focuses on nonlinear optics, photonic crystals, soliton dynamics, and plasmonic systems. Notable contributions include studies on soliton microcombs, metamaterial-enhanced optical effects, and relativistic lightsail propulsion concepts. He has pioneered work on pure-quartic solitons and their applications in fiber lasers, as well as investigations into Förster resonance energy transfer in engineered metamaterials. Educations: MEng in Applied Physics, Delft University of Technology (1982) PhD in Optics, University of Rochester (1987) His publications span over 300 works, including key contributions to Optics Express as Editor-in-Chief from 2007–2012. He has received prestigious awards such as the Pawsey Medal (1999), Esther Hoffman Beller Medal (2017), and Beatty Steel Medal (2024). Current research activities include ARC-funded projects on optical microcombs and dispersion-engineered solitons. His work bridges theoretical models and experimental implementations, with applications in ultrafast optics, nanophotonics, and space propulsion systems leveraging optical forces.
Mark Ainsworth is a Francis Wayland Professor of Applied Mathematics at Brown University and holds a joint faculty appointment with Oak Ridge National Laboratory. He obtained his PhD from Durham University (1989) and has held prominent roles such as Director of the Centre for Numerical Algorithms and Intelligent Software (2011-2012). His research focuses on numerical analysis, particularly finite element methods for partial differential equations, a posteriori error estimation, and high-performance computing challenges like resiliency on exascale systems. Education: PhD in Mathematics, Durham University, 1989 BSc in Mathematics, Durham University, 1986 Research Interests: Numerical approximation of PDEs A posteriori error estimation and adaptive methods High order finite element methods Resiliency of numerical algorithms on emerging architectures Fractional PDEs and scientific data compression Awards: SIAM Fellow (2014) FIMA (2010) Whitehead Prize (2004) J.L. Lions Prize (2004) Fellow of Royal Society of Edinburgh (2003) Grants & Leadership: Co-PI for ARO MURI on fractional PDEs (2015-2020) Directed NAIS center (2011-2012), a £5M multi-institutional initiative Organized major international conferences on computational mathematics Labs/Teams: Collaborations include Oak Ridge National Lab and international research networks in numerical analysis and scientific computing.
Rachid Malti is a Professor in the Automatic Control research group at the University of Bordeaux, France, specifically working within the CRONE team at IMS (Laboratoire de l'intégration, du matériau au système). His academic career spans over two decades with significant contributions to fractional calculus applications in control engineering and system identification. Professor Malti's research focuses on: Development of fractional order system identification methods Stability analysis of fractional and time-delay systems Experimental design for fractional model validation Applications in energy systems, thermal networks, and battery modeling CRONE Toolbox development for fractional differential signal processing His publication record demonstrates consistent theoretical and applied contributions, with recent work expanding into district heating networks, lithium-ion batteries, and climate modeling while maintaining strong theoretical foundations in fractional calculus. Professor Malti frequently collaborates with researchers including Stéphane Victor, Abir Mayoufi, and Patrick Lanusse across international boundaries. Professor Malti has published extensively in top-tier journals including Automatica, Communications in Nonlinear Science and Numerical Simulation, and Fractional Calculus and Applied Analysis, establishing himself as a leading researcher in fractional order control systems.
Dr. Lateef Akanji is a Senior Lecturer in the Department of Petroleum Engineering at the School of Engineering, University of Aberdeen, where he has been contributing since 2014. He previously served as Lecturer and Head of the Petroleum Technology Research Group at the University of Salford, Assistant Professor at King Saud University, and Visiting Lecturer at the University of Leoben. His academic journey includes a PhD from Imperial College London and degrees from the University of Ibadan. University: University of Aberdeen School: School of Engineering Position: Senior Lecturer, Petroleum Engineering Email: l.akanji@abdn.ac.uk Education: PhD, Petroleum Engineering, Imperial College London M.Sc., Petroleum Engineering, University of Ibadan B.Sc. (Honours), Petroleum Engineering, University of Ibadan DIC (Diploma of Imperial College) Research Interests: Dr. Akanji's research centers on multiphase flow in porous and permeable media, with applications in enhanced oil recovery (EOR) in clastic, carbonate, and unconventional shale reservoirs. His work integrates theoretical, experimental, and computational fluid dynamics, utilizing platforms like Python, C++, and Fortran. He is pioneering the application of artificial intelligence in petroleum engineering, particularly in EOR screening and production optimization. His research includes pore-scale modeling, gas-lift systems, and nuclear reactor flow dynamics. Publication Trends: His recent publications (2025–2021) reflect a strong focus on fluid displacement in porous media, shale reservoir characterization, AI applications in energy, and nuclear safety. Notable themes include computational modeling of multiphase flow, biosurfactant EOR, and advanced numerical methods for reservoir simulation. Scientific Awards and Honors: Fellow of the Higher Education Academy (FHEA) Chartered Engineer (CEng) Chartered Petroleum Engineer European Engineer (Eur Ing) Member of the Energy Institute (MEI) Advising and Grants: Dr. Akanji supervises numerous PhD students in areas such as AI-based production optimization, permeability upscaling, and biosurfactant EOR. He leads research funded by PTDF, TETFUND, Sonangol, and Elphinstone, focusing on high-pressure high-temperature flow loops, gas-lift pilot rigs, and neuro-fuzzy screening systems. His collaborative projects involve institutions in the UK, Austria, and Australia. Laboratories and Research Platforms: He contributes to the development of the Complex System Modelling Platform (CSMP++), a C++-based API for simulating multi-physics flow in porous systems, co-developed with ETH Zurich and Montanuniversität Leoben. He also leads a technology innovation platform for EOR, including experimental rigs for biosurfactant screening and gas-lift stability testing.
Dr. Axel Lubk is a Group Leader at the Institute for Solid State Research (IFW Dresden) , specializing in advanced electron microscopy techniques for materials science. His research spans four key areas: (1) TEM method development (high-resolution imaging, tomography, holography, and in-situ techniques), (2) charge particle optics and scattering theory , (3) magnetic nanotextures (domain walls, skyrmions), and (4) plasmonics (mode hybridization in heterogeneous structures and semiconductor heterostructures). Dr. Lubk’s work focuses on three-dimensional magnetic texture analysis using electron holography and tomography, particularly in systems like skyrmion tubes , FeGe , and Cr2O3 thin films . He has pioneered techniques for vector-field electron tomography and phase retrieval under varying boundary conditions, advancing nanoscale magnetic imaging. His recent studies include plasmonic properties in AgAu nanosphere chains , thermoelectric multilayer systems , and topological insulators like NiRh2Sb and TaTMTe4 . Dr. Lubk has published extensively in high-impact journals such as Nature Communications and Advanced Materials , with a focus on TEM instrumentation and quantitative analysis . He frequently presents at international conferences like the International Microscopy Congress and European School of Magnetism , emphasizing applications in spintronics , quantum materials , and nanostructured systems . His contributions to holographic vector-field electron tomography and machine learning for spectrum-image data have set new standards in electron microscopy.
Juan C. Vasquez is a Professor at Aalborg University's Faculty of Engineering and Science, Department of Energy Technology, and Co-Director of the Center for Research on Microgrids (CROM). He holds a PhD in Automatic Control from the Technical University of Catalonia and has held academic positions at Aalborg University since 2011. His research focuses on microgrid control, renewable energy integration, power electronics, and smart grids. He has supervised numerous PhD and master’s students and leads projects funded by EU and national grants. Education: BS in Electronics Engineering (Autonomous University of Manizales, Colombia, 2004); PhD in Automatic Control (Technical University of Catalonia, Spain, 2009). Research interests include operation and control strategies for AC/DC microgrids, maritime microgrids, energy management systems, and IoT integration in smart grids. He has authored 648+ publications, including highly cited works, and received awards like the Young Investigator Award (2019) and Clarivate’s Highly Cited Researcher status since 2017. Key projects: EU-DREAM (Digital Services for Energy Transition), NEST (National Research Infrastructure), and ActRes (Resilience in Energy Systems). Collaborations include Virginia Tech and Ritsumeikan University.
Lina von Sydow is a Professor in Computational Science at Uppsala University's Department of Information Technology. She serves as Section Dean for the Mathematical-Computer Science Section since July 2023. Her academic journey includes becoming an Associate Professor in 2000, Senior Lecturer since 1997, and leading the Department of Information Technology from 2018 to 2023. PhD in Domain Decomposition Methods (1995, Uppsala University) Postdoctoral Fellow at Oxford University (1996-1997) Her research spans computational science with dual focuses on Computational Finance and Ice Sheet Modeling . In finance, she develops numerical methods for option pricing using PDEs, radial basis functions, and stochastic volatility models. In climate science, she contributes to ice sheet dynamics through full Stokes models and adaptive time-stepping approaches, particularly in simulating grounding line migration. Recent publications (2025) address gender disparities in IT education, including comparative analysis of admission trends and intervention studies to boost female enrollment. Earlier works (2020-2015) focus on high-order finite difference methods for financial derivatives, BENCHOP benchmarking projects, and preconditioning techniques for PDEs. Scientific awards include Excellent Teacher (2013) She actively collaborates on educational reforms, co-authoring studies like Gender-aware course reform in Scientific Computing (2013). Her leadership roles include Head of Department (2018-2023) and Section Dean (2023-present), influencing academic governance and interdisciplinary research. Labs and teams: Works with Uppsala University's Computational Science group, Elmer/ICE project collaborators (e.g., Per Lötstedt, Gong Cheng), and international partners in numerical finance and climate modeling.
Hacer Atar Yıldız is an Associate Professor at the Department of Electronics and Communication Engineering, Faculty of Electrical and Electronics Engineering at Istanbul Technical University (ITU). She holds a B.Sc. (1997) and M.Sc. (2000) in Electronics Engineering from Karadeniz Technical University, and a Ph.D. (2015) in Electronics Engineering from ITU. Her research focuses on analog circuit design, integrated circuits, analog filters, memristor structures, and graphene sensors. Education: Ph.D. in Electronics Engineering (2015), Istanbul Technical University M.Sc. in Electronics Engineering (2000), Karadeniz Technical University B.Sc. in Electronic Communication Engineering (1997), Karadeniz Technical University German Language Education (2001), Munich Technical University Research Interests: Her work emphasizes innovative analog circuit solutions, including memristor-based systems, neural networks, and sensor technologies. Notable contributions include memcapacitor/meminductor emulator circuits and cryogenic bandgap designs. She also explores applications in plant identification using copula models and thermal compensation for microbolometers. Professional Experience: Associate Professor at ITU (2022–present) Researcher at Virginia University (2018) Expert Engineer at Türk Telekom (2003–2009) Intern at Marco GmbH (Munich, 2001–2002) Teaching: She has taught courses such as Introduction to Electronics, Electronic Design, and Analog Circuits at both undergraduate and graduate levels. Recent courses include EHB 222E and EHB 335. Languages & Hobbies: Fluent in English and German. Enjoys swimming, long-distance running, Turkish folk music, and outdoor activities.
Hong Wang is a Professor in the Department of Mathematics at the University of South Carolina, part of the McCausland College of Arts and Sciences. He specializes in numerical analysis and differential equations, with a focus on numerical methods for fractional and variable-order equations. His work addresses complex boundary conditions, optimal control, and scientific computing challenges in advection-diffusion systems. Education Ph.D. in Mathematics, University of Wyoming (1992) Research Interests His research emphasizes numerical approximation techniques for differential/integral equations, particularly fractional diffusion-wave equations, variable-order models, and stochastic systems. Key areas include finite element methods, spectral methods, and fast algorithms for solving high-dimensional and time-dependent problems. He explores applications in optimal control, viscoelasticity, and multi-scale modeling. Recent Work Trends Recent publications highlight advancements in fractional calculus applications, including variable-exponent diffusion, distributed-order equations, and stochastic fractional differential equations. His work often combines theoretical analysis with computational efficiency, addressing challenges like nonsmooth parameters and singular density functions. Grants and Advising No specific grants or advisees are listed, but his research collaborations span computational mathematics, applied physics, and engineering systems. Labs/Teams No dedicated lab or team is explicitly mentioned, though his research aligns with computational and applied mathematics groups at the University of South Carolina.
