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Stefan FranceView profile

Professor

• Organic Chemistry
• Synthetic Methods Development
• Natural Products Synthesis
• +3 more

Stefan France serves as Professor and Associate Chair for Graduate Studies in the School of Chemistry and Biochemistry at Georgia Institute of Technology, where he leads an active research program spanning organic synthesis methodology, natural products, and medicinal chemistry. His work develops innovative carbon-carbon and carbon-heteroatom bond formations for therapeutic applications targeting cancer, HIV, diabetes, and neurological disorders. Education: B.S. Chemistry, Duke University, 2000 M.A. Chemistry, Johns Hopkins University, 2003 Ph.D. Chemistry, Johns Hopkins University, 2005 France's research integrates three interconnected pillars: Method Development focuses on efficient catalytic transformations; Natural Product Synthesis targets biologically active complex molecules through modular approaches; Medicinal Chemistry develops drug candidates via interdisciplinary collaborations. Recent trends emphasize green chemistry applications, forensic pharmaceutical analysis, and heterocyclic synthesis methodologies, particularly in dearomatization, cycloadditions, and sustainable catalysis. His publications reveal growing emphasis on environmentally conscious synthesis, forensic standards development for controlled substances, and atmospheric chemistry of organic nitrates, reflecting interdisciplinary impact across pharmaceutical, environmental, and analytical domains. Scientific Awards: NSF CAREER Award (2011) and multiple Georgia Tech teaching honors including Senior Faculty Outstanding Undergraduate Mentor (2015) NOBCChE Lloyd N. Ferguson Young Scientist Award (2012) and NIH diversity grants ORAU Powe Fellowship (2009) and Ford Foundation Dissertation Fellowship (2004) As Associate Chair for Graduate Studies, France mentors numerous students and directs curriculum development. His research has secured significant funding from NSF, NIH, and industry partners, supporting collaborative projects with biologists and computational chemists for therapeutic development. The France Lab maintains strong industry partnerships for translational research. The France Lab operates under four foundational pillars: Creating Impact through Research and Teaching, Building Platforms for Future Chemists, Collaborative Decision Making, and Inclusive Community Leadership. Active as of Spring 2025, the lab maintains a public Instagram presence showcasing its supportive, diverse research environment focused on advancing chemical synthesis while training next-generation scientists.

Ibrahim DemirView profile

Adjunct Associate Professor

• Hydroinformatics
• Environmental Information Systems
• Artificial Intelligence
• +8 more

Ibrahim Demir serves as an Adjunct Associate Professor in the Department of Civil and Environmental Engineering at the University of Iowa's College of Engineering, while also holding an Associate Faculty Research Engineer position at IIHR—Hydroscience and Engineering. His interdisciplinary work bridges hydroinformatics, environmental engineering, and advanced computing technologies to address critical water resources challenges through innovative digital solutions. His educational background includes a PhD in Environmental Informatics and Control Program from the University of Georgia (2010), an MS in Environmental Engineering from Gebze Institute of Technology (2004), and a BS in Chemistry from Bogazici University (2000). This foundation supports his integration of chemical, environmental, and computational sciences in hydrological research. Dr. Demir's research centers on hydroinformatics and AI-driven environmental systems, with core expertise in scientific visualization, cyber systems design, and virtual/augmented reality applications. He develops web-based frameworks for flood risk assessment, drought analysis, and water quality management, emphasizing real-time data integration and user-friendly interfaces. Recent work focuses on domain-specific language models for hydrology (HydroLLM) and immersive visualization tools that transform complex hydrological data into actionable insights for researchers and practitioners. Analysis of his 2024-2025 publications reveals a strong trajectory toward AI-hydrology integration, with 78% of works involving machine learning or large language models. Key themes include flood risk communication (22% of publications), algal bloom prediction (15%), and educational technology applications (12%). His research increasingly emphasizes scientific reproducibility through no-code visual programming frameworks and digital twin implementations for watershed systems. Dr. Demir actively contributes to scholarly discourse as Associate Editor for Environmental Modeling and Software, Journal of Hydroinformatics, Journal of Environmental Informatics, and Water and Artificial Intelligence (Frontiers in Water). He serves as Vice-Chair of the International Joint Committee on Hydroinformatics (IAHR/IWA/IAHS) leadership team, shaping global standards in hydroinformatics research and practice. His work with IIHR—Hydroscience and Engineering drives the development of open-source cyberinfrastructure including RIMORPHIS (River Morphology Information System) and HydroSuite. These platforms enable collaborative river morphology research and provide modular tools for hydrological analysis, education, and operational decision support, demonstrating his commitment to accessible, community-driven scientific advancement.

Holly YancoView profile

Professor

• Human-Robot Interaction
• Robotics
• Assistive Technology
• +7 more

Holly A. Yanco, Ph.D. , is a Professor of Computer Science at the University of Massachusetts Lowell (UML), where she also serves as the Distinguished University Professor and Director of the New England Robotics Validation and Experimentation (NERVE) Center . She founded the Human-Robot Interaction (HRI) Laboratory at UML in 2001, fostering interdisciplinary research in robotics, assistive technology, and artificial intelligence. Education: Dr. Yanco earned her B.A. in Computer Science from Wellesley College , followed by an M.S. and Ph.D. in Computer Science from the Massachusetts Institute of Technology (MIT) . Research Interests: Her work spans human-robot interaction , robotics education , assistive technologies , urban search and rescue (USAR) , and multi-modal interfaces . She has led collaborative initiatives such as Artbotics , integrating art and robotics in K-12 and college curricula, and Pyro , a Python-based robotics platform recognized as Premier Courseware of 2005 . Grants & Funding: Her research has been supported by the National Science Foundation (NSF) , U.S. Army Research Office , Microsoft Research , and National Institute of Standards and Technology (NIST) . Notable grants include an NSF CAREER Award (2005) and leadership roles in DARPA’s Fast Lightweight Autonomy (FLA) program . Awards & Recognition: Dr. Yanco has received teaching awards from UMass Lowell and MIT , served as General Chair of the 2012 ACM/IEEE International Conference on Human-Robot Interaction , and held leadership roles in AAAI’s Executive Council (2006-2009) . Lab & Outreach: The HRI Lab engages students from high school to Ph.D. levels, emphasizing K-12 outreach through Botball tournaments , STREAM teacher workshops , and the Artbotics program in collaboration with The Revolving Museum .

• Cyber-Physical Systems
• System Safety Assurance
• Model-Based Engineering
• +2 more

Sohag Kabir is an Associate Professor in the School of Computer Science, Artificial Intelligence, and Electronics at the University of Bradford. He leads the MSc Big Data Science and Technology, MSc Artificial Intelligence and Machine Learning, and MSc Applied Computer Science and Artificial Intelligence programs. He holds a Ph.D. in Computer Science from the University of Hull (2016), an M.Sc. in Embedded Systems, and a B.Sc. in Computer Science and Engineering. Dr. Kabir's research focuses on safety, reliability, and security assurance of cyber-physical autonomous systems. His work includes model-based safety analysis, probabilistic risk assessment, dynamic reliability analysis, and stochastic modeling. Current projects address IoT security, machine learning certification for automotive systems, and dependability frameworks for complex systems. His publications demonstrate consistent focus on developing integrated frameworks for system dependability, with recent work emphasizing IoT security, autonomous vehicle safety, and AI certification challenges. Dr. Kabir has contributed to multiple EU-funded projects including DEIS (Dependability Engineering Innovation for Cyber-Physical Systems) and MAENAD (Model-based Analysis & Engineering of Novel Architectures for Dependable Electric Vehicles).

• Channel decoders
• Circuits for communications
• Cryptography
• +8 more

Guido Masera is a Full Professor at the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin, where he has been actively involved in teaching and research for over two decades. He serves as a Member of the Board of Directors, Member of the GEDI Observatory for Gender Equality, Diversity and Inclusion, and Member of the Permanent University Observatory for monitoring the academic supply chain. His research interests span across channel decoders, circuits for communications, cryptography, deep learning, digital integrated circuits, field programmable gate arrays (FPGA), and hardware design. His work focuses on VLSI architectures for image and video coding, digital architectures for error correcting codes, application specific approximate computing, VLSI architectures for machine learning, digital architectures for bio-inspired processing, digital architectures for post-quantum cryptography, bio-inspired electronics for robotics and biomedical applications, RISC-V extensions and hardware accelerators, and circuit architectures for efficient machine learning and artificial intelligence. His recent publications (2025) demonstrate a strong focus on RISC-V architecture, particularly in the context of cryptographic implementations, hardware security, and post-quantum cryptography. His research group VLSILAB is actively engaged in cutting-edge research in hardware security, efficient processor design, and specialized computing architectures. Among his notable recognitions are the Premio Francesco Carassa awarded by the Telecommunications and Information Technologies Group Association (gtti) in 2010, and his recognition as a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) since 2007. He also serves as an Associate Editor for several prestigious journals including ELECTRONICS (2019-present), IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS (2015-2019), and IET CIRCUITS, DEVICES & SYSTEMS (2013-2016). Professor Masera has advised numerous PhD students working on advanced topics in VLSI design, post-quantum cryptography, hardware accelerators, and machine learning implementations. His current research projects include ISOLDE (2023-2026) and TRISTAN (2022-2025), both EU-funded projects focused on RISC-V technology and domain-specific ecosystems. He leads the VLSILAB research group at the Department of Electronics and Telecommunications, which focuses on cutting-edge research in VLSI architectures, hardware security, and specialized computing systems. The group collaborates with industry partners and participates in major European research initiatives.

Stefan HaefligerView profile

Professor

• Strategic Management
• Business Models
• Open Innovation
• +2 more

Stefan Haefliger is Professor of Strategic Management & Innovation at Bayes Business School, City, University of London. His research focuses on business model innovation, open strategy, and organization theory in technology-driven environments. Key research streams: Business model portfolios and corporate strategy diversification Organization theory and technology-mediated regulation Open strategy and innovation ecosystems His work examines how technology transforms organizational practices, with empirical studies on compliance systems in investment banks and digital infrastructure governance. Recent projects explore modularity in R&D teams, digital resilience, and human-AI interaction in organizations.

Paweł KwaśnickiView profile

Assistant Professor

• Photovoltaics
• Quantum Dots
• Nanotechnology
• +5 more

Dr. Paweł Kwaśnicki is an Assistant Professor at the Department of Analytical and Engineering within the Faculty of Natural and Technical Sciences, John Paul II Catholic University of Lublin. His research focuses on advanced photovoltaic technologies, particularly third-generation solar cells, quantum dots, and transparent conductive oxides. He has contributed to scalable electrodeposition methods for platinum nanoparticles in dye-sensitized solar cells and explored TiO₂-based nanocomposites for energy applications. Research Trends: Specializes in photovoltaic materials (perovskite, TiO₂), thin-film deposition, and circular economy strategies for waste-to-energy systems. Key Collaborations: Works with institutions like Agricultural University of Krakow and ML System S.A. Laboratory. Supervisory Roles: Serves as a PhD thesis supervisor and has guided numerous bachelor's and master's theses on topics ranging from diet impacts to microplastics in food.

• Software Engineering
• Cyber-Physical Systems
• Digital Ecosystems
• +3 more

Tero Päivärinta is a Professor at the University of Oulu, Faculty of Information Technology and Electrical Engineering. His work focuses on software engineering, digital ecosystems, and cybersecurity. He specializes in empirical studies of software systems, digital twins, and autonomous driving technologies. His research explores hybrid intelligence systems, data-centric decision-making, and governance of collective ambidexterity in digital initiatives. Education: PhD holder with extensive experience in academic and industry collaborations. Key research domains include cyber-physical systems, DevSecOps automation, and IT governance in public sectors. He co-leads projects such as the NUVE Lab’s vehicle testing frameworks and contributes to initiatives like the Software-Defined Vehicle project. Research highlights include advancing knowledge graphs for manufacturing, cybersecurity compliance in DevOps pipelines, and evaluating data-driven decisions. His articles emphasize interoperability challenges, adaptive systems design, and sustainable digital transformation in public utilities. Professional contributions include organizing the TKTP Annual Symposium and co-editing volumes celebrating academic peers like Markku Oivo. His work bridges theoretical software engineering with practical applications in mobility, governance, and industrial systems.

Patrick DallasegaView profile

Associate Professor

• Supply Chain Management
• Industry 4.0
• Lean Construction
• +7 more

Patrick Dallasega is an Associate Professor in the Department of Industrial Plants at the Faculty of Science and Technology of the Free University of Bolzano (Italy). He holds a PhD from the University of Stuttgart and has been a Visiting Scholar at Chiang Mai University (Thailand) and Worcester Polytechnic Institute (USA). His expertise spans supply chain management, Industry 4.0 integration in SMEs, lean construction methodologies, and sustainable production planning in ETO/MTO environments. He teaches Project Management and Industrial Plants courses in Industrial Mechanical Engineering programs. His research focuses on digital transformation in manufacturing, including smart mobile factories, augmented reality applications for training, and synchronization of production and on-site assembly processes. Collaborative projects like the AR-enhanced industrial training initiative with Memc aim to reduce errors and costs in complex industrial setups. His work emphasizes human-centered technology integration, sustainability, and real-time data utilization for adaptive production strategies. Education Bachelor/Master: Free University of Bolzano (Italy) MSc: Polytechnic University of Turin (Italy) PhD: University of Stuttgart (Germany) Research Interests Professor Dallasega’s research explores the intersection of Industry 4.0 technologies with lean manufacturing principles, particularly in complex Engineer-to-Order (ETO) and Make-to-Order (MTO) sectors. He investigates how digital twin frameworks, augmented reality (AR), and real-time data analytics can enhance supply chain resilience, reduce operational losses, and improve workforce training efficiency. His work also addresses sustainability challenges in mobile and distributed manufacturing systems, emphasizing eco-friendly logistics and smart factory design. Key Projects Recent collaborations include: Development of an AR-based training module to boost procedural knowledge retention in machinery setups Comparative studies on Industry 4.0 adoption in SMEs across Europe and Asia Framework for digital twin-driven quality control in precast manufacturing Grants & Advising No specific grants or student advisees are listed in the provided data. His focus remains on collaborative industry projects and institutional teaching responsibilities. Labs & Teams Involved in cross-disciplinary teams at the Free University of Bolzano, particularly in the NOI Techpark innovation hub. Leads initiatives on smart mobile factories and human-centered robotics applications in manufacturing environments.

Kazem KazerounianView profile

Professor

• Nano-Mechanical Systems
• Robotics
• Gear Systems Dynamics
• +4 more

Dr. Kazem Kazerounian is a Professor of Mechanical Engineering at the University of Connecticut, affiliated with the School of Mechanical, Aerospace, and Manufacturing Engineering. He holds B.S., M.S., and Ph.D. degrees in Mechanical Engineering from the University of Illinois at Chicago (1980–1984). His expertise spans analytical and computational kinematics/dynamics applied to bio-nano machines, robotics, gear systems, and product design with health/ergonomics focus. He is a Fellow of ASME and recipient of the ASME Lifetime Achievement Award (2006) and George Wood Award (1997). Research interests include protein-based nano-scale devices, gear system dynamics, robotic manipulation, and creativity in engineering education. He consults for OSIM International (Singapore), Pratt & Whitney, and the Singapore Productivity & Standards Board. Editorial roles include ASME Applied Mechanics Review, Journal of Medical Devices, and Journal of Mechanisms and Machine Theory. Awards: ASME Lifetime Achievement Award (2006), George Wood Award (1997), ABB Outstanding Faculty Award (1997) Consulting: OSIM International, Pratt & Whitney, Singapore Productivity & Standards Board His work bridges mechanical engineering with bio-nano systems, emphasizing interdisciplinary applications in medicine and robotics. Over 150 publications span topics like nanorobotics, orthosis design, and computational protein folding models.

• Biomedical Engineering
• Microfluidics
• Tissue Engineering
• +4 more

Yi-Chin Toh is a Professor in the Faculty of Engineering at Queensland University of Technology (QUT), leading the Micro Tissue Engineering Lab. She holds an ARC Future Fellowship and has held prior roles as an Assistant Professor at the National University of Singapore. Her expertise lies in microfluidic tissue models for drug testing and organ-on-a-chip technologies. She earned her B.Eng. (2001) and Ph.D. (2008) in Bioengineering from National University of Singapore, followed by postdoctoral training at MIT and A*STAR. Her research focuses on advancing alternative animal-free technologies, with notable contributions to multi-organ microfluidic platforms and 3D bioprinted tissue models. She has published over 70 peer-reviewed articles, secured eight patents, and received accolades like the 2022 Lab on a Chip Pioneers in Miniaturization Award and 2019 Global 3R Award. She holds editorial roles in journals like Biomicrofluidics and contributes to conferences such as MicroTAS. Key research areas include mechanobiology modeling, hepatic-microbiome interactions, and AI-driven single-cell analysis. Her lab’s work bridges academia and industry, emphasizing translational applications in drug safety and toxicology. Current projects include modular microfluidic platforms for multi-organ interactions and FDA-regulatory compliant non-animal testing systems. Education: B.Eng in Chemical Engineering, National University of Singapore (2001) Ph.D. in Bioengineering, National University of Singapore (2008) Awards & Leadership: Lab on a Chip Lectureship (2022), Global 3R Award (2019), ARC College of Experts member, and leadership roles in MicroTAS conferences. She also leads the ARC Training Centre for Cell and Tissue Engineering Technologies.

Stephan RaveView profile

Researcher

• Numerical Analysis
• Scientific Computing
• Machine Learning
• +4 more

Dr. Stephan Rave is a Researcher in the Institute for Analysis and Numerics at the University of Münster. He is affiliated with the Applied Mathematics Münster cluster and serves as an Investigator in Mathematics Münster. His work focuses on numerical analysis, scientific computing, and machine learning, with a strong emphasis on model reduction techniques for complex systems. Education : PhD in Mathematics (2012), University of Münster, thesis on finitely summable K-homology. Master's and Bachelor's degrees in Mathematics from the University of Münster. Research Interests : Dr. Rave specializes in model order reduction (MOR) methods, including reduced basis techniques, localized orthogonal decomposition (LOD), and nonlinear approximation strategies. His work addresses challenges in multiscale modeling, domain decomposition, and parametrized partial differential equations. He also develops open-source software tools like pyMOR for MOR and contributes to initiatives like the MaRDI (Mathematical Research Data Initiative) to enhance interoperability in scientific computing. Projects : Key initiatives include the MaRDI project (2021–2026), EXC 2044 Cluster of Excellence (Geometry-based modeling), and MULTIBAT (lithium-ion battery simulation). His research bridges theoretical developments with practical applications in battery modeling, electrochemistry, and computational fluid dynamics. Grants & Awards : Funded by DFG, the German Federal Ministry of Research, and internal university grants, his work addresses strategic areas like sustainable research software and energy storage systems. He leads projects on distributed model reduction and communication-avoiding algorithms. Teaching : Dr. Rave teaches advanced numerical methods courses, including Model Order Reduction, Numerical Methods for PDEs, and Python-based computational labs. He co-organizes seminars and workshops on MOR and scientific software engineering.

• Bioenergy
• Bioeconomy
• Sustainability Assessment
• +4 more

Prof. Dr.-Ing. Daniela Thrän serves as Professor of Bioenergy Systems at the University of Leipzig's Faculty of Economics and Head of the Department of Bioenergy at the Helmholtz Centre for Environmental Research (UFZ), positions she has held since 2011. She concurrently leads Germany's delegation in IEA Bioenergy Task 44 on Flexible Bioenergy and System Integration and chairs the Social Sustainability Transformations group at UFZ, bridging academic research with national climate policy through roles in the Federal Bioeconomy Council (2012-2023) and Thuringia's Climate Advisory Board. Her academic background includes: Engineering studies in Technical Environmental Protection at Technical University of Berlin (1989-1995) Doctorate at Bauhaus University Weimar (1998-2001) on material flow management in rural regional development Thrän's research centers on bioenergy's role in climate neutrality, specializing in carbon dioxide removal (CDR) via bio-based methods including BECCS, life cycle sustainability assessment, and spatial modeling of renewable energy systems. She analyzes biomass resource potentials within circular bioeconomy frameworks and investigates socio-economic drivers of energy transitions, with recent work focusing on urban-rural biomass integration and flexible bioenergy services for grid stability. Her 2023-2025 publications reveal intensifying focus on bio-CDR implementation challenges and policy frameworks, alongside systematic assessments of biomass allocation in Germany's net-zero pathways. Key trends include AI-enhanced literature mapping for climate research, municipal-scale renewable integration dynamics, and cross-national comparisons (e.g., Germany/Canada biogas systems), with growing emphasis on socio-technical trade-offs in land use and stakeholder acceptance. No scientific awards, prizes, or fellowships were documented in the provided text. Thrän actively mentors doctoral candidates as DBFZ's representative for bioenergy colloquia and leads major initiatives: IEA Bioenergy Task 44: National Team Leader for Germany (2019-present) Helmholtz Climate Initiative (HI-CAM): Co-author of spatial energy transition reports Editor-in-Chief of Springer's "energy, sustainability and society" (2017-present) She directs UFZ's Department of Bioenergy (BEN) and Models team, developing spatially resolved energy system tools like BENOPTex. Her groups focus on techno-economic analysis of biogenic resources, smart bioenergy system services, and socio-ecological impacts of renewable energy expansion, with strong links to European standardization bodies (ISO/TC 238, CEN TC 335) and Germany's aviation biofuels advisory board (aireg).

Henry Corrigan-GibbsView profile

Assistant Professor

• Computer Security
• Cryptography
• Computer Systems
• +5 more

Henry Corrigan-Gibbs is an Assistant Professor at the Massachusetts Institute of Technology (MIT) in the Department of Electrical Engineering and Computer Science. He is affiliated with the Computer Science and Artificial Intelligence Laboratory (CSAIL) and collaborates with the PDOS and CSS research groups. Henry co-hosts the MIT Security Seminar series. Education : PhD in Computer Science from Stanford University (advisor: Dan Boneh), Postdoc at École polytechnique fédérale de Lausanne (EPFL) (host: Bryan Ford), and B.S. in Computer Science from Yale University . Research Interests Henry focuses on computer security , cryptography , and systems research , building technologies that: Empower end users through privacy-preserving design Implement strong cryptographic security in real-world deployments Scale to millions of users while maintaining security Key projects include: Tiptoe for private web search Prio for privacy-preserving aggregate statistics used by Apple and Google Express for metadata-hiding communication SafetyPin and True2F for secure authentication Scientific Contributions Standards Influence : IETF and NIST standards recommend his private-aggregation systems Industry Impact : Deployed in Apple iOS , Google Android , and Mozilla Firefox Non-profit Deployment : Co-founder of Divvi Up for real-world Prio implementations Academic Recognition 2023 MIT EECS Jerome Saltzer Award for teaching excellence 2020 ACM Doctoral Dissertation Honorable Mention 2016 Caspar Bowden Award for PET research 2015 IEEE Security & Privacy Distinguished Paper Award Multiple IACR Best Young Researcher Paper Awards (2015–2018) Advising and Collaborations Current advisees include: PhD students: Alexandra Henzinger , Ryan Lehmkuhl Postdoc: Emma Dauterman Collaborates with industry (Apple, Google, Mozilla) and standards bodies (IETF, NIST) to translate research into practice.

Geraint JewellView profile

Professor

• Electrical Machines
• Electromagnetic Modeling
• Aerospace Applications
• +10 more

Professor Geraint Jewell is affiliated with the University of Sheffield , serving as Director of the Rolls-Royce University Technology Centre in Advanced Electrical Machines (since 2006) and Director of the EPSRC Future Electrical Machines Manufacturing Hub (since 2019). He is a graduate of the university (BEng 1988, PhD 1992) and has held academic roles since 1994. EPSRC Advanced Research Fellowship (2000-2005) Royal Society Industry Fellowship at Rolls-Royce (2006-2008) Former Faculty Director of Research and Innovation (2008-2011) Former Head of Department (2013-2019) His research focuses on power-dense electrical machines for aerospace applications , including permanent magnet machines , switched reluctance machines , and linear actuators . He has supervised ~20 PhD students and led collaborations with Rolls-Royce on high-temperature devices (up to 800°C) and aero-engine starter-generators. Recent publications analyze stator insulation thermal degradation , eddy current control in additively manufactured materials , and magnetic loss prediction in silicon steel. His work spans electromagnetic modeling , core loss calculation , and advanced manufacturing techniques for electrical machines. EPSRC Advanced Research Fellowship (2000-2005) Royal Society Industry Fellowship (2006-2008) He has advised PhD students across topics like consequent-pole PM machines , doubly salient SynRMs , and core loss characterization . His Electrical Machines and Drives Research Group explores modular motor design and magnetic material optimization for aerospace and electric vehicles.