Prof. Dr. Markus Zimmermann leads the Chair of Product Development and Lightweight Design at the Technical University of Munich (TUM). With a background in mechanical engineering from TU Berlin and the University of Michigan, and a doctorate from MIT on solid-state singularities, he bridges academic rigor with industrial application. His career spans 12 years at BMW focusing on vehicle development before transitioning to academia. Specializes in solution space engineering for robust design Expert in additive manufacturing and systems engineering Develops methodologies for managing design complexity and uncertainty His research focuses on multidisciplinary design optimization and lightweight structures , particularly in robotics and automotive systems . His team applies digital twin frameworks and attribute dependency graphs to enhance design processes. Recent publications emphasize topology optimization in robotic systems and thermal management for medical X-ray sources. Key trends in his 2024-2025 publications include: Topological optimization for additive manufacturing and robotics Application of solution spaces to manage design uncertainty Development of compact X-ray systems for medical therapy Integration of digital twin technologies in industrial contexts
R. Edwin García is a Professor at the School of Materials Engineering at Purdue University, where he has been faculty since 2005. He holds appointments in the Materials Engineering department within Purdue's College of Engineering, specifically in the School of Materials Engineering located in the Neil Armstrong Hall of Engineering at Purdue's West Lafayette campus. His educational background includes: B.S. in Physics from the National University of Mexico (1996) M.S. in Materials Science and Engineering from Massachusetts Institute of Technology (2000) Ph.D. in Materials Science and Engineering with a minor in Applied Mathematics from Massachusetts Institute of Technology (2003) Professor García's research focuses on the design of materials and devices through the development of a fundamental understanding of the solid state physics of individual phases, their short and long range interactions, and associated microstructural properties and time evolution. His current research emphasizes establishing relationships between material properties and resultant performance and degradation in electrochemical systems. He integrates computational approaches ranging from kinetic Monte Carlo, phase field and level set methods, to finite elements, finite volumes, and symbolic computing. His work particularly addresses microstructure design, crystallographic texture, and grain boundary science and engineering to control the topology of underlying phases and establish practical relations between processing, microstructure, and material properties. His recent publications demonstrate a strong focus on lithium-ion battery technology, ferroelectric materials, and computational modeling of material behaviors. The research trends show increasing integration of machine learning with traditional computational methods, exploration of novel sintering techniques like flash sintering, and deeper investigation into the fundamental mechanisms of material degradation in energy storage systems. His work spans multiple length scales from atomistic to continuum modeling, reflecting a comprehensive approach to materials design and analysis. Professor García teaches several courses including MSE 230 (Structure and Properties of Materials), MSE 350 (Thermodynamics of Materials), MSE 597G (Modeling and Simulation of Materials), MSE 597I (Introduction to Computational Materials), and MSE 597N (Physical Properties of Crystals). He mentors graduate students in areas related to computational materials science, battery technology, and microstructural evolution. His research group, the Laboratory of Computational Microstructures, focuses on developing home-grown analytical theories and algorithms to resolve relevant time and length scales in materials systems. The group's work has significant implications for portable power sources, including rechargeable batteries and fuel cells, as well as for ferroelectric ceramic applications.
Professor Shubhra Pasayat is affiliated with the Department of Electrical and Computer Engineering and Materials Science & Engineering at the University of Wisconsin-Madison. She holds a PhD (2021) and MS (2017) from University of California, Santa Barbara, and a B.Tech (2013) from Indian Institute of Technology Kharagpur. Research focus: MOCVD growth of III-nitrides/oxides for optoelectronics, power electronics, quantum materials, and bio-photonics Key applications: LEDs, LASERs, HEMTs, bio-photonics, and sanitization technologies Her research interests center on wide bandgap semiconductor materials, particularly group-III nitrides and oxides. She works on strain relaxation techniques using porous GaN substrates, quantum dot engineering for visible light emission, and high-voltage GaN HEMT development. Current projects include lattice engineering for improved crystal quality and thermal management in RF devices. Publications highlight advancements in ultraviolet lasers, high-electron-mobility transistors, and micro-LEDs. Her work spans fundamental material studies and device optimization for industrial applications like electric vehicles, 5G/6G communications, and horticultural lighting. 2024 Awards : NSF CAREER, ONR DEPSCoR, WARF Early Career Innovator 2022 Awards : UCSB ECE Outstanding Dissertation, JAP Best Paper She teaches ECE 235 Introduction to Solid State Electronics and mentors research at both graduate and undergraduate levels.
Prof. Catherine O'Sullivan is a Professor of Particulate Soil Mechanics at Imperial College London's Department of Civil and Environmental Engineering, part of the Faculty of Engineering. She leads the Geotechnics Section and serves as Editor-in-Chief of the ASCE Journal of Geotechnical and Geoenvironmental Engineering. Her research focuses on particulate soil mechanics, employing Discrete Element Modelling (DEM) and micro-CT imaging to study sand behavior, reservoir sandstones, and internal erosion. Notable recognitions include the 2016 Shamsher Prakash Research Award and the 2021 President’s Teaching Innovation Award. Education : PhD in Civil Engineering, University of California, Berkeley (2002) MEngSc in Civil Engineering, University College Cork (Ireland) BEng (Civil Engineering), University College Cork (Ireland) Research Interests : Prof. O'Sullivan's work integrates computational and experimental methods to explore granular material behavior. Key areas include DEM validation, μCT analysis, and pore network modeling. Her group collaborates across disciplines, involving physicists and mechanical engineers alongside civil engineers. Awards & Recognition : 2015 Geotechnique Lecture Student Choice Supervision Award (nominated twice) 2023 Alert Geomechanics Special Lecture Advising & Grants : She supports PhD and postdoctoral researchers through Imperial scholarships and fellowships. Her students often explore particulate soil behavior, with many securing prestigious awards. Labs & Teams : Leads the Geotechnics Section at Imperial, fostering interdisciplinary research in geomechanics and computational modeling.
Dane Morgan is a Professor in the Department of Materials Science & Engineering at the University of Wisconsin-Madison, College of Engineering. His research focuses on computational materials science for materials design, including ab initio electronic structure modeling, multiscale methods, and machine learning applications in materials discovery. His work spans nuclear materials, battery and fuel cell electrodes, and electronic materials. Education : PhD, 1998, University of California, Berkeley MS, 1994, University of California, Berkeley BA, 1992, Swarthmore College Research Interests : Computational materials science, ab initio methods for electronic structure and thermokinetics, machine learning for materials discovery, electrochemical systems modeling, and applications in nuclear materials, batteries, and electronic materials. His work integrates advanced computational techniques with experimental validation. Scientific Awards : 2024 APL Materials, Editors Pick 2023 Microscopy and Microanalysis Best Paper Award (Instrumentation and Software category) 2023 IEEE Transactions on Plasma Science Best Paper Award 2023 Kellet Mid-Career Award 2015 TMS Materials Genome Initiative Ambassador 2006 3M Technical Nontenured Faculty Grant
Dr. Christopher M. Wolverton is a Professor of Materials Science and Engineering at Northwestern University , where he leads the Wolverton Research Group . His work focuses on computational materials science with applications in energy sustainability , particularly in batteries , hydrogen storage , and thermoelectrics . PhD in Physics from University of California, Berkeley BS in Physics (summa cum laude) from University of Texas, Austin His research leverages first-principles quantum mechanical simulations and machine learning to enable virtual materials synthesis before laboratory testing. The group specializes in hybrid computational methods integrating Density Functional Theory (DFT) , Monte Carlo simulations , and phase-field microstructural models . The article portfolio shows leadership in energy storage materials , with recent work on data-driven nanoparticle facet control , mixed-anion semiconductors , and machine learning-accelerated discovery . Publications span top journals including Nature Energy , Nature Materials , and Science . 2006 Ford Motor Company Technical Achievement Award 2005 Ford Patent & Publication Awards 2003 Ford Environmental/Physical Sciences Recognition As advisor to PhD candidates Zhenpeng Yao , Shiqiang Hao , and Shane Patel , he fosters interdisciplinary research connecting materials informatics with experimental validation . The group maintains active collaborations with Argonne National Lab and MIT/Harvard teams.
Julia A. Mundy is the John L. Loeb Associate Professor of the Natural Sciences and Engineering and Applied Sciences at Harvard University. Her research focuses on designing quantum materials at the atomic scale using molecular-beam epitaxy (MBE) to synthesize metastable thin films. She leads the Mundy Group, which explores superconductors, frustrated magnets, and oxide interfaces for quantum and energy applications. Her work bridges materials synthesis, characterization, and fundamental physics. Affiliations: Harvard University, School of Engineering and Applied Sciences, Applied Physics Department Labs: Mundy Group (LISE 7th floor) Research interests include MBE growth of novel oxides, thin film superconductors, and 2D electronic systems. She has pioneered methods for creating room-temperature multiferroics and discovered superconductivity in layered nickelates. Her group uses advanced tools like aberration-corrected electron microscopy and synchrotron-based spectroscopy. Key achievements include the 2024 Moore Inventor Fellowship, NSF CAREER Award, and Packard Fellowship. Her work on transparent superconductors and fluoride-ion battery materials highlights interdisciplinary impact. Notable Grants: DOE Early Career Award, NSF MRI funding for LEEM/PEEM microscopy Team: 15+ current members including graduate students, postdocs, and undergraduates
Dr. Richard Fair is the Lord-Chandran Distinguished Professor of Engineering at Duke University, with a career spanning semiconductor physics, digital microfluidics, and lab-on-a-chip systems. His research group collaborates with faculty across Duke, Harvard, and Stanford in bioengineering, genomics, and environmental science to develop applications-driven microfluidic platforms. Ph.D. in Electrical and Computer Engineering, Duke University (1969) B.S.E.E., Duke University (1964) M.S.E.E., Pennsylvania State University (1966) Research interests focus on electrowetting-based microfluidics for biosensing, diagnostics, and synthetic biology applications. Key innovations include adaptive droplet routing , magnetic bead manipulation , and integrated optical sensors for real-time analyte detection in environmental and medical contexts. Recent publications emphasize deep reinforcement learning for biochip automation, fluorescent nucleosome detection , and inorganic ion analysis in aerosols. Collaborations with institutions like Advanced Liquid Logic and NSF-funded projects highlight his interdisciplinary approach. IEEE Third Millennium Medal (2000) Solid State Science and Technology Award (Electrochemical Society, 2003) Gordon E. Moore Medal (2009) Fellow, IEEE and Electrochemical Society Grants include NSF awards with Nan Jokerst and Krish Chakrabarty for adaptive lab-on-a-chip optical control, DARPA funding for genomic engineering platforms, and collaborations with the Desert Research Institute on airborne particle sensing. His lab develops scalable solutions for environmental monitoring, clinical diagnostics, and synthetic biology applications.
Jack Beuth is a Professor of Mechanical Engineering at Carnegie Mellon University (CMU), affiliated with the College of Engineering. He has been on the faculty since 1992 and leads the NextManufacturing Center, focusing on additive manufacturing (AM) research. His work emphasizes process mapping for AM, material science, and machine learning integration in manufacturing processes. Key affiliations include the Engineering Research Accelerator and the Manufacturing Futures Institute. Education: Ph.D. in Engineering Sciences, Harvard University (1992) M.S. in Engineering Sciences, Harvard University (1989) M.S. in Engineering Science and Mechanics, Virginia Tech (1987) B.S. in Engineering Science and Mechanics, Virginia Tech (1984) Research Interests: Additive Manufacturing (process modeling, material characterization, and defect analysis) Melt pool dynamics and thermal modeling Machine learning for process optimization and quality control Advanced materials for AM (e.g., Ti-6Al-4V, Inconel 718) His research has led to innovations like 'process map' approaches for AM, enabling better control over variables such as melt pool geometry and microstructure. Awards and Recognition: Ralph R. Teetor Educational Award (1998) George Tallman and Florence Barrett Ladd Development Professorship (2000) ASME Curriculum Innovation Award (2005) Benjamin Richard Teare Teaching Award (2009) Grants and Collaborations: $3.5M cooperative agreement with the U.S. Army Combat Capabilities Development Command’s Army Research Laboratory (ARL) for AI-driven AM process optimization. Collaborations with Westinghouse Electric Company on 3D-printed nuclear components, such as spacer grids for pressurized water reactors. Labs and Teams: NextManufacturing Center: A research hub for AM innovation, emphasizing industrial partnerships and applied research. Beuth’s Additive Lab: Specializes in melt pool analysis, process mapping, and material behavior under AM conditions.
Zoran Cenev holds a Tenure Track Assistant Professor position within the Mechatronics and Dynamics section of the Department of Mechanical and Production Engineering at the School of Engineering, Aarhus University. His primary institutional affiliation is with AU Engineering, and contact details include email zoran.cenev@mpe.au.dk and telephone +45 20 64 75 44, with office location Aarhus N, 5128-140. Research interests focus on interdisciplinary applications of magnetic and robotic systems: Robotic micromanipulation via electromagnetic needles Ferrofluid-based biofabrication for skeletal muscle engineering Laser-induced photothermal droplet control Theoretical modeling of particle dynamics at fluid interfaces Surface engineering for underwater metallic stability Nanostructure formation through ion bombardment His recent publications (2023-2025) reveal a dominant trend in adapting ferrofluids for biomedical automation, particularly 3D bioprinting of magnetically responsive tissues and droplet manipulation on engineered surfaces. This work bridges mechanical engineering with regenerative medicine, emphasizing practical implementations of theoretical models for microscale precision. Scientific awards are not documented in the provided information. As a faculty member, Dr. Cenev likely mentors graduate students and pursues research grants, though specific advisees or funding details are absent. Departmental laboratories and workshops support his experimental work in mechatronics, with emphasis on magnetic manipulation systems and surface characterization.
Azita Emami serves as the Andrew and Peggy Cherng Professor of Electrical Engineering and Medical Engineering at the California Institute of Technology (Caltech), where she concurrently holds leadership roles as Executive Officer for Electrical Engineering and Director of the Center for Sensing to Intelligence. Appointed to Caltech's faculty in 2007, she progressed from Assistant Professor to her current endowed professorship through demonstrated scholarly excellence. Her academic foundation includes: B.S. in Electrical Engineering from Sharif University of Technology (1996) M.S. in Electrical Engineering from Stanford University (1999) Ph.D. in Electrical Engineering from Stanford University (2004) Professor Emami pioneers mixed-mode integrated circuit systems that bridge theoretical innovation with practical applications. Her research emphasizes ultra-low power consumption and high reliability in scalable semiconductor technologies, targeting transformative solutions across multiple domains. Key thrusts include: Biomedical implantables for neural recording/stimulation and gastrointestinal monitoring Photonics-electronics co-design for energy-efficient optical interconnects Machine learning-enhanced signal processing for brain-computer interfaces Miniaturized magnetic sensors with unprecedented noise performance Her work consistently demonstrates how circuit-level innovations enable breakthrough capabilities in medical diagnostics and high-speed computing. Analysis of her 2021-2024 publications reveals a strategic convergence of biomedical sensing and intelligent signal processing . While maintaining strong contributions to optical interconnects (accounting for ~40% of recent output), her lab increasingly focuses on closed-loop medical systems where low-power analog neural networks interpret physiological signals. This evolution reflects growing NIH and industry interest in implantable/wearable health technologies, with her group leading in CMOS-based sensor miniaturization and energy efficiency. Her professional recognition includes: IEEE Solid-State Circuits Society Distinguished Lecturer appointment Mentorship excellence is evidenced by students receiving prestigious awards including the Jakob van Zyl Predoctoral Research Award (Saransh Sharma, Ryoto Sekine) and Charles Wilts Prize (Kuan-Chang Chen). Her research program leverages strategic partnerships with Heritage Medical Research Institute and industry collaborators, supported through center-based funding like the Center for Sensing to Intelligence. Administrative leadership spans departmental governance (as Executive Officer) and conference organization (ISSCC technical committees). She directs Caltech's Mixed-mode Integrated Circuits and Systems Lab (MICS) , which operates as a nexus for cross-disciplinary innovation between electrical engineering and medical applications. The lab's industry-collaborative framework accelerates translation of circuit concepts into real-world biomedical solutions through the Center for Sensing to Intelligence.
Dr. Lukas Frey is a Researcher at ETH Zurich, affiliated with the Chair of Physical Chemistry and the Institute of Molecular Physical Sciences (IMPS). His work focuses on biophysical studies of membrane proteins, lipid dynamics, and protein aggregation mechanisms. Key research areas include structural biology of ion channels, NMR spectroscopy of membrane proteins in nanodiscs, and the role of lipid environments in modulating protein dynamics. Frey employs advanced techniques like mass photometry and solid-state NMR to investigate molecular mechanisms in biological systems. His recent studies address amyloid fibril formation, pH-dependent α-synuclein polymorphism, and cholesterol-mediated modulation of membrane protein behavior. Based at the HCI F 228 facility in Zurich, Frey collaborates on projects involving lipid bilayer environments, ion channel function, and the structural basis of protein aggregation. His email is lukas.frey@phys.chem.ethz.ch, and he holds an ORCID identifier 0000-0002-1052-1104. Research contributions span from fundamental biophysical insights to methodological advancements in membrane protein analysis.
Dr. Kristin A. Persson is a Professor and Daniel M. Tellep Distinguished Professor in Engineering at the University of California, Berkeley's Department of Materials Science and Engineering. She leads the Persson Group at Lawrence Berkeley National Laboratory (LBNL), focusing on atomistic computational methods for energy materials. As director of the Materials Project, she pioneers high-throughput computing and data-driven approaches to accelerate material discovery for clean energy applications, including batteries, electrolytes, and photocatalysts. Her research spans lithium-ion and multivalent batteries, with a focus on electrolyte design, interfacial chemistry, and sustainable materials. Persson has directed the Materials Project since its inception, a global initiative to computationally predict material properties and provide open-access data. She holds affiliations with LBNL’s Energy Sciences Area and collaborates with industry and academia on projects like the Electrolyte Genome and piezoelectric materials databases. Key achievements include election to the National Academy of Engineering (2025), Royal Swedish Academy of Sciences (2024), and Fellowships from the AAAS (2022) and APS (2021). Her group’s work has produced over 200 publications, with recent highlights on disordered cathodes, ML-driven material predictions, and circular polymers. Persson advises a dynamic team of ~50 graduate students, postdocs, and staff, fostering interdisciplinary innovation in energy storage and materials informatics. Awards include DOE’s Distinguished Scientist Fellowship (2024), Cyril Stanley Smith Award (2022), and Web of Science Highly Cited Researcher recognition (2020). Her lab’s infrastructure supports projects from computational workflows to experimental collaborations, with a focus on translating theory into real-world energy solutions.
Masato Kato serves as Professor in the Department of Biochemistry at the University of Texas Southwestern Medical Center since 2020 and concurrently as Team Leader at Japan's National Institutes for Quantum and Radiological Science and Technology. His academic trajectory includes progressive appointments from Assistant Professor (2004-2014) to Associate Professor (2014-2020) at UT Southwestern, with prior postdoctoral training at Harvard Medical School and Nara Institute of Science and Technology. 2020-present: Professor, Department of Biochemistry, UT Southwestern 2020-present: Team Leader, National Institutes for Quantum and Radiological Science and Technology, Japan 2014-2020: Associate Professor, Department of Biochemistry, UT Southwestern 2010-2014: Assistant Professor, Department of Biochemistry and Internal Medicine, UT Southwestern 2004-2010: Assistant Professor, Department of Internal Medicine, UT Southwestern 1999-2004: Postdoctoral Fellow, Ellenberger Lab, Harvard Medical School 1998-1999: Postdoctoral Fellow, Hakoshima Lab, Nara Institute of Science and Technology Dr. Kato's research pioneers the biophysical characterization of protein phase separation, particularly focusing on low-complexity domains (LCDs) in neurodegenerative disease contexts. His work establishes fundamental mechanisms of biomolecular condensate formation, including hydrogel polymerization, liquid-solid transitions, and mutation-induced dysregulation in ALS/FTD. Key contributions demonstrate how C9orf72-encoded poly-dipeptides disrupt nucleocytoplasmic transport and how redox states regulate Ataxin-2 phase behavior, bridging structural biochemistry with pathological mechanisms. Analysis of his 22 publications reveals a cohesive research program centered on LCD-driven phase transitions. The most recent 15 articles (2012-2019) systematically investigate pathological aggregation in neurodegeneration, structural basis of condensate formation, and regulatory mechanisms like phosphorylation and oxidation. This body of work establishes LCDs as central players in both physiological RNA granule assembly and disease-associated solidification, with strong emphasis on C9orf72-related ALS/FTD mechanisms. Dr. Kato maintains active leadership within the McKnight Laboratory at UT Southwestern, where his team employs integrated approaches spanning structural biology, cell biology, and biophysics to dissect phase separation mechanisms. His collaborative network includes prominent neuroscience and biochemistry groups, with co-authorship on key studies in Cell, Science, and PNAS.
Arunima Singh is an Assistant Professor in the Department of Physics at Arizona State University (ASU), with graduate faculty status in the Materials Science and Engineering Department. Her work focuses on computational materials discovery, leveraging first-principics simulations and data science to accelerate the design of materials for energy applications. She leads research at the Computational Materials Design Lab and co-leads a thrust at ULTRA, a DOE-Energy Frontier Research Center, and has received the 2023 Department of Energy Early Career Research Program Award. Ph.D., Cornell University (2014) B.Tech., Indian Institute of Technology Kharagpur (2009) Her research bridges materials science , surface science , and renewable energy , with a strong emphasis on 2D materials , nanostructures , and machine learning for materials design. She also explores electronic properties at material interfaces and phonon behavior at grain boundaries. The 2025–2023 articles highlight her expertise in heterostructures , wide bandgap materials , and data-driven discovery , with recurring themes in solar energy conversion , nanoengineering , and first-principles simulations . These works often involve machine learning and high-throughput workflows for materials optimization. Scientific Awards 2023 Department of Energy (DOE) Early Career Research Program Award She teaches courses such as Quantum Theory of Solids I , University Physics I: Mechanics , and research/dissertation sections (PHY 792, MSE 792, etc.). Her service includes expertise in computational modeling , solar materials , and nanoscience .
