Dr. Kai Gong is an Assistant Professor of Civil and Environmental Engineering at Rice University, with affiliations at the Rice Advanced Materials Institute and Ken Kennedy Institute. His research focuses on sustainable infrastructure materials, environmental sustainability, and materials science. He holds a Ph.D. in Civil & Environmental Engineering and Materials Science from Princeton University, an MEngSci from Monash University (Australia), and dual B.S. degrees from Monash University and Central South University (China). Research Interests: Development of durable, sustainable infrastructure materials Waste encapsulation and conversion to value-added products Carbon mineralization and utilization Advanced characterization techniques (synchrotron/neutron scattering) Data-driven modeling and atomistic simulations Notable Awards: 2023 Le Chatelier Medal (Cement and Concrete Research) 2024 Giatec Award for Best Paper in Sustainability Walbridge Fund Graduate Award (2019) His work integrates computational methods (e.g., molecular dynamics) with experimental techniques to address decarbonization challenges in infrastructure. The Gong Research Group actively seeks motivated researchers for opportunities in sustainable materials innovation.
Suchi Saria is the John C. Malone Associate Professor at Johns Hopkins University , with appointments in the Whiting School of Engineering (Computer Science), the Bloomberg School of Public Health (Health Policy & Management), and the Whiting School (Applied Math & Statistics). She directs the Machine Learning and Healthcare Lab and co-founded the Bayesian Health startup. Education: PhD in Computer Science from Stanford University (advisor: Daphne Koller), NSF Computing Innovation Fellowship at Harvard (2011), prior research at UMass (Barto, Madhavan), and industry experience at Aster Data Systems (acquired by Teradata). Research Focus: Saria develops statistical machine learning tools to extract insights from heterogeneous clinical data (structured/unstructured EHRs, sensor streams). Her work enables counterfactual reasoning for personalized treatment plans, dataset shift mitigation in healthcare AI, and weak supervision frameworks for mobile health apps. Key applications include sepsis prediction , Parkinson’s symptom tracking , and critical care optimization . Article Trends: Recent publications emphasize AI safety (2024-2025), addressing racial bias , transparency frameworks , and dynamic monitoring for clinical deployments. Her work spans conformal prediction , causal modeling , and policy guidelines for health AI. Scientific Awards: Sloan Research Fellowship (2018) DARPA Young Faculty Award (2016) MIT Technology Review TR35 Innovator (2017) Popular Science Brilliant 10 (2016) IEEE Intelligent Systems AI’s 10 to Watch (2015) NSF Computing Innovation Fellowship (2011) Rambus Fellowship (2004-2010) Best Paper Awards in ML, Informatics, and Medicine venues Advising & Grants: Saria mentors PhD students/postdocs in machine learning and health informatics , including funded projects like the NSF Smart and Connected Health Grant (2014) and Google Research Award (2014). Her lab’s TREWScore system (Science Translational Medicine 2015) is deployed in hospitals, while her Bayesian Health startup commercializes AI solutions for provider experience.
Prof. Dr. Taner Akbay is a faculty member at Yeditepe University, Faculty of Engineering , Department of Materials Science and Nanotechnology Engineering. He has held academic positions at institutions including Kyushu University, Oita University, and Imperial College London. Education: PhD in Materials Engineering (1993, Imperial College London); Master’s (1989) and Bachelor’s (1986) degrees from Middle East Technical University. His research spans Materials Engineering , Metallurgy , and Solid Oxide Fuel Cells (SOFCs) , with a focus on oxide ion conductivity, laser surface treatment, and phase transformations. Recent work explores photocatalysis , anion intercalation , and CO2 reduction using computational and experimental approaches. Key article trends include SOFC optimization (2004–2009), strain effects on catalysts (2015–2020), and dual-carbon battery technology (2016–2020). His work bridges fundamental metallurgy and advanced energy materials . Scientific Awards: Postdoctoral Research Sponsorship Award (EPSRC, UK) JSPS Fellowship (Japan) Daiwa Adrian Prize (2016, UK) PhD Studentship at Imperial College (European Commission) He has supervised multiple PhD and Master’s theses, including projects on dual-carbon batteries , microwave absorption nanocomposites , and rare earth recovery . Administrative roles include Head of Department (2020–2021). Non-University Experience: Worked with Mitsubishi Materials Corporation (2001), Çolakoğlu Metalurji (2010), and National Research Council Canada (2009).
Yan Liu is a full professor in the Thomas Lord Department of Computer Science at the University of Southern California (USC), serving as Director of the USC Machine Learning Center within the Viterbi School of Engineering. He holds courtesy appointments in the Ming Hsieh Department of Electrical Engineering and the Quantitative and Computational Biology Department. Before joining USC in 2010, he was a research staff member at IBM's T.J. Watson Research Center. He earned his M.S. and Ph.D. from Carnegie Mellon University. His research focuses on machine learning for time series, physics-informed AI, and interpretable models, with applications in healthcare, sustainability, and social media. Notable projects include developing AI for surgical training, analyzing misinformation on social platforms, and predicting cancer treatment outcomes. He has held leadership roles in top conferences like ICLR and ACM KDD, and serves as Associate Editor-in-Chief of TPAMI and Board Member of ICLR. Education: Ph.D., Carnegie Mellon University Affiliations: USC Machine Learning Center, Viterbi School of Engineering Service: General Chair (ICLR 2023, ACM KDD 2020), Program Chair roles across multiple conferences His lab, the Melady Group, emphasizes foundational ML advancements and interdisciplinary applications. Recent work includes physics-aware neural networks and time-series foundation models.
Professor Jasper van Wezel is a distinguished academic in the field of Condensed Matter Theory at the University of Amsterdam's Faculty of Science, where he serves as Professor in the Institute for Theoretical Physics (ITFA) within the Institute of Physics. With a career spanning over two decades, he has progressed from Assistant Professor (2014-2016) to Associate Professor (2016-2024) and currently holds the position of Professor since 2024. His academic journey began with a PhD in theoretical condensed matter physics from Leiden University in 2007, followed by prestigious fellowships at Argonne National Laboratory and Homerton College, Cambridge. PhD in theoretical condensed matter physics (cum laude), Leiden University, 2007 Master's diploma in theoretical condensed matter physics (cum laude), Leiden University, 2003 Dutch VWO Diploma (cum laude), Dalton Scholengemeenschap, Den Haag, 1997 US High School Diploma (cum laude), Sanford High School, Maine, USA, 1998 Professor van Wezel's research focuses on several interconnected areas within Condensed Matter Theory. His work explores competing instabilities in Charge Density Wave materials, including Superconductivity and Charge Order, Combined Charge and Orbital Order, and Transition-metal dichalcogenides. He has made significant contributions to Topology in Condensed Matter, particularly examining the Role of crystal symmetries and Topology in non-Hermitian systems. A major theme in his research involves investigating the Connections between Quantum and Classical behaviour, with special emphasis on Spontaneous Symmetry Breaking both in equilibrium (The role of the Thin Spectrum) and dynamically (Spontaneous loss of Unitarity). Analysis of Professor van Wezel's recent publications reveals a strong focus on quantum phenomena in condensed matter systems, with particular attention to topological aspects, symmetry breaking, and connections to fundamental physics concepts like black hole thermodynamics. His work often bridges theoretical concepts with potential experimental realizations, as evidenced by studies on electron patterns in materials like TaS2 and theoretical frameworks for understanding quantum phase transitions. Bristol Physics Teaching Award (2014) Students' Award for Outstanding Teaching (2014) Fellow of the Higher Education Academy (2014) Aneesur Rahman Fellowship at Argonne National Laboratory (2010-2012) Junior Research Fellowship at Homerton College, Cambridge (2007-2010) Physics 'Discovery of the year' by Leiden University Physics department (2005) 'Onderwijsprijs Natuurkunde' teaching award (2004/2005) Professor van Wezel has secured numerous research grants including an ENW-M grant (2023), an ENW-Groot project with Leiden University (2021), and a prestigious VIDI personal grant from NWO (2014). He has supervised over 50 students at various levels, including PhD candidates, MSc students, and BSc students, fostering the next generation of physicists. His leadership extends to organizing conferences, serving on PhD committees, and holding administrative roles such as chair of the educational committee for the Dutch Research School in Theoretical Physics. His research group at the University of Amsterdam's Institute for Theoretical Physics maintains active collaborations with institutions worldwide, including Leiden University, University of Cambridge, University of Bristol, and research centers in France, Germany, and Poland. The group's work combines analytical theoretical approaches with computational methods to tackle fundamental questions in quantum condensed matter physics.
Josie Hughes is a Tenure Track Assistant Professor at the Swiss Federal Institute of Technology Lausanne (EPFL) within the School of Engineering's Institute of Mechanical Engineering. She leads the Computer Robot Design and Fabrication Laboratory (CREATE Lab) and serves on the doctoral program committee for Robotics, Control and Intelligent Systems. Her roles include teaching courses in product development, engineering design, and data-driven manufacturing methods while maintaining active research and student supervision. Her research centers on soft robotics with emphasis on adaptive design, fabrication techniques, and real-world applications. Key areas include agricultural robotics (exemplified by the GraspBerry raspberry harvester), biomimetic materials like self-healing e-skins, and developmental robotics (BabyBot project). She pioneers approaches integrating morphological computation, variable stiffness mechanisms, and machine learning for robotic control, while championing open-source principles and diversity in robotics through accessible educational initiatives like balloon robot kits. Analysis of her recent publications reveals dominant trends in soft robotics adaptability, particularly in variable-stiffness structures, sensor integration, and task-specific optimization. Her work bridges fundamental material science with practical applications in agriculture, food science, and human-robot interaction, frequently employing computational methods like Bayesian optimization and neural networks for design and control. Scientific awards: No specific awards were mentioned in the source materials. Dr. Hughes actively supervises 16 doctoral students across diverse projects including soft grippers for agriculture, biomimetic locomotion, and robotic manipulation systems. Her advising portfolio shows strong alignment with her research themes, with current students working on topics like modular soft arms, agricultural automation, and developmental robotics. While grant details weren't specified, her high publication volume indicates robust research funding. The CREATE Lab under her leadership focuses on holistic co-design of hardware and software for soft robotic systems, with notable projects including the GraspBerry agricultural harvester and BabyBot developmental platform. The lab emphasizes open-source development and educational outreach, maintaining strong industry and academic collaborations while pushing boundaries in reconfigurable robotics and human-centered applications.
David S. Eisenberg is a Professor of Chemistry and Biochemistry and Biological Chemistry at the University of California, Los Angeles, where he also serves as Director of the UCLA-DOE Institute for Genomics and Proteomics and as an HHMI Investigator. His research focuses on protein interactions, particularly the structural basis for conversion of normal proteins to the amyloid state and conversion of prions to the infectious state. Dr. Eisenberg earned his undergraduate degree in biochemical sciences from Harvard College and his D.Phil. degree in theoretical chemistry from Oxford University on a Rhodes Scholarship. His postdoctoral research was on ice and water with Walter Kauzmann at Princeton and in protein crystallography with Richard Dickerson. He joined the UCLA faculty after his postdoctoral studies. Dr. Eisenberg and his research group focus on protein interactions in amyloid and prion diseases. These diseases involve protein aggregation where normal functional proteins convert to abnormal aggregated forms. Systemic amyloid diseases like dialysis-related amyloidosis result from fiber accumulation until organ failure, while neurodegenerative diseases like Alzheimer's, Parkinson's, ALS, and prion conditions appear to be caused by smaller oligomers. In 2005, his team determined the atomic-level structure for the amyloid fiber spine, revealing a 'steric zipper' of two parallel beta sheets packed across a dry interface. Since then, they've determined approximately 90 amyloid spines from 15 disease-related proteins. In 2010, they identified the structure of a toxic amyloid-related oligomer consisting of six anti-parallel beta strands forming a cylindrical barrel. His recent publications demonstrate continued innovation in amyloid research, with focus areas including structural prediction of amyloid formation, mechanisms of tau fibril disassembly in Alzheimer's disease, cryo-EM analysis of amyloid polymorphism, and structure-based design of inhibitors for amyloid toxicity. His work integrates computational, structural, and biochemical approaches to understand protein aggregation across multiple disease contexts. Dr. Eisenberg has received numerous prestigious awards and honors: National Academy of Sciences Member American Philosophical Society Member Institute of Medicine Member Howard Hughes Medical Institute Investigator Biophysical Society Emily M. Gray Award Harvard Westheimer Medal UCLA Seaborg Medal Technion - Israel Institute of Technology Harvey Prize in Human Health As Director of the UCLA-DOE Institute for Genomics and Proteomics and an HHMI Investigator, Dr. Eisenberg leads significant research initiatives in protein structure and aggregation. His laboratory combines X-ray crystallography, bioinformatics, and biochemical techniques to investigate protein interactions, with particular emphasis on amyloid-forming proteins and their role in disease. The Eisenberg Lab, located in Boyer Hall at UCLA, maintains an active research program investigating the structural basis of protein aggregation. The lab continues to build on its landmark discoveries of amyloid structures while exploring new frontiers in understanding protein misfolding diseases and developing potential therapeutic interventions.
Judith Driscoll is Professor of Materials Science at the University of Cambridge in the Department of Materials Science & Metallurgy. She holds the prestigious Royal Academy of Engineering Chair in Emerging Technologies and serves as a Visiting Staff Member at Los Alamos National Laboratory. As the founding Editor-in-Chief of APL Materials, she has significantly contributed to the materials science community. Dr. Driscoll's research focuses on Energy Efficient Oxide Materials for Information and Communications Technologies and energy devices. Her work spans the development of non-volatile memory, resistive switching devices, and ferroelectric materials for neuromorphic computing applications. She investigates oxide thin films for applications ranging from data storage to energy generation and conversion, with particular emphasis on creating more energy-efficient device technologies to handle the exponential growth of data-centric applications. Her recent publications demonstrate strong trends in developing novel oxide-based memory devices with improved energy efficiency, particularly for AI applications. The work shows significant progress in hafnium-zirconium oxide ferroelectrics, resistive switching mechanisms, and vertically aligned nanocomposite structures for enhanced device performance. These innovations address critical challenges in reducing the unsustainable energy demands of modern computing, particularly for artificial intelligence systems. Fellow of the Royal Academy of Engineering Fellow of the Materials Research Society Fellow of the American Physical Society Fellow of IOM3, IOP, and Women Engineers Society Fellow of the American Academy of Arts and Sciences Recipient of ERC Advanced Grant Editor-in-Chief of APL Materials Dr. Driscoll leads a vibrant research group that has secured significant funding including her Royal Academy of Engineering Research Chair, an ERC Advanced Grant, and an ECCS-EPSRC grant in collaboration with researchers from the USA. She has founded the Cambridge Centre for Neuromorphic Computing (Neucam) in 2023. Her group operates world-leading growth equipment including pulsed laser deposition with RHEED control, high temperature oxide sputtering, and spatial ALD systems. She collaborates extensively across the University of Cambridge and with international partners to solve complex materials challenges, with her group's role often being to identify optimal materials for functional goals, predict fabrication methods, and then create and characterize these materials.
Dr. Adriana Bocchini is a Researcher at the University of Paderborn , affiliated with the Theoretical Materials Physics department and the Quantum Materials Modelling group. Her work focuses on computational modeling of materials, particularly crystal defects, surface adsorption, and electrochemical properties using advanced theoretical methods. Research Interests: Adriana's research spans Theoretical Materials Physics and Quantum Materials Modelling , with a focus on Defect modeling in ferroelectric materials Surface adsorption mechanisms Electronic structure calculations First-principles simulations Recent Publications: She has contributed to studies on radiation-induced defects in KTiOPO 4 , Mg doping effects in lithium niobate, phosphonic acid interactions with bismuth oxide, and electrochemical properties of doped RTP crystals, all leveraging computational approaches like Density Functional Theory (DFT). Labs & Teams: Adriana is actively involved in the Theoretical Materials Physics and Quantum Materials Modelling groups at the University of Paderborn, advancing computational studies in materials science.
Prof. Dr. Frank Pollmann is a Full Professor (W3) at the Department of Physics PH-I, Technical University of Munich (TUM), leading the Chair of Theoretical Solid-State Physics since 2022. His research focuses on condensed matter theory and quantum information concepts , particularly in systems of correlated electrons and quantum many-body dynamics . PhD: Max Planck Institute for the Physics of Complex Systems / TU Ilmenau (2006) Postdoc: UC Berkeley (2008-2010) Group Leader: MPIPKS Dresden (2011-2016) Associate Professor: TUM (2017-2022) His work spans topological phases , frustrated spin systems , and non-equilibrium quantum dynamics , utilizing tensor network methods and quantum information theory to study phenomena like many-body localization and Hilbert space fragmentation . His publications demonstrate trends in quantum scar states , Kardar-Parisi-Zhang hydrodynamics , and quantum transport anomalies . Scientific Awards : ERC Consolidator Grant (2017) Walter Schottky Prize (2015) Otto-Hahn Medal (2007) He teaches courses including Advanced Methods in Quantum Many-Body Theory , Solid State Theory , and Topology in Condensed Matter , while leading the Pollmann Group under the TUM School of Natural Sciences.
Ralph H. Colby serves as Professor of Materials Science and Engineering and Chemical Engineering at Pennsylvania State University's College of Earth and Mineral Sciences, holding the Corning Faculty Fellowship. His research focuses on molecular-level dynamics in complex fluids, particularly polymers, ionomers, and liquid crystalline systems. With over 130 publications and authorship of the textbook Polymer Physics (2003), he directs an active research program examining structure-property relationships in soft matter. B.S. in Materials Science and Engineering, Cornell University (1979) M.S. in Chemical Engineering, Northwestern University (1983) Ph.D. in Chemical Engineering, Northwestern University (1985) Professor Colby's research spans polymer physics, rheology, and materials for energy applications. His group employs mechanical rheology, dielectric spectroscopy, and scattering techniques to investigate ion transport in single-ion conductors for batteries, dynamics of glass-forming liquids, and self-assembly in polyelectrolyte systems. Current work emphasizes structure-property relationships in ionomers, liquid crystalline polymers, and branched architectures. Analysis of recent publications reveals consistent focus on ionomer membranes for energy applications, processing-structure relationships in advanced polymers, and fundamental dynamics of complex fluids. Key trends include increasing integration of computational modeling with experimental characterization, expansion into sustainable materials processing, and growing emphasis on applications in battery technology and biomedical materials. Penn State Faculty Scholar Medal for Outstanding Achievement (2022) Bingham Medal, Society of Rheology (2012) American Chemical Society Fellowship Corning Faculty Fellowship in Materials Science and Engineering Professor Colby leads multiple federally funded projects including NSF's 'Fundamental Studies of Flow-Induced Polymer Crystallization' and DOE's 'Conduction mechanisms and structure of ionomeric single-ion conductors'. His group maintains strong industry partnerships with Corning Incorporated and participates in interdisciplinary initiatives like the Penn State Intercollege Graduate Degree Program in Materials Science and Engineering. Current research includes collaborations on breast cancer adherence interventions in Rwanda and conjugated polymer development for flexible electronics. The Colby Research Group operates specialized facilities for rheological characterization, dielectric spectroscopy, and X-ray scattering at Penn State's Materials Research Institute. The team maintains active collaborations with national laboratories and international research groups, focusing on translating fundamental polymer physics discoveries into practical applications for energy storage and advanced manufacturing.
Dr. Samir H. Mushrif is a Professor in the Department of Chemical and Materials Engineering at the University of Alberta . Prior to this role, he served as faculty at the School of Chemical and Biomedical Engineering at Nanyang Technological University (NTU), Singapore . He holds a PhD in Chemical Engineering from McGill University and completed postdoctoral research at the University of Delaware, USA . Education : PhD (Chemical Engineering, McGill University), Postdoc (University of Delaware) His research focuses on computational catalysis , molecular modeling , and reaction engineering for biomass conversion and CO2 reduction . He develops novel catalysts, solvents, and reactor systems using integrated quantum mechanical and classical molecular simulations , synergized with experimental data to enable sustainable energy and chemical production . Recent publications highlight trends in condensed phase chemistry for biomass reactions, machine learning applications in solvent configuration prediction, and mechanistic studies of lignin-carbohydrate complex deconstruction. His work bridges methane activation on metal oxides, hydrodeoxygenation of bio-oil compounds, and polymerization pathways in lignin structures. Scientific Awards include: NSERC Doctoral and Post-doctoral Fellowships Discovery International Award 2017 (Australian Research Council) NANYANG EDUCATION AWARD 2016 (Singapore) SCBE Teaching Excellence Awards (Silver 2015, Gold 2016) Bharat Gaurav (Pride of India) Award 2014 Dr. Mushrif's NSERC Discovery Grant (2018), CFI John R. Evans Leaders Fund Grant (2022), and AcRF Tier-2 Grant (Singapore, 2015) have advanced his work. Current PhD and Master's students include José Carlos Velasco Calderón , Arul Mozhi Devan Padmanathan , and Sagar Bathla , among others. The CARES Lab (Catalysis Research for Sustainability) under his leadership combines ab initio molecular dynamics , machine learning potentials , and Density Functional Theory to design materials for renewable energy . Collaborations span institutions in France , Canada , India , and the UK .
Morteza Fayazi is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Utah, with an adjunct position in the Kahlert School of Computing. His research focuses on Electronic Design Automation (EDA), applying machine learning to automate analog and mixed-signal circuit design, and developing high-performance computing systems. He holds a B.Sc. from Sharif University of Technology, and M.S.E./Ph.D. degrees from the University of Michigan. His research interests include AI-driven EDA, RF/circuit automation, and energy-efficient processors. Key achievements include the MEDAL lab’s work on terahertz radars, systolic-array processors (e.g., DAP and Versa), and open-source frameworks like FASCINET and Tablext. He has received awards such as the 2024 College of Engineering Dean’s ETR Fund and the 2017 Outstanding Undergraduate Thesis Award. Teaching responsibilities include multiple iterations of the Digital System Design course (ECE/CS 3700). His work spans over 15 peer-reviewed articles in IEEE Transactions, ACM, and top conferences like ICCAD and VLSI-SOC, emphasizing automation, efficiency, and AI integration in hardware design.
Elison Matioli is a Professor at the Institute of Electrical Engineering (STI) at EPFL and director of the POWERlab. He holds a B.Sc. in Applied Physics and Applied Mathematics from Ecole Polytechnique (France), a B.Sc. in Electrical Engineering from the University of São Paulo (Brazil), and a Ph.D. in Materials Science from the University of California, Santa Barbara. His postdoctoral research at MIT focused on electrical engineering and computer science. His research centers on advanced semiconductor devices, particularly GaN-based power electronics, microfluidic cooling systems, and nanotechnology innovations for high-power applications. Key areas include developing high-efficiency GaN transistors, optimizing power conversion systems, and exploring terahertz generation through nanoplasma switches. His work emphasizes integrating novel materials (e.g., diamond, LiNiO) and cooling solutions to enhance device performance and reliability. Publications highlight breakthroughs in GaN power devices, microfluidic integration for thermal management, and ultrafast switching technologies. His contributions span device physics, fabrication techniques, and energy-efficient systems, with applications in next-generation power electronics and renewable energy infrastructure.
Meng Cheng is an Assistant Professor of Physics at Yale University, specializing in condensed matter theory. He holds a B.S. from Nanjing University (2008) and a Ph.D. in Condensed Matter Theory from the University of Maryland (2013). After a postdoctoral position at Microsoft Research Station Q (2013–2016), he joined Yale in 2017. His research focuses on quantum criticality, fractonic phases, and symmetric topological phases, with a particular emphasis on classification and characterization of exotic quantum matter. He has received prestigious awards including the NSF CAREER Award (2019) and the Alfred P. Sloan Fellowship (2019). Key research interests include topological superconductivity, global symmetry interactions, and applications in quantum information. His work bridges theoretical frameworks with experimental implications, exploring topics like Wilson loop operators, disorder operators, and entanglement entropy in gapless systems. He has contributed to advancements in understanding symmetry-enriched topological phases and their surface topological order. Publications span high-impact journals and cover topics such as fractionalization in electronic insulators, quantum Hall effects, and topological stabilizer models. His talks highlight interdisciplinary approaches, including seminars at the Perimeter Institute and Université de Montréal on fractonic topological phases and infinite-component Chern-Simons theories. Awards and grants underscore his contributions to advancing theoretical physics, with a focus on fostering innovation in quantum materials and computational methods. Teaching and mentorship activities further his commitment to education within the Yale Physics Department.
