جستجوی استاد راهنمای دانشگاهی

Peichen Zhongمشاهده پروفایل

استادیار

• Materials Science
• Machine Learning
• Computational Modeling
• +۵ مورد دیگر

Dr. Peichen Zhong is an Assistant Professor in the Department of Materials Science and Engineering at the National University of Singapore (NUS). He leads the Applied Machine Learning and Materials Modeling (AM³) Group, focused on advancing computational methods for clean energy technologies. His research integrates machine learning with atomistic simulations to tackle challenges in battery materials, disordered materials, and sustainable energy systems. Education: B.S. in Physics from University of Science and Technology of China (2018); Ph.D. in Materials Science from UC Berkeley (2023, advised by Prof. Gerbrand Ceder); Postdoctoral training at Lawrence Berkeley National Lab and BIDMaP, co-advised by Persson, Cheng, and Krishnapriyan. Research Interests: Computational modeling of battery cathodes/electrolytes, AI-driven interatomic potentials, statistical mechanics in disordered materials, and generative models for scientific discovery. Key areas include Li/Na-ion batteries, solid-state reactions, and sustainable energy materials. Awards: BIDMaP Emerging Scholar Fellowship (UC Berkeley CDSS, 202?), 2023 Rising Stars in Materials Science (CMU/MIT/Stanford). Labs/Teams: The AM³ Group at NUS MSE focuses on interdisciplinary research combining theory, computation, and AI4Science. Current openings include PhD students and postdoctoral researchers.

Chris G. Van de Walleمشاهده پروفایل

استاد

• Computational Materials Science
• Semiconductors
• Nitride Materials
• +۷ مورد دیگر

Chris G. Van de Walle is the Herbert Kroemer Distinguished Professor in the Department of Materials at the University of California, Santa Barbara's College of Engineering. As a member of the National Academy of Engineering and fellow of multiple prestigious scientific societies including the American Physical Society and Materials Research Society, he leads the Computational Materials Group which is part of UCSB's strong computational science cluster within the Materials Department. His research interests focus on novel electronic materials, particularly wide-band-gap semiconductors (III-V nitrides, II-VI compounds), transparent conductors, complex oxides, loss mechanisms in light emitters, two-dimensional conductors, quantum information science, and the physics and chemistry of hydrogen interactions with solids. His group uses first-principles computational techniques to study atomic and electronic structure of crystalline, polycrystalline and amorphous materials, interfaces, surfaces, defects, and heterojunctions. Analysis of his recent publications reveals a strong focus on semiconductor materials for quantum technologies, with particular emphasis on GaN, Ga 2 O 3 , and related compounds. His work combines computational materials science with applications in optoelectronics, quantum information, and energy technologies, demonstrating consistent innovation in understanding defects and their role in material properties. Major Awards and Recognitions: Aneesur Rahman Prize for Computational Physics (APS) Materials Theory Award (MRS) Vannevar Bush Faculty Fellowship (DoD) John Bardeen Award (TMS) Medard W. Welch Award (AVS) Highly Cited Researcher (Clarivate Analytics) Professor Van de Walle has mentored numerous successful researchers, including Dr. Fangzhou Zhao (Corbett Prize winner) and Dr. Mark Turiansky (APS Nicholas Metropolis Award recipient). His group maintains strong connections with the UCSB Quantum Foundry and the Solid State Lighting and Energy Electronics Center, demonstrating collaborative research efforts across multiple disciplines. The group actively investigates defects for quantum information science, loss mechanisms in light emitters, nitride semiconductors, halide perovskites, oxides, and hydrogen interactions with materials.

Patrick Rinkeمشاهده پروفایل

استاد مدعو

• Theoretical Physics
• Material Science
• Computational Science
• +۱ مورد دیگر

Patrick Rinke serves as an Adjunct Professor in the Department of Applied Physics at Aalto University, Finland. His research bridges theoretical physics, materials science, and computational methodologies with a strong focus on machine learning applications. His computational work spans electronic structure theory, materials design, and atmospheric chemistry. Rinke's research integrates Bayesian optimization, active learning, and high-throughput computational screening to accelerate materials discovery, particularly in hybrid perovskites, catalysts, and biomaterials. Recent work demonstrates machine learning's transformative potential in predicting molecular properties, optimizing materials functionality, and solving complex physical chemistry problems. His scientific contributions have been recognized with multiple awards: Thesis Prize from the Institute of Physics (2003) DFG Research Scholarship (2007-2009) Outstanding Postdoctoral Achievement Award (2009) Outstanding Referee of Physical Review Letters (2014) August-Wilhelm Scheer Visiting Professorship (2017)

Kai Gongمشاهده پروفایل

استادیار

• Sustainable Infrastructure Materials
• Environmental Sustainability
• Materials Science
• +۴ مورد دیگر

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.

Adriana Bocchiniمشاهده پروفایل

پژوهشگر

• Theoretical Materials Physics
• Quantum Materials Modelling
• Computational Materials Science
• +۳ مورد دیگر

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.

Samir H. Mushrifمشاهده پروفایل

استاد

• Computational Catalysis
• Molecular Modeling
• Reaction Engineering
• +۷ مورد دیگر

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 .

Steven Hoekstraمشاهده پروفایل

دانشیار

• Atomic Physics
• Molecular Physics
• Stark Deceleration
• +۵ مورد دیگر

Prof. dr. Steven Hoekstra is an Associate Professor of Atomic and Molecular Physics at the University of Groningen's Faculty of Science and Engineering, within the Van Swinderen Institute. His research focuses on precision measurements using cold molecules to explore fundamental physics, including Stark deceleration, laser cooling, and searches for physics beyond the Standard Model. He leads the NL-eEDM program at Nikhef, investigating the electron's electric dipole moment. Hoekstra is also involved in educational innovation, having received the Teacher of the Year award (2020) and a Senior Teacher Qualification (2023). He has supervised over 11 PhD theses and currently mentors 5 students. His work combines experimental techniques with theoretical insights, addressing questions like symmetry violations and quantum dynamics. Key projects include manipulating BaF molecules with electrostatic fields and exploring levitated nanoparticles as sensors. Hoekstra has secured major grants, including NWO VICI (2022) and VIDI (2013), and collaborates internationally on projects like the European Strategy for particle physics. Recent articles highlight advancements in molecular beam control, spin-precession methods for EDM searches, and opportunities in radioactive molecules. He actively participates in the Physics Olympiad Netherlands as chair, contributing to science outreach and education.

Quek Su Yingمشاهده پروفایل

دانشیار

• Materials Science
• Condensed Matter Physics
• Theoretical Physics
• +۵ مورد دیگر

Associate Professor Quek Su Ying is affiliated with the Department of Physics at the National University of Singapore (NUS) and serves as Assistant Dean (Special Duties). Her research focuses on theoretical and computational approaches to understanding the electronic, vibrational, and transport properties of emerging materials, particularly 2D and organic systems. Affiliations : Institute of High Performance Computing, Centre for Advanced 2D Materials, NUS Research Interests : First principles calculations (mean field and many-electron perturbation theory), interface science, electronic energy level alignment, and transport in emerging materials. Her work includes studies of exciton condensation, quantum emitters, and valleytronic control via magnetic fields. Article Trends : Recent publications highlight investigations into 2D materials, organic-inorganic interfaces, and quantum phenomena. Topics include exciton dynamics, defect engineering, charge density waves, and spin-dependent transport, employing advanced ab initio methods like GW theory. Scientific Awards : Singapore NRF Fellowship Advising & Collaborations : Her group develops state-of-the-art computational methods and collaborates with experimental teams. Notable affiliations include Google Scholar Profile and partnerships with institutions like the Institute of High Performance Computing. Labs & Teams : Associated with the Centre for Advanced 2D Materials at NUS, which supports interdisciplinary research on graphene and related 2D systems. Her work bridges theoretical modeling and experimental validation.

Qingguo Liمشاهده پروفایل

استاد

• Biomechanical system design
• Energy harvesting
• Wearable sensors
• +۴ مورد دیگر

Qingguo Li is a Professor and Associate Head at the Department of Mechanical and Materials Engineering , Queen's University , and a member of the Ingenuity Labs Research Institute . He specializes in biomechanical system design, energy harvesting, wearable sensors, gait analysis, and load carriage systems. His research integrates robotics, biomedical engineering, and sensor technology to develop human-centric devices and mobility aids. Current Roles : Professor, Associate Head, Queen's University Research Institute : Ingenuity Labs Research Institute Lab : Bio-Mechatronics and Robotics Laboratory His work focuses on biomechanical energy harvesting , IMU-based motion analysis , and assistive device development . Key applications include stroke rehabilitation, gait monitoring, and wearable power generation systems. Articles span cable-driven robots , smart walkers , and 3D printing mechanisms , emphasizing human-robot interaction and dynamic modeling . The lab explores sensor calibration , adaptive control algorithms , and human movement optimization . Areas of impact include rehabilitation engineering , load carriage stability , wearable sensor accuracy , and assistive robotics . His team develops solutions for gait asymmetry detection , post-stroke mobility , and low-cost energy systems , leveraging machine learning and kinetic modeling .

Christopher M. Wolvertonمشاهده پروفایل

استاد

• Computational Materials Science
• Energy Storage Materials
• First-Principles Quantum Mechanics
• +۷ مورد دیگر

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.

Andrew S. Rosenمشاهده پروفایل

استادیار

• Energy and Environment
• Surface Science and Catalysis
• Theory and Computation
• +۵ مورد دیگر

Andrew S. Rosen is an Assistant Professor in the Department of Chemical and Biological Engineering at Princeton University, leading the Rosen Research Group since his appointment. He became an associated faculty member of the Princeton Plasma Physics Laboratory (PPPL) in June 2025, expanding his collaborative impact in energy research. His work focuses on computationally guided materials discovery to address urgent sustainability challenges beyond traditional trial-and-error approaches. Education Ph.D. in Chemical Engineering, Northwestern University (2021) B.S. in Chemical Engineering, Tufts University (2015) Research Focus Dr. Rosen integrates quantum-chemical calculations , high-throughput computing , and machine learning to design novel materials for energy storage, catalysis, and environmental applications. His group specializes in porous framework solids and molecular materials with tailored electronic properties, emphasizing synthesis pathways to bridge computational predictions with experimental realization. This research targets unprecedented materials for clean energy technologies through AI-enhanced quantum modeling. Research Support NSF grant awarded June 25, 2025 ScienceAtScale NERSC Award received June 10, 2025 Invited speaker at ASE CECAM Workshop (June 24, 2025) Group and Collaborations The Rosen Research Group leverages open-source software and big data initiatives like the Materials Project, maintaining strong ties with experimental teams to validate computational discoveries. Their work directly addresses climate challenges through materials innovation, with recent focus on electronic structure properties for catalytic applications.

Arunima Singhمشاهده پروفایل

استادیار

• Materials Science
• Computational Physics
• Surface Science
• +۷ مورد دیگر

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 .

Emilio Artachoمشاهده پروفایل

استاد

• Condensed Matter Physics
• Computational Physics
• Molecular Dynamics
• +۴ مورد دیگر

Professor Emilio Artacho is a faculty member in the Department of Physics at the University of Cambridge, based at the Cavendish Laboratory. He transitioned from the Department of Earth Sciences in 2011, where he was granted a Professorship in 2006. His research focuses on computational simulations of non-equilibrium processes in condensed matter, particularly using first-principles molecular dynamics and density-functional theory. He co-developed the SIESTA program for linear-scaling electronic structure calculations, widely utilized in computational materials science. Artacho’s work spans far-from-equilibrium phenomena in irradiated matter, multiferroics, nanoconfined water systems, and surface chemistry. His contributions include studies of electronic stopping power in materials, 2D electron gas formation at ferroelectric interfaces, and the structural dynamics of water under confinement. His academic roles include adjunct positions at Ikerbasque (Nanogune, Spain) and visiting professorships at institutions like the University of California, Berkeley, and École Normale Supérieure de Lyon. Research interests are anchored in theoretical condensed matter physics, with applications to nanomaterials, radiation effects, and interfacial phenomena. His computational methods bridge quantum mechanics and classical dynamics, enabling insights into complex systems like proton-irradiated solar cells and confined water films.

Ashis K. Patraمشاهده پروفایل

استاد

• Inorganic Chemistry
• Bioinorganic Chemistry
• Therapeutic Applications of Metal Complexes
• +۳ مورد دیگر

Ashis K. Patra is a full-time Professor in the Department of Chemistry at the Indian Institute of Technology Kanpur (IIT Kanpur). After obtaining his Ph.D. from the Indian Institute of Science (IISc) Bangalore in 2008, he carried out post-doctoral research at Harvard University and the University of Georgia before joining IIT Kanpur in 2012. Education & Academic Training Ph.D. (2008), Indian Institute of Science (IISc), Bangalore M.Sc. (2002), The University of Burdwan Research Interests Professor Patra leads an interdisciplinary program that sits at the interface of inorganic chemistry, chemical biology, and medicinal chemistry. His work is organized into three principal thrusts: Therapeutic Applications of Metal Complexes: Design and mechanistic evaluation of cytotoxic transition-metal complexes that target nucleic acids and proteins, aiming to overcome multidrug resistance in cancer. Nitric Oxide Delivery from Transition Metal Nitrosyls: Development of photo- and redox-triggered metal nitrosyl complexes for controlled NO release to biological targets such as hemoglobin, myoglobin, and glutathione. Luminescent Lanthanide Complexes: Synthesis and photophysical characterization of Eu(III) and Tb(III) complexes that serve as luminescent probes and theranostic agents. Research Output & Impact His group has published extensively in leading journals including Dalton Transactions , Inorganic Chemistry , Chemical Science , and Journal of Inorganic Biochemistry . The collective work demonstrates a clear trajectory from fundamental coordination chemistry to translational applications in drug delivery and bioimaging, with recurring themes of redox control, light activation, and biological targeting. Scientific Awards & Fellowships CSIR Junior & Senior Research Fellowships (2001, 2003) West Bengal SLET Qualification (2001) International Travel Grants from CSIR & INSA (2006) DST Fast-Track Fellowship for Young Scientists (2013) Erasmus Mundus NAMASTE Scholarship for Academic Staff (2014) JSPS Invitation Fellowship (2016) Teaching & Mentoring Professor Patra teaches core and advanced courses in inorganic chemistry, including Inorganic Chemistry Laboratory, Bioinorganic Chemistry, and Frontiers in Inorganic Chemistry. He actively mentors Ph.D. and master’s students (full list available on his lab website ) and has established the Laboratory of Inorganic Chemical Biology in the Old Core Lab complex at IIT Kanpur.

• Machine Learning
• Bioinformatics
• Deep Generative Models
• +۳ مورد دیگر

Anders Krogh is a Professor at the Department of Computer Science, University of Copenhagen, and also holds a position at the Department of Public Health in the Section for Health Data Science and AI. He serves as the head of the Center for Health Data Science (HeaDS) in the Faculty of Health and Medical Sciences. Previously, he was affiliated with the Department of Biology at the University of Copenhagen until 2020. Dr. Krogh earned his PhD in theoretical physics but transitioned into machine learning and bioinformatics during his doctoral studies. His research spans both theoretical foundations and practical applications in these fields. He is particularly renowned for his pioneering work on hidden Markov models for biological sequences, which has had significant impact in computational biology. In recent years, Krogh's research has focused on deep generative models applied to gene expression data and other biomedical applications. His work bridges computer science with healthcare, developing AI-driven approaches for precision medicine, cancer diagnostics, and analysis of complex biological systems. His current research integrates machine learning with quantum computing applications in biomolecular modeling. Analysis of his recent publications reveals a strong trend toward applying artificial intelligence to healthcare challenges, particularly in rare diseases, cancer diagnostics, and personalized medicine. His work increasingly incorporates federated learning approaches to address privacy concerns while enabling collaborative research across institutions. There's also a growing emphasis on quantum computing applications in biomolecular modeling and drug discovery. As head of the Center for Health Data Science, Krogh leads interdisciplinary research efforts that bring together computer scientists, medical researchers, and clinicians. His team develops novel computational frameworks like MOSAIC for multimodal analysis of rare cancers and multiDGD for multi-omics data integration. These tools are designed to translate AI innovations into clinical practice while addressing the unique challenges of medical data.