Find Academic Supervisors

Ewa LugerView profile

Professor

• Responsible AI
• Human-Data Interaction
• AI Ethics
• +7 more

Professor Ewa Luger serves as Professor and Chair of Human-Data Interaction at the University of Edinburgh, co-Programme Director of AHRC’s Bridging Responsible AI Divides (BRAID), and codirector of the EPSRC Responsible NLP Centre for Doctoral Training. She actively bridges academia, policy, and industry through roles in the DCMS college of experts and Centre for Artificial Intelligence (Future of Privacy Forum). Her educational background spans: BA (Hons) in International Relations & Politics MA in International Relations PhD in Computer Science Luger’s research investigates social, ethical, and interactional dimensions of AI systems, with emphasis on policy design, user consent, and exclusion frameworks. She pioneers work on responsible AI implementation across critical domains including voice interfaces, journalism, public service media, and accounting institutions. Her specific research trajectories include: Responsible AI governance and ethical deployment Human-Data Interaction paradigms Intelligibility of AI for expert/non-expert users Security/safety of cloud/edge systems AI adoption readiness in professional contexts Language model applications in real-world settings Her scholarly recognition includes: Alan Turing Institute Fellowship Fellowship at Corpus Christi College, University of Cambridge Luger has secured over £40 million in research funding since 2016 through EPSRC, ESRC, AHRC, and DataLab grants. Current leadership roles span the AHRC BRAID programme, EPSRC Fixing the Future project, UKRI Digital Twinning Network, and Responsible NLP CDT. She founded the annual 'Conversations' workshop on chatbot research in 2015, fostering global academic-industry collaboration. Her interdisciplinary work operates through dynamic project teams including the Network Plus in Human Data Interaction, DCODE EU consortium, and BBC-focused PubVIA initiative, integrating computer science, social sciences, and humanities perspectives to address AI’s societal challenges.

Thomas HermannView profile

Researcher

• Auditory Data Science
• Interactive Sonification
• Smart Environments
• +5 more

Dr. rer. nat. Thomas Hermann is a faculty member at Bielefeld University's Faculty of Engineering, leading the Ambient Intelligence Group and coordinating the Computer Science program. He specializes in sonification, auditory data science, and smart environments. Head of Ambient Intelligence Working Group Computer Science Program Coordinator Member of multiple academic advisory boards His research focuses on interactive sonification for biomedical applications, quantum systems, and smart environments. Key projects include ECG sonification for cardiac diagnosis, real-time auditory feedback in swimming, and sonic interfaces for AR cooperation. Recent publications span 2025 with Python-based sonification tools ( pya AGen ), quantum system sonification, and ST-elevation myocardial infarction monitoring. He contributes to open-access supplementary materials and interdisciplinary workshops. As a researcher , Hermann develops practical sonification frameworks like Panson for facial behavior analysis, CardioScope for portable ECG monitoring, and Base Cube One for smart environments. His work bridges academic research with industry applications.

AnHai DoanView profile

Professor

• Data Integration
• Entity Matching
• Data Cleaning
• +4 more

AnHai Doan is the Vilas Distinguished Achievement Professor and Gurindar S. Sohi Professor in the Department of Computer Science at the University of Wisconsin-Madison. His research focuses on data integration, entity matching, and data science, with particular emphasis on building end-to-end systems that leverage machine learning, scalable data management, and human-data interaction. He leads the Magellan project, which develops open-source tools for entity matching as part of the Python data ecosystem. Dr. Doan's research interests include: Data cleaning and integration: Building end-to-end data integration systems as parts of the Python ecosystem of open-source data tools Data science: Developing an agenda that integrates research, system building, education, and outreach, with focus on data quality Crowdsourcing: Pioneering work on using crowdsourcing for data management and integration Knowledge bases: Building community-centric knowledge bases His recent work shows a strong trend toward developing practical systems for data integration that combine machine learning with traditional database techniques. The Magellan project represents a comprehensive effort to build an end-to-end entity matching system, with numerous publications spanning entity matching algorithms, debugging tools, and cloud-based matching services. His research increasingly focuses on the intersection of data science and data management, particularly on data quality issues. Selected scientific awards: Gurindar S. Sohi Professorship (2020) Vilas Distinguished Achievement Professorship (2018) SIGMOD Research Highlight Award (2017) Vilas Associate, UW-Madison (2016) Alfred P. Sloan Research Fellowship (2007) NSF CAREER Award (2004) ACM Doctoral Dissertation Award (2003) Dr. Doan has been actively involved in service to the data management community, including serving on the SIGMOD Advisory Board, as associate editor for VLDB, and co-chairing the industrial program for VLDB. He has also played a key role in strategic initiatives at UW-Madison, including helping to establish the School of Computer, Data, and Information Sciences. He has mentored numerous students and researchers through his work on the Magellan project and related research efforts. Additionally, he co-founded GreenBay Technologies to commercialize Magellan, which was later acquired by Informatica. He leads the Database Group at UW-Madison and has been instrumental in developing data science educational programs at both undergraduate and graduate levels. His work bridges research, education, and practical applications in the rapidly evolving field of data management and data science.

Anja LiekfeldView profile

Adjunct Professor

• Ophthalmology
• Optical Device Technology
• Refractive Surgery
• +3 more

Anja Liekfeld serves as Adjunct Professor of Ophthalmic Optics/Optical Device Technology at Brandenburg University of Technology since 2018 while concurrently holding the position of Chief Physician at Klinikum Ernst von Bergmann's Department of Ophthalmology in Potsdam since 2009. Her dual roles bridge academic research in optical engineering with clinical ophthalmology practice, focusing on technological advancements for eye care delivery. Her educational foundation includes medical studies at Essen and Berlin Universities (1986-1992), state examination (1992), ophthalmology residency at Charité (1994-1997), specialist certification (1997), doctoral degree magna cum laude (1997), and habilitation on capsular bag models for cataract research (2007). Liekfeld's research centers on optical properties of intraocular lenses, clinical applications of medical devices in ophthalmology, refractive surgery techniques (laser and IOLs), cataract surgery technologies, glaucoma diagnostics/therapy, and gerontological ophthalmology. Her work emphasizes translating engineering principles into clinical solutions for complex vision correction challenges. Over 25 years of publications reveal evolving expertise from molecular glaucoma research to advanced IOL development. Recent work focuses on multifocal/toric lenses, dysphotopsia analysis, and visual outcomes measurement, demonstrating consistent innovation at the optics-clinical interface with practical applications for patient care. Her accolades include: DOG/SFO Travel Grant (2000) DGII Best Presentation Award (2008) DOC Gold Medal (2011) Focus Magazine Top Doctor (2013-2021) Stern Magazine Top Doctor (2022) As an educator, she trains surgical assistants, diet technicians, and operating room staff while teaching ophthalmology to visually impaired pedagogy students at Humboldt University. She conducts international wet labs for surgeons and optometrists, serves on editorial boards for Concept and Karger Kompass Ophthalmologie, and reviews for major ophthalmology journals. Active in professional societies including DGII, ESCRS, DOG, BBAG, and BDOC, she chairs Brandenburg's Ophthalmology Examination Board since 2021 and serves on the board of Die Augenchirurginnen e.V. Her research utilizes human capsular bag models for cataract studies and maintains focus on improving optical device performance in clinical settings.

Xiaoqing PanView profile

Professor

• Materials Science
• Electron Microscopy
• Atomic-scale Characterization
• +6 more

Xiaoqing Pan is a Professor and Henry Samueli Endowed Chair in Engineering at the University of California, Irvine, with dual appointments in the Department of Materials Science and Engineering and the Department of Physics and Astronomy. He serves as Director of the Irvine Materials Research Institute (IMRI) and the Center for Complex and Active Materials (NSF MRSEC). A renowned electron microscopy expert, Pan has developed advanced transmission electron microscopy (TEM) techniques for atomic-scale material characterization. Ph.D., Universität des Saarlandes, Germany (1991) His research focuses on atomic-scale structure-property relationships in oxide heterostructures, ferroelectrics, nanocatalysts, and 2D functional materials. Pan leads development of novel 4D-STEM and momentum-resolved vibrational electron microscopy methods to study single-atom catalysts and complex oxides. With over 400 high-impact publications in Nature , Science , and Nature Materials , his work has been recognized by major fellowships and awards from the American Ceramic Society, American Physical Society, and National Science Foundation. Pan's recent work includes: Atomic-scale analysis of grain boundary phonon anisotropy Advances in FeSe/SrTiO 3 interface electron-phonon coupling Plastic waste upcycling through carbon intermediate interception Control of metal-support interactions in photocatalysts Strain engineering in high-entropy oxide films His laboratory at UCI represents the forefront of materials characterization technology development.

Rachel PottingerView profile

Professor

• Data Management
• Database Systems
• Data Integration
• +7 more

Rachel Pottinger is a Professor in the Department of Computer Science at the University of British Columbia within the Faculty of Science. She has been at UBC since 2004, progressing from Assistant Professor to Associate Professor in 2012 and to full Professor in 2021. She is affiliated with research centers including CAIDA (Centre for Artificial Intelligence Decision-making and Action) and DFP (Designing for People), and is part of ICICS (Institute for Computing, Information and Cognitive Systems). Her research focuses on data management, particularly semantic data integration, metadata management, and making data more accessible and understandable to users. She leads the Data Management and Mining Lab and has supervised numerous doctoral and master's students. Her work addresses three main areas: helping people understand and explore their data, managing data not well supported by databases, and coordinating data across multiple databases. Her recent publications demonstrate strong trends in database usability, data provenance visualization, query recommendation systems, and building information modeling integration. Her work bridges theoretical database concepts with practical human-centered applications, particularly in making complex data systems more accessible to non-expert users. UBC Computer Science Department Faculty Teaching Award 2013 Computer Science Department Teaching Award 2010 CS Department Teaching Award Denice Denton Emerging Leader Award 2007 Pottinger has supervised numerous PhD and Master's students, with research focusing on data provenance, database usability, and data coordination. She has been involved in significant research projects related to data lakes, open data navigation, and query recommendation systems. Her current research explores table annotation and discovery in data lakes, query refinement for aggregation queries, and query prediction based on past user behavior. She is actively involved in the academic community, serving as Secretary-Treasurer for SIGMOD, on the VLDB Journal editorial board, and as a member of the Computing Research Association's Board of Directors. She previously served as General Co-Chair of SIGMOD 2020 and as Associate Head for the Undergraduate Program of the Department of Computer Science from 2018-2020.

Dorte HammershøiView profile

Professor

• Acoustics
• Hearing Science
• Audio Engineering
• +5 more

Dorte Hammershøi is a Professor in the Department of Electronic Systems at The Technical Faculty of IT and Design, Aalborg University, Denmark. Her research focuses on acoustics, sound engineering, and hearing science with significant contributions to human hearing, ear canal acoustics, and audio technology applications. Her research interests include: Temporary Threshold Shift and frequency resolution in human hearing Ear canal acoustics and sound pressure level measurement Distortion Product Otoacoustic Emission (DPOAE) analysis Impulse response and acoustic impedance studies Hearing aid technology and rehabilitation methodologies Virtual reality audio interfaces and accessibility applications Professor Hammershøi's recent publications demonstrate a strong clinical-engineering interdisciplinary approach, bridging theoretical acoustics with practical hearing rehabilitation applications. Her work on hearing aid fitting methodologies, occupational noise exposure effects, and virtual reality audio interfaces shows consistent innovation in translating engineering principles to clinical practice. The research shows particular attention to individualized hearing solutions and accessibility technologies. Her scientific contributions have been recognized with: Dansk Lydpris 2020 (awarded November 17, 2021) Ambassadør for Aalborg (awarded September 15, 2004) Professor Hammershøi has supervised 5 PhD students and led numerous research projects including the ongoing "Audio Only VR for Blind Gamers" project (2024-2028) funded by the Independent Research Foundation of Denmark, and the completed "BEAR: Better Hearing Rehabilitation" project (2016-2022). Her research has attracted significant media attention with 110 press/media appearances discussing hearing damage prevention, tinnitus, and public health implications of noise exposure. She maintains active professional engagement through committee memberships (46 documented activities), international collaborations, and contributions to clinical practice guidelines. Her work continues to influence both academic research and practical applications in hearing science and audio engineering.

Chen SunView profile

Assistant Professor

• Computer Vision
• Deep Learning
• Machine Learning
• +8 more

Chen Sun is an Assistant Professor of Computer Science at Brown University and a part-time Staff Research Scientist at Google DeepMind . His research bridges computer vision, machine learning, and artificial intelligence , focusing on multimodal representation learning, visual commonsense, and controllable video generation . He directs the PALM🌴 research lab , which explores scalable models for robotic planning, video understanding, and human activity recognition . Chen Sun earned a Ph.D. in Computer Science from the University of Southern California (2016) , advised by Professor Ram Nevatia , and a Bachelor of Science in Computer Science from Tsinghua University (2011) . His lab's work has been supported by Adobe, Honda, Meta, NASA, and Samsung , and he is affiliated with the NSF AI Research Institute on Interaction for AI Assistants . His research spans multimodal transformers, embodied agents, and physics-informed video generation . Key trends include Learning from unlabeled videos for human activity recognition Developing controllable generation techniques using motion trajectories and physics-based signals Advancing scalable frameworks for video-language tasks Scientific awards include the Brown University Richard B. Salomon Faculty Research Award and Samsung Global Research Outreach Award . He has served as Workshop Chair (CVPR 2025) , Action Editor (TMLR) , and Area Chair for top conferences like ICLR, CVPR, and NeurIPS . Chen Sun mentors a dynamic team including Ph.D. students Apoorv Khandelwal (Presidential Fellow) Calvin Luo (Research Mobility Fellow) Nate Gillman (Math Department) Shijie Wang Tian Yun (co-advised with Ellie Pavlick) Yuan Zang Zilai Zeng Zitian Tang and alumni now pursuing Ph.D. programs at Princeton, Cornell, UBC, and UNC . His teaching portfolio includes graduate-level courses on Deep Learning (CSCI 2470) , Advanced Topics in Deep Learning (CSCI 2952N) , and a short course on Multimodal Transformers at ICASSP 2022 and AAAI 2023 .

Jonas KuhnView profile

Professor

• Computational Linguistics
• Natural Language Processing
• Large Language Models
• +5 more

Jonas Kuhn is a professor at the Institute for Natural Language Processing (IMS) at University of Stuttgart. He is working at the interface between language and computers, combining linguistics and computer science. Kuhn's research interests span a wide range of computational linguistics topics including: Language models and spatial reasoning Analysis of large language models (LLMs) through linguistic theories Political text analysis and discourse networks Computational approaches to literature and cultural studies Retrieval-augmented language modeling Semantic change detection Dependency parsing and syntactic analysis His recent publications (2023-2025) focus on the intersection of neural language processing with fields as diverse as spatial reasoning, literary analysis, and political discourse. This reflects his interdisciplinary approach that bridges fundamental language research with practical technology development. As a faculty member at one of Germany's largest computational linguistics centers, Kuhn contributes to both fundamental research and technological development in language processing systems.

Ziyu YaoView profile

Assistant Professor

• Natural Language Processing
• Artificial Intelligence
• Knowledge Grounding
• +14 more

Ziyu Yao is an Assistant Professor in the Department of Computer Science at George Mason University , co-leading the George Mason NLP Group . He is affiliated with the C4I & Cyber Center , Center for Advancing Human-Machine Partnership , and Institute for Digital InnovAtion at GMU. PhD in Computer Science and Engineering from Ohio State University (2021) Internships: Microsoft Semantic Machines, Carnegie Mellon University, Microsoft Research, Fujitsu Lab of America, Tsinghua University Research Interests: Focus on Natural Language Processing (NLP) and Artificial Intelligence (AI) , particularly advancing LLM systems through knowledge grounding , reasoning , and planning . Key areas include: Mechanistic Interpretability for LLMs Interactive Semantic Parsing/Code Generation Responsible and Trustworthy NLP Interfaces Interdisciplinary Applications in Mathematics Education and Network Communication Recent Articles (2024-2025) explore trends in LLM cascading for cost efficiency, mechanistic interpretability surveys, vision-language model reasoning, and interdisciplinary educational technology. Collaborations span institutions like Microsoft Research , William & Mary , and University of Cambridge . Scientific Awards: Presidential Fellowship (OSU Graduate School, 2020) Graduate Student Research Award (OSU CSE, 2021) Top Reviewer at NeurIPS 2023 Advising & Grants: Mentors PhD students like Murong Yue , Hao Yan , and Mohamed Aghzal . Leads NSF projects on AI-driven Mathematics Education and LLM Interpretability , alongside grants from Commonwealth Cyber Initiative and Microsoft Accelerate Foundation Models Research . Organized workshops at COLM 2025 and ICML 2025 . Labs & Teams: Co-leads the NLP Lab at GMU and collaborates with the MathVC NSF Project team (w/ Jennifer Suh, William & Mary). Develops platforms like Gentopia for tool-augmented LLMs and IntelliExplain for non-professional programmers.

Bjoern BraunschweigView profile

Professor

• Physical Chemistry
• Interface Science
• Soft Matter
• +5 more

Professor Bjoern Braunschweig is a W2 Professor for Physical Chemistry at the Institute of Physical Chemistry within the Faculty of Chemistry and Pharmacy at the University of Muenster. His research group focuses on fluid interfaces, hierarchical materials, and responsive systems, utilizing advanced nonlinear optical spectroscopy techniques such as sum-frequency generation (SFG) and second-harmonic scattering (SHS) to investigate molecular structures at interfaces. He leads the ERC-funded SUPERFOAM project, which aims to establish molecular-level understanding of foam formation and stability. His research interests span across interface science, soft matter physics, electrocatalysis, and responsive materials. Braunschweig's work particularly emphasizes molecular self-assembly at fluid interfaces, electrode/electrolyte interfaces in ionic liquids, and the development of light- and temperature-responsive materials. His group investigates how molecular building blocks like surfactants, polymers, and proteins determine macroscopic properties of soft materials such as foams and emulsions. The research group has published extensively on photoswitchable arylazopyrazole surfactants, thermoresponsive polymer systems, CO 2 electrocatalysis in ionic liquids, and ion-specific effects at interfaces. Their recent publications demonstrate a strong focus on molecular-level understanding of interface phenomena with applications in energy conversion, smart materials, and environmental processes. ERC Starting Grant (2014) BASF fellowship (2014) Max Buchner research fellowship (2012) DAAD Travel Grant (2012) Feodor Lynen fellowship (2009) Dissertation award (2009) Professor Braunschweig supervises multiple PhD students and postdoctoral researchers, including Billura Shakhayeva, Tim Blinzer, Tan Phat Pham, and Zugang Cong. His former students include notable researchers such as Natalia García Rey, Marco Schnurbus, and Eric Weißenborn. The group maintains strong collaborations with researchers across Europe, particularly with Michael Ryan Hansen, Andreas Heuer, and Monika Schönhoff at the University of Muenster, as well as international partners in Poland and the United States. Their research combines experimental approaches with theoretical modeling to develop fundamental understanding of interface phenomena with practical applications in materials science and energy technologies.

Joanna AizenbergView profile

Professor

• Adaptive Materials
• Biomineralization
• Surface Science
• +4 more

Joanna Aizenberg is the Amy Smith Berylson Professor of Materials Science and Professor of Chemistry and Chemical Biology at Harvard University’s School of Engineering and Applied Sciences (SEAS). She is a Core Faculty Member at the Wyss Institute for Biologically Inspired Engineering and Co-Director of the Kavli Institute for Bionano Science and Technology. Her research focuses on understanding biological architectures and applying these principles to develop advanced synthetic materials and devices. Current Positions: Amy Smith Berylson Professor of Materials Science, Harvard SEAS Professor of Chemistry and Chemical Biology, Harvard Core Faculty Member, Wyss Institute Co-Director, Kavli Institute for Bionano Science and Technology Research Interests: Joanna Aizenberg’s lab explores adaptive materials, biomineralization, surface science, bio-inspired optics, self-assembly, and bio-nano interfaces. The group investigates how biological systems economically design multifunctional, adaptive materials to inspire new synthetic routes and nanofabrication strategies. These advancements aim to impact fields such as architecture, energy efficiency, and medicine. Recent Article Trends: Her recent publications emphasize bio-inspired materials, catalysis, surface engineering, and fluid dynamics. Topics include superhydrophobic coatings, PdAu alloy catalysts, liquid crystal elastomers, and microbial contamination reduction. The interdisciplinary work integrates nanofabrication, computational modeling, and environmental applications. Research Group Members: Kathy Liu Gurminder Paink Haritosh Patel Atalaya Wilborn Garrick Lim

Bob Beitle Jr.View profile

Professor

• Biochemical Engineering
• Bioseparation
• Fermentation
• +5 more

Dr. Bob Beitle Jr. is a Professor of Chemical Engineering and Senior Associate Vice Chancellor for Research and Innovation at the University of Arkansas. He joined the department in 1993, earned tenure in 1998, and was promoted to Full Professor in 2006. His research spans biochemical engineering , bioseparation , fermentation , and adaptive technology for the disabled , with significant work on protein purification, catalytic nanoparticles, and sustainable bioprocesses. Education: BS, MS, PhD in Chemical Engineering from the University of Pittsburgh (1987, 1991, 1993) Dr. Beitle's research combines experimental and computational approaches, focusing on peptide-directed nanoparticle synthesis and biocatalysis . His recent publications highlight advancements in MOF-based separations , CO2 capture materials , and viral detection platforms . He has secured grants like the CAREER Award and led projects in industrial partnerships and student development . Scientific contributions include multiple patents in bioseparation and software interfaces. Awards span decades: teaching honors (1988–2007) and mentorship recognition . He serves on the Cell and Molecular Biology Program Advisory Committee and the Executive Committee for the Biochemical Technology Division of ACS . Lab initiatives involve genomic data-driven affinity tail design and membrane-assisted fermentation systems .

Salvador Barraza LopezView profile

Professor

• 2D Materials
• Ferroelectricity
• Topological Materials
• +4 more

Salvador Barraza-Lopez is a Professor of Physics at the University of Arkansas' College of Arts & Sciences. A theoretical physicist specializing in 2D materials, he developed discrete differential geometry approaches for strain effects in graphene and pioneered 2D ferroelectric research. As a DOE Early Career Awardee (2016) and MonArk NSF Quantum Foundry co-founder, he leads interdisciplinary collaborations across physics, materials science, and mathematics. PhD in Physics from University of Illinois-Urbana Champaign (2006) Postdoctoral work at Virginia Tech and Georgia Tech Established theory of structural transformations in 2D ferroelectrics His research spans quantum phase transitions in 2D systems, strain engineering, and topological materials. Three major review articles in Reports on Progress in Physics (2017, 2023) and Reviews of Modern Physics (2021) synthesize his work on mechanical, electronic, and optical properties of strained 2D materials. Recent publications focus on winding Berry dipoles in strained graphene, size-dependent ferroelectric transitions in homobilayers, and symmetry-breaking effects in moiré superlattices. Collaborations with Kai Chang (Beijing) and Stuart Parkin (MPI-Halle) demonstrate international impact. Awards: DOE Early Career Award (2016) Outstanding Mentor Recognition (2013) Young Investigator of the Year (2013) Mentored 2 NSF Graduate Fellows (Erin Farmer, Joseph Roll) and 3 Goldwater Scholars. Current group includes 2 undergraduates, 3 PhD students, and 2 postdocs. His theoretical frameworks enabled experimental collaborations with DOE labs and Max Planck Institute, securing $0.5M for Arkansas supercomputer upgrades (2024).

Huaxiang FuView profile

Professor

• Ferroelectric Materials
• Quantum Dots
• Density Functional Theory
• +4 more

Dr. Huaxiang Fu is a Professor in the Department of Physics at the University of Arkansas' College of Arts & Sciences, where he has been since 2002. His research focuses on first-principles computational studies of bulk and nanomaterials, particularly ferroelectric materials, quantum dots, and organic-inorganic hybrid materials. Education: Ph.D., Fudan University, China (1994) Postdoctoral Associate, National Renewable Energy Lab, Colorado (1995–1998) Postdoctoral Associate, Geophysical Lab, Carnegie Institution of Washington, DC (1999–2000) Dr. Fu's research spans five key areas: phase transitions in low-dimensional ferroelectrics, finite electric fields in solids, defect physics in ferroelectrics, hyperferroelectricity, and organic-inorganic hybrid materials. His work often employs density functional theory and computational modeling to explore polarization behavior, strain effects, and electronic structure. His recent publications highlight trends in ferroelectricity under strain , defect-induced polarization changes , and spin-orbit coupling effects . Notable collaborations include researchers at Carnegie Institution and University of Arkansas. Teaching: Undergraduate: General Physics, Statics, Mechanics of Materials, University Physics II, Electromagnetism, Fortran Programming, Computational Physics in C++, Physics for Architects II, Thermal Physics. Graduate: Statistical Mechanics, Solid State Physics, Optical Properties of Materials, Advanced Solid State Physics, Physics at the Nanoscale, Quantum Mechanics, Mathematical Methods. Research Contributions: 2004: Nature publication on ferroelectric nanodisks 2000: Nature paper on polarization rotation in piezoelectrics 2013: Pioneering work on electromechanical angular momentum coupling