Tatsunori Hashimoto is an Assistant Professor of Computer Science at Stanford University, specializing in artificial intelligence, machine learning, and natural language processing. His research focuses on developing robust and ethical language models, addressing challenges in bias mitigation, fairness, and transparency. He leads projects like the Stanford Alpaca, exploring instruction-following models and their societal impacts. Key research interests include generative models, AI ethics, and privacy-preserving techniques. His recent work examines language model behaviors, security risks, and the societal implications of AI systems. Notable contributions include frameworks for auditing language models, improving factual accuracy, and reducing disparities in speech recognition. His publications highlight advancements in long-context processing, few-shot learning, and automated benchmarking. He emphasizes practical applications of AI while addressing dual-use concerns and ensuring alignment with human values.
Dr. Heidi Ashton is an Associate Professor in Cultural and Creative Ecologies at the University of Warwick's Centre for Cultural and Media Policy Studies (CCMPS). She holds a concurrent role as a global research fellow at the Creative Industries Policy and Evidence Centre (PEC). Her work bridges academic research with practical insights from over 25 years of experience as a freelance dancer, choreographer, and producer across global creative sectors. Key affiliations include Director of Education for SCAPVC and external PhD evaluator at Bahria University, Pakistan. Research interests focus on freelance workers' rights within creative industries, social security access, and policy impacts on arts education and cultural participation. Notable projects include collaborations with Equity Union on social security challenges and with Prof. Prue Huddleston on arts education policy. Her work has influenced UK policy debates, including House of Lords citations and Guardian features. Teaching responsibilities span undergraduate and postgraduate levels, including modules on creative industry workplaces and policy analysis. Current PhD supervision explores cultural policy-labour dynamics and digital platforms' role in creative work. Recent projects include the 'Urban Village' community arts initiative in Coventry and pandemic impact studies on cultural sectors. Publications address freelance worker vulnerabilities, comparative cultural policies (e.g., UK vs USA), and educational apartheid critiques. Her 2024 co-authored 'State of the Arts' report provides a UK-wide cultural sector health check, presented to DCMS officials and arts leaders.
James Grantham Turner is the James D. Hart Chair and Distinguished Professor of English at the University of California, Berkeley. He specializes in 18th-century British literature, gender and sexuality studies, Renaissance and Early Modern studies, narrative and the novel, poetry, and drama. His research bridges literature and art history, focusing on sexuality, gender, ecology, and classical antiquity. He holds degrees from Oxford University (B.A., 1968; M.A., Cert.Ed.; D.Phil., 1977) and has taught at institutions including Oxford, Sussex, Northwestern, and Michigan before joining Berkeley in 1990. Turner’s recent work includes The Villa Farnesina: Palace of Venus in Renaissance Rome (2022), winner of the PROSE Award in Art History, and Eros Visible: Art, Sexuality and Antiquity in Renaissance Italy (2017). His research explores interdisciplinary histories of sexuality, combining European literature, social history, and art. He has contributed to major exhibitions at the Metropolitan Museum of Art, National Gallery of Victoria, and the Getty Museum. Awarded fellowships from the Guggenheim Foundation, NEH, and ACLS, Turner’s scholarship spans over 100 articles and books. He has served on editorial boards for PMLA , Eighteenth-Century Studies , and others. His recent conference papers include discussions on Milton’s cosmology and Renaissance erotic art. He currently teaches at Berkeley and maintains office hours in Wheeler Hall. Turner’s research also intersects with global sexualities, food studies, and classical mythology. His work emphasizes cross-cultural analysis, from Italian Renaissance palaces to Enlightenment-era libertinism. He continues to explore intersections of art, literature, and sexuality across pre-modern Europe.
Jiajun Wu is an Assistant Professor of Computer Science and, by courtesy, of Psychology at Stanford University. He holds multiple affiliations including membership in Bio-X, Faculty Affiliate status at the Institute for Human-Centered Artificial Intelligence (HAI), and membership in both the Wu Tsai Human Performance Alliance and Wu Tsai Neurosciences Institute. Dr. Wu earned his Ph.D. and S.M. in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology before joining Stanford. Dr. Wu's research program focuses on creating AI systems that understand and interact with the physical world through the integration of computer vision, machine learning, robotics, and cognitive science. His work emphasizes physics-based modeling combined with deep learning to develop systems capable of perceiving, reasoning about, and predicting physical interactions. Key research areas include 3D scene understanding, neurosymbolic AI approaches, multimodal perception (combining vision, sound, and language), and embodied intelligence for robotics applications. His lab develops novel frameworks that bridge the gap between neural networks and symbolic reasoning to create more interpretable and robust AI systems. Analysis of Dr. Wu's recent publications reveals a strong trajectory toward integrated multimodal understanding for embodied AI. His work increasingly combines vision, sound, and language processing with physical reasoning to create systems that can interact meaningfully with the physical world. There's a clear progression from foundational computer vision research toward practical robotics applications, with significant emphasis on foundation models for robotics, sim2real transfer techniques, and creating comprehensive datasets for embodied AI research. Dr. Wu's exceptional contributions have been recognized with numerous prestigious awards including the NSF CAREER award (2024), Young Investigator Programs from ONR (2024) and AFOSR (2023), the Okawa research grant (2024), and being named to IEEE Intelligent Systems' 'AI's 10 to Watch' (2024). He has received multiple best paper awards at leading conferences including ICRA (2024), SIGGRAPH Asia (2023), and CoRL (2023). Dr. Wu actively mentors a large cohort of students across multiple levels, serving as primary advisor for doctoral candidates, master's students, and numerous independent researchers. His research is supported by substantial funding from major technology companies including Google, Meta, Amazon, Samsung, and J.P. Morgan, as well as government agencies like NSF, ONR, and AFOSR, reflecting the significance and impact of his work in physical AI and multimodal perception systems. Dr. Wu leads a dynamic research group at Stanford that collaborates extensively with the Wu Tsai Neurosciences Institute and Institute for Human-Centered AI. Current projects include developing neurosymbolic models for computer graphics, creating multisensory datasets like OBJECTFOLDER 2.0 for sim2real transfer in robotics, and building foundation models for embodied intelligence that can understand and manipulate objects with human-like physical intuition.
Zoya Popovic is a Distinguished Professor and holds the Lockheed Martin Endowed Chair in RF Engineering at the University of Colorado Boulder's Department of Electrical, Computer, and Energy Engineering. She earned a Dipl.Ing. from the University of Belgrade (1985) and a PhD from Caltech (1990). She has advised over 50 PhD students and was a visiting professor at Technical University of Munich (2001). Her research focuses on high-efficiency microwave/millimeter-wave circuits, smart antenna arrays, wireless powering systems, and biomedical microwave applications. Notable contributions include quasi-optical imaging techniques and low-noise amplifier designs. Key awards: IEEE Microwave Prizes (1993/2006), Humboldt Research Award (2000), Terman Medal (2001) Lab Group Website: [Link] Recent work emphasizes in-band full-duplex systems, GaN MMICs, and quantum-based waveform modulation. Her group maintains advanced facilities for millimeter-wave and terahertz research.
Michael Feeley is an Associate Professor in the Department of Computer Science at the University of British Columbia (UBC), affiliated with the Institute for Computing, Information and Cognitive Systems (ICICS). His research focuses on operating systems, distributed systems, and their applications in scalable file systems, cloud storage, and mobile computing. He leads projects such as the Unico file system, Parallax storage system, and Remus virtual machine replication framework. His research interests include peer-to-peer file systems, mobile ad hoc networks, interference mitigation in wireless networks, and system software for workstation clusters. He has supervised numerous graduate students, contributing to advancements in distributed systems and networking. His work often addresses challenges in resource management, fault tolerance, and performance optimization. Publications span topics like interference detection in WiFi networks, dynamic program analysis (Tralfamadore), and distributed storage solutions. Feeley teaches courses such as CPSC 213, emphasizing operating systems fundamentals. His office is located in CISR 393, with contact details available via email and phone.
Ronnie Sircar is the Eugene Higgins Professor of Operations Research and Financial Engineering at Princeton University , where he contributes to the Department of Operations Research and Financial Engineering (ORFE). His work spans financial mathematics, stochastic modeling, and applied probability, with a focus on market volatility, optimal investment strategies, and dynamic game theory. Email: sircar@princeton.edu Office: Sherrerd Hall, Room 208, Princeton, NJ 08544 His research interests include: Stochastic Volatility: Asymptotic analysis, calibration, and impact on option pricing and portfolio optimization. Mean Field Games: Applications to cryptocurrency mining, energy markets, and interbank network formation. Portfolio Theory: Forward performance processes, drawdown constraints, and risk-averse strategies. Credit Risk: Multi-name credit derivatives, CDO valuation, and risk measures. Energy Systems: Renewable reliability, unit commitment, and electricity market design. Recent publications emphasize mean field games in energy and blockchain, stochastic volatility in portfolio optimization, and machine learning applications for financial engineering. He has advised graduate students such as Giulia Crippa, Nicolas Garcia, and Burak Aydin, often collaborating with researchers including M. Soner, P. Chan, and A.M. Reppen.
Michael Muehlebach leads the independent Learning and Dynamical Systems research group at the Max Planck Institute for Intelligent Systems in Tuebingen, Germany. His interdisciplinary work bridges machine learning, dynamical systems theory, and control engineering to develop algorithms for cyber-physical systems with theoretical guarantees and practical implementations. Dr. Muehlebach received his B.Sc. and M.Sc. in Mechanical Engineering from ETH Zurich in 2010 and 2013, specializing in robotics and control systems. He completed his Ph.D. at ETH's Institute for Dynamic Systems and Control under Prof. R. D'Andrea in 2018, followed by postdoctoral research with Prof. Michael I. Jordan at UC Berkeley. His research focuses on constrained optimization, reinforcement learning, and control theory with applications in robotics. He pioneered approaches that express constraints in terms of velocities rather than positions, enabling more efficient optimization algorithms. His work spans theoretical foundations to physical implementations, including the One-Wheel Cubli balancing robot and electromagnetic navigation systems. Recent publications reveal a strong trend toward physics-informed machine learning, particularly for robotics applications requiring real-time performance and safety guarantees. Dr. Muehlebach has received numerous prestigious awards: Outstanding D-MAVT Bachelor Award Willi-Studer prize for best Master's degree ETH Medal and HILTI prize for doctoral thesis Branco Weiss Fellowship (2018) Emmy Noether Fellowship (2020) Amazon Fellowship (2024) He actively mentors doctoral researchers including Hao Ma, Melis Ilayda Bal, and Onno Eberhard, with research supported by multiple grants. His group maintains strong collaborations with Bernhard Schölkopf's Empirical Inference group at the Max Planck Institute. The Learning and Dynamical Systems group develops innovative hardware and software platforms, including Floaty (a wind-harnessing flying robot), advanced electromagnetic navigation systems, and data-efficient learning methods for robotic table tennis. Their approach combines rigorous theoretical analysis with practical validation on physical systems, emphasizing the integration of known physical structure into machine learning algorithms to improve sample efficiency and ensure generalization.
Mark J. Loewenstein is the Monfort Professor of Commercial Law at the University of Colorado Law School, where he has been a faculty member since 1979. He teaches courses in Business Associations, Securities Law, and Contracts, and has established himself as a leading scholar in business law. Professor Loewenstein previously practiced business law at a Chicago law firm before joining academia and has maintained strong connections with the legal profession throughout his career. Professor Loewenstein's educational background includes: JD from the University of Illinois, Champaign-Urbana BA from the University of Illinois, Champaign-Urbana Professor Loewenstein's research focuses on business associations, agency law, and securities law, with particular expertise in corporate governance. His scholarly work examines the legal structures of business organizations, fiduciary duties in unincorporated entities, and the evolving landscape of corporate law. He has made significant contributions to understanding LLC governance, veil piercing doctrines, and the application of good faith principles in business contexts. His comparative work on stakeholder protection in Germany and Japan demonstrates his international perspective on corporate governance issues. Analysis of Professor Loewenstein's publications reveals a consistent focus on the intersection of business organization law and corporate governance. His work spans theoretical examinations of agency principles, practical analyses of LLC structures, and historical perspectives on corporate law developments. A notable trend in his scholarship is the examination of how traditional corporate law concepts apply to newer business forms, particularly limited liability companies. His publications also demonstrate a strong interest in the balance between state and federal regulation of business entities. Professor Loewenstein has received significant professional recognition: Monfort Professor of Commercial Law (endowed chair) Fulbright Scholar at Hokkaido University, Japan (1990-91) Visiting Professor at University of Michigan Law School (1999) Throughout his career, Professor Loewenstein has demonstrated exceptional service to both the University of Colorado Law School and the broader legal community. He served as associate dean for academic affairs for nine years and associate dean for research for four years. He was a member of Colorado's Securities Board from 1995 to 2000 and contributed to the drafting of the 1994 Colorado Business Corporation Act. As a delegate to the ABA House of Delegates (1999-2005) and active member of the ABA's business law committee, he has influenced business law development at the national level. His service extends to editorial roles for legal publications and frequent presentations at professional conferences. Professor Loewenstein maintains strong connections with the legal practice community through his ongoing service on the Colorado Bar Association's Corporate Law Revision Committee and his contributions to continuing legal education programs. His work bridges academic scholarship and practical legal application, making him a valued resource for both students and practitioners.
Kumar Varoon Agrawal is an Associate Professor at École Polytechnique Fédérale de Lausanne (EPFL), holding the Gaznat Chair for Advanced Separations. He is affiliated with the School of Basic Sciences (SB), the Institute of Chemical Sciences and Engineering (ISIC), and the Laboratory of Advanced Separations (LAS) in Sion, Switzerland. Additionally, he contributes to the Swiss Doctoral School in Chemical and Bioengineering (SCGC) and serves as Vice President of the Confédération des Chimistes et des Génie Chimique (CCE). Research Focus: Material Chemistry & Engineering at the Ångström scale for high-performance inorganic and hybrid membranes, emphasizing energy-efficient molecular separations. Teaching: Courses include Fundamentals of separation processes , Diffusion and mass transfer , and Chemical engineering product design . Scientific Contributions: His 15 most recent publications (2025-2020) span topics like graphene pore engineering , 2D material synthesis , carbon capture , and gas separation membranes , with keywords such as Nanotechnology , Materials Science , and Molecular Transport . Subfields include Atomic-Scale Pores , Membrane Stability , and Industrial Scalability . Students and Collaborations: He advises 10 current PhD students and has mentored 9 past PhD candidates in areas like graphene membranes , ion separation , and MOF films . He is an Academic Referent for the EPFL Carbon Team and a committee member for the EDCH Doctoral Program in Chemistry and Chemical Engineering.
Risto Miikkulainen is a Professor of Computer Science and Neuroscience at the University of Texas at Austin and VP of AI Research at Cognizant AI Lab. He directs the UTCS Neural Networks Research Group and is currently on leave from UT, working on Evolutionary Computation and Deep Learning at Sentient Technologies, Inc. Education: Ph.D. in Computer Science, UCLA, 1990 M.S. in Applied Mathematics, Helsinki University of Technology (now Aalto University), 1986 Risto Miikkulainen's research focuses on biologically-inspired computation such as neural networks and evolutionary computation. His work spans three main areas: (1) Neuroevolution, evolving complex deep learning architectures and recurrent neural networks for sequential decision tasks in robotics, games, and artificial life; (2) Cognitive Science, developing models of natural language processing, memory, and learning that shed light on disorders such as schizophrenia and aphasia; and (3) Computational Neuroscience, studying the development, structure, and function of the visual cortex, episodic memory, and language processing. His research combines theoretical understanding of biological information processing with practical applications for developing intelligent artificial systems. His recent publications (2025) show a strong focus on evolutionary approaches to AI development, particularly in neural architecture search, loss function optimization, and explainable AI. Many papers explore the intersection of evolutionary computation with deep learning, creating more efficient and transparent AI systems. His work spans theoretical foundations and practical applications in areas ranging from environmental control systems to cognitive modeling. Scientific Awards: College of Fellows, International Neural Network Society, 2024 Best Pathway to Impact Award, NeurIPS Climate Change workshop, 2024 AAAI Fellow, 2023 IEEE CIS Evolutionary Computation Pioneer Award, 2020 Gabor Award, International Neural Network Society, 2017 Outstanding Paper of the Decade Award, International Society for Artificial Life, 2017 IEEE Fellow, 2016 Multiple Best Paper Awards at GECCO, CIG, and CEC conferences Deployed Application Award, AAAI/IAAI-2013, AAAI/IAAI-2018 Miikkulainen has extensive experience mentoring students through undergraduate research courses like CS378 Computational Intelligence in Game Design I and II, where students develop independent research projects on the OpenNERO research platform. He has received multiple awards for deployed applications, demonstrating the practical impact of his research. His work has led to the development of the NERO game platform, which serves as both an educational tool and research platform for AI. He directs the UTCS Neural Networks Research Group, which focuses on neuroevolution, cognitive science models, and computational neuroscience. The group has developed the NERO (Neuro-Evolving Robotic Operatives) platform, a machine learning game that allows users to train intelligent agents through evolutionary computation. The group's work spans theoretical research and practical applications in AI, with connections to both academic and industry partners.
Dr. Robin Laycock is a Senior Lecturer in the Department of Health and Biomedical Sciences at RMIT University. He leads the Social and Cognitive Neuroscience (SoCoNeuro) Lab, focusing on behavioral and neural mechanisms of social perception in neurotypical and neurodivergent populations, including autism spectrum disorders and the neurocognitive effects of concussion. His research integrates methodologies such as eye-tracking, EEG, and fNIRS to study visual perception, face processing, and the impact of stress/anxiety on cognition. Dr. Laycock holds a PhD from La Trobe University, where he investigated visual processing pathways. His work also includes the BabyFace study, exploring social perception in pre-term infants using fNIRS. He is affiliated with RMIT’s Healthy Foundations Research Group and supervises research projects on topics like concussion neurocognition and social media’s neurobiological effects. Research interests span visual neuroscience, social neuroscience, and clinical applications of neuroimaging. He teaches undergraduate courses in Biological Psychology and supervises postgraduate research in vision science, neuropsychology, and affective neuroscience. His lab’s recent studies examine sex differences in sports-related concussion neuroimaging and the role of deepfakes in emotion perception research. He actively collaborates on projects addressing autism traits, stress effects on visual processing, and neuroimaging advancements.
Rosa Andujar is a Senior Lecturer in Liberal Arts at King's College London, where she is affiliated with both the Department of Liberal Arts and the Department of Classics within the Faculty of Arts & Humanities. She serves as Editor of the American Journal of Philology and holds positions on the editorial boards of Brazilian journals Nuntius Antiquus and PhaoS - Revista de Estudos Clássicos. Dr. Andujar was elected to the Program Committee of the Society for Classical Studies for a three-year term (2022-2025), serving as Vice President for Program and Chair from 2023-2025. Her research focuses on two complementary areas: Ancient Greek tragedy, particularly the tragic chorus and its performance capabilities Global receptions of Greek drama, with special emphasis on Latin America and the Caribbean Dr. Andujar's work examines how engagements with Graeco-Roman antiquity intersect with questions of gender, race, class, and national identity. She has particular expertise in Cuban adaptations of Greek tragedy and Latinx receptions of classical drama, exploring how these cultural encounters create new narratives that challenge traditional understandings of classical reception. Her research has been recognized with prestigious awards including the 2020 London Hellenic Prize for 'The Greek Trilogy of Luis Alfaro' and the 2022 AJP Best Article Prize. She has secured significant research funding from the Loeb Classical Library Foundation, British Academy, A. G. Leventis Foundation, Harvard Center for Hellenic Studies, Andrew W. Mellon Foundation, and Fundación BBVA. Dr. Andujar's current research projects include 'The Cambridge Companion to Classics and Race' (edited volume), 'La Puerta Electra/The Electra Door' (critical bilingual anthology of Cuban rewritings), and 'Tragedy and Revolución' (monograph on Greek drama in Caribbean cultural history), supported by recent fellowships from the Loeb Classical Library Foundation and British Academy. She is actively involved in academic service as Editor of the American Journal of Philology, co-editor of the 'Classics and the Postcolonial' book series for Routledge, and Advisory Board member of 'Hesperides: Classics in the Luso-Hispanic World.' Her external examining work for the University of Birmingham (2018-2023) demonstrates her commitment to academic standards across institutions.
Dr. KN Sasidhar is a Researcher in the Department of Microstructure Physics and Alloy Design at Heinrich Heine University Düsseldorf. His work focuses on advanced materials science, particularly corrosion mechanisms, alloy design, and nanoscale structural analysis. He employs cutting-edge techniques like in situ synchrotron investigations and deep learning frameworks to study material behavior under extreme conditions. Current research emphasizes corrosion resistance in stainless steels, phase transformations during nitriding, and radiation effects on coatings. Key achievements include pioneering studies on nanoscale amorphization in metallic systems, data-centric approaches for materials discovery, and the development of predictive models for alloy performance. His work bridges experimental materials characterization with computational methods, addressing challenges in energy and aerospace applications. Publications span corrosion analysis, microstructural evolution under irradiation, and phase separation phenomena. Collaborative projects involve synchrotron facilities and interdisciplinary teams focusing on materials informatics. No formal awards or grants are explicitly listed in the provided texts, though his prolific publication record indicates active academic engagement.
Anne E. White is the School of Engineering Distinguished Professor of Engineering and associate vice president for research administration at the Massachusetts Institute of Technology (MIT). She serves in the Department of Nuclear Science and Engineering within MIT's School of Engineering and is a key researcher at the Plasma Science and Fusion Center (PSFC). White has held significant leadership roles including NSE department head from 2019 to 2023 and co-chair of the MIT Climate Nucleus from 2021 to 2024. She currently chairs the Fusion Energy Sciences Advisory Committee (FESAC), providing federal advisory input to the U.S. Department of Energy Office of Science. White received her PhD in physics from UCLA, where she conducted research at the Electric Tokamak. Her early career included research positions at the National Spherical Torus Experiment at Princeton Plasma Physics Laboratory and the DIII-D National Fusion Facility at General Atomics before joining MIT as a faculty member. Her educational background laid the foundation for her expertise in plasma physics and fusion energy research. Professor White's research focuses on magnetic fusion energy, specifically on understanding turbulent transport in magnetically confined fusion plasmas. Her work spans diagnostic development, novel experimentation, and validation of nonlinear gyrokinetic codes. She aims to demonstrate nuclear fusion as a practical part of the world's sustainable energy future. Her group develops and uses radiometers, reflectometers, and interferometers to measure fluctuations in plasma density, temperature, and flows in tokamaks. This research is critical for improving predictive capabilities of turbulent transport models, which is essential for developing viable fusion reactors. Analysis of Professor White's recent publications reveals a strong focus on plasma diagnostics and turbulence measurements across multiple tokamak facilities. Her work spans experimental measurements on ASDEX Upgrade, Alcator C-Mod, NSTX, and DIII-D tokamaks, with particular emphasis on electron temperature fluctuations, turbulence characterization, and transport model validation. A significant theme is the development and application of novel diagnostic techniques for simultaneous measurements of multiple plasma parameters. Her research increasingly incorporates computational approaches, including gyrokinetic simulations and machine learning methods, to interpret experimental data and advance predictive capabilities in fusion plasma physics. Professor White has received numerous prestigious awards throughout her career: Fellow, American Physical Society Division of Plasma Physics (2019) Cecil and Ida Green Career Development Professor, MIT (2014) American Physical Society Katherine E. Weimer Award (2014) Fusion Power Associates Excellence in Fusion Engineering Award (2014) Junior Bose Award for Excellence in Teaching, MIT (2014) PAI Outstanding Faculty Award from MIT student chapter of the American Nuclear Society (2013) Norman C. Rosenbluth Career Development Professor, MIT (2012-2014) Department of Energy Early Career Award (2011-2016) Marshall N. Rosenbluth Outstanding Doctoral Thesis Award (2009) As an educator and mentor, Professor White has advised numerous students through MIT's Department of Nuclear Science and Engineering. She has taught courses including Principles of Plasma Diagnostics, Seminar in Fusion & Plasma Physics, and Introduction to Plasma Physics. Her leadership extends to developing educational resources, notably leading a team in 2018 to create a free MITx MOOC focused on nuclear science and engineering for global high school learners. Professor White has secured significant research funding through Department of Energy awards, including the Early Career Award (2011-2016) and various fusion energy fellowships throughout her career. Her research group at MIT's Plasma Science and Fusion Center has contributed to multiple major fusion facilities and has been instrumental in advancing understanding of plasma turbulence and transport. Professor White leads the Fusion and Plasmas Lab at MIT, which focuses on diagnostic development and turbulence measurements in fusion plasmas. Her team has made significant contributions to research on four major tokamaks: Alcator C-Mod, ASDEX Upgrade, DIII-D, and National Spherical Torus Experiment Upgrade. At MIT's Plasma Science and Fusion Center, she previously served as assistant division head for magnetic fusion energy collaborations and ran the Gyrokinetic Simulation Working Group and the Alcator C-Mod Transport Group. Her lab maintains close collaboration between experimental work, theoretical modeling, and computational simulation to advance the understanding of plasma turbulence and transport phenomena critical for fusion energy development.
