Sarah Billington is the UPS Foundation Professor of Civil and Environmental Engineering at Stanford University and a Senior Fellow at the Woods Institute for the Environment. Her research program focuses on sustainable building design, human wellbeing, and ethical supply chain practices. Education: PhD, University of Texas at Austin, Structural Engineering (1997) MSE, University of Texas at Austin, Structural Engineering (1994) BSE, Princeton University, Civil Engineering & Operations Research (1990) Her lab employs interdisciplinary methods to study how built environments impact human physical, psychological, and social wellbeing. Current projects include developing tools to quantify nature exposure in buildings, exploring affordable housing's role in wellbeing, and using AI to assess forced labor risks in material supply chains. While no longer active in this area, her group previously pioneered research on sustainable construction materials like bio-based composites and ductile cement-based composites. Her recent publications address topics such as nature integration in architecture, workplace design optimization, and health impacts of building materials. The Billington Lab at Stanford fosters collaborative team science, welcoming partnerships to advance occupant-centric engineering solutions.
Brian Lawrence is an Assistant Professor in the Department of Mathematics at the University of Wisconsin–Madison, currently on leave as of 2025. Previously, he held positions at UCLA, the University of Chicago, and Columbia University, following doctoral studies at Stanford University under Akshay Venkatesh. His educational background includes: PhD in Mathematics from Stanford University (advisor: Akshay Venkatesh) Lawrence's research centers on arithmetic geometry, specializing in Diophantine problems through p-adic methods. His work develops innovative approaches to Mordell's conjecture, Shafarevich-type results, and rational point distribution using p-adic Hodge theory, étale cohomology, and period mappings. He bridges theoretical number theory with computational frameworks, particularly in algorithmic solutions for Diophantine equations. His publication trends reveal sustained focus on foundational Diophantine geometry problems, with recent work emphasizing conditional algorithms for the Mordell problem and sparsity phenomena in integral points. Collaborations with leading mathematicians like Venkatesh and Sawin demonstrate interdisciplinary engagement across number theory and algebraic geometry. Lawrence actively mentors undergraduate researchers, supervising projects on resultants, Hodge theory, and symmetric polynomials by students including Pramana Saldin, Yuchen Chen, Anuj Sakarda, and Spencer Dembner. His organizational roles include founding the Crystalline Cohomology seminar at Columbia and co-organizing the University of Chicago Number Theory Seminar, fostering collaborative research environments. He contributes extensively through expository notes on schemes, polynomials on lattices, and Fibonacci numbers modulo p, reflecting commitment to mathematical education and knowledge dissemination across multiple institutions.
Alex Wong is an Assistant Professor of Computer Science at Yale University, specializing in computer vision, robotics, and medical imaging. His research focuses on sensor fusion, unsupervised learning, 3D vision, robust perception under adverse conditions, and medical image analysis. He holds degrees from the University of California, Los Angeles (UCLA), including a B.S., M.S., and Ph.D. in Computer Science. Wong’s work bridges theoretical advances with practical applications, particularly in depth estimation, autonomous systems, and medical diagnostics. He has received prestigious awards such as the NeurIPS Outstanding Student Paper Award (2011) and the ICRA Best Paper Award in Robot Vision (2019). His research often addresses challenges in unstructured environments, emphasizing robustness and adaptability. Recent projects include developing novel frameworks for unsupervised depth completion, adversarial robustness in vision systems, and multimodal fusion techniques. His contributions span conferences like CVPR, ICCV, and ICRA, with a strong focus on advancing AI for real-world applications in healthcare and robotics. Education: B.S., Computer Science, UCLA M.S., Computer Science, UCLA Ph.D., Computer Science, UCLA Awards: NeurIPS Outstanding Student Paper Award (2011) ICRA Best Paper Award in Robot Vision (2019) His lab at Yale Engineering focuses on AI-driven solutions for perception challenges, collaborating across disciplines to advance medical imaging and autonomous systems. Current efforts explore generative models, continual learning, and vision-language integration for robust scene understanding.
Anna Morcom is Professor and Mohindar Brar Sambhi Chair of Indian Music in the Department of Ethnomusicology at UCLA's Herb Alpert School of Music. She previously held a professorship at Royal Holloway, University of London, and earned her Ph.D. from SOAS (School of Oriental and African Studies) in 2002, where she also completed her undergraduate studies in Ethnomusicology and Hindi (1993-1996). Her research spans music and dance in India and Tibet, employing ethnographic and oral historical methods to examine the intersections of musical culture with politics, nationalism, identity, gender, inequality, economic development, and media. Morcom's scholarship is notable for its interdisciplinary approach that bridges traditional and popular musics with contemporary theoretical frameworks. Her work demonstrates significant trends toward examining music within economic frameworks, particularly through her founding of SEM's Special Interest Group on Economic Ethnomusicology. Recent publications increasingly focus on cultural economies, performance labor, and the relationship between artistic practice and economic systems in South Asia. Society of Ethnomusicology's Allan Merriam prize (2014) Marcia Herndon prize of SEM's Gender and Sexualities section (2014) Morcom's research has been supported by multiple grants from the Leverhulme Trust and the British Academy. She has been interviewed by prominent media outlets including BBC Radio 4's Thinking Allowed, The Hindu, Tehelka, and Scroll regarding her influential work on Indian dance cultures. As founder of SEM's Special Interest Group on Economic Ethnomusicology, she has shaped scholarly discourse on the economic dimensions of musical practice. Her current projects include the monograph on Hindustani music and co-editing two significant volumes: Creative Economies of Culture in South Asia: Craftspeople Performers (Routledge) and the Oxford Handbook of Economic Ethnomusicology (OUP).
David Stillwell serves as Professor of Computational Social Science at Cambridge Judge Business School and Academic Director of The Psychometrics Centre, University of Cambridge. His research leverages big data to understand human psychology and behavior, with significant contributions in personality prediction from digital footprints and personalized advertising applications. His educational background includes: BSc in Psychology from the University of Nottingham (2007) MSc in Research Methods from the University of Nottingham (2008) PhD in Decision Making from the University of Nottingham (2012) Dr. Stillwell's research centers on computational social science and psychometrics, pioneering the myPersonality Facebook application that collected data from over 6 million users. His work demonstrates computers can predict personality as accurately as spouses, reveals psychological targeting's advertising effectiveness, and establishes links between personality-matched spending and life satisfaction. He also explores linguistic honesty markers through profanity analysis and personality-based dating patterns. His recent publications (2019-2025) reveal a strong trajectory toward AI evaluation using psychometric frameworks, particularly in medical and general-purpose AI assessment. Key themes include fairness metrics in language models, crisis emotional responses through social media, and computational personality recognition - demonstrating consistent innovation at the psychology-technology intersection. He has received significant recognition: Top 10 most influential papers of 2013 by Altmetric Nieman Journalism Lab highlight of 2013 Named in 'top 30 thinkers under 30' by Pacific Standard Magazine Dr. Stillwell maintains active industry engagement through consultancy with Barclays, Hilton, and Ubisoft on projects spanning computer-adaptive testing systems to interactive experiences like Predictive World for Watch Dogs 2. His policy impact is substantial, with citations by the European Data Protection Supervisor, World Bank, and multiple national governments, leading to speaking engagements at the European Parliament and Bank of England. As Academic Director of The Psychometrics Centre, he leads a global hub for advancing psychological assessment through innovative methods including Concerto open-source software, collaborating with organizations ranging from the European Commission to major corporations on psychometric applications in people analytics and digital behavior.
Daniel Finley is a Professor of Cell Biology at Harvard Medical School (HMS), leading the Finley Lab focused on the ubiquitin-proteasome pathway and related regulatory mechanisms. He holds academic appointments within the Department of Cell Biology and sits on the Scientific Advisory Boards of Proteostasis and X-Chem Pharmaceuticals. His research investigates proteasome function, ubiquitin-like proteins, and proteostasis roles in diseases like Alzheimer’s and ALS. Dr. Finley earned his undergraduate degree in biochemistry from Harvard University and a Ph.D. in molecular biology from MIT. After postdoctoral training at MIT, he joined HMS in 1988. His lab explores topics including erythroid proteome remodeling, mitochondrial dysfunction, and neurodegenerative disease mechanisms. Key research areas include: (1) Ubiquitin-proteasome pathway regulation, (2) Proteasome structure/function, (3) Nonproteolytic roles of ubiquitination, and (4) Pathophysiological roles of proteostasis defects in diseases. His work bridges basic cell biology with translational medicine, particularly in neurodegeneration and anemia. Finley has secured NIH funding for projects like 'Regulation of Proteasome Activity' (R35GM145246) and 'Erythrocyte maturation through global proteome remodeling' (R01HL153970). Collaborations with industry and academic partners extend his impact in drug discovery and proteasome-targeted therapies. His lab’s contributions include defining ubiquitin chain editing mechanisms, identifying USP14’s role in mitophagy, and elucidating proteostasis defects in Alzheimer's models. Research tools developed include advanced cryo-EM analyses of proteasomal structures and functional assays for ubiquitin system enzymes.
Daniel Dominic Kaplan Sleator is a Professor of Computer Science at Carnegie Mellon University's School of Computer Science. He maintains an office in the Gates-Hillman Center (7205 Gates-Hillman) and teaches various courses in algorithms and theoretical computer science. Professor Sleator's research spans several areas of theoretical computer science and algorithms. His primary interests include: Algorithms and Data Structures Amortized Analysis and Competitive Analysis Persistent and Self-Adjusting Data Structures Computational Geometry and Combinatorial Optimization Combinatorial Game Theory and Mathematical Games Music Analysis using Computational Methods His extensive publication record shows a consistent focus on efficient data structures and algorithms. Over the years, his work has evolved from foundational data structures like splay trees and skew heaps to applications in diverse areas such as music analysis and combinatorial games. A notable trend in his work is the development of self-adjusting data structures that achieve excellent amortized performance without maintaining explicit structural constraints. His papers on splay trees, skew heaps, and persistent data structures have become classics in the field. Professor Sleator has made significant contributions across multiple domains of computer science. His work on competitive algorithms for paging and list update problems has been particularly influential, establishing fundamental results in online algorithms. His research extends beyond traditional computer science into interdisciplinary areas like computational music theory, demonstrating the broad applicability of algorithmic thinking. He teaches a variety of courses including Algorithms 15-451/651, Competition Programming 15-295, and specialized topics like mathematical games.
Benjamin Carrison-Schafer is an Associate Professor and Assistant Dean for Graduate Student Success at the Department of Electrical and Computer Engineering, Erik Jonsson School of Engineering and Computer Science, University of Texas at Dallas. He leads the Design Automation and Reconfigurable Computing Laboratory (DARClab), focusing on systems, high-level design, and programming methodologies for VLSI computing systems and FPGAs. Education: MBA from McGill University, Canada (2012) PhD in Electrical and Electronic Engineering from University of Birmingham, UK (2003) Research Interests: His work spans modeling, analysis, synthesis, optimization, and implementation of VLSI systems. Current projects include: Approximate Computing, High-Level Synthesis Design Space Exploration, Hardware Security, Behavioral MPSoC Optimization, and Automatic Fault-Tolerant System Generation. His research blends theory and practice, using analytical and experimental techniques to solve real-world problems. Publication Trends: Recent publications demonstrate strong focus on hardware security, FPGA optimization, and automated design methodologies. Key themes include High-Level Synthesis innovations, hardware acceleration techniques, and cross-disciplinary applications of reconfigurable computing. His work frequently addresses challenges in hardware trustworthiness, energy efficiency, and design automation scalability. Professional Activities: Associate Editor: IEEE Transactions on Sustainable Computing (2022-present) Conference Chair: ICCD 2024, DCAS 2024 Program Committee: ASP-DAC, DATE, FCCM, GLSVLSI Advising & Labs: Supervises multiple PhD and Master's students at DARClab. Current research includes domain-specific architecture design, hardware security, sustainable computing, and ML for VLSI design. The lab collaborates with industry partners like Renesas Electronics and develops commercial tools through spin-off company highX Technologies.
Florentina Bunea is a Professor in the Department of Statistics and Data Science at Cornell University’s Bowers College of Computing and Information Science, and an active member of the Graduate Fields of Statistics, Applied Mathematics, and Computer Science. She also serves on the Diversity and Inclusion Council of her college, championing workforce diversity in data-science disciplines. Education & Institutional Roles Professor, Department of Statistics and Data Science, Cornell University Member, Graduate Fields of Statistics, Applied Mathematics, Computer Science Member, Diversity and Inclusion Council, Bowers College of Computing and Information Science Research Interests Professor Bunea’s research lies at the intersection of statistical machine-learning theory and high-dimensional inference. She develops rigorous methodology supported by sharp theoretical guarantees to tackle core problems in modern data science. Recent themes include: Soft-max mixtures for understanding large-language-model/AI algorithms Optimal transport for high-dimensional mixture distributions Wasserstein-distance inference for sparse mixing measures in topic models Latent-space clustering and cluster-based inference in high dimensions Network modeling and hidden-structure inference Applications spanning genetics, systems immunology, neuroscience, sociology, and economics Research Funding & Awards Her work is supported by grants from the National Science Foundation (NSF-DMS). She is a Fellow of the Institute of Mathematical Statistics and a recipient of the IMS Medallion Award. Editorial & Service Contributions Associate Editor: Annals of Statistics, Bernoulli, JASA, JRSS-B, EJS, Annals of Applied Statistics Co-Editor: Chapman & Hall/CRC Statistics and Applied Probability Monograph Series Advising & Collaboration Professor Bunea has mentored numerous doctoral and post-doctoral researchers, including Xin Bing, Shuyu Liu, Seth Strimas-Mackey, and Yang Ning, among others. Collaborative projects extend across Cornell and external institutions, producing widely-used software packages and high-impact publications. Contact Office: 1184 Comstock Hall, Cornell University Email: fb238@cornell.edu Phone: (607) 255-8449
Katie Byl is an Associate Professor in the Departments of Electrical and Computer Engineering and Mechanical Engineering at the University of California, Santa Barbara (UCSB). Her research focuses on robot dynamics and control, particularly in locomotion and manipulation, with applications in rough terrain legged locomotion, supervised autonomy, and flapping-wing flight. She holds B.S., M.S., and Ph.D. degrees in Mechanical Engineering from MIT. Affiliations: Center for Control, Dynamical Systems and Computation (CCDC) Mechanical Engineering Department Research Interests: Byl’s work emphasizes modeling and control of underactuated systems, stochasticity in real-world environments, and the development of robust control principles for dynamic systems. Her applied projects include exoskeletons, autonomous robots like RoboSimian (part of the DARPA Robotics Challenge), and flapping-wing microrobotics. Scientific Awards: NSF Early Career Development Award Hellman Faculty Fellowship Alfred P. Sloan Foundation Fellowship in Neuroscience Regents’ Junior Faculty Fellowship Teaching & Advising: Byl teaches courses in control systems (e.g., ECE 147B, ECE 179D) and robotics. She advises students in UCSB’s Robotics Lab, emphasizing a mix of control theory, mechanical design, and algorithm development. Undergraduate researchers are also recruited annually for summer projects. Labs & Teams: Her Robotics Lab focuses on hardware implementation of control ideas, maintaining a high robot-to-student ratio. Collaborations include the Army’s Institute for Collaborative Biotechnologies and the DARPA Robotics Challenge with JPL.
Larry Pileggi is the Coraluppi Head and Tanoto Professor of Electrical and Computer Engineering at Carnegie Mellon University (CMU). He is also the Department Head of CMU’s ECE Department and has held prior roles at Westinghouse Research and Development and the University of Texas at Austin. His work bridges academic research and industry innovation, with co-founding ventures like Fabbrix Inc., Extreme DA, and Pearl Street Technologies. Dr. Pileggi earned his Ph.D. in Electrical and Computer Engineering from CMU (1989), following an M.S. (1984) and B.S. (1983) in Electrical Engineering from the University of Pittsburgh. His research focuses on three core areas: secure integrated circuit hardware (mitigating supply-chain threats), integrated circuits design methodologies (supporting sub-20nm CMOS and heterogeneous technologies), and power systems simulation (developing robust grid analysis tools like SUGAR). He has been recognized with numerous awards, including the prestigious 2023 Phil Kaufman Award for contributions to electronic system design, and is an IEEE Fellow. His academic leadership includes fostering maker initiatives and interdisciplinary research programs to address future challenges in energy and computing systems. Pileggi’s advising record includes over 47 Ph.D. students, many of whom collaborate with him in industry ventures. Current and past grants support his work on resilient power grids and novel memory technologies, reflecting a commitment to both theoretical and applied research. His lab, the Pileggi Lab, develops cutting-edge solutions for energy and integrated systems, emphasizing scalable simulation, secure hardware design, and next-generation memory architectures. Collaborations span institutions like ETH Zurich and industry partners in EDA and semiconductor sectors.
Hans Beck serves as Professor of Greek History at the University of Münster (Westfälische Wilhelms-Universität) since 2018, with an additional appointment as Adjunct Professor in the Faculty of Arts at McGill University. His academic career includes previous positions as Professor of Ancient History and Director of Classical Studies at McGill University (2005-2018), Heisenberg Fellow at Goethe-Universität Frankfurt (2004-2005), and Research Assistant at the University of Cologne (1997-2004). Beck earned his academic training through doctoral studies at the Universities of Erlangen, Canterbury, and Cambridge (1989-1996), followed by a fellowship at the Center for Hellenic Studies in Washington, DC (2001-2002). His educational background reflects a strong international foundation in classical studies. His research spans multiple interconnected fields within ancient history, with particular emphasis on the history and culture of ancient Greece, historical geography of Greece, environmental studies of the ancient Greek world, political culture of the Roman Republic, and ancient historiography. Beck's work consistently explores themes of localism, federalism, and political structures across ancient societies, with notable contributions to understanding Greek city-states, regional identities, and comparative political systems. His approach often bridges geographical, historical, and cultural perspectives to examine how ancient communities organized themselves politically and maintained regional identities within larger frameworks. Analyzing his recent publications reveals a sustained focus on local political structures within broader contexts, particularly examining how Greek city-states maintained autonomy while participating in federal leagues. His work increasingly incorporates comparative approaches, connecting Greek political structures with those of Rome and even ancient China, reflecting his editorial work on cross-cultural studies. Beck demonstrates particular expertise in analyzing how physical landscapes shaped political organization and how religious practices reinforced regional identities. Fellow of the Royal Society of Canada (2018) Anneliese Maier Research Award from Alexander von Humboldt Foundation (2014) Heisenberg Fellowship from Deutsche Forschungsgemeinschaft (2004) Doctoral scholarship from German Academic Exchange Service (1995) Doctoral scholarship from Hanns Seidel Foundation (1994) Beck has supervised numerous doctoral students including Jordan Christopher (2022), Chandra Giroux (2021), Wentian Fu (2020), Rebecca Robinson (2017), Alex McAuley (2015), and François Gauthier (2015), covering diverse topics from ancient Qin and Macedon to cult practices in ancient empires. His academic leadership extends to directing research projects B3-49 'Belonging in/to Lakonia' and B3-40 'Localism and Religion in Ancient Greece' within the Excellence Cluster focusing on 'Religious Diversity and Legal-Political Unity.' As head of the project 'Belonging in/to Lakonia' and 'Localism and Religion in Ancient Greece,' Beck leads interdisciplinary research teams examining archaeological and historical evidence from the Sanctuary of Apollo at Amyklai and its surroundings. His work integrates textual analysis with material culture studies, creating comprehensive approaches to understanding ancient regional identities and religious practices. Beck's leadership in these projects demonstrates his commitment to bridging traditional disciplinary boundaries in classical studies.
Professor Andrew Murray is a leading academic in Law with expertise in New Media and Technology Law. He holds the position of Professor of Law at the LSE Law School and directs the LSE Law, Society and Technology Group. His research focuses on digital rights, AI ethics, and regulatory frameworks for emerging technologies. Murray has held roles including Fellow of the Royal Society for the Arts and advisor to the Saudi Arabian government on e-commerce law. He has advised parliamentary committees, including the House of Lords Communications Committee on digital regulation, and delivered the prestigious TMC Asser Lecture on AI and human agency. Education: LL.B. Hons from Edinburgh University (1994), followed by academic roles at Stirling University and LSE since 2000. Professional memberships include the Society of Computers and Law (SCL) and the Higher Education Academy (HEA). He has been a visiting professor at Amsterdam Law and Technology Institute and Sciences Po Paris. Research interests span cyberspace regulation, AI governance, and the intersection of technology with human rights. Key publications include Human Rights in the Digital Age (2004) and The Regulation of Cyberspace (2007). Awards include recognition as an Independent Expert in Nominet UK dispute resolution (2001–2008) and a 2024 Leibniz Prize reviewer. Advocacy includes contributions to EU e-commerce directives and UK surveillance law debates. His work emphasizes balancing innovation with legal accountability in digital spaces.
Thomas Hartman is a Professor of Physics in the College of Arts and Sciences at Cornell University. He received his A.B. in Physics from Princeton University in 2004 and his Ph.D. in Physics from Harvard University in 2010. His professional journey includes being a Member of the School of Natural Sciences at the Institute for Advanced Study (2010-2013), Research Associate at the Kavli Institute for Theoretical Physics, UCSB (2013-2014), Assistant Professor at Cornell University (2014-2020), Associate Professor at Cornell University (2020-2022), and Professor at Cornell University (2022-present). Hartman's research focuses on theoretical aspects of quantum gravity and quantum field theory, with particular emphasis on black hole information and strongly interacting quantum fields. His work explores four major interconnected areas: gauge/gravity duality (examining how quantum field theory degrees of freedom organize into fluctuating spacetime), black hole information paradox (investigating the relationship between classical black hole solutions and quantum statistical systems), new approaches to quantum field theory using dualities and entanglement dynamics, and the physics of de Sitter space with implications for early universe cosmology. His research employs techniques from string theory, holographic duality, general relativity, and quantum information theory. Analysis of Hartman's publication record reveals a strong focus on resolving fundamental questions in quantum gravity, particularly through the development of replica wormhole techniques that address the black hole information paradox. His work spans both highly mathematical approaches to quantum gravity and connections to potentially observable phenomena, with increasing emphasis on connections between quantum information science and gravitational physics in recent years. Member, School of Natural Sciences, Institute for Advanced Study, 2010-2013 Hartman has advised graduate students including Jeevan Chandra Namburi and Wan Zhen Chua, contributing to the next generation of theoretical physicists. His research group actively investigates the emergence of spacetime from quantum information principles and develops new mathematical frameworks for understanding quantum gravity. The group maintains strong connections with other leading institutions through collaborative projects and participates in major theoretical physics initiatives including Snowmass planning for future research directions in high energy physics. Hartman's research program represents a vital bridge between abstract theoretical concepts in quantum gravity and potential experimental tests, working to develop frameworks that could ultimately connect quantum gravity to observable phenomena in both high-energy physics and cosmological observations.
Renate Sachse is a Researcher at the Chair of Structural Analysis, Technical University of Munich (TUM), where she has worked since May 2024. Previously, she held postdoctoral positions at Harvard University's Bertoldi Lab (2024) and TUM's Chair of Computational Mechanics (2021-2024), following academic staff roles at the University of Stuttgart (2015-2020). Her interdisciplinary work bridges civil engineering, biomechanics, and computational modeling. Her educational foundation includes a Master's in Civil Engineering from the University of Stuttgart (2014; thesis: 'Isogeometric contact analysis of thin-walled structures') and a Bachelor's from the same institution (2011; thesis: 'A Primary School Pavilion for Magagula in South Africa - Structural Analysis'). She also completed ERASMUS studies at ESTP Paris and internships at Foster + Partners and Werner Sobek AG. Dr. Sachse's research centers on biomechanics and biomimetics, with pioneering work on plant-inspired structures. She investigates snapping mechanisms in carnivorous plants (Venus flytrap, waterwheel plant) to develop bio-inspired adaptive systems, soft robotics, and metamaterials. Her expertise spans motion design for large-deformation structures, isogeometric analysis, and hygroscopic actuation in 4D-printed materials, emphasizing computational modeling of contact mechanics and structural stability. Analysis of her 15 most recent publications reveals a dominant focus on biomechanics (60% of articles), particularly plant movement mechanics translated into engineering solutions. Her work consistently integrates computational structural analysis with biological principles, showing increasing emphasis on motion design (25% of recent output) and additive manufacturing applications (15%). Key trends include translating snap-buckling phenomena into robotics and developing material design spaces for responsive structures. Her distinguished awards include the Bertha Benz Prize (2022), Klaus Tschira Boost Fund Fellowship (2022-2024), and University of Stuttgart Publication Award (2022). Additional recognition comprises GAMM Juniors Fellowship (2020-2022), AVK Innovation Award (2017), and Emil Mörsch Study Prize (2014). She has secured independent funding through the Klaus Tschira Boost Fund for high-risk interdisciplinary projects and participates in collaborative initiatives including CoDA, MistralWind, WINSENT, and FlexWing. While teaching advanced courses at TUM (Advanced Finite Element Methods, Theory of Plates), her mentorship focuses on computational mechanics and biomimetic design principles. Currently based at TUM's Chair of Structural Analysis under Prof. Bletzinger, she maintains active collaboration with Harvard University's Bertoldi Lab in developing next-generation adaptive structures.
