Sarah Dean is an Assistant Professor in the Computer Science Department at Cornell University, affiliated with the College of Engineering. Her research focuses on the interplay of machine learning, optimization, and dynamics in real-world systems, particularly in control theory, recommendation systems, and ethical AI. Education: PhD in EECS, University of California, Berkeley (2021) Postdoctoral Research, University of Washington (2021-2022) Research Interests: Data-driven control systems, reinforcement learning, recommendation systems, user dynamics, algorithmic fairness, and the societal impacts of AI. She emphasizes foundational understanding of how learning systems interact with human and social processes. Recent Work Trends: Her articles explore topics like bilinear system identification, user participation dynamics in recommendation platforms, and ethical considerations in AI development. Recent work includes harm mitigation strategies and mathematical modeling of AI-human feedback loops. Awards: AI2050 Early Career Fellow (2024) Best Paper at ICML 2018 (Delayed Impact of Fair Machine Learning) Best Student Paper in Imaging Systems (OSA Congress 2018) Advising & Labs: Advises over 15 graduate and undergraduate students. Leads research on interactive ML systems, with contributions to projects like the 'MSGD' repository for streaming data learning. Active in the GEESE group, promoting socially responsible computing.
Professor Harry E. Ruda holds the Stanley Meek Chair in Advanced Nanotechnology at the University of Toronto's Faculty of Applied Science and Engineering. He directs the Centre for Advanced Nanotechnology and leads the Electronic-Photonic Materials Group. His research spans semiconductor nanostructures, focusing on nanoelectronics and nanophotonics, with notable contributions to nanowire growth, quantum transport, and plasmonic effects. Education: B.Sc. in Physics, Imperial College London Ph.D. in Physics, MIT His research interests include: Semiconductor nanowire growth via VLS process Quantum transport and spintronics Nonlinear optical effects in quantum dots/nanowires Surface state control through passivation Photonic crystal structures for optical devices Carrier dynamics in low-dimensional systems Recent publications highlight advancements in InAs nanowire sensors, Coulomb impurity effects, photonic crystal design, and hybrid superconducting/semiconductor devices. His work bridges fundamental electron dynamics and applied quantum technologies. Scientific Awards: Fellow, Canadian Academy of Engineering Fellow, Royal Society of Canada Fellow, Institute of Physics (UK) Fellow, Institute of Nanotechnology Fellow, Institution of Engineering and Technology Fellow, Institute of Materials, Minerals and Mining Fellow, Canadian Academy of Engineering Teaching: MSE335: Materials Physics MSE490: Professional Ethics and Practice MSE1023: Quantum Transport
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.
Professor Todd Squires is a distinguished faculty member in the Department of Chemical Engineering at the University of California, Santa Barbara, within the Robert Mehrabian College of Engineering. His research focuses on the fundamental principles of transport phenomena as applied to interfaces, membranes, and complex fluids, employing theoretical, computational, and experimental approaches to address significant challenges in micro-scale fluid mechanics. Dr. Squires' educational background includes: BS in Physics, UCLA (1995) BA in Russian Language and Literature, UCLA (1995) PhD in Physics, Harvard University (2002) His research interests span microfluidics and electrokinetics, active and nonlinear microrheology of complex materials, polymer dynamics and sensors, with particular emphasis on non-linear electrokinetic flows, interfacial rheology, and the self-assembly of nanostructured materials. His work bridges fundamental fluid mechanics with practical applications in microfluidic devices, energy storage, and biomedical systems, demonstrating the versatility of this fascinating field. Analysis of Professor Squires' recent publications reveals a consistent focus on interfacial phenomena, with particular attention to the rheological properties of fluid interfaces, particle dynamics in complex fluids, and novel microfluidic techniques for measuring and manipulating these systems. His research demonstrates strong interdisciplinary connections between chemical engineering, physics, and materials science, with applications spanning energy storage, biomedical engineering, and environmental systems. Professor Squires has received numerous prestigious awards and honors: 2018 Robert W. Vaughan Lecture in Chemical Engineering, Caltech 2015 Elected Fellow of the American Physical Society 2013 Mid-Career Award, American Electrophoresis Society 2012 The Dudley Saville Memorial Lecture at Princeton 2010 Pierre Gilles de Gennes Prize 2010 Allan P. Colburn Memorial Lectureship, University of Delaware 2009 Francois Frenkiel Award for Fluid Mechanics 2009 Camille Dreyfus Teacher-Scholar Award 2008 Beckman Young Investigator 2007 NSF CAREER Award 2005 'Rising Star' - Chronicle of Higher Education As principal investigator of the Squires Group, Professor Squires leads a dynamic research team that combines experimental, theoretical, and computational approaches to investigate transport phenomena at interfaces. His work has been supported by major funding agencies including the National Science Foundation, with his CAREER award indicating early recognition of his potential as both researcher and educator. While specific grant details aren't provided in the source material, his extensive publication record and prestigious awards suggest robust and sustained research funding. The Squires Group maintains state-of-the-art laboratory facilities for studying micro-scale fluid mechanics, including specialized equipment for microrheology measurements, microfluidic device fabrication, and interfacial characterization. Their research environment fosters collaboration across disciplines, with connections to materials science, physics, and biomedical engineering researchers at UCSB and beyond.
Prof. Gabriela Hug is a Full Professor at ETH Zurich's Department of Information Technology and Electrical Engineering, serving as Deputy Head of the Department and Deputy Head of the Power Systems and High Voltage Lab. She leads the Energy Science Center (ESC) and holds adjunct roles at Carnegie Mellon University. Her research focuses on modeling, control, and optimization of electric power systems for sustainable energy transitions. Education: PhD in Information Technology and Electrical Engineering, ETH Zurich (2004–2008) MSc in Information Technology and Electrical Engineering, ETH Zurich (1999–2004) Research Interests: Her work addresses challenges in smart grid integration, renewable energy systems, and advanced control strategies. Key areas include vehicle-to-grid technologies, distribution network optimization, and energy storage system planning. She emphasizes data-driven approaches and collaborative frameworks for grid resilience and flexibility. Key Achievements: Recipient of the 2019 ALEA Award (ETH Zurich) NSF Career Award (2013) IEEE Outstanding Young Engineer Award (2013) Leadership & Roles: Co-Director, NCCR Automation (Swiss National Centre of Competence in Research) Board Chair, Energy Science Center (ESC) Adjunct Faculty, Carnegie Mellon University Labs & Teams: Power Systems Laboratory (ETH Zurich) Energy Science Center (multi-disciplinary research hub)
Pieter van Goor is a Research Fellow at the Australian National University (ANU), affiliated with the School of Engineering and the Systems Theory and Robotics (STR) group. He holds a PhD in Control Theory (completed 2022) and dual bachelor's degrees (BEng/BSc, 2018). His research focuses on equivariant systems theory, state estimation, and robotics applications. Key contributions include equivariant observer design, Lie group-based control, and geometric data fusion. Education: Bachelor of Engineering (Research & Development) (Honours) in Mechatronics (ANU, 2018) Bachelor of Science in Mathematics (ANU, 2018) PhD in Control Theory (ANU, 2022) Research Interests: Equivariant systems theory, nonlinear control, robotics applications, state estimation on Lie groups, sensor fusion, and geometric control methods. His work emphasizes symmetry exploitation in filter design and observer construction for systems with inherent geometric structures. Grants & Collaborations: Active collaborations include work with Robert Mahony and institutions like the IEEE. Research spans theoretical frameworks (e.g., equivariant filters) and applied systems (e.g., ArduPilot autopilot, event cameras). Labs/Teams: Member of the Systems Theory and Robotics (STR) group at ANU, focusing on advanced control theory and robotics.
Matthew O'Toole is an Associate Professor at Carnegie Mellon University's School of Computer Science, holding joint appointments in the Robotics Institute and Computer Science Department. His research focuses on computational imaging, integrating optics, electronics, and computational processing to innovate visual information capture and display. Education: PhD (Computer Science, University of Toronto, 2016), MSc (2009), BSc (Honors Computer Science and Mathematics, University of British Columbia, 2007). Prior roles include Banting Postdoctoral Fellow at Stanford University and visiting scholar at MIT Media Lab's Camera Culture group. Research interests emphasize programmable imaging systems, transient imaging, non-line-of-sight sensing, and holographic displays. Key innovations include vibration sensing via dual-shutter optics and radar super-resolution for autonomous vehicles. Awards include runner-up best paper recognitions at ICCV 2007, CVPR 2014, and SIGGRAPH 2017 dissertation honors. Advisees include Dorian Chan and Arjun Teh. Grants supported by Canadian Banting Fellowships. Active in workshop organization (CVPR Computational Cameras 2016-2017) and course development on computational imaging at SIGGRAPH 2014. Labs/Teams: Leads research in computational imaging and robotics at CMU, collaborating with industry partners like NVIDIA and MDA. Current projects explore LiDAR-radar fusion, holographic projection systems, and dynamic scene reconstruction.
Alexis Battle is an Associate Professor at Johns Hopkins University with appointments in Biomedical Engineering , Computer Science , and Genetic Medicine (secondary). She directs the Malone Center for Engineering in Healthcare and serves as Deputy Director of the Data Science and AI Institute . Educated at Stanford University (PhD in Computer Science, 2013), Battle transitioned to academia after leadership roles at Google. Research Focus: Battle’s work bridges genomics and machine learning , emphasizing the impact of genetic variation on human health. Her lab develops tools like Watershed to predict functional effects of rare variants, aiming to enhance rare disease diagnosis. Key themes include non-coding DNA analysis , personalized genomics , and systems biology , with applications in cardiovascular disease and neurodegenerative disorders . Publications & Awards: Over 60 peer-reviewed articles in journals like Nature , Science , and Genome Biology , with recent emphasis on single-cell transcriptomics , multiomics integration , and telomere biology . Recipient of the President’s Frontier Award (2022), Microsoft Investigator Fellowship (2019), and Searle Scholar (2016). Scientific Awards: 2022 President’s Frontier Award 2019 Microsoft Investigator Fellowship 2019 Johns Hopkins Discovery Award 2017 Johns Hopkins Catalyst Award 2016 Searle Scholar Advising & Funding: Mentors 11 PhD students, 3 undergraduates, and postdoctoral fellows. Her research is funded by NIH, Searle Scholars, and institutional grants. The Battle Lab collaborates on projects like the GTEx Consortium , focusing on gene regulation and clinical genomics .
Professor Simo Särkkä holds a position in Sensor Informatics and Medical Technology at the Department of Electrical Engineering and Automation (EEA), Aalto University. His research focuses on multi-sensor data processing, Bayesian filtering, machine learning, and their applications in medical technology, brain imaging, and inverse problems. He leads research groups including the Helsinki Institute for Information Technology (HIIT) and Sensor Informatics and Medical Technology. His work bridges theoretical advancements in probabilistic methods with practical implementations in healthcare and engineering. Key research interests include Gaussian processes, stochastic differential equations, quantum machine learning, and signal processing. He has contributed to advancements in algorithms for nonlinear state-space models, parallel computing techniques, and medical imaging technologies such as scatter correction in CT scans. His methodologies are applied across domains like autonomous systems, robotics, and bioengineering. Notable publications span topics like quantum-assisted Gaussian regression, physics-informed machine learning for industrial processes, and parallel-in-time numerical methods. His work emphasizes computational efficiency and robustness in high-dimensional and real-time systems.
Professor Jiyuan Tu is a Professor in the Department of Mechanical and Automotive Engineering at RMIT University's School of Engineering. He specializes in computational fluid dynamics (CFD), multiphase flows, and their applications in renewable/nuclear energy, biomedical engineering, and built environment systems. His research has led to over 500 peer-reviewed articles, 9 books, and $10M+ in ARC grants. He has supervised over 50 postgraduate students and received prestigious awards such as the RMIT Research Excellence Award (2012) and Fulbright Senior Scholar Award (2008). Research interests include CFD modelling of bioaerosol transport, drug delivery systems, and thermal energy storage. He pioneered numerical models for multiphase flows, contributing to software implementations in industries. Notable works include books on CFD and multiphase flow analysis, and leadership in international conferences like COBEE 2018. He holds honorary professorships at Tsinghua University and is Editor-in-Chief of the Experimental and Computational of Multiphase Flow journal. Industry experience includes roles at ANSTO (1996-2001). Awards span fellowships from JSPS, KOSEF, and Fulbright programs. Grants include ARC Discovery, Linkage, and LIEF projects. His work ranks him among the world’s top researchers in pebble bed reactors and airborne infection studies (SciVal 2016-2025).
Kenneth McLaughlin is the Evelyn and John G. Phillips Distinguished Chair in Mathematics at Tulane University's School of Science & Engineering. He holds a Ph.D. and B.A. in Mathematics from New York University (1994 and 1989). Prior to Tulane, he served as faculty at the University of North Carolina, Chapel Hill, the University of Arizona, Universidade Federal de Brasília, and Colorado State University, where he also held leadership roles as Department Head and Chair. His research focuses on integrability, applying techniques across mathematics to study complex systems and phenomena. He has held visiting positions at institutions worldwide, including France, Italy, Brazil, Belgium, and the UK. McLaughlin’s research spans integrable systems, nonlinear dynamics, and asymptotic analysis. His work often involves the Riemann-Hilbert problem approach, orthogonal polynomials, and random matrix theory. Notable contributions include studies on soliton gases, the KdV equation, and universality in quantum operator dynamics. His recent articles explore topics such as asymptotic behavior of polynomials, soliton gas condensation, and hydrodynamic limits in integrable systems. McLaughlin’s academic career is marked by interdisciplinary collaboration and international research engagement.
Dr. Michael Mühlebach is a Lecturer at the Department of Information Technology and Electrical Engineering, ETH Zurich, and affiliated with the Max Planck Institute for Intelligent Systems in Tübingen, Germany. He holds a Bachelor's (2010) and Master's (2013) from ETH Zurich, recognized with awards for academic excellence in Robotics, Systems, and Control. His research focuses on multibody dynamics, nonlinear system control, and model predictive control, with applications in robotics and aerospace systems. His work spans theoretical advancements in variational integrators and practical implementations in systems like the Cubli (a reaction wheel-based 3D inverted pendulum) and flying platforms for ducted fan actuation. Publications highlight contributions to model predictive control schemes with stability guarantees, nonlinear analysis, and distributed event-based state estimation. Key awards include the Outstanding D-MAVT Bachelor Award and Willi-Studer Prize. His research integrates control theory with real-world applications, emphasizing both foundational mathematics and engineering implementations. No grants or lab affiliations are explicitly listed in the provided text.
Fatma Kılınç-Karzan is an Associate Professor of Operations Research at Carnegie Mellon University's Tepper School of Business, with a courtesy appointment as Associate Professor of Computer Science. She is also affiliated with the Algorithms Combinatorics and Optimization (ACO) PhD Program and was a Visiting Scientist at Berkeley's Simons Institute for the Theory of Computing during Fall 2017. Her educational background includes a PhD from Georgia Institute of Technology's H. Milton Stewart School of Industrial & Systems Engineering with a minor in Mathematics, supervised by Prof. Arkadi Nemirovski. She earned her B.S. and M.S. degrees from the Industrial Engineering Department of Middle East Technical University with a minor in Information Systems. Dr. Kılınç-Karzan's research spans mathematical optimization with emphasis on convex and non-convex optimization theory, algorithms, and applications. Her work bridges theoretical foundations with practical implementations in optimization under uncertainty (robust optimization, chance constraints, distributionally robust optimization), machine learning (preference learning from limited data), and business analytics. She develops foundational theory for large-scale optimization problems with applications in decision making under uncertainty and high-dimensional statistical inference. Analysis of her recent publications reveals a strong focus on convex hull characterizations, semidefinite programming relaxations, distributionally robust optimization, and online convex optimization frameworks. Her work demonstrates increasing integration of optimization theory with machine learning applications, particularly in developing data-driven approaches for decision making under uncertainty. NSF CAREER Award (2015) INFORMS Optimization Society Young Researcher Prize (2015) INFORMS Junior Faculty Interest Group (JFIG) Best Paper Award (2014) BP Junior Faculty Chair (2014-2015) Faculty Giving Chair (2012-2013) Wimmer Fellowship (2012-2013) Dr. Kılınç-Karzan has successfully mentored numerous PhD students who have received prestigious awards, including the 2021 INFORMS Optimization Society Best Student Paper (1st prize) and multiple honorable mentions. Her research has been supported by significant grants including an NSF CAREER Award, an ONR grant (with S. Küçükyavuz), and an AFOSR grant. She serves on editorial boards for Mathematical Programming, Operations Research, Mathematics of Operations Research, and other leading journals, and has held leadership positions in professional societies including the Mathematical Optimization Society and INFORMS Computing Society. Through her affiliations with CMU's Tepper School, Computer Science Department, and ACO Program, she collaborates across disciplines to advance optimization theory and its applications. Her professional service includes committee chair roles for major INFORMS competitions and program committee leadership for international optimization conferences.
David A. Hsieh is the Bank of America Professor of Finance at the Fuqua School of Business, Duke University, where he has been a faculty member since 1993. Previously, he served as Associate Professor and Assistant Professor at the University of Chicago's Graduate School of Business from 1981-1989. His extensive research has significantly contributed to the understanding of hedge funds, financial risk management, and nonlinear dynamics in financial markets. Massachusetts Institute of Technology, Ph.D. in Economics, 1981 Yale University, B.S. in Economics and Mathematics, 1976 (Summa Cum Laude, Phi Beta Kappa) Phillips Academy, Andover, 1972 (Cum Laude) Dr. Hsieh's research primarily focuses on the dynamics of asset prices and their implications for financial risk management. He has made significant contributions to understanding risk and return characteristics in hedge funds and commodity funds, pioneering work on nonlinear dynamics applications to financial markets. His research has evolved from early work on exchange rates and volatility modeling to more recent comprehensive analyses of hedge fund strategies, performance measurement, and industry structure. Hsieh's publication history reveals a clear progression from foundational work on nonlinear dynamics in financial markets to increasingly sophisticated analyses of hedge fund strategies and risk characteristics. His recent work, often in collaboration with William Fung and other prominent finance researchers, has focused on mega hedge fund firms, franchise value in the industry, and the evolution of hedge fund strategies toward more index-like products. The research consistently combines rigorous theoretical frameworks with robust empirical analyses across diverse market conditions. CAIA Award for Excellence in Alternative Investment Research (2015) CFA Institute Graham and Dodd Award of Excellence (2004) Bank of America Faculty Award (2002) Duke Cross-Continent Executive MBA Teaching Excellence Award (2002) Fischer Black Memorial Foundation Robert J. Schwartz Memorial Prize (1999) Smith Breeden First Prize (1990) Yale Science and Engineering Association High Scholarship Award (1976) Russell Henry Chittenden Prize (1976) Dr. Hsieh has served as a consultant for the International Monetary Fund (2007-2016) and the Bank for International Settlements (1998), and as a Visiting Scholar at both the International Monetary Fund and the Board of Governors of the Federal Reserve System. His editorial service includes Finance Editor for Management Science (2003-2009) and Associate Editor roles for several leading finance journals. He has developed extensive research resources including a Hedge Fund Data Library that has become widely used in academic and industry research.
Lourens Waldorp is an Associate Professor at the University of Amsterdam within the Faculty of Social and Behavioural Sciences , specifically the Department of Psychological Methods . His research focuses on network theory, causal inference, and statistical modeling in psychology and neuroscience. University of Amsterdam IAS Fellow (2024) His research interests include: Network psychometrics Causal inference in psychological models High-dimensional statistical methods Dynamical systems in psychopathology Graph theory applications Signal processing for biophysical data The trends in his recent publications center on causal modeling, network analysis of psychopathology, and statistical techniques for time-series data. He has developed methods for perturbation graphs, moderated network models, and dynamic intervention frameworks. Notable scientific awards : IAS Fellowship for 6 months (2024) He advises PhD students like Kyra Evers and collaborates with researchers across disciplines, including J. Haslbeck , D. Borsboom , and O. Ryan . His work intersects with network theory and clinical psychology .
