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Stefanie MuellerView profile

Associate Professor

• Human-Computer Interaction
• Computational Fabrication
• 3D Printing
• +7 more

Stefanie Mueller is the TIBCO Career Development Associate Professor at MIT's Electrical Engineering and Computer Science Department, with joint affiliation in Mechanical Engineering. She leads the HCI Engineering Group at the Computer Science and Artificial Intelligence Laboratory (CSAIL), focusing on advancing fabrication techniques through hardware/software innovations that enable novel object interactions. Develops computational fabrication methods combining photochromic dyes, lenticular lenses, birefringent materials, and optical illusions Co-chaired ACM CHI 2023 and ACM UIST 2020 program committees Recipients of 9 MIT EECS Best Undergraduate Researcher Awards among mentees Her research spans four key directions: Appearance-changing Objects: Photo-Chromeleon (ACM UIST 2019), Lenticular Objects (ACM UIST 2021), and Polagons (ACM CHI 2023) demonstrate reprogrammable surfaces through advanced materials and optical engineering. Tracking Systems: InfraredTags (ACM CHI 2022) and G-ID (ACM CHI 2020) enable passive object tracking via infrared markers and slicing artifacts. Embedded Sensing: MechSense (ACM CHI 2023) and Sprayable User Interfaces (ACM CHI 2020) integrate sensing capabilities into complex geometries. Curved Surface Prototyping: FlexBoard (ACM CHI 2023) and CurveBoard (ACM CHI 2020) develop specialized tools for non-planar electronics. Her recent publications focus on functionality segmentation (UIST 2023), fluorescent markers (UIST 2023), and machine-knitted haptics (UIST 2023). These works combine machine learning, material science, and interactive design principles to push fabrication boundaries. Scientific recognition includes: 2022 MIT Technology Review Innovators Under 35 2020 Microsoft Research Faculty Fellowship 2020 Alfred P. Sloan Research Fellowship 2019 ACM UIST Best Paper Award 2019 NSF CAREER Award 2018 MIT EECS Outstanding Educator Award 2017 Forbes 30 Under 30 in Science Mentoring 9 PhD students and over 20 master's students, her lab has produced 20+ publications at top HCI conferences. She redesigned MIT's 6.810 Engineering Interactive Technologies course during the pandemic, maintaining hands-on learning through home electronics kits and Slack-based collaboration.

David BindelView profile

Associate Professor

• Applied Numerical Linear Algebra
• Eigenvalue Problems
• Network Analysis
• +5 more

David Bindel is an Associate Professor in the Department of Mathematics at Cornell University, affiliated with the College of Arts and Sciences, College of Engineering, and Cornell Ann S. Bowers College of Computing and Information Science. He earned his Ph.D. in Mathematics from the University of California, Berkeley in 2006. His research focuses on applied numerical linear algebra, eigenvalue problems, and their applications in plasma physics, network analysis, and nonlinear systems. He develops methods for analyzing complex systems, including magnetic confinement in stellarators, stability of MHD systems, and community detection in networks. His work bridges theoretical foundations with practical computational tools, such as formal verification of linear algebra algorithms and scalable Gaussian process models. Bindel’s research explores the interplay between structure and computation, leveraging eigenvalue analysis to address challenges in computer vision, opinion dynamics, and engineering design. He has contributed to advancements in numerical methods for large-scale systems, including iterative solvers, spectral approximation techniques, and stochastic optimization. His interdisciplinary approach spans applied mathematics, computer science, and physics, with applications in fusion energy, machine learning, and network science. Recent work highlights include high-order expansions for magnetic confinement, adaptive filtering for dynamical systems, and Bayesian optimization strategies. His publications emphasize rigorous analysis alongside computational scalability, addressing both theoretical and practical aspects of modern scientific computing. Despite no explicitly listed awards, his contributions reflect significant impact in his fields.

Jeremy HahnView profile

Assistant Professor

• Algebraic Topology
• Structured Ring Spectra
• Chromatic Homotopy Theory
• +4 more

Jeremy Hahn is an Assistant Professor at the Massachusetts Institute of Technology (MIT), affiliated with the Department of Mathematics within the School of Science. His research focuses on Algebraic Topology, particularly structured ring spectra, chromatic homotopy theory, and equivariant homotopy theory. Supported by grants from the Sloan Foundation and the National Science Foundation (DMS-1803273), his work has contributed to foundational advances in topological K-theory, algebraic K-theory, and manifold topology. Education details are not explicitly listed, though past teaching roles at Harvard University suggest prior academic training. His research interests span topics including: Structured ring spectra constructions (e.g., truncated Brown-Peterson spectra) Chromatic redshift phenomena and algebraic K-theory Equivariant orientations and C_p actions Applications of homotopy theory to manifold classification Notable recent work includes counterexamples to Ravenel's telescope conjecture, advancements in motivic filtrations of topological cyclic homology, and the construction of multiplicative structures on classical spectra. Collaborations with researchers such as Robert Burklund, Dylan Wilson, and Allen Yuan reflect his active engagement in the global topology research community. Teaching includes advanced courses like Algebraic Topology I (18.905) and past roles as a teaching assistant for Linear Algebra (18.06) and multivariable calculus at MIT. His research has been supported by multiple NSF grants and the Sloan Fellowship, indicating sustained academic excellence and leadership in the field.

• Geometric Topology
• Geometric Group Theory
• Low-Dimensional Topology
• +6 more

Prof. Harry Hyungryul Baik is a Tenured Associate Professor at KAIST's Department of Mathematical Sciences since 2017. He holds a PhD from Cornell University (2014) and a B.S. from KAIST (2009), advised by William Thurston, John Hubbard, and Dylan Thurston. His research focuses on geometric topology, geometric group theory, and low-dimensional topology, with notable contributions to mapping class groups, Kleinian groups, and Teichmüller theory. Education: PhD in Mathematics (Cornell, 2014), B.S. in Mathematics (KAIST, 2009). Key research areas include asymptotic translation lengths, laminar groups, and circular orders of groups. He co-leads the KAIST-KIAS joint research group 2K-GATE as Director, emphasizing collaboration between topologists. Research highlights: Characterization of Fuchsian groups via laminations, unsmoothability of mapping class group actions on 1-manifolds, and exponential torsion growth in random 3-manifolds. His work bridges topology with dynamical systems and geometric group theory, often involving collaborations with institutions like KIAS and MPIM. Awards include the Sangsan Prize (2018), Young-KAST membership (2020–2023), and multiple grants from Samsung and POSCO. He advises 7 PhD students and has mentored 15+ alumni, many of whom hold postdoc positions globally. His lab actively hosts conferences like the KAIST Geometric Topology Fair. Labs/Teams: Director of 2K-GATE (KAIST-KIAS), core member of the KAIST Topology Research Group, collaborator with international networks including the Harvard-MIT-Princeton topology axis.

Burak OzdoganlarView profile

Professor

• Manufacturing Processes
• Biomedical Engineering
• Materials Science
• +7 more

Burak Ozdoganlar is a Ver Planck Endowed Chair Professor of Mechanical Engineering at Carnegie Mellon University (CMU) and Associate Director of the Engineering Research Accelerator. He holds courtesy faculty positions in Biomedical Engineering and Materials Science and Engineering. Ozdoganlar earned his Ph.D. in Mechanical Engineering from the University of Michigan (1999), M.S. degrees from Ohio State University (1993, 1995), and a B.S. in Aeronautical Engineering from Istanbul Technical University (1991). Ph.D., Mechanical Engineering, University of Michigan (1999) MS, Mechanical Engineering, Ohio State University (1995) MS, Aeronautical and Astronautical Engineering, Ohio State University (1993) BS, Aeronautical Engineering, Istanbul Technical University (1991) Ozdoganlar’s research focuses on multi-scale manufacturing processes (macro/micro/nano), precision engineering , structural dynamics , and modal testing , with applications in biomedical device fabrication , microneedle arrays , soft electronics , and 3D ice printing for vascular networks. His work bridges computational modeling with experimental validation. Recent scientific awards include the 2023 AIMBE College of Fellows induction, ASME Fellow (2019), and NSF CAREER Award (2006). He served as interim CTO of the Advanced Robotics for Manufacturing (ARM) Institute and chaired the ASME-MED Manufacturing Equipment Technical Committee. Ozdoganlar leads projects in scalable manufacturing for implantable medical devices , bioelectric medicine , and wearable robotics . His lab develops 3D ice-printed vascular templates for tissue engineering and liquid metal circuits for soft electronics, funded by institutions like the Manufacturing Futures Institute and ARPA-H.

David LeighView profile

Professor

• Synthetic molecular machines
• Synthetic molecular knots and links
• Supramolecular chemistry

David Leigh is a Professor in Organic Chemistry at the University of Manchester , UK. He has held prestigious positions including the Sir Samuel Hall Chair (2014–present), Forbes Chair at the University of Edinburgh (2001–2012), and Chair of Synthetic Chemistry at the University of Warwick (1998–2001). His research focuses on synthetic molecular machines, supramolecular chemistry, and molecular knots. Fields of Scholarship : Synthetic molecular machines, Synthetic molecular knots and links, Supramolecular chemistry His work includes creating hydrogen-bonded molecular rotors , reversible rotary molecular motors , and artificial ribosome mimics . Article trends highlight nanotechnology , molecular engineering , and self-assembly advancements. Scientific Awards : Royal Society of Chemistry Pedler Award (2014), ERC Advanced Grant (2014), Bakerian Prize (2013), Tilden Prize (2010), Fellow of the Royal Society (2009), etc. Leigh has led groundbreaking projects funded by the European Research Council (2008, 2014) and held an EPSRC Senior Research Fellowship (2005–2010). His lab at the University of Manchester explores bottom-up molecular design and stimuli-responsive systems.

• Radar System Design
• Signal Processing
• MIMO Radar
• +6 more

Professor Kim Eun-hee is a faculty member in the Department of Defense Systems Engineering at Sejong University, specializing in advanced radar technologies and signal processing. Her work bridges theoretical research and practical applications in defense systems. Ph.D. in Mechanical Engineering (2004), KAIST M.Sc. in Engineering (1996), KAIST B.Sc. in Precision Engineering (1994), KAIST Her research focuses on radar system design, including airborne active phased array radar, automotive radar, broadband noise radar, and over-the-horizon radar. She explores waveform optimization, MIMO architectures, and signal processing algorithms to enhance radar performance in complex environments. Publications highlight her expertise in MIMO radar configurations, Doppler-insensitive waveforms, and machine learning integration for signal analysis. She leads industry-academic collaborations with organizations like Hanwha Systems and LIG Nex1. She contributes to technical committees, including the Sensor and Signal Processing Division of the Korean Society of Military Science and Technology. Her laboratory (Defense Radar Technology Laboratory) focuses on radar design, signal processing, and sensor integration.

Amilcare PorporatoView profile

Professor

• Ecohydrology
• Soil-Atmosphere Interaction
• Hydrologic Time Series
• +2 more

Amilcare Porporato is the Thomas J. Wu '94 Professor of Civil and Environmental Engineering at Princeton University, with joint appointment at High Meadows Environmental Institute. His research integrates hydrology, ecology, and thermodynamics to study soil-water interactions and sustainable resource management. Education includes: Ph.D. Polytechnic of Milan (1996) M.S. Civil Engineering, Polytechnic of Milan (1992) Research explores nonlinear hydrologic systems, soil moisture dynamics, ecohydrology, and environmental complexity using theoretical and experimental approaches. His work advances understanding of water-biota interactions across scales from pore-level processes to landscape evolution. Honors and Awards: Hydrologic Sciences Award, AGU Borland Lecturer American Geophysical Union Fellow Inaugural Landolt Chair, EPFL Teaches courses on Environmental Thermodynamics (ENV 385/CEE 385) and Ecohydrology (CEE 587/ENV 587).

Primoz SkrabaView profile

Professor

• Applied Topology
• Geometry
• Algebra
• +5 more

Dr. Primoz Skraba is a Professor in Applied and Computational Topology at the School of Mathematical Sciences, Queen Mary University of London. As Deputy Head of the Centre for Probability, Statistics and Data Science, he bridges theoretical topology with practical applications in data analysis, machine learning, and optimization. Education : PhD in Electrical Engineering from Stanford University (2009) Prior Roles : Positions at INRIA, France; Jozef Stefan Institute, Slovenia; University of Primorska; University of Nova Gorica His research focuses on applying topological methods to analyze complex data. Key areas include: Stability of persistence diagrams for quantitative control in finite sampling Variants of persistence (zig-zag, robustness, multiparameter) Algorithmic Complexity in computational topology Stochastic Topology for random geometric models (Poisson, Boolean) Recent publications emphasize persistent homology in random geometric complexes, universality theorems, and integrating topological methods into machine learning. He received grants from the Leverhulme Trust, EPSRC, and Alan Turing Institute for projects on topological universality and AI foundations. His advisee Gabryel Mason-Williams explores wireless sensor network applications of homology.

Taner AkbayView profile

Professor

• Materials Engineering
• Metallurgical Engineering
• Physical Metallurgy
• +6 more

Prof. Dr. Taner Akbay is a faculty member at Yeditepe University, Faculty of Engineering , Department of Materials Science and Nanotechnology Engineering. He has held academic positions at institutions including Kyushu University, Oita University, and Imperial College London. Education: PhD in Materials Engineering (1993, Imperial College London); Master’s (1989) and Bachelor’s (1986) degrees from Middle East Technical University. His research spans Materials Engineering , Metallurgy , and Solid Oxide Fuel Cells (SOFCs) , with a focus on oxide ion conductivity, laser surface treatment, and phase transformations. Recent work explores photocatalysis , anion intercalation , and CO2 reduction using computational and experimental approaches. Key article trends include SOFC optimization (2004–2009), strain effects on catalysts (2015–2020), and dual-carbon battery technology (2016–2020). His work bridges fundamental metallurgy and advanced energy materials . Scientific Awards: Postdoctoral Research Sponsorship Award (EPSRC, UK) JSPS Fellowship (Japan) Daiwa Adrian Prize (2016, UK) PhD Studentship at Imperial College (European Commission) He has supervised multiple PhD and Master’s theses, including projects on dual-carbon batteries , microwave absorption nanocomposites , and rare earth recovery . Administrative roles include Head of Department (2020–2021). Non-University Experience: Worked with Mitsubishi Materials Corporation (2001), Çolakoğlu Metalurji (2010), and National Research Council Canada (2009).

Marina AlbertiView profile

Professor

• Urban Ecology
• Environmental Planning
• Ecosystem Dynamics
• +9 more

Marina Alberti is a Professor of Urban and Environmental Planning at the University of Washington, affiliated with the Department of Urban Design and Planning. She directs the Interdisciplinary Ph.D. Program in Urban Design and Planning and leads the Urban Ecology Research Laboratory. Her expertise lies in studying the interactions between urban development patterns and ecosystem dynamics, focusing on resilience, socio-ecological innovation, and biocomplexity. Her research emphasizes interdisciplinary approaches to urban ecological problems, with a strong focus on Geographic Information Systems (GIS), land cover change, and environmental performance metrics. She has developed simulation models integrating urban development and ecological processes, supported by NSF, NOAA, and Washington state grants. NSF Biocomplexity Program Grant : Developing simulation models for urban-ecological integration. Washington State Department of Transportation Grant : Remote sensing for impervious surface estimation. NOAA/Washington Department of Ecology Grant : GIS analysis of land use and shoreline habitats. Her work spans urban planning, ecological assessment, and policy-making, with a methodological emphasis on GIS, remote sensing, and land use dynamics. She has contributed extensively to journals like International Regional Science Review , Urban Ecosystems , and BioScience , addressing topics such as urban gradients, biodiversity, and environmental sustainability. Alberti's teaching includes Urban Ecology, Environmental Planning, GIS, and advanced research design, reflecting her commitment to training the next generation of urban ecologists.

Alexei KitaevView profile

Professor

• Quantum Computation
• Topological Quantum Phases
• Anyons
• +4 more

Alexei Kitaev is the Ronald and Maxine Linde Professor of Theoretical Physics and Mathematics at the California Institute of Technology (Caltech). His research focuses on quantum computation, topological quantum phases, anyons, topological insulators and superconductors, and the black hole information paradox. He has pioneered the concept of topological quantum computation, where quantum information is protected through topological properties of many-body systems. His recent publications explore quantum error correction, scrambling dynamics, and holographic principles in SYK-like models, reflecting his interdisciplinary impact on quantum physics, computer science, and condensed matter. His work on the Sachdev-Ye-Kitaev model has advanced understanding of quantum chaos and gravitational phenomena. Kitaev has received numerous accolades, including the MacArthur Award (2008), Breakthrough Prize in Fundamental Physics (2012), Dirac Medal (2015), and Oliver Buckley Condensed Matter Prize (2017). He has taught advanced courses such as 'Quantum Computation' and 'Advanced Condensed-Matter Physics' at Caltech. Scientific Awards: MacArthur Award (2008) Breakthrough Prize in Fundamental Physics (2012) Dirac Medal (2015) Oliver Buckley Condensed Matter Prize (2017)

Samir H. MushrifView profile

Professor

• Computational Catalysis
• Molecular Modeling
• Reaction Engineering
• +7 more

Dr. Samir H. Mushrif is a Professor in the Department of Chemical and Materials Engineering at the University of Alberta . Prior to this role, he served as faculty at the School of Chemical and Biomedical Engineering at Nanyang Technological University (NTU), Singapore . He holds a PhD in Chemical Engineering from McGill University and completed postdoctoral research at the University of Delaware, USA . Education : PhD (Chemical Engineering, McGill University), Postdoc (University of Delaware) His research focuses on computational catalysis , molecular modeling , and reaction engineering for biomass conversion and CO2 reduction . He develops novel catalysts, solvents, and reactor systems using integrated quantum mechanical and classical molecular simulations , synergized with experimental data to enable sustainable energy and chemical production . Recent publications highlight trends in condensed phase chemistry for biomass reactions, machine learning applications in solvent configuration prediction, and mechanistic studies of lignin-carbohydrate complex deconstruction. His work bridges methane activation on metal oxides, hydrodeoxygenation of bio-oil compounds, and polymerization pathways in lignin structures. Scientific Awards include: NSERC Doctoral and Post-doctoral Fellowships Discovery International Award 2017 (Australian Research Council) NANYANG EDUCATION AWARD 2016 (Singapore) SCBE Teaching Excellence Awards (Silver 2015, Gold 2016) Bharat Gaurav (Pride of India) Award 2014 Dr. Mushrif's NSERC Discovery Grant (2018), CFI John R. Evans Leaders Fund Grant (2022), and AcRF Tier-2 Grant (Singapore, 2015) have advanced his work. Current PhD and Master's students include José Carlos Velasco Calderón , Arul Mozhi Devan Padmanathan , and Sagar Bathla , among others. The CARES Lab (Catalysis Research for Sustainability) under his leadership combines ab initio molecular dynamics , machine learning potentials , and Density Functional Theory to design materials for renewable energy . Collaborations span institutions in France , Canada , India , and the UK .

Adrian LewView profile

Professor

• Computational Solid Mechanics
• Numerical Algorithms
• Hydraulic Fracturing Simulation
• +3 more

Adrian Lew is a Professor of Mechanical Engineering at Stanford University, specializing in computational solid mechanics and numerical algorithms. His research focuses on hydraulic fracturing simulation, embedded boundary methods, and material model design. He holds a PhD in Mechanical Engineering from Caltech (2003). His work bridges advanced numerical techniques with real-world applications in geophysics, material science, and structural engineering. Education: PhD, Mechanical Engineering, California Institute of Technology, 2003 Research Interests: Lew's group develops algorithms for time-integration embedded boundary methods and hydraulic fracturing simulations. Key areas include curvilinear crack propagation, universal meshing for complex geometries, and high-fidelity fracture mechanics. His work on variational integrators and discontinuous Galerkin methods has advanced computational efficiency in nonlinear elasticity and thermodynamics. Publications: Recent articles emphasize mesh optimization (DVRlib), fracture path instabilities, and magma chamber dynamics. His methodologies address challenges in 3D crack modeling, fluid-structure interaction, and high-order approximations in domains with singularities. Advising & Grants: Lew's research is supported by projects in computational geophysics and material science. Though no advisees are listed, his work involves collaborative teams focused on algorithmic innovation and high-performance computing.

Joseph EremondiView profile

Assistant Professor

• Programming Languages
• Type Theory
• Dependent Types
• +12 more

Joseph Eremondi is an Assistant Professor in the Department of Computer Science at the University of Regina, Faculty of Science, Canada. He began his tenure in 2024 after serving as a Royal Society Newton International Fellow at the University of Edinburgh, where he conducted postdoctoral research with Ohad Kammar in the Laboratory for Foundations of Computer Science. He earned his PhD from the University of British Columbia (UBC) under the supervision of Ron Garcia at the UBC Software Practices Laboratory. His research is centered on programming languages theory, with a strong focus on type systems that enhance software reliability and usability. He is particularly known for his work in dependent types, gradual typing, and the integration of both paradigms. His research interests include: Dependent pattern matching and its semantic foundations Gradual dependent types and approximate normalization Error message generation and usability in dependently typed languages Static analysis using set constraints and SMT solvers Theoretical properties of reversal-bounded counter automata and shuffle operations His recent publications, appearing in premier venues like POPL, ICFP, and CPP, reflect a consistent trajectory toward making advanced type systems more accessible and practical. Key themes include coverage semantics for dependent pattern matching, formal models of gradual dependent typing, and improving the developer experience through better tooling and error diagnostics. Notable scientific recognitions include the NSERC Discovery Grant (awarded in 2025) and the prestigious Royal Society Newton International Fellowship. These awards underscore the impact and promise of his research program on the usability of dependently typed programming languages. Joseph is actively mentoring and recruiting graduate students, particularly in areas such as dependently typed programming (Lean, Agda, Idris, Coq), gradual typing, live programming environments, and static analysis. He emphasizes close collaboration within a small, focused research group. He has also served on program committees, including for TyDe and POPL Artifact Evaluation, demonstrating active engagement in the programming languages community. His work bridges theoretical rigor with practical implementation, evident in his artifact releases on GitHub and integration with tools like Ott and DrRacket. He maintains a personal website and open-source repositories that support reproducibility and community involvement.