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Katherine MilkmanView profile

Professor

• Behavioral Economics
• Judgment and Decision Making
• Behavior Change
• +3 more

Katherine L. Milkman (Katy) is the James G. Dinan Professor at the Wharton School of the University of Pennsylvania, with secondary appointments in Penn's Perelman School of Medicine and School of Arts & Sciences. She co-founded and co-directs the Behavior Change for Good Initiative, a research center dedicated to advancing the science of lasting behavior change. Her work integrates economics and psychology to address challenges like savings, exercise adherence, vaccination rates, and discrimination through large-scale field experiments. Education: PhD in Computer Science and Business from Harvard University; Bachelor's degree (summa cum laude) in Operations Research and Financial Engineering from Princeton University. Research Focus: Milkman's research leverages big data and behavioral science to understand decision-making failures (e.g., self-control, discrimination) and design scalable interventions. Her recent work emphasizes: Nudge-based strategies for education, health, and finance Diversity enhancement in organizational settings Habit formation through incentive structures Publication Trends: Her 15 most recent articles (2022-2025) primarily involve megastudies testing behavioral interventions. Key themes include: leveraging email/reminders to improve math education and vaccination rates; addressing loan delinquency through nudges; and using stereotyping dynamics to increase diversity in hiring. Over 80% employ field experiments across healthcare, finance, and education sectors. Awards & Honors: Thinkers50 Top Management Thinker (2021, 2023) Schmidt Futures Innovation Fellow (2022) Fellow, Association for Psychological Science (2020) Multiple teaching awards from Wharton (2015, 2016) William F. O’Dell Award for impactful research (2017) Advisory & Grants: Milkman has advised major organizations including The White House, Google, Walmart, and the U.S. Department of Defense. Her Behavior Change for Good Initiative secures funding for large-scale social impact research. She hosts Schwab's behavioral economics podcast Choiceology and contributes to policy through op-eds in The New York Times and Scientific American . Labs & Teams: Co-directs the Behavior Change for Good Initiative, collaborating with interdisciplinary researchers (e.g., Angela Duckworth, Sendhil Mullainathan) on longitudinal studies. The initiative designs and tests interventions across health, education, and savings domains.

Herb WinfulView profile

Professor

• Nonlinear Optics
• Laser Physics
• Quantum Tunneling
• +2 more

Herb Winful is a Professor of Optics at the University of Michigan's College of Engineering, Department of Electrical and Computer Engineering. He specializes in nonlinear optics, laser physics, quantum tunneling , and photonics , with a focus on phenomena like superluminal group velocities, frequency comb generation, and light storage via stimulated Brillouin scattering. Research areas span quantum tunneling times , nonlinear photonic materials , and coherent beam combining in fiber laser arrays. His work includes frequency comb spectroscopy using quantum-well diode lasers, ultrafast erbium fiber lasers , and negative group delay engineering in birefringent waveguides. The article list reveals expertise in supercontinuum generation , evanescent wave dynamics , photonic crystals , and nonlinear pulse manipulation . Key subfields include stimulated Brillouin/Raman scattering , parabolic similaritons , and time-domain modeling of optical systems. Award-winning scientific contributions include resolving the Hartman effect paradox and optimizing fiber laser arrays for high-power applications. His research bridges theoretical insights with practical innovations in optical engineering and quantum optics .

Boris KausView profile

Professor

• Geodynamics
• Lithospheric Deformation
• Numerical Modeling
• +5 more

Boris Kaus is a Full Professor and Chair of Geophysics and Geodynamics at the Institute of Geosciences, Johannes Gutenberg University Mainz, Germany. His research focuses on understanding geological processes from grain scale to planetary scale using mathematical and numerical models. Funded by the German Research Foundation, European Research Council, and BMBF, his work spans lithospheric deformation, melt migration, fold-and-thrust belts, and high-performance computing applications in geosciences. His research interests center on geodynamic modeling of lithospheric processes, including subduction zones, mantle convection, and crustal deformation. Kaus develops novel numerical approaches to simulate complex geological phenomena, with emphasis on coupling between erosion, lithosphere dynamics, and mantle flow. His group creates specialized software for high-performance computing systems to tackle multi-scale geophysical problems. His scientific awards include the Paul Niggli Medal, EGU Arne Richter Award, multiple ERC grants (Starting, Proof-of-Concept, Consolidator), and the Carl Friedrich Gauss Lecturer honor. He has received recognition for editorial contributions including G-Cubed's Excellence in Refereeing award. ERC Consolidator Grant MAGMA (2018-2023) ERC Proof of Concept Grant SALTED (2016-2017) ERC Starting Grant MODEL (2010-2015) John von Neumann Excellence Project for HPC ETH Medal for Ph.D. thesis Kaus actively supervises graduate students and leads research projects funded by major European and German agencies. His group develops open-source software like GeophysicalModelGenerator.jl and maintains strong collaborations with international institutions including ETH Zürich and USC. Current projects focus on magma dynamics, lithospheric shear localization, and the development of advanced numerical methods for geodynamic simulations. The research group operates within the Geodynamics & Geophysics team at JGU Mainz, utilizing high-performance computing resources and collaborating with multiple European research initiatives including IMPRS and FORTHEM networks. Their laboratory specializes in numerical modeling of Earth systems with applications to tectonics, volcanology, and crustal evolution.

• Process Technology
• Device Design
• Silicon Carbide (SiC) Electronics
• +3 more

Carl-Mikael Zetterling is a Professor and Head of Department at Kungliga Tekniska Högskolan (KTH) in Stockholm, Sweden, affiliated with the School of Electrical Engineering and Computer Science (ICT) and the Electronics and Embedded Systems department. His research focuses on process technology and device design for high-temperature, high-power silicon carbide (SiC) electronics, expanding into SiC-based analog and integrated circuits. He has authored over 300 publications, including books on SiC process technology and plagiarism prevention. Dr. Zetterling has held leadership roles such as Vice Dean of the School of ICT (2013–2017) and teacher representative on KTH's faculty board. He has collaborated internationally at Stanford University, Kyoto University, and Kyoto Institute of Technology. His work addresses applications in extreme environments, including Venus exploration and fusion reactor monitoring, with a focus on radiation tolerance and thermal resilience. The 15 most recent publications highlight trends in wide bandgap semiconductors, gamma irradiation effects on SiC devices, and high-temperature integrated circuits. His articles span structural health monitoring with machine learning, novel SiC diode designs, and radiation-hardened electronics. Key contributions include advancements in self-aligned contacts, trench MOSFETs, and compact modeling for extreme conditions. While no formal awards are listed, his roles in technical program committees (TMS Electronic Materials Conference, IEEE SISC Conference) and editorial work demonstrate significant academic service. He teaches courses ranging from digital design to high-temperature electronics, overseeing degree projects in embedded systems, communication, and nanotechnology.

Florian ZaussingerView profile

Professor

• Thermal Convection
• Fluid Dynamics
• Astrophysics
• +6 more

Prof. Florian Zaussinger is a faculty member at the Faculty of Applied Computer and Life Sciences at Mittweida University of Applied Sciences. His research focuses on thermal convection, fluid dynamics, and numerical simulations in both geophysical and astrophysical contexts. He has contributed extensively to studies on microgravity experiments, including the GeoFlow and AtmoFlow projects conducted on the International Space Station (ISS). University: Mittweida University of Applied Sciences Faculty: Applied Computer and Life Sciences Department: Mathematics Contact: +49 3727 58-1381 | florian.zaussinger@hs-mittweida.de | Building 6, Room 6-131 His research involves advanced numerical modeling of complex fluid systems, including spherical convection, dielectric heating, and double-diffusive processes. He has developed and applied computational tools like the ANTARES code to simulate convection in DA white dwarfs, planetary atmospheres, and Earth's mantle. His work bridges theoretical fluid mechanics with experimental validation in space-based microgravity environments. Recent publications highlight his expertise in thermo-electrohydrodynamic convection, planetary fluid flow analysis, and microgravity-induced instabilities. While the scraped data does not list scientific awards or students directly, his academic profile emphasizes interdisciplinary collaboration with engineering and life sciences, particularly in applied mathematics for fluid dynamics and experimental data processing.

Michael LevinView profile

Professor

• Developmental Biology
• Bioelectricity
• Cognitive Science
• +7 more

Michael Levin is a Distinguished Professor at Tufts University in the Department of Biology within the School of Arts and Sciences. He serves as Director of both the Allen Discovery Center at Tufts University and the Tufts Center for Regenerative and Developmental Biology. His laboratory investigates the intersection of developmental biology, artificial life, bioengineering, synthetic morphology, and cognitive science. Allen Discovery Center at Tufts Tufts Center for Regenerative and Developmental Biology Tufts/UVM: ICDO Harvard Wyss Institute Stibel Dennett Consortium for Brain and Cognitive Science The Proteus Institute MIT Science and Technology Center EBICS Levin's research focuses on understanding diverse intelligence in evolved, designed, and hybrid complex systems. His lab combines developmental biophysics, computer science, and behavioral science to study how cognition scales up from cellular competencies to organism-level behaviors. A key specialty is developmental bioelectricity—the study of how somatic electrical networks store, process, and act on information to control large-scale body structure. His team creates tools to read and edit the bioelectric code guiding proto-cognitive computations in the body. Levin's publications reveal a strong focus on bioelectricity, morphogenesis, and non-neural cognition across multiple model systems including Xenopus, planarians, and synthetic living constructs. His recent work explores collective intelligence as a unifying concept across biological scales, the development of microfluidic devices for measuring electrical connectivity, and optical estimation of bioelectric patterns in living embryos. His research spans fundamental developmental mechanisms to potential biomedical applications in regeneration and disease treatment. As an editor, Levin serves as Co-Editor-in-Chief of Bioelectricity and Founding Associate Editor of Collective Intelligence. He has mentored numerous post-doctoral fellows and graduate students who have gone on to establish their own research programs. His lab has received significant attention for creating novel biological machines (xenobots) and demonstrating that cells can store and transmit behavioral memory outside the brain. The Levin Lab maintains several significant research initiatives including the Allen Discovery Center at Tufts, the Tufts Center for Regenerative and Developmental Biology, and collaborations with the Wyss Institute at Harvard. The lab employs a multidisciplinary approach combining wet lab experiments with computational modeling to investigate how living systems achieve goal-directed behavior and pattern formation.

Matthew JenssenView profile

Associate Professor

• Discrete Probability
• Probabilistic/Extremal Combinatorics
• Statistical Physics
• +5 more

Matthew Jenssen is a Reader in Probability at King's College London and a UKRI Future Leaders Fellow. He holds a BA and MMath from the University of Cambridge (2012–2013) and a PhD from the London School of Economics (supervised by Jozef Skokan and Julia Boettcher). His research focuses on the intersection of combinatorics, statistical physics, and theoretical computer science, particularly on large-scale structure formation in systems with local interactions. Notable contributions include advancements in sphere packing, Ramsey numbers, and random matrix theory. Jenssen has held postdoctoral positions at the University of Oxford and the University of Birmingham before joining King’s in 2023. His research group at King’s explores discrete probability, extremal combinatorics, and algorithms, with applications to statistical physics and high-dimensional geometry. Key achievements include a groundbreaking improvement on sphere packing lower bounds and resolving extremal questions in graph theory. Jenssen’s work often bridges combinatorial theory with computational methods, yielding impactful results in probabilistic combinatorics. Scientific awards include the UKRI Future Leaders Fellowship (2020). His grants include a 2023–2026 project on statistical physics methods in combinatorics and geometry. Jenssen collaborates widely, with notable co-authors including Will Perkins, Jozef Skokan, and Felix Joos. He is actively involved in the Probability Group at King’s and contributes to international conferences and arXiv publications.

Joseph WoodView profile

Professor

• Visual Analytics
• Data Visualization
• Geographic Information Science
• +5 more

Professor Joseph Wood is a Professor of Visual Analytics at City St George's, University of London, where he serves as a founding member of the giCentre. His academic career spans over three decades, with continuous contributions to Geographic Information Science and visualization since 1990. He previously served as Head of Department for Computer Science at City University between 2014 and 2017. Professor Wood's educational background includes a PhD in Geographical Information Science from the University of Leicester (1996), an MSc in the same field from the University of Leicester (1990), and a BSc in Physical Geography & Geology from the University of Sheffield (1989). His academic progression shows steady advancement from Research Scholar at the University of Leicester (1990-1992) through various lecturer and senior positions to his current professorship. His research interests center on visual analytics and data visualization, with particular expertise in geographic information science and terrain analysis. Professor Wood has developed innovative methods bridging GI Science, Data Visualization, and education domains. His specific interests include narrative of visual analytic design, computational thinking in pedagogy, and novel visualization design for geographic data. His work demonstrates a consistent focus on making complex spatial data understandable through innovative visualization techniques. Analysis of Professor Wood's recent publications reveals a strong emphasis on practical applications of visualization techniques across diverse domains including transportation, epidemiology, sports analytics, and historical migration patterns. His work shows an evolution from foundational geographic information science toward broader applications in visual analytics, with increasing focus on narrative structures, responsive design, and accessibility considerations in visualization. The interdisciplinary nature of his research is evident in collaborations spanning computer science, geography, urban planning, and public health domains. Professor Wood has been actively involved in the academic community, serving on organizing and program committees for major international conferences including IEEE Infovis and VAST, Eurovis, GIScience, Spatial Accuracy, and Geomorphometry. His contributions to the field have been recognized through invitations to deliver keynote talks at prestigious venues ranging from GeoComputation to TEDx, where he presented on topics such as visualizing movement behavior of cyclists. As an advisor, Professor Wood has supervised numerous PhD and Master's students, with current supervision of Julia Crossley (Student conceptualisation of abstraction in computer science) and Jude Nzemeke (Understanding student misconception in recursive algorithmic thinking). His extensive supervision history includes completed PhDs on topics ranging from cycling behavior to spatio-social relations in photographic archives. His academic leadership extends to software development, with contributions to tools like litvis, elm-vega/el-vegalite, giCentre Utils, handy, and LandSerf GIS. Professor Wood is an active member of professional organizations including IEEE (2007-present), Association of Computing Machinery (ACM) (2007-present), and Association of Geographic Information (AGI) (1997-present), demonstrating his commitment to interdisciplinary collaboration across computer science and geographic information domains.

Mike RubensteinView profile

Assistant Professor

• Swarm Robotics
• Multi-Robot Systems
• Decentralized Control
• +3 more

Mike Rubenstein is an Assistant Professor with joint appointments in the Department of Computer Science and Department of Mechanical Engineering at Northwestern University. He holds the Lisa Wissner-Slivka and Benjamin Slivka Professorship in Computer Science and is affiliated with the Center for Robotics and Biosystems. His educational background includes a Ph.D. in Computer Science from the University of Southern California, an M.S. in Electrical Engineering from USC, and a B.S. in Electrical Engineering from Purdue University. Prior to joining Northwestern, he completed a postdoctoral fellowship at Harvard University's Self-Organizing Systems Research Group. Rubenstein's research focuses on advancing multi-robot systems to enable capabilities beyond traditional single robots, emphasizing parallelism, adaptability, and fault tolerance at scale (hundreds to millions of robots). His work spans swarm shape control, modular self-reconfigurable robotics, bio-inspired satellite constellations, and novel sensing for air vehicle swarms. Key themes include algorithmic control for large-scale systems and hardware innovations to overcome current limitations in swarm robotics. His advising has produced notable student achievements, including Petras Swissler's Best Student Paper Award at DARS 2021 and Drew Curtis's NDSEG Fellowship. Research trends across his publications reveal a consistent emphasis on scalability, real-world applicability, and bridging hardware constraints with algorithmic innovation in swarm systems. Rubenstein actively mentors graduate students and leads projects involving swarm robotics platforms like FireAnt and PCBot. His lab focuses on developing systems where simplicity in individual robots enables emergent complexity at the swarm level, with applications ranging from space exploration to medical imaging.

Yves BoubenecView profile

Associate Professor

• Auditory Neuroscience
• Perceptual Attention
• Sound Encoding
• +3 more

Dr. Yves Boubenec is an Associate Professor at École Normale Supérieure (ENS)-PSL University, Paris, France. He serves as Head of the LSP Neuro Platform and Director of Studies at the Department of Cognitive Studies. Academic Rank: Associate Professor Institution: ENS-PSL Departments: Cognitive Studies (ENS), LSP Neuro Platform Email: yves.boubenec@ens.psl.eu Research Focus: Boubenec investigates neural mechanisms of auditory perception and cognition using integrated methodologies spanning single-neuron electrophysiology to large-scale neuroimaging. His work reveals how context, learning, and multisensory interactions shape sound encoding in mammalian neocortex. Primary Research Themes Context-dependent auditory encoding Perceptual attention mechanisms Task-driven neural plasticity Self-supervised learning models Population-level cortical dynamics Human/ferret auditory comparisons Publication Trends: Recent work (2024-2025) examines speech production networks, premotor auditory categorization, and algebraic structures in sound learning. Earlier studies (2018-2022) focus on population gating, hierarchical auditory coding, and self-voice mechanisms. 2025 Self-voice frequency analysis Hierarchical ferret auditory cortex mapping Temporal window constraints 2024 Premotor category hemodynamics Self-supervised sound structures Human speech cortical encoding Methodological Expertise: Combines awake ferret functional UltraSound, Neuropixels recordings, and computational modeling to analyze neural representations across spatial scales. Specializes in translating animal model findings to human auditory processes.

Tesla JeltemaView profile

Professor

• observational cosmology
• particle astrophysics
• dark matter
• +3 more

Tesla Jeltema is a Professor in the Department of Physics at the University of California, Santa Cruz and serves as Associate Director of the Santa Cruz Institute for Particle Physics (SCIPP). Her office is located in ISB 305 at 1156 High Street, Santa Cruz, CA 95064. She currently holds the position of Deputy Spokesperson for the LSST Dark Energy Science Collaboration (DESC). Her research centers on: Observational cosmology and particle astrophysics Constraints on dark matter and dark energy properties Galaxy evolution and large-scale structure formation She actively contributes to major international projects: Rubin Observatory LSST DESC Dark Energy Survey (DES) Dark Energy Spectroscopic Instrument (DESI) Scientific recognition includes: 2020 Meenakshi Narain Mentoring Award from the American Physical Society Dr. Jeltema mentors 3-5 graduate students and 4-8 undergraduate/postbaccalaureate researchers through programs including Cal-Bridge, DESC, DES, and UCSC's STEM Diversity initiatives (CAMP and UC LEADS). She founded and advises the UCSC Women in Physics and Astrophysics Club since 2011 and serves on multiple diversity and inclusion committees. Her institutional affiliations include the Santa Cruz Institute for Particle Physics and the Department of Physics at UC Santa Cruz.

Ashley WillisView profile

Senior Lecturer

• Fluid Dynamics
• Turbulence
• Astrophysical Fluid Dynamics
• +3 more

Dr. Ashley Willis is a Senior Lecturer in Fluid Dynamics at the University of Sheffield's School of Mathematical and Physical Sciences. He holds roles including Admissions Head and Programme Leader for Study Abroad. His research focuses on fluid dynamics, turbulence, astrophysical flows, and magnetohydrodynamics, with applications in clean energy and planetary systems. Willis completed his Ph.D. in Applied Mathematics at Newcastle University (2002) and has held postdoctoral positions at the University of Bristol, Leeds, and a Marie Curie Fellowship at Ecole Polytechnique, Paris. He leads the Fluid Dynamics Group and is part of the cross-faculty Sheffield Fluid Mechanics Group. His research interests include transition to turbulence, nonlinear dynamics, and magnetic field generation in planetary interiors. He supervises PhD students like Shijun Chu and collaborates with industry on projects like turbulence suppression in pipe flows. Key contributions include the open-source Openpipeflow simulation code and studies on dynamo action in geophysical flows. Publications highlight work on turbulent transition mechanisms, optimal flow configurations, and dynamo theory. His teaching includes courses on mechanics, fluid dynamics, and mathematical modeling of natural systems.

• Computational Social Science
• Natural Language Processing
• Human-Computer Interaction
• +3 more

Cristian Danescu-Niculescu-Mizil is an Associate Professor in the Department of Computer Science at Cornell University's College of Engineering, where he leads research at the intersection of computational social science and human-computer interaction. His work examines how language shapes and reflects social dynamics in digital environments, with applications for platform design and community health. His research focuses on computational social science , natural language processing , and human-computer interaction , particularly analyzing online discourse evolution, social influence mechanisms, and community dynamics. Key methodologies include large-scale data analysis, machine learning, and longitudinal modeling of language behavior across platforms like Reddit, Twitter, and Wikipedia. Analysis of his recent publications reveals strong trends in cross-platform misinformation tracking , AI-driven content moderation , and linguistic adaptation in support communities . His work consistently bridges technical NLP advances with sociological insights, emphasizing ethical implications and real-world interventions for healthier online ecosystems. Scientific recognition includes: NSF CAREER Award for foundational work in computational social science Multiple industry research awards from Google and Facebook ACM SIGCHI Best Paper Award for community health research He actively mentors doctoral students in computational social science, with several advisees now faculty at top institutions. His research is supported by NSF grants focused on social dynamics modeling and NLP for community health, often collaborating with social scientists and industry partners. Current projects investigate AI moderation systems and longitudinal language evolution in online communities through the Digital Discourse Lab .

G. Scott WatsonView profile

Professor

• Early Universe Cosmology
• Inflation
• Dark Matter
• +3 more

Prof. G. Scott Watson is a Professor in the Department of Physics at Syracuse University, affiliated with the College of Arts & Sciences. His research focuses on the interplay between fundamental particle physics and cosmology, particularly early universe cosmology, inflationary models, dark matter/energy, and string theory applications. He holds a Ph.D. in Physics from Brown University (2005) and B.S. degrees in Mathematics and Physics from the University of North Carolina at Wilmington (2000). Key research interests include string phenomenology as a quantum gravity framework, probing inflationary scenarios through cosmic microwave background (CMB) studies, and exploring dark matter origins. He leads major projects like CMB-S4 and contributes to the CMBPol mission concept. Watson has received the American Physical Society Outstanding Referee Award (2021) and serves on high-profile collaborations such as the Inflation Probe Study Analysis Group (IPSAG). Teaching responsibilities include advanced courses like Quantum Field Theory, Relativity and Cosmology, and Quantum Mechanics II. He actively mentors students through independent studies and advises on graduate admissions. Watson has secured significant grants, including a Department of Energy-funded project on theoretical particle physics and cosmology (2013–2025) and NSF support for cosmic acceleration research (2018–2023).

Jacqueline McClearyView profile

Assistant Professor

• Astrophysics
• Cosmology
• Weak Gravitational Lensing
• +4 more

Dr. Jacqueline McCleary is an Assistant Professor of Physics at Northeastern University's College of Science, specializing in observational cosmology with a focus on galaxy clusters and dark matter. She leads research using weak gravitational lensing to study cosmic structures, collaborating on projects like the COSMOS-Web (JWST), SuperBIT (balloon telescope), and LoVoCCS surveys. Her work leverages multi-wavelength data from space, stratospheric, and ground-based observatories. Education: M.S. in Astronomy (New Mexico State University), M.S. and Ph.D. in Physics (Brown University), Postdoctoral Fellow at NASA's Jet Propulsion Laboratory. She transitioned to Northeastern as an ADVANCE Future Faculty Fellow before becoming a tenure-track faculty member in 2022. Research Interests: Dark matter interactions, galaxy cluster dynamics, gravitational lensing techniques, and next-generation observational platforms. Her team develops advanced algorithms and instrumentation for high-resolution imaging. Recent Contributions: COSMOS-Web has enabled unprecedented observations of distant galaxies using JWST, while SuperBIT's stratospheric flights provide diffraction-limited data. Key publications focus on lensing surveys, data reduction techniques, and dark matter-halo relationships. Awards: Recognized as a Northeastern ADVANCE Future Faculty Fellow. Media Engagement: Regularly comments on space exploration, asteroid risks, and cosmic phenomena for public outlets.