جستجوی استاد راهنمای دانشگاهی

Amy Angertمشاهده پروفایل

استاد

• Evolutionary Ecology
• Species Geographic Distributions
• Climate Change Ecology
• +۵ مورد دیگر

Amy Angert is a Professor in the Department of Botany at the University of British Columbia's Faculty of Science. She holds a Canada Research Chair Tier 2 and is recognized as an Academy Member in Evolution and Ecology (2025). Dr. Angert joined UBC in 2012 after serving as an assistant professor at Colorado State University and completing postdoctoral research at the University of Arizona. Her academic journey includes a B.A. from Washington University in St. Louis (1998) and a Ph.D. from Michigan State University (2005). Dr. Angert's research focuses on the evolutionary ecology of species' geographic distributions, investigating what limits adaptation at the edges of species' ranges, why closely related species vary dramatically in range size, and how ranges are likely to shift in response to climatic changes. Her lab combines experimental manipulations in the field and laboratory with observations of natural populations, utilizing tools from quantitative genetics and physiological ecology. Much of her work centers on species within the genus Mimulus (monkeyflowers) due to their ecological diversity, genomic resources, and ease of propagation. Her recent publications reveal strong patterns of climate-driven range shifts, evolutionary rescue during extreme drought events, and the role of biotic interactions in determining range dynamics. Dr. Angert's scientific contributions have been recognized through prestigious awards including election to the American Academy of Arts and Sciences. Her work has significant implications for predicting species responses to climate change and informing conservation strategies. She leads an active research group with numerous graduate students and postdoctoral fellows, fostering the next generation of evolutionary ecologists. Her lab maintains strong collaborative networks across institutions and has received consistent funding to support their innovative research on the mechanisms constraining species' distributions in a changing climate. Dr. Angert's work bridges theoretical and empirical approaches to understand the eco-evolutionary dynamics of range expansion and the consequences of divergence in niche properties for patterns of distribution and abundance.

Rana Adhikariمشاهده پروفایل

استاد

• Gravitational Waves
• Dark Matter Detection
• Quantum Metrology
• +۶ مورد دیگر

Rana Adhikari is a Professor of Physics at the California Institute of Technology (Caltech). Holding a B.S. from the University of Florida (1998) and a Ph.D. from MIT (2004), he has been at Caltech since 2006, progressing from Assistant Professor to full Professor in 2012. His research focuses on advancing detector technologies for fundamental physics experiments in gravitational waves, dark matter, and near-field gravity studies. Education: B.S. in Physics, University of Florida (1998); Ph.D. in Physics, MIT (2004) Caltech Faculty: Assistant Professor (2006-12), Professor (2012-present) Adhikari's group specializes in precision measurements at the intersection of classical and quantum physics. Key research areas include: Mechanical oscillators and their thermodynamic limits Nonlinear optics for interferometric applications Quantum information constraints in classical sensors Adaptive optics using thermal actuation Cryogenic silicon interferometers for cosmological observations High-quality silicon opto-mechanical systems for LIGO applications Laser gyroscope technology for rotation sensing The group's work on gravitational wave detection has produced numerous publications in leading journals like Physical Review X , Physical Review D , and Optics Express . Their research often combines experimental physics with machine learning techniques for noise cancellation in laser interferometers. Adhikari's team also engages with undergraduate researchers through programs like the International LIGO SURF students, creating opportunities for young scientists in gravitational physics. His publications reveal a consistent focus on gravitational wave detector optimization, quantum metrology, and cosmological observations through advanced instrumentation.

Feng Chenمشاهده پروفایل

دانشیار

• Nonparametric and semiparametric statistics
• Point processes and self-exciting processes
• Statistical computing
• +۳ مورد دیگر

Associate Professor Feng Chen is a faculty member at the School of Mathematics & Statistics, University of New South Wales, specializing in statistical methodology development and applications. His research bridges theoretical statistics and practical implementations across financial modeling, spatiotemporal processes, and public health analysis. PhD in Statistics from University of Hong Kong (2008) MSc in Applied Probability & Statistics from Lanzhou University (2004) BSc in Mathematics from Lanzhou University (2001) Research focuses include: Nonparametric and semiparametric statistical methods Point process modeling with emphasis on Hawkes processes Statistical computing and algorithm development Applications to financial data, earthquake analysis, and public health Recent publications demonstrate methodological advances in: Hawkes process estimation with complex data structures Renewal process applications in seismology GARCH modeling with missing data Spatiotemporal clustering analysis Scientific recognition includes: UNSW Science Staff Impact Award (2023) Professional roles: Director of Research Postgraduate Studies (2023--) Associate Editor for multiple journals Statistics Honours Coordinator (2013-2018) Active participant in statistical societies

Siegfried Egglمشاهده پروفایل

استادیار

• Astrodynamics
• Planetary Defense
• Celestial Navigation
• +۶ مورد دیگر

Siegfried Eggl is an Assistant Professor in the Department of Aerospace Engineering at the University of Illinois at Urbana-Champaign , with additional affiliations as an Affiliate Faculty in the Department of Astronomy (2022–present) and the National Center for Supercomputing Applications (NCSA) (2021–present). His research bridges astrodynamics, planetary defense, and celestial navigation, focusing on spacecraft trajectory optimization, asteroid deflection, and autonomous navigation systems. Education: B.S., Astrophysics, University of Vienna (2005) M.S., Astrophysics, University of Vienna (2008) M.S., Computational Physics, University of Vienna (2009) Ph.D., Astrophysics, University of Vienna (2013) Research Interests: Eggl investigates astrodynamics for planetary defense, including momentum transfer in asteroid impacts (e.g., NASA’s DART mission). He develops algorithms for celestial navigation using variable stars and studies space domain awareness to address satellite constellation interference. His work also explores dynamical systems in binary star environments and computation/data-driven approaches to orbital mechanics. Recent Publications highlight advancements in planetary defense simulations , celestial navigation algorithms , and asteroid impact dynamics . Topics include state transition matrix computation , ejecta momentum analysis , and binary asteroid system modeling . Scientific Awards: LSST Architect Award (2021) Space Foundation 2023 Space Achievement Award (DART Team) AIAA Award for Engineering Excellence (DART Team, 2023) Asteroid 2000 GT167 named 'Eggl' (2023) 2024 Engineering Council Outstanding Advisors Best paper award at AIAA Guidance, Navigation, and Control Conference (2024) Eggl contributes to professional societies such as the AIAA , American Astronomical Society (Division on Dynamical Astronomy) , and International Astronomical Union , where he co-leads the Centre for the Protection of the Dark and Quiet Sky. His APEX research group at UIUC focuses on planetary defense and astrodynamics.

Robert J. Trappمشاهده پروفایل

استاد

• Severe Storms
• Tornadoes
• Radar Meteorology
• +۵ مورد دیگر

Robert J. Trapp serves as Director of the School of Earth, Society, and Environment and Head of Climate, Meteorology and Atmospheric Sciences at the University of Illinois, while also holding a Professorship at the National Center for Supercomputing Applications (NCSA). His leadership spans both academic and research domains within atmospheric sciences. Trapp's research focuses on severe convective storms, tornado dynamics, and radar meteorology with significant contributions to understanding bow echoes, tornadic vortex signatures, and the impacts of climate change on severe weather. His work integrates advanced numerical modeling with observational data from field campaigns like BAMEX and VORTEX, utilizing Doppler radar systems including WSR-88D and Doppler On Wheels (DOW). His publication record demonstrates consistent research output from 1995-2007, with recent work emphasizing telescoping model approaches for evaluating severe convective storms under future climate scenarios. Key methodological contributions include objective analysis techniques for weather radar data and multi-platform observational strategies for severe thunderstorms. Trapp maintains active research collaboration through the National Center for Supercomputing Applications, leveraging computational resources for atmospheric modeling. His work bridges fundamental atmospheric dynamics with practical severe weather forecasting applications. Professional service includes leadership roles as Director and Department Head, indicating significant administrative responsibilities alongside research activities. His scholarly contributions appear primarily in conference proceedings and peer-reviewed journals focused on meteorology and atmospheric science.

Inna Sharfمشاهده پروفایل

استاد

• Dynamics and Control
• Space Robotics
• Unmanned Aerial Vehicles (UAVs)
• +۳ مورد دیگر

Inna Sharf is a Professor at the Department of Mechanical Engineering, Faculty of Engineering, McGill University. She is affiliated with the Aerospace Mechatronics Laboratory, focusing on dynamics, control, and robotics. Her work spans space robotics, UAVs, forestry automation, and multibody systems. Ph.D., University of Toronto B.ASc., University of Toronto Her research interests include: Dynamics and control of robotic systems Space robotics for debris removal and on-orbit servicing Unmanned aerial vehicles (quadrotors, indoor airships) Forestry robotics for tree-harvesting automation Multibody dynamics and contact modeling Recent publications emphasize: Control algorithms for quadrotors and UAV swarms De-orbitation strategies using natural resonances Motion planning under dynamic constraints Thermalling and energy-efficient flight for gliders Collaborative payload transport and adaptive control Tether and net-based debris capture systems

• Human-Machine Interaction
• Usability Testing
• User Experience (UX)
• +۵ مورد دیگر

Jürgen Sauer is a Full Professor at the University of Fribourg , affiliated with the Department of Psychology under the Faculty of Letters and Human Sciences . With over 120 publications, his research focuses on Human-Machine Interaction , Usability Testing , User Experience (UX) , and Automation Design , particularly in high-stakes environments like X-ray baggage screening and spaceflight simulations . Email: juergen.sauer@unifr.ch Phone: +41 26 300 7622 Address: RM 01 bu. C-1.117, Rue PA de Faucigny 2, 1700 Fribourg Orcid: 0000-0003-2105-1694 His research projects, funded by the Swiss National Science Foundation (FNS), include: Improving work design for airport security officers (2019-2024): Developed pictorial scales for measuring psychological constructs in security environments. Social stress and support in hybrid teams (2018-2023): Investigated machine-induced social stressors and mitigation through social support. Automation in visual inspection tasks (2014-2018): Examined adaptable automation for baggage screening and system reliability effects. Usability testing effectiveness (2012-2016): Analyzed cultural background impacts and non-usability product features influencing test outcomes. Key contributions include the Luggage Inspection Simulation (LIS) environment for modeling work environments and the development of pictorial usability scales for multilingual applicability. His work bridges ergonomics , human factors , and applied psychology , with notable collaborations with researchers like Adrian Schwaninger and Andreas Sonderegger . His recent publications (2025-2014) analyze: Human-machine performance under false alarms and miscues Social stressor dynamics in hybrid teams Usability scale animation effects Phubbing behavior in professional contexts Accessible website design for non-disabled users

• Glaciology
• Climate Change
• Ice Sheet Dynamics
• +۳ مورد دیگر

Dr Amber Leeson is a Reader in Glaciology at Lancaster Environment Centre , Lancaster University. She serves as Associate Director for Research and leads projects integrating data science , numerical modeling , and remote sensing to study climate change impacts on the Greenland and Antarctic Ice Sheets . Her current research focuses on supraglacial hydrology , digital twinning of ice sheets , and firn evolution . Current Research Themes Ice sheet surface climate representation in models Supraglacial hydrology and ice sheet dynamics Firn evolution (past, present, future) Leadership Roles Associate Director for Research, Lancaster Environment Centre Treasurer and Secretary, International Glaciological Society Theme Lead for Environment, Data Science Institute (DSI) Her teaching includes courses on Glacial Systems, Environmental Processes, and Global Change. She supervises undergraduate and master's dissertations in Polar Science . Recent projects include Arctic Extremes (ARCTEX) , 5D Antarctica (5DAIS) , and AI Forecasting for Ice Shelf Collapse (AI4IS) . Amber's scientific contributions span climate model calibration, firn densification studies, and supraglacial lake dynamics. She has held advisory roles for the UK Polar Network , AGU Cryosphere Committee , and UKNCAR . Her work unites glaciology , data science , and climate modeling to address planetary-scale environmental challenges.

Aaron A. Kingمشاهده پروفایل

استاد

• Theoretical Ecology
• Epidemiological Dynamics
• Evolutionary Biology
• +۵ مورد دیگر

Aaron A. King, Ph.D. , is the Nelson G. Hairston Collegiate Professor of Ecology and Evolutionary Biology, Complex Systems, and Mathematics at the University of Michigan and an External Professor at the Santa Fe Institute . He is a Fellow of the American Association for the Advancement of Science and a Biological Sciences Scholar at the University of Michigan. His research integrates mathematical modeling, statistical inference, and empirical data to study ecological and epidemiological systems. Education: Ph.D. in Applied Mathematics, University of Arizona, 1999 M.A. in Mathematics, University of Hawai'i, 1992 B.A. summa cum laude in Mathematics, Rice University, 1989 Research Interests: Dr. King's lab focuses on the dynamics of ecological, epidemiological, and evolutionary systems . His work includes: Modeling host-pathogen systems (COVID-19, influenza, dengue, pertussis, cholera, malaria) Antibiotic resistance in hospital settings Statistical inference for ecological and epidemiological data Integration of genomic and epidemiological data Mathematical frameworks for understanding parasite infections and immune responses Scientific Awards: Fellow of the American Association for the Advancement of Science Biological Sciences Scholar, University of Michigan Teaching and Mentorship: Dr. King teaches courses in Mathematical Ecology , Adaptive Systems , and Statistical Inference . He mentors graduate students and postdoctoral fellows, including Avinash Subramanian and Madeline Peters , and is affiliated with multiple interdisciplinary centers at the University of Michigan. Lab and Collaborations: He leads the King Laboratory of Theoretical Ecology & Evolution , which emphasizes reproducible research and rigorous theoretical approaches. The lab collaborates with institutions like the Santa Fe Institute and accepts students from programs such as Ecology & Evolutionary Biology , Applied & Interdisciplinary Mathematics , and Data Science .

Kyle Dawsonمشاهده پروفایل

استاد

• Cosmology
• Observational Astronomy
• Dark Energy
• +۵ مورد دیگر

Kyle Dawson is a Professor of Physics and Astronomy at the University of Utah, where he has been employed since 2009. He currently serves as both a full Professor and Director of Graduate Studies in the Department of Physics and Astronomy, having progressed from Assistant Professor (2008-2015) to Associate Professor (2015-2019) before achieving his current position in 2019. His institutional affiliation places him within the College of Science at the University of Utah, a major research university in the western United States. Dawson earned his BA in Physics from Cornell University in 1998, followed by a PhD in Physics from the University of California, Berkeley in 2004. After completing his doctoral studies, he served as a postdoctoral researcher at the Lawrence Berkeley National Laboratory before joining the University of Utah faculty. His educational background in physics provided the foundation for his transition into observational cosmology, where he has made significant contributions through large-scale spectroscopic surveys. Professor Dawson's research focuses on observational cosmology through large spectroscopic surveys designed to measure the fundamental properties of the universe. He is currently the co-Spokesperson for the Dark Energy Spectroscopic Instrument (DESI), a major cosmological survey that has produced numerous high-impact publications in 2024-2025. Previously, he served as Principal Investigator for the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), which concluded in 2020 with final cosmological measurements. His work centers on measuring baryon acoustic oscillations to constrain cosmic expansion history, dark energy properties, neutrino masses, and to test General Relativity. His research group employs techniques including galaxy clustering analysis, quasar astrophysics, and large-scale structure mapping to address fundamental questions in cosmology. The analysis of Dawson's recent publications reveals a strong focus on extracting cosmological constraints from the DESI survey data. His work spans multiple aspects of cosmological analysis, including baryon acoustic oscillation measurements, full-shape power spectrum analysis, imaging systematics mitigation, and cross-correlation studies with cosmic microwave background data. The publications demonstrate collaborative work with large international teams and contribute to increasingly precise measurements of cosmological parameters, with particular attention to dark energy equation of state, neutrino masses, and potential deviations from General Relativity. Professor Dawson has secured significant research funding throughout his career, including multiple grants from the Department of Energy (DOE), NASA, and the National Science Foundation. His grant portfolio includes leadership roles in major cosmological surveys like DESI and eBOSS, as well as support for postdoctoral researchers and graduate students. His research group has mentored numerous students who have gone on to successful careers in academia, industry, and data science fields. Dawson leads a vibrant research group at the University of Utah focused on cosmological data analysis from large spectroscopic surveys. His current team includes two postdoctoral researchers (Angela Berti and Sarah Eftekharzadeh) and a graduate student (Allyson Brodzeller). The group specializes in galaxy clustering analysis, quasar astrophysics, and machine learning applications to spectroscopic data. The research environment fosters collaboration with international teams working on DESI and related cosmological surveys, providing students with opportunities to engage with cutting-edge cosmological research and large-scale data analysis techniques.

Sahani Pathirajaمشاهده پروفایل

مدرس

• Data Science
• Bayesian Inference
• Stochastic Analysis
• +۷ مورد دیگر

Dr. Sahani Pathiraja is a Lecturer (tenure track assistant professor) at UNSW Sydney , specializing in Data Science . Her research bridges mathematical and statistical foundations with practical applications in environmental and biomedical sciences. Research Focus : Sequential Bayesian inference, Monte Carlo methods, stochastic analysis of non-linear filtering, uncertainty quantification, and real-time parameter estimation. Current Projects : Co-investigator in the ARC Industrial Transformation Training Centre: Data Analytics for Resources and Environment (DARE) and the Next Generation Graduate Program (NGGP) in Sports Data Science and AI . Research Supervision : Dr. Pathiraja supervises PhD students in areas including: Bayesian inference Stochastic differential equations Data assimilation Non-linear filtering Scientific Collaborations : Her work intersects with environmental science, biomedical applications, and machine learning. Projects include stochastic hydrology, SDEs, and operator learning for environmental systems. Contact Information : Email: s.pathiraja@unsw.edu.au Phone: +61 2 8065 0836 Office: Room 2070, Level 2, The Red Centre, UNSW Sydney

Alex Archibaldمشاهده پروفایل

استاد

• Atmospheric Chemistry
• Climate Science
• Environmental Science
• +۵ مورد دیگر

Professor Alex Archibald is the Professor of Atmospheric Chemistry in the Yusuf Hamied Department of Chemistry at the University of Cambridge. His research group investigates atmospheric chemistry-climate interactions through fundamental laboratory studies atmospheric observations numerical model simulations . Research interests focus on chemistry-climate feedbacks , including hydrogen economy impacts biogenic hydrocarbon oxidation air pollution mitigation marine sulfur cycling machine learning applications . Recent publications emphasize hydrogen-soil deposition dynamics ozone-temperature relationships DMS chemistry in Earth systems hydrogen economy climate implications AI-driven climate modeling transboundary pollution studies . Teaching includes Part I Kinetics of Chemical Reactions Part II Chemistry in the Atmosphere Part III IDP1 projects . The research team has 15+ current and former students working on topics from Martian atmospheric modeling to urban temperature extremes.

Bradley Hayesمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Robotics
• Human-Robot Interaction
• +۵ مورد دیگر

Bradley Hayes is an Associate Professor in the Department of Computer Science at the University of Colorado Boulder, affiliated with the College of Engineering and Applied Science. He leads the Collaborative AI and Robotics (CAIRO) Lab, focusing on creating autonomous robots that collaborate effectively with humans through advances in explainable AI, machine learning, and human-robot interaction. His prior research includes foundational work at MIT's Interactive Robotics Group and Yale's Social Robotics Lab. Research interests span Explainable AI, Learning from Demonstration, Hierarchical Reinforcement Learning, Computer Vision, Natural Language Processing, and Cognitive Science. His work emphasizes making human-robot teams more efficient and safe through innovations like emotionally expressive robotic motion, socially aware navigation, and AR-based collaboration tools. Key contributions include techniques for robust robotic exploration, generative occupancy mapping, and systems for improving human trust through predictable robot behavior. His work has been applied to teleoperation training, surgical assistance, and space exploration scenarios. Grants and partnerships support development of assistive robotic canes and AR interfaces for collaborative tasks. Lab activities emphasize translating theoretical advancements into practical systems through close collaboration between researchers, engineers, and end-users. Education efforts include developing foundational robotics curricula addressing autonomy, perception, and control systems.

• Survival Analysis
• Nonparametric Regression
• Semiparametric Regression
• +۴ مورد دیگر

Ingrid Van Keilegom is a Full Professor at the Faculty of Economics and Business (FEB) at KU Leuven. She is a member of the LISS – KU Leuven Institute of Sports Science and serves as a program director for the POC Master in Statistics. Senior academic staff member of FEB Council and Campus Council Observer in Faculty of Science Council Member of LStat General Assembly Her research focuses on Survival Analysis and Nonparametric Regression , with expertise in: Dependent Censoring Cure Models Measurement Error Correction Quantile Regression Multivariate Statistical Inference Causal Surrogacy Metrics Recent publications emphasize copula-based methods, quantile regression for censored data, and applications to biomedical and economic forecasting. Key projects include instrumental variable approaches for endogeneity in cure models, bankruptcy prediction via machine learning, and measurement error modeling in multivariate settings. Notable affiliations: Centre for Efficiency and Productivity Analysis Collaborations in pharmaceutical statistics and actuarial science

Jakob Eg Larsenمشاهده پروفایل

دانشیار

• Human Computer Interaction (HCI)
• Personal Informatics
• Quantified Self
• +۳ مورد دیگر

Jakob Eg Larsen is an Associate Professor at the Technical University of Denmark (DTU), affiliated with the Department of Applied Mathematics and Computer Science (DTU Compute) within the Cognitive Systems Section. He leads the Mobile Informatics and Personal Data Laboratory (MILAB). His research focuses on Human-Computer Interaction (HCI), Personal Informatics, Quantified Self, and Information Visualization, with applications in wearable technology, mental health, and healthcare. He teaches courses in Digital Media Engineering, including user experience, mobile application prototyping, and personal informatics. Education: PhD (2005) and MSc in Computer Science (1999) from the University of Copenhagen, with additional studies in cognitive psychology. Research emphasizes wearable devices for mental health interventions (e.g., PTSD treatment), physical activity tracking in pregnancy, and personalized hearing aid systems. Over 98 publications and 12 supervised PhD projects highlight his contributions to HCI, mHealth, and data-driven healthcare solutions. Labs/Teams: MILAB focuses on mobile informatics and personal data interaction. Collaborations span interdisciplinary fields like audiology, clinical psychology, and public health.