جست‌وجوی استاد و پژوهشگر

Bin Chenمشاهده پروفایل

دانشیار

• Econometrics
• Financial Econometrics
• Time Series Analysis
• +۴ مورد دیگر

Bin Chen is an Associate Professor of Economics at the University of Rochester, affiliated with the School of Arts & Sciences. He holds a Ph.D. in Economics from Cornell University (2007), an M.A. from Xiamen University (2001), and a B.A. from Xiamen University (1998). His research focuses on econometric theory and financial econometrics, particularly in testing structural changes, diffusion models, and nonparametric methods. He has published in top journals like Econometrica , Journal of Econometrics , and Econometric Theory . Key awards include the PEPR Grant (2011–2013) and the Chinese Government Award for Outstanding Students Abroad (2005). He has advised graduate students such as Liquan Huang and served on committees for Tak Wai Chau (Economics) and Zhen Chen (Biostatistics). His computational expertise includes MATLAB, GAUSS, and STATA, with access to financial databases like CRSP and NYSE TAQ. Chen has presented at conferences worldwide, including the Econometric Society World Congress and symposia in Seoul and Xiamen. He is a member of the Econometric Society and has reviewed for journals such as Journal of Econometrics and Quantitative Economics .

• Chemical modeling of planetary atmospheres
• Exoplanetary atmospheres
• Astrochemistry
• +۷ مورد دیگر

Dr. Éric Hébrard is a Senior Lecturer in Astrophysics at the University of Exeter since 2018, with prior academic roles including NASA Goddard Senior Research Fellow and CNRS Research Associate. His work bridges planetary atmospheres, astrochemistry, and combustion modeling with expertise in 3D chemical simulations. PhD in Physics and Chemistry of Planetary Atmospheres, Université Paris 7 (2006) Magna cum laude Magistère Interuniversitaire de Chimie, ENS Paris (2003) Research focuses on: Exoplanetary atmosphere modeling (hot Jupiters, TRAPPIST-1e) Photochemical kinetics and UV absorption Coupling of atmospheric circulation and chemistry Cross-disciplinary combustion-atmosphere analogs Chemical validation strategies for model accuracy Scientific contributions include: NASA-funded research on organic-rich habitable zones Development of KIDA kinetic database for astrochemistry STFC Consolidated Grant for multi-dimensional chemical models Quantum chemistry integration for Titan atmosphere studies Awards: Higher Education Academy Fellowship (ASPIRE program) NASA Postdoctoral Fellowship (2015-2017) CNES Postdoctoral Fellowship (2007-2009)

Donat Fähمشاهده پروفایل

استاد

• Seismology
• Geophysics
• Earthquake Engineering
• +۷ مورد دیگر

Prof. Donat Fäh is a faculty member at ETH Zurich's Institute of Geophysics, part of the Swiss Seismological Service (SED). His work focuses on advancing seismic hazard assessment and site response modeling in Switzerland and beyond. He leads interdisciplinary projects integrating geophysical surveys, machine learning, and empirical data to refine risk models for urban areas like Basel and Lucerne. Key contributions include developing the ERM-CH23 national earthquake risk framework and improving methodologies for nonlinear soil behavior analysis using KiK-net data from Japan. His research emphasizes high-resolution amplification mapping, subsurface characterization via ambient vibrations, and understanding glacial and subaqueous slope dynamics. Research interests span seismic site effects, soil mechanics, landslide stability monitoring, and the application of advanced geophysical inversion techniques. He collaborates internationally to enhance earthquake risk communication and building code compliance, particularly in low seismicity regions. Current efforts include refining 3D geophysical models for urban settings and exploring Bayesian methods for subsurface structure identification. His work bridges fundamental geophysical research with practical engineering solutions for infrastructure resilience. Advising and grants: No formal advisees or grant details are explicitly listed in the provided texts. His collaborative projects, however, suggest involvement in large-scale initiatives such as URBASIS and the Swiss strong-motion network modernization. Labs and teams: Prof. Fäh is affiliated with the Swiss Seismological Service (SED) and actively contributes to ETH Zurich’s seismic monitoring infrastructure. His team collaborates with institutions in Japan (KiK-net network) and applies cutting-edge geophysical techniques to study subglacial environments and lakebed geotechnics.

Maud Rotgerمشاهده پروفایل

استاد

• Experimental Spectroscopy
• High-Resolution Spectroscopy
• Theoretical Spectroscopy
• +۳ مورد دیگر

Maud Rotger is a Professor at the University of Reims Champagne-Ardenne and has served as Director of the GSMA (Groupe de Spectrométrie Moléculaire et Atmosphérique, UMR CNRS 7331) since January 2018. She holds a university professorship (Professeur CEx1) and has extensive administrative roles, including managing the CNRS unit GSMA since 2017. Her research focuses on experimental and theoretical spectroscopy of molecules such as hexafluorides, diode laser absorption spectroscopy, and analyses of ethylene spectra. She has supervised numerous doctoral students in collaboration with international institutions like the University of Tunis. Rotger’s academic career spans over 30 years, including roles as Chair and Vice-President of the Physics Department. Her research emphasizes high-resolution spectroscopy of molecules in nanoporous solids and their applications. She has contributed to advancing spectral databases like VAMDC and HITRAN. Her supervision of doctoral students includes projects on molecular spectroscopy, line profiles, and collaborations with Tunisian researchers. Despite no explicit awards listed, her leadership and research contributions highlight her prominence in molecular and atmospheric spectrometry.

• Phytoremediation
• Contaminated Site Management
• Plant Ecology in Hostile Environments
• +۵ مورد دیگر

Béatrice Gervais-Bergeron is an Associate Professor at the École d'urbanisme et d'architecture de paysage (Faculty of Urban Planning) at Université de Montréal since December 2024. She holds a PhD in Biological Sciences (2024) and a B.Sc. in Environmental Biology (2019) from McGill University. Her research focuses on phytotechnologies, plant ecology in contaminated environments, and functional trait-based solutions for urban resilience. Affiliations: Member of the Institut de recherche en biologie végétale (IRBV) Teaching: APA1130 Ecology and Sustainable Development; APA2130 Plant Ecology Theory and Practice Programs: Architectural, Landscape Architecture, and Sustainable Development programs Her work combines fundamental plant ecology with applied ecological design, particularly in industrial brownfields and ultramafic soils of southern Québec. Current research investigates plant community adaptations in metal-rich soils to improve contaminated site remediation strategies. Key Projects: Phytoremediation techniques for Ministère des Transports soils (2026-2030); Boisé Steinberg urban phytotechnology applications Awards: 2024 Marcelle-Gauvreau Scholarship; 2023 SQP Research Grant Supervision: Currently guiding 4 students across thesis, internships, and directed studies focusing on functional traits, spectral correlations, and urban ecosystem resilience. Labs/Teams: Active member of IRBV, collaborating internationally on hyperaccumulator plant research.

Bin Maمشاهده پروفایل

استاد

• Bioinformatics
• Mass Spectrometry
• Protein Sequencing
• +۲ مورد دیگر

Bin Ma is Professor of Computer Science at the University of Waterloo's Cheriton School of Computer Science, specializing in bioinformatics and computational proteomics. He develops novel mass spectrometry methods and algorithms for protein sequencing and antibody discovery. Education: Ph.D. Computer Science, Peking University B.Sc. Computer Science, Peking University Professor Ma's research creates computational tools for de novo protein sequencing using mass spectrometry data. His innovations enable high-accuracy determination of protein amino acid sequences without reference databases. Current applications include identifying neutralizing antibodies for COVID-19 and detecting cancer biomarkers. Recent publications (2021-2024) focus on clinical proteomics advancements: M-protein monitoring for multiple myeloma (2021), antibody discovery from serum (2024), and neoantigen identification (2024). His 15 most cited works demonstrate consistent innovation in mass spectrometry data analysis and diagnostic applications. Professor Ma leads research funded by national agencies and industry partners. He collaborates with clinical researchers to translate computational methods into medical diagnostics. Professional service includes editorial work for bioinformatics journals and conference program committees.

• Telecommunications
• Wireless Sensor Networks
• Air Quality Monitoring
• +۷ مورد دیگر

Alexandre Manuel de Castro Passos de Almeida is an Assistant Professor in the Department of Information Science and Technology at the University Institute of Lisbon (ISCTE-IUL), where he also contributes to the School of Technology and Architecture. He is an Associate Researcher at the Institute of Telecommunications - IUL, actively involved in the Radio Systems Group, focusing on telecommunications and sensor-based environmental monitoring. PhD in Telecommunications, ISCTE-IUL, 2012 His research interests span telecommunications, wireless sensor networks, air quality monitoring, computer architecture, and robotics. He has led and contributed to innovative projects such as ExpoLis, which uses mobile sensor networks on public buses to map urban air pollution. His work bridges engineering and environmental science, aiming to influence urban policy and public health through real-time data systems. The most recent publications highlight a strong trend toward deploying low-cost, mobile sensor networks for environmental monitoring, particularly in urban settings. His work integrates computer systems, signal processing, and sustainable technology, with applications in smart cities, public health, and robotics. Topics like air quality mapping, energy harvesting, and noise-aware robot navigation reflect a multidisciplinary approach to solving real-world problems. He has advised seven Master’s students at ISCTE-IUL, guiding research in sensor networks, air pollution, database performance, robotic navigation, and personal photography assistants. While no specific scientific awards are listed, his contributions to funded research projects and consistent scholarly output indicate recognition in his field. He has held leadership roles in academic governance, including Vice President of the Pedagogical Council, underscoring his institutional engagement. His teaching portfolio includes core courses such as Fundamentals of Computer Architecture, Operating Systems, and Big Data Processing, delivered across multiple undergraduate and postgraduate programs. He is involved in research projects that combine academic innovation with practical urban applications, particularly through the deployment of scalable, open-source environmental sensing systems.

• Big Data Management
• Data Mining
• Graph Learning
• +۹ مورد دیگر

Dr. YANG, Renchi is an Assistant Professor in the Department of Computer Science at Hong Kong Baptist University, Faculty of Science. He earned his BEng in Software Engineering from Beijing University of Posts and Telecommunications and his PhD in Computer Science from Nanyang Technological University, followed by a postdoctoral fellowship at the National University of Singapore. His research is centered on developing efficient algorithms and systems for large-scale data management and analysis. His research interests include: Big Data Management and Analysis Graph Learning and Network Embedding Databases and Data Management (especially graph query processing and similarity search) The Web and Information Retrieval (search, ranking, recommendation, web mining) Data Mining and Machine Learning (social network analysis, text mining, large language models) Dr. Yang’s recent publications span top conferences such as KDD, SIGMOD, WWW, ICDE, and AAAI, focusing on scalable graph clustering, network embedding, GNNs, and LLM integration. His work emphasizes algorithmic efficiency, scalability, and practical applications in real-world graph data. Scientific honors include: VLDB 2021 Best Research Paper Award 2022 ACM SIGMOD Research Highlight Award Best Paper Award Nominee in WWW 2022 Honorable mention as best PC member in WWW 2022 Dr. Yang actively mentors PhD and research students, currently supervising several RPg students including LIN Xiaoyang, LAI Yurui, and ZHENG Haoran. He has secured research funding enabling PhD scholarships and research assistant positions. He serves on the program committees of major conferences like VLDB, KDD, WWW, and SIGIR, and reviews for journals including TKDE and VLDBJ. He is a key member of the Database Research Group at HKBU, which has published extensively in top venues, including 8 papers at SIGMOD 2023. His research lab, the LAGAS Group, focuses on large-scale graph analytics and systems. The team is actively working on projects involving graph clustering, embedding, GNNs, and integration with large language models. Dr. Yang is currently recruiting PhD students for 2026 and research assistants for 2025, indicating active and expanding research operations.

• Astronomy
• Astrophysics
• Exoplanets
• +۴ مورد دیگر

Amy Bonsor is an Official Fellow and Director of Studies in Natural Sciences (Physical) at Queens' College, University of Cambridge. Her academic work focuses on the intersection of astronomy and planetary science, particularly examining the composition and evolution of planetary systems through the lens of white dwarf pollution. Dr. Bonsor's research primarily centers on understanding the composition of exoplanetary material by studying polluted white dwarfs. Her work combines observational astronomy with theoretical modeling to investigate planetary debris disks, tidal interactions, and the geochemical signatures of accreted planetary material. She has made significant contributions to understanding how white dwarfs can serve as cosmic laboratories for studying the bulk composition of exoplanetesimals, including their differentiation processes and volatile content. Her recent publications reveal a strong emphasis on the chemical analysis of planetary material through white dwarf spectroscopy, with particular attention to mineralogy, elemental abundances, and the implications for planetary formation and evolution. She has pioneered approaches combining machine learning with traditional astronomical techniques to categorize and interpret white dwarf spectral data at scale. As Director of Studies in Natural Sciences at Queens' College, Dr. Bonsor plays a key role in undergraduate education within the Physical Sciences track of Cambridge's renowned Natural Sciences Tripos. Her leadership position indicates her standing within the Cambridge academic community and her commitment to nurturing the next generation of scientists.

Li Liمشاهده پروفایل

استاد

• Environmental Engineering
• Water Quality
• Climate Change
• +۵ مورد دیگر

Li Li is a Professor in the Department of Civil and Environmental Engineering at Pennsylvania State University. She leads the Li Reactive Water research group, focusing on the Critical Zone and its response to climate change and human activities. Her work examines interactions between water, soils, rocks, roots, and microbes, with implications for water quality and sustainability. Research interests include reactive transport modeling, stream chemistry dynamics, and the impacts of climate extremes on hydrological systems. She has contributed to high-profile studies such as the discovery of ancient carbon release via rivers and the effects of extreme rainfall on nutrient loss in American soils. Recent recognitions include dual awards from the Earth and Space Association (2024) and being named an Institute of Energy and the Environment Fellow. Her lab actively collaborates on projects like the BioRT-HBV model and applications of deep learning in hydrological data analysis. Key projects: Facilitating environmental investigations with single-column models, maximizing CO₂ trapping in geological formations Leadership roles: IEE Fellow, Principal Investigator of NSF-funded research

• Soil Science
• Measurement Error Analysis
• Soil Chemistry
• +۶ مورد دیگر

Cynthia van Leeuwen is a Postdoctoral Research Fellow at Wageningen University & Research , specializing in Soil Geography and Landscape . Her work focuses on quantifying uncertainties in soil data and improving spectral modeling techniques. PhD in Soil Science (completed Aug 2024) as part of a project on soil databases with quantified uncertainties Active collaborations with researchers like Gerard Heuvelink, V. L. Mulder, and N. J. Kuhn Dr. van Leeuwen's research interests span: Measurement error analysis in soil data Development of pedotransfer functions Soil chemistry and spectral modeling Environmental applications of uncertainty quantification Her publications demonstrate expertise in: Statistical modeling of soil measurement errors Calibration of spectral data Wind erosion and PM10 emissions analysis Dr. van Leeuwen has contributed to significant projects like The development and use of a soil database with quantified uncertainties (2019-2024), and her work has been cited over 80 times in academic literature.

Sarah Rugheimerمشاهده پروفایل

دانشیار

• Astrobiology
• Astrophysics
• Exoplanet Atmospheres
• +۴ مورد دیگر

Prof. Sarah Rugheimer is an Associate Professor and the Allan I. Carswell Chair for the Public Understanding of Astronomy at York University, Toronto. Her research focuses on modeling exoplanet atmospheres, biosignatures, and early Earth conditions, aiming to detect life beyond Earth. She is a TED Fellow (2020), Caroline Herschel Prize winner, and Harvard Horizons Scholar. Rugheimer teaches astrobiology courses and advocates for scientific literacy, co-hosting the podcast 'Self-care with Drs. Sarah.' She actively promotes gender equity in STEM, curating resources on systemic biases and mentoring students. Her work bridges academia and public outreach, emphasizing the societal impact of scientific communication. Education: B.Sc. Physics (University of Calgary), M.A. & Ph.D. Astrophysics (Harvard University). Research: Specializes in detecting biosignatures using telescopes like James Webb and LUVOIR. Her spectral databases guide exoplanet studies across stellar types. She explores prebiotic molecules (e.g., HCN) and how stellar activity affects planetary atmospheres. Awards: TED Fellowship, Caroline Herschel Prize, Distinction in Teaching (Harvard). Teaching/Outreach: Designed popular courses at St. Andrews and Tufts. Mentors D.Phil. students at Oxford and advocates for inclusive education. Co-founded PolicyLab for science policy advocacy. Labs/Teams: Leads research on exoplanet atmospheres and co-hosts a podcast promoting researcher well-being. Collaborates on GeoBus outreach and Cite Black Women initiatives.

Erica Goldمشاهده پروفایل

مدرس

• Phonetics
• Sociolinguistics
• Forensic Speech Science
• +۴ مورد دیگر

Erica Gold serves as a Lecturer in the Department of Linguistics within the College of Humanities, Arts, Behavioral and Social Sciences at California State University San Marcos. Her academic background includes a Ph.D. in Linguistics and MSc in Forensic Speech Science from the University of York, UK, and a B.A. in Linguistics from UC San Diego. Ph.D. in Linguistics; University of York, U.K. MSc in Forensic Speech Science; University of York, U.K. B.A. in Linguistics; University of California San Diego Dr. Gold's research focuses on the intersection of phonetics and sociolinguistics, employing acoustic, auditory, and data-intensive approaches to inform both linguistic theory and forensic applications. Her primary interests include phonetic variation in vowels, speaking tempo, hesitation markers, and voice quality as they relate to regional and social accents/dialects, with particular attention to inter-speaker and intra-speaker variability across different populations. Her work bridges theoretical linguistics with practical forensic speaker identification applications. Analysis of her publication record reveals consistent specialization in forensic phonetics, with particular emphasis on speaker identification methodologies, regional dialect variation (especially West Yorkshire English), and the application of acoustic analysis to forensic evidence. Her research demonstrates methodological rigor through the development and validation of speech tempo measures, voice quality analysis, and large-scale regional speech databases for forensic reference populations. Dr. Gold serves as an Editorial Assistant for Babel: The Language Magazine, which publishes linguistics content for lay audiences, and is a Full Member of the OSAC subcommittee on Speaker Recognition for the National Institute for Standards and Technology, where she contributes to developing forensic speaker recognition standards. She teaches foundational linguistics courses including LING 101: Mysteries of Human Language and LING 200: English Grammar and Syntax, bringing her research expertise in phonetics and forensic applications into the classroom. Her professional activities demonstrate strong engagement with both academic linguistics and practical forensic applications through publications, committee work, and database development.

Junlin Yuanمشاهده پروفایل

دانشیار

• Fluid Dynamics
• Turbulence Modeling
• Computational Fluid Dynamics (CFD)
• +۴ مورد دیگر

Dr. Junlin Yuan is an Associate Professor in the Department of Mechanical Engineering at Michigan State University, within the College of Engineering. Her research focuses on large-scale numerical simulations of complex turbulent shear flows, particularly addressing non-equilibrium turbulence, wall roughness, and fluid-structure interaction. Applications span engineering, environmental, and bio-locomotive systems. She has secured funding from NSF, ONR, and industry partners. Education: Ph.D. Mechanical Engineering, Queen's University, Canada (2015) M.S. Mechanical Engineering, Queen's University, Canada (2011) B.Eng. Aerospace Engineering, Northwestern Polytechnical University, China (2009) Research Interests: Dr. Yuan's work emphasizes understanding turbulence in complex geometries through direct numerical simulations (DNS) and developing physics-based models. Key areas include roughness sublayer dynamics, adverse pressure gradient effects, hyporheic exchange modeling, and turbulence-induced noise prediction. Her lab, the Turbulence Simulation & Modeling (TSM) Lab, bridges fundamental turbulence physics with practical engineering challenges. Grants & Advising: She secured a $400k NSF grant (CC* Compute) for high-memory computing infrastructure and a $490k NSF award on biomimetic fluid-structure interaction. Advised PhD students include Guangchen Shen, Saurabh Pargal, and Sai Mangavelli. Students have received fellowships such as the Richard H. Brown Endowed Fellowship and CFD Society of Canada scholarships. Labs & Teams: Directs the TSM Lab, which employs DNS and CFD tools to explore turbulence in environmental and engineered systems. Collaborates on projects involving sediment-water interface dynamics and rough wall aerodynamics.

James R. Greenمشاهده پروفایل

استاد

• Machine Learning
• Biomedical Informatics
• Computational Biology
• +۹ مورد دیگر

James R. Green is a Professor in the Department of Systems and Computer Engineering at Carleton University , where he has been a faculty member since 2005. He holds a PhD from Queen's University and is a licensed Professional Engineer (P.Eng.) and Senior Member of IEEE. His work integrates machine learning, biomedical informatics, and high-performance computing. His educational background includes: B.A.Sc. in Systems Design Engineering, University of Waterloo (1998) M.Sc.(Eng.), Queen's University (2000) PhD, Queen's University (2005) Dr. Green's research focuses on machine learning challenges in biomedical informatics , particularly class imbalance and rare event prediction. Key areas include protein structure, function, and interaction prediction; microRNA detection in unique species; non-contact neonatal monitoring; and accelerating scientific computing via parallel architectures like the Cell BE processor. His lab has developed several widely used bioinformatics tools such as PIPE, ProtDCal, and PCI-SUMO. His recent publications reflect a strong trend in computational biology and machine learning , with applications in proteomics, genomics, and medical diagnostics. He has published over 100 peer-reviewed papers and secured funding from NSERC, CIHR, CFI, ORF, OCE, MITACS, and IBM. Scientific and teaching recognitions include: Three teaching awards NSERC Best Project Award (twice: 2006-2007 and 2007-2008) Multiple student projects resulting in conference papers (e.g., CMBEC) He has supervised numerous undergraduate capstone projects in areas such as assistive technologies, robotic systems, and bioinformatics. His teaching portfolio includes courses in Pattern Classification, Machine Learning, Computer Architecture, and Biomedical Engineering. He leads an active research group that bridges computer engineering and life sciences, fostering interdisciplinary collaboration. Lab and research team initiatives include: Development of open-access web servers for protein analysis Collaborations with biologists and clinicians Integration of hardware and software for medical applications