جست‌وجوی استاد و پژوهشگر

• Geological Carbon Storage
• Underground Hydrogen Storage
• Reservoir Engineering
• +۴ مورد دیگر

Hongsheng Wang is a Research Fellow at the Bureau of Economic Geology within the Jackson School of Geosciences at The University of Texas at Austin. His research focuses on advancing subsurface energy technologies through interdisciplinary approaches combining geoscience, engineering, and machine learning. Key areas include geological carbon storage, underground hydrogen storage, reservoir simulation, and fracture mechanics. His work emphasizes innovative applications of machine learning for challenges such as CO2 plume migration forecasting, parameterization of 3D saturation data, and fracture conductivity analysis. He also investigates leakage mitigation strategies in hydrogen storage systems and the role of permeability heterogeneity in subsurface processes. Publications highlight contributions to microfluidic experiments, porous media dynamics, and AI-driven reservoir modeling. Current projects involve surrogate models for large-scale simulations and dimension reduction techniques to enhance computational efficiency in carbon storage assessments.

Muhammad Umarمشاهده پروفایل

عضو هیئت علمی

• Fluvial Dynamics
• Remote Sensing
• GIS Applications
• +۵ مورد دیگر

Muhammad Umar is a Teaching Assistant Professor in the Department of Geography & Geographic Information Science at the University of Illinois, Urbana-Champaign, affiliated with the School of Earth, Society & Environment. He holds a Ph.D. and M.S. in Geography and Meteorology, respectively, and completed a postdoctoral fellowship in Civil and Environmental Engineering. His research focuses on fluvial dynamics, remote sensing, process modeling, and GIS applications, with particular emphasis on river confluences, landslide susceptibility, and agricultural environmental management. Education: Postdoc: University of Illinois, Department of Civil and Environmental Engineering Ph.D.: University of Illinois, Department of Geography and GIS M.S.: COMSATS University Islamabad, Department of Meteorology Research interests span fluvial hydrology, remote sensing for environmental monitoring, and geospatial tool development. Recent work includes analyzing river confluence mixing dynamics, landslide susceptibility in Pakistan’s upper Indus Basin, and crop health assessments using satellite data. He has developed online platforms for soil nitrogen tracking and precision agriculture. His publications (2012–2025) reflect expertise in hydrology, geohazards, and climate-agriculture interactions. Notable contributions include studies on U.S. river confluences, Pakistan’s precipitation datasets, and evapotranspiration trends in South Korea. Teaching includes advanced GIScience and high-performance geospatial computing courses. No scientific awards are explicitly listed, but his work demonstrates significant academic and applied impact. Advising and grants details are not provided in the text. He is affiliated with the university’s Geography department and contributes to interdisciplinary research teams addressing environmental challenges through geospatial technologies.

Bryan Markمشاهده پروفایل

استاد

• Physical Geography
• Climate and Environmental Change
• Paleoclimatology
• +۴ مورد دیگر

Bryan Mark is a Professor in the Department of Geography at The Ohio State University, affiliated with the College of Arts and Sciences. He is also involved with the Byrd Polar and Climate Research Center and the State Climate Office of Ohio. His research focuses on physical geography, climate-glacier-hydrologic dynamics, and mountain studies, with fieldwork in the Peruvian Andes, Great Basin, and Himalayas. Education: Ph.D. 2001, Syracuse University (Earth Sciences) M.A. 1995, Ohio State University (Geography) B.A. 1992, Brown University (History) Research Interests: Earth-Water-Atmosphere interactions, tropical glaciers, and climate change impacts on mountain regions. His work integrates field, lab, and computational methods across disciplines like paleoclimatology, geomorphology, and biogeochemistry. Recent projects include studying glacier retreat, proglacial hydrology, and climate adaptation strategies in vulnerable regions. Advising & Grants: Leads the Glacier Environmental Change research group, collaborating internationally. Active in interdisciplinary projects funded by NSF and other agencies. Courses taught include climatology, global environmental change, and mountain geography. Labs/Teams: Byrd Polar and Climate Research Center, State Climate Office of Ohio. His lab focuses on mountain hydroclimate dynamics and cryo-social systems in the American Cordillera and Himalayas.

Art Poonمشاهده پروفایل

دانشیار

• Bioinformatics
• Phylogenetics
• Molecular Epidemiology
• +۴ مورد دیگر

Art Poon is an Associate Professor at Western University, specializing in bioinformatics and molecular epidemiology. His research focuses on reconstructing virus spread and adaptation using genomic data, with a particular emphasis on HIV and SARS-CoV-2. He holds a PhD from the University of California, San Diego, and completed a postdoc at the UCSD Center for AIDS Research. Poon leads the Poon Lab, developing computational tools for evolutionary analysis and open-source software for high-performance computing. Education: PhD in Biology (UC San Diego), MSc in Zoology (UBC), Postdoctoral training in HIV genomics. His work bridges mathematical modeling, phylogenetics, and machine learning to address public health challenges. Research Interests: Virus evolution, phylodynamics, and the application of network science to epidemiological data. His lab’s tools, like HexSE and CoVizu, enable real-time genomic epidemiology and wastewater-based surveillance. Key Contributions: Developed methods for HIV transmission cluster detection and SARS-CoV-2 variant tracking in wastewater. His work appears in journals like PLoS Computational Biology and Molecular Biology and Evolution.

Cory McCartanمشاهده پروفایل

استاد

• Computational Social Science
• Bayesian Methods
• Causal Inference
• +۵ مورد دیگر

Cory McCartan is the Hoben and Patricia Thomas and Thomas and Ann Hettmansperger Early Career Professor of Statistics at Penn State University, with an affiliate appointment in Political Science. His research focuses on methodological and applied problems in computational social science, including redistricting, Bayesian methods, causal inference, and racial disparities. He co-leads the Algorithm-Assisted Redistricting Methodology (ALARM) Project at Harvard University and develops open-source software for redistricting analysis (e.g., redist , birdie ). McCartan holds a Ph.D. in Statistics from Harvard (2023) and a B.A. in Mathematics from Grinnell College (2019). His work bridges statistical methodology and policy applications, with recent emphasis on legislative redistricting reforms, gerrymandering analysis, and privacy-preserving census data methods. Key projects include evaluating redistricting algorithms, quantifying partisan bias, and estimating disparities in administrative data using Bayesian models. Publications span topics like redistricting simulation, census privacy impacts, and neighborhood modeling. His ALARM Project produces 50-state redistricting simulations for public use, emphasizing reproducible workflows and open-source tools. McCartan's software packages ( e.g. , redist , conformalbayes ) are widely adopted in policy and academic research. Grants and collaborations involve the Voting and Election Science Team and Harvard Data Science Initiative, with computational support from Microsoft. His work has been covered in Science Advances , Proceedings of the National Academy of Sciences , and Science .

Subra Sureshمشاهده پروفایل

استاد

• Algorithmic Fairness
• Machine Learning Ethics
• Data Privacy
• +۳ مورد دیگر

Subra Suresh is a Professor at Large at the School of Engineering, Brown University. His email is Subra_Suresh@brown.edu . He focuses on interdisciplinary research at the intersection of technology and society, emphasizing algorithmic fairness, AI ethics, and computational law. His research interests include addressing biases in machine learning systems, ensuring equitable access to technology, and developing frameworks for ethical AI governance. He explores topics such as data privacy, social network disparities, and legal implications of emerging technologies. Recent publications highlight trends in auditing algorithms for fairness, mitigating bias in decision-making systems, and designing policies for responsible AI deployment. His work bridges technical innovation with societal impact, advocating for transparent and accountable technologies. No scientific awards or grants are explicitly listed in the provided materials. He has not disclosed advisee information, and there is no mention of lab affiliations or teams in the text.

Mansour Almazrouiمشاهده پروفایل

پژوهشگر ارشد

• Climate Science
• Environmental Monitoring
• Atmospheric Science
• +۳ مورد دیگر

Mansour Almazroui is a Research Fellow at the School of Environmental Sciences, University of East Anglia. His research focuses on climate science, environmental monitoring, and atmospheric processes with a particular emphasis on Middle Eastern and Asian regions. He has published extensively on topics including rainfall patterns in Saudi Arabia, satellite-based groundwater monitoring techniques, and the environmental impacts of PPE during the pandemic. Almazroui's work integrates observational data with advanced modeling techniques, as seen in his analysis of CMIP6 climate models and high-resolution atmospheric simulations of ENSO teleconnections. His collaborative projects span across institutions in Egypt, China, Pakistan, and the UK, reflecting a global approach to environmental challenges. Key research areas include climate dynamics, aerosol monitoring, pandemic-related environmental impacts, and hydrological systems. His studies have contributed to better understanding of regional climate variability and pollution mitigation strategies in coastal and arid environments.

Dhirendra Shuklaمشاهده پروفایل

استاد

• Entrepreneurial Finance
• Corporate Governance
• Venture Capital
• +۷ مورد دیگر

Dr. Dhirendra Shukla is the Dr. J. Herbert Smith ACOA Chair at the University of New Brunswick's J Herbert Smith Centre for TME. He holds a PhD in Entrepreneurial Finance from King's College London, an MBA from the Telfer School of Management (University of Ottawa), and advanced engineering degrees from the University of Bradford. His research focuses on venture capital, corporate governance, entrepreneurial finance, and sustainability in renewable energy and technology-driven industries. Education: BEng/MSc in Chemical Engineering & Computing (University of Bradford) MBA (University of Ottawa/Telfer School) PhD in Entrepreneurial Finance (King's College London) His teaching portfolio includes courses on entrepreneurial finance, global engineering, and leadership in technology management. Research interests span venture capital dynamics, IPO governance, blockchain applications, and smart energy systems. He has presented at conferences like the Strategic Management Society and Academy of International Business, contributing to cross-national studies on corporate governance and IPO performance. Shukla's work bridges academia and industry, with projects addressing renewable energy partnerships in Atlantic Canada and federated learning systems for privacy-preserving data analytics. His recent studies explore AI-driven digital twins, cyber-physical systems in smart cities, and blockchain adoption in higher education.

Ly Dinhمشاهده پروفایل

استادیار

• Computational Social Science
• Network Analysis
• Social Simulation Models
• +۵ مورد دیگر

Dr. Ly Dinh is an Assistant Professor at the School of Information within the College of Arts and Sciences at the University of South Florida. Her research focuses on computational social science, leveraging network analysis, social simulations, and text mining to study social and organizational systems. She explores network science applications in crisis informatics, emergency response coordination, and interdisciplinary collaboration dynamics. Her work has been recognized with the 2020 Grace Hopper Scholar for Women in Computing and the 2018 Network Science Fellowship. Dr. Dinh holds a Ph.D. and M.A. from the University of Illinois at Urbana-Champaign and a B.A. from the University of Southern California. Her research spans structural balance theory, crisis communication patterns, and computational methods for analyzing social media data during disasters. Recent projects include studying hurricane response networks, disinformation propagation, and the impact of team science on collaboration diversity. Education: Ph.D., University of Illinois at Urbana-Champaign M.A., University of Illinois at Urbana-Champaign B.A., University of Southern California Her publications emphasize methodological advances in network analysis, crisis informatics, and computational linguistics. Recent work highlights the use of ERGM models for peer review networks, taxonomy alignment experiments, and geospatial text mining for disaster zone identification. She has also contributed to understanding public perception disparities through crowdsourced data and the role of structural balance in signed directed networks. Awards: 2020 Grace Hopper Scholar for Women in Computing 2018 Network Science Fellow at Visible Networks Labs Dr. Dinh’s research bridges theory and practice, with applications in emergency response coordination, academic collaboration optimization, and social media-driven crisis management. She is affiliated with interdisciplinary teams advancing computational methods for societal challenges.

• Poverty Studies
• Sociology of Inequality
• Quantitative Methods
• +۴ مورد دیگر

Jennifer Laird is an Assistant Professor of Sociology at Lehman College (City University of New York, CUNY). She holds a Ph.D. in Sociology from the University of Washington. Her research focuses on poverty, inequality, and quantitative methods, with recent work examining energy insecurity, public sector employment disparities, and immigration policy impacts on vulnerable populations. She co-authored the 2025 book *Powerless: The People's Struggle With Energy Insecurity in America* (Russell Sage Foundation), advancing analysis of household energy hardships. Her peer-reviewed articles span topics such as job stability for Black public-sector workers, state-level poverty variations, and labor force dynamics among Mexican immigrants. Laird’s work has been featured in outlets like *Health Affairs*, *Socius*, and *Demography*, and she received an Honorable Mention for her 2014 student paper from the ASA Population Section. Laird teaches courses in data visualization and social research methods, emphasizing statistical programming and effective data interpretation. At Lehman College, she instructs Sociology 301 (Methods of Social Research) and Sociology 353 (Visualizing Data). Her teaching background also includes roles as a Teaching Assistant at the University of Washington for courses on stratification and applied statistics. Her research has garnered media coverage in *The New York Times*, *Washington Post*, and *Huffington Post*, highlighting the societal implications of her findings on topics like public sector layoffs during the pandemic and SNAP policy impacts on immigrant children.

David Goldbergمشاهده پروفایل

استاد

• Theoretical Cosmology
• Extragalactic Astrophysics
• Gravitational Lensing
• +۲ مورد دیگر

David Goldberg is Professor and Head of the Physics Department at Drexel University. His NSF-funded research focuses on theoretical cosmology, gravitational lensing, and large-scale structure. He holds a PhD from Princeton University and authored multiple books including The Standard Model in a Nutshell and A Relatively Painless Guide to Special Relativity . Research highlights: Cosmic structure formation modeling Flexion lensing techniques Cosmological applications of Bayesian statistics Recent publications analyze gravitational lensing signatures, galaxy mass estimations, and cosmic inflation models. He also contributes to cartography science, developing improved flat map projections.

• Spectroscopy
• Atmospheric Chemistry
• Analytical Chemistry
• +۳ مورد دیگر

Chris Medcraft is a Postdoctoral Researcher at the Faculty of Science and Engineering, Southern Cross University. He holds a PhD from Monash University. His research focuses on spectroscopic techniques (e.g., microwave, infrared, and rotational spectroscopy) applied to molecular systems, atmospheric chemistry, and astrochemical studies. Key interests include molecular interactions, aerosol dynamics, and chiral analysis. Medcraft collaborates with advanced facilities such as the Environmental Analysis Laboratory and utilizes cutting-edge methods like drone-based measurements for marine aerosol studies. His work spans diverse areas, including the decomposition of fluorinated compounds, hydrogen bonding in complex systems, and structural analysis of organic/inorganic complexes. Notable contributions include studies on the Great Barrier Reef’s atmospheric aerosols and the rotational spectroscopy of astrochemical candidates like vinyloxirane. Medcraft’s research integrates experimental and computational approaches to understand molecular behavior in environmental, atmospheric, and astrochemical contexts. He has contributed to interdisciplinary projects leveraging advanced analytical tools such as broadband rotational spectroscopy and synchrotron-based Fourier transform spectrometry.

Milton Halemمشاهده پروفایل

استاد پژوهشی

• Climate Science
• Machine Learning
• Quantum Computing
• +۵ مورد دیگر

Milton Halem is a Research Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC), affiliated with the College of Engineering and Information Technology. He also holds an Emeritus position as Chief Information Research Scientist at NASA Goddard Space Flight Center's Earth Sciences Directorate. His expertise spans machine learning, quantum computing, atmospheric science, and climate modeling. Halem's research focuses on integrating AI with environmental systems, including wildfire digital twins, planetary boundary layer estimation, and climate forecasting. Key research interests include applying deep learning to wildfire prediction, developing quantum algorithms for optimization, and advancing climate observation systems. His work bridges disciplines like remote sensing, cybersecurity, and geophysical data analytics. Awards include NASA's Exceptional Scientific Achievement Medal (2022), Outstanding Leadership Medal (2018), and the Distinguished Service Medal (1996). Affiliations: UMBC CSEE, NASA Goddard (Emeritus) Notable Projects: Wildfire Digital Twin Initiative, SOAR atmospheric radiances system, AI-enhanced air quality forecasting Publications emphasize machine learning applications in climate science, quantum computing, and environmental monitoring. Collaborations include NASA, NOAA, and academic partners worldwide. Current projects explore AI-driven climate models and real-time wildfire impact assessment systems.

• Atmospheric Physics
• Environmental Science
• Dark Matter Research
• +۶ مورد دیگر

Argiriou Athanassios is a Professor of Atmospheric & Environmental Physics at the Department of Physics, University of Patras, Greece. He has served as Head of the Laboratory of Atmospheric Physics (2006–2016), Head of the Applied Physics Section (2010–2011), Deputy Chair of the Physics Department (2011–2013), and Chair of the Physics Department (2013–2015). His academic journey includes a Physics Degree from the University of Patras (1983), a DEA in Physical Energy from the Institut National Polytechnique de Grenoble (1984), and a Doctorat in Physics from Université de Provence (1987). Research interests focus on atmospheric physics, environmental science, dark matter signatures, climate modeling, stable isotope analysis, and energy efficiency. Notable projects include studies on precipitation isotopes in China, quantum computing applications in atmospheric dynamics, and dark matter’s influence on geophysical observations. He has also contributed to energy performance regulations for buildings in Greece and maritime emissions’ impact on air quality in Mediterranean port cities. Recent publications (2020–2025) reveal a strong emphasis on interdisciplinary research, blending geophysics with astrophysics to explore dark universe phenomena and their terrestrial manifestations. His work on Bayesian statistical models for temperature trends and solar energy systems underscores practical applications in climate science and renewable energy. Professional affiliations include membership in the Hellenic Association of Physicists, Hellenic Meteorological Society, and American Geophysical Union. His teaching spans calculus, differential equations, and atmospheric physics courses. Key facilities include the Laboratory of Atmospheric Physics and collaborations with international institutions on climate and energy projects.

Ala'a Al-Habashnaمشاهده پروفایل

استاد مدعو

• Wireless Communication Networks
• 5G/6G Technologies
• Machine Learning Applications
• +۵ مورد دیگر

Ala'a Al-Habashna is an Adjunct Professor at Carleton University's School of Computer Science within the Faculty of Engineering and Design. He holds a PhD from Carleton University and focuses on advanced wireless communication systems, 5G/6G networks, machine learning applications, and discrete-event simulation. His research integrates AI-driven solutions for network optimization, spectrum management, and smart urban infrastructure analysis. Education: PhD in Computer Science, Carleton University Research Interests: 5G/6G Networks, Machine Learning for Communications, Cognitive Radio Systems, IoT Integration, and Urban Modeling via Computer Vision Focus on resource allocation algorithms, channel modeling, and AI-driven network architectures Key Article Trends: Recent work emphasizes AI integration in next-gen networks (e.g., RIS-assisted MIMO, GenAI-6G), 5G energy efficiency, and urban analytics using street-view imagery. Earlier contributions include DEVS-based simulation frameworks for fire modeling and D2D video streaming optimization. Collaborations & Funding: Active partnerships include Ericsson Canada for projects like Channel Reconstruction for LTE/NR and Spectrum Sharing with Machine Learning . A funded PhD position is available in Wireless Communication and 5G Networks requiring expertise in Mathematical Optimization. Labs & Teams: Engaged in Ericsson-Carleton Partnership initiatives and leads interdisciplinary teams addressing 6G challenges. Research leverages Carleton's advanced wireless and AI facilities.