جست‌وجوی استاد و پژوهشگر

Jason Schwebkeمشاهده پروفایل

استادیار

• Taxation
• Tax Compliance
• Tax Policy
• +۴ مورد دیگر

Jason Schwebke is an Assistant Professor of Accounting at Texas Tech University's Rawls College of Business. He holds a PhD from the University of Central Florida and advanced degrees from Northern Illinois University. His expertise spans taxation, data analytics, and behavioral decision-making in accounting contexts. Education: PhD in Accounting, University of Central Florida (2021) MS in Accounting Science (Tax), Northern Illinois University (2012) BS in Finance, Northern Illinois University (2010) Research Focus: Tax compliance mechanisms, tax policy implications, ethical issues in taxation, and data analytics applications in accounting education and practice. He explores topics such as taxpayer behavior in automated systems, decision-making under tax autonomy, and fraud detection through digital tools. Teaching: Specializes in taxation and data analytics courses at undergraduate and graduate levels, with notable curriculum development in Power BI and Microsoft tools integration. Professional Affiliations: Enrolled Agent (IRS), Series 65 Financial Advisor, and operates a part-time tax consultancy. Served as litigation expert in U.S. District Court (2021–2022). Honors: 2025 Texas Tech Alumni Association New Faculty Award 2025 Lyons School Research Fellowship 2024 Big XII Faculty Research Fellowship Service: Associate Editor for Accounting and the Public Interest , coordinates Rawls College's Research Workshop, and chairs PhD committee initiatives. Active in conference organizing and peer-review activities for top accounting journals.

Sameer Singhمشاهده پروفایل

استاد

• Machine Learning
• Natural Language Processing
• Model Interpretability
• +۳ مورد دیگر

Sameer Singh is a Professor of Computer Science at the University of California, Irvine's Donald Bren School of Information and Computer Sciences. He also holds affiliations with Linguistics and EECS departments. His research primarily focuses on the robustness and interpretability of machine learning algorithms, along with models that reason with text and structure for natural language processing. Dr. Singh received his PhD from the University of Massachusetts, Amherst in 2014, an MS in Computer Science from Vanderbilt University in 2007, and a BEng in Electrical Engineering from the University of Delhi in 2004. His research interests span machine learning robustness, natural language processing, model interpretability, and knowledge representation. Singh investigates how to make AI systems more reliable and understandable, particularly focusing on testing methodologies for NLP models and developing techniques to improve model behavior. His work bridges theoretical understanding with practical applications in AI safety and reliability. Analysis of Singh's recent publications reveals a strong focus on language model interpretability, bias detection, and model robustness. His work explores how language models process information, where they fail, and how to make them more reliable. A significant portion of his recent research examines the limitations of multimodal models, language model alignment techniques, and addressing social biases in AI systems. Dr. Singh has received numerous prestigious awards including the Kavli Fellowship from the National Academy of Sciences, the NSF CAREER award, UCI Distinguished Early Career Faculty award, and the Hellman Faculty Fellowship. His papers have won multiple awards including at KDD 2016, ACL 2018, EMNLP 2019, AKBC 2020, and ACL 2020. His research group has secured substantial funding from major organizations including the Allen Institute for AI, Amazon, NSF, DARPA, Adobe Research, Hasso Plattner Institute, NEC, Base 11, and FICO. Singh previously served as an Allen Fellow at the Allen Institute for AI (2021-2023) and is currently a co-founder and CTO of Spiffy AI in Seattle. He completed postdoctoral research at the University of Washington after earning his PhD. Dr. Singh maintains an active presence in the AI community through his work on projects like AutoPrompt and Checklist, which have become influential tools for testing and interpreting NLP models. His research continues to shape how the field approaches model evaluation and interpretability.

Arijit Khanمشاهده پروفایل

دانشیار

• Graph Neural Networks
• Blockchain
• Data Management
• +۵ مورد دیگر

Arijit Khan is an Associate Professor in the Department of Computer Science at Aalborg University, Denmark. He leads the Data Engineering, Science and Systems group and is affiliated with the Technical Faculty of IT and Design. His research focuses on Graph Neural Networks , Blockchain , Data Management , and AI interpretability . He is the Principal Investigator (PI) of a major project on Data Management, Fundamental Algorithms, and Machine Learning for Emerging Problems in Large Networks (2022–2027). Research Interests : Graph Data Management & Machine Learning Blockchain Transaction Analysis Large Language Model + Knowledge Graph Synergies Healthcare AI (e.g., ICU glucose prediction) Explainable AI for Graph Neural Networks Research Trends : His publications emphasize neuro-symbolic systems , uncertain graph analysis , and AI-driven blockchain insights . Recent work bridges large language models with knowledge graphs and explores GPU performance optimization via shader code analysis. Awards & Grants : No explicit awards listed, but his active research grants include a 5-year project on large network analysis with interdisciplinary applications in life and health sciences. Funding emphasizes algorithmic innovation and data science integration. Labs/Teams : Head of the Data Engineering, Science and Systems research group, focusing on AI for societal impact ('AI for the People') and scalable graph data systems. Collaborations span blockchain analytics, healthcare informatics, and GPU architecture design.

• Construction Informatics
• Digital Construction
• Building Information Modelling (BIM)
• +۴ مورد دیگر

Mattias Roupé is an Associate Professor, Head of Department, and Research Area Leader at the Department of Construction Management and Engineering at Chalmers University of Technology. His research focuses on digital construction processes, including Building Information Modelling (BIM), Total BIM, Virtual Reality (VR), and digital twins. He holds a Ph.D. in Virtual Reality for decision-making in urban planning and building design. His work combines technical advancements in visualization and computational methods with human-centric aspects like perception and decision-making in design collaboration. Education: Ph.D. in Virtual Reality applications for urban planning and building design. Research interests span model-based construction processes, data-driven design, and immersive technologies for user involvement in healthcare and infrastructure projects. Notable projects include the Total BIM initiative, exploring integrated digital workflows, and the Digital Twin Cities Centre, advancing smart city technologies. His publications emphasize VR integration, BIM adoption challenges, and collaborative design tools. He leads several research grants funded by organizations like SBUF and Formas, focusing on construction innovation. Key contributions include frameworks for BIM-based scheduling, VR in healthcare facility design, and BIM-GIS integration for railway infrastructure. His work bridges technical and human factors to enhance construction efficiency and sustainability.

Debajyoti Mondalمشاهده پروفایل

دانشیار

• Information visualization
• Graph drawing
• Computational geometry
• +۶ مورد دیگر

Dr. Debajyoti Mondal is an Associate Professor in the Department of Computer Science at the University of Saskatchewan. His research focuses on algorithms, network visualization, computational geometry, and visual analytics. He holds a PhD from the University of Manitoba and has held postdoctoral positions at the University of Waterloo and Microsoft Research. Mondal's work spans interdisciplinary applications, including collaborations with Saskatoon Transit and academic medicine. He has authored over 100 peer-reviewed publications and secured grants such as NSERC Discovery, CFI, and Canada First Research Excellence grants. His awards include the 2023 New Scholar RSAW Award. Education: Ph.D. in Computer Science, University of Manitoba, 2016 MSc in Computer Science, University of Manitoba, 2012 BSc. Engg. in Computer Science, Bangladesh University of Engineering and Technology, 2009 Research Interests : Algorithms, graph drawing, computational geometry, visual analytics, and interdisciplinary applications in software engineering, transportation, and bioinformatics. His lab (VGA Lab) develops visualization systems for big data analysis. Key Contributions : Advanced theoretical foundations in computational geometry and graph drawing, developed practical visualization tools, and contributed to climate-related projects like Global Water Futures. Grants & Awards : NSERC Discovery Grant (2018-2024) CFI Grant (2021-2025) Microsoft Research Internship (2015-2016) New Scholar RSAW Award (2023) Labs/Teams : Leads the VGA Lab, collaborating with interdisciplinary teams on projects like Clone-World (software clone visualization) and SET-STAT-MAP (mixed data visualization).

Philipp Lensingمشاهده پروفایل

استاد

• Virtual Reality
• Augmented Reality
• Mixed Reality
• +۵ مورد دیگر

Prof. Dr.-Ing. Philipp Lensing serves as a Professor in the Faculty of Engineering and Computer Science at Osnabrück University of Applied Sciences. His academic work focuses on cutting-edge developments in virtual and augmented reality systems, computer graphics, and game programming. His research interests span Virtual Reality , Augmented Reality , Mixed Reality , Game Programming , Computer Graphics , and Natural User Interfaces . Prof. Lensing has pioneered work in real-time global illumination techniques, avatar calibration systems, and the integration of virtual content with real environments. His research has been applied across diverse domains including landscape planning, physics education, medical rehabilitation, and industrial engineering. Prof. Lensing's recent publications reveal a strong trend toward practical applications of VR/AR technologies in scientific, educational, and industrial contexts. His work increasingly focuses on multimodal interaction, haptic feedback systems, and the integration of VR with complex scientific instrumentation like scanning probe microscopy. He has supervised numerous student projects focused on VR/AR applications, game development, and 3D modeling. His teaching includes courses on Computer Graphics, 3D Game Programming, Virtual and Augmented Realities, and 3D Modeling and Animation. Prof. Lensing leads several research projects including GROWTH (funded by BMBF), VRnano (BMBF), VRFlow Suite, VR-Physio-BOX, and MoDal-MR, all exploring innovative applications of immersive technologies in various practical contexts.

János Kertészمشاهده پروفایل

استاد

• Statistical Physics
• Complex Networks
• Financial Analysis
• +۹ مورد دیگر

János Kertész is a Professor at the Department of Network and Data Science at Central European University (CEU) since 2012, and previously held the position of Professor at the Budapest University of Technology and Economics (1992–2018). He obtained his PhD in Physics from Eötvös University (1980) and DSc from the Hungarian Academy of Sciences (1989). His research spans statistical physics applications, complex networks, and financial analysis. He has authored over 280 papers and served on editorial boards of journals like Journal of Physics A and Physical Review E . His research focuses on interdisciplinary topics including social network dynamics, systemic risk in economic systems, and algorithmic bias in digital environments. Notable awards include the Széchenyi Prize (Hungary’s highest scientific honor) and the Finland Distinguished Professorship. He has led projects such as SAI (Socially Explainable AI) and HUMANE-AI-NET, addressing algorithmic bias and AI ethics. His work bridges physics-based modeling with real-world social and economic systems, emphasizing computational approaches to corruption, opinion formation, and innovation diffusion. Key contributions include modeling cascading failures in interdependent networks and analyzing attention dynamics on platforms like Sina Weibo during the pandemic. He advises on systemic risk mitigation strategies and collaborates internationally, with visiting roles in Germany, the U.S., France, Italy, and Finland.

Ben Masonمشاهده پروفایل

دانشیار

• Geological Earthquake Engineering
• Cascading Hazards
• Coastal Geotechnics
• +۷ مورد دیگر

Ben Mason is an Associate Professor in the Department of Geological Sciences and Engineering at the University of Nevada, Reno (joined January 2025). Previously, he held faculty positions at Oregon State University's College of Engineering and conducted research at the U.S. Geological Survey's Geologic Hazards Science Center in Golden, Colorado. He holds a Professional Engineer certification (State of Colorado). Education: Ph.D. in Civil and Environmental Engineering, University of California, Berkeley, 2011 M.S. in Civil and Environmental Engineering, University of California, Berkeley, 2007 B.S. in Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, 2006 Research Focus: Mason's work centers on geological earthquake engineering, cascading hazards (e.g., earthquake-tsunami interactions), coastal geotechnics, and post-disaster field reconnaissance. He has conducted extensive studies on fault displacement uncertainty, anthropogenic impacts on ground failure, and sediment instability during tsunami events. His recent projects include analyses of the 2023 Türkiye earthquakes (Pazarcık and Kahramanmaraş) and the 2022 Chihshang earthquake in Taiwan. Publications Trends: His recent articles emphasize advanced modeling techniques for seismic hazards, integration of field observations with theoretical frameworks, and contributions to building code improvements. He frequently collaborates on multi-hazard studies involving tsunami and earthquake interactions, particularly focusing on soil dynamics and liquefaction mechanisms in coastal regions. Grants & Advising: No specific grants or advisee information is provided in the text. However, his involvement with the GEER team (Geo-engineering Extreme Events Reconnaissance) indicates active participation in disaster-response research initiatives. Labs/Teams: Participates in the GEER team for post-disaster geotechnical investigations and collaborates with research groups studying seismic risks and coastal infrastructure resilience. His work leverages centrifuge modeling facilities and state-of-the-art geophysical analysis tools.

Falguni Mukherjeeمشاهده پروفایل

استاد

• GIS
• Urban Governance
• Remote Sensing
• +۳ مورد دیگر

Falguni Mukherjee is a tenured Professor in the Department of Environmental and Geosciences at Sam Houston State University (SHSU) and currently serves as the Associate Dean for Graduate Student Success at the Graduate and Professional School (TGPS). In her administrative role, she focuses on graduate student recruitment, retention, and engagement across campus. She also acts as the university’s faculty and staff ombudsperson, having established the ombuds office at SHSU. Her academic background includes a PhD from the University of Wisconsin-Milwaukee, an M.S. in GIS from the University of Texas at Dallas, and a Bachelor’s in Civil Engineering. Her research explores the intersection of science, society, and technology, particularly examining how technology shapes urban governance in non-Western contexts like South Asia. Central themes include the use of GIS and remote sensing in environmental studies and governance. She investigates urban local bodies’ adoption of digital tools in India, environmental impacts of urbanization, and malaria risk modeling via GIS and remote sensing. Dr. Mukherjee teaches courses such as GIS Principles and Applications, Cartography and Visualization, and GIS Project Management. Her work bridges technical GIS applications with societal implications, emphasizing interdisciplinary approaches to urban planning, e-governance, and technology’s role in public policy. Her publications highlight trends in GIS for e-governance, pandemic response technologies, and spatial analysis of environmental challenges. She advocates for inclusive GIS practices, including participatory methods and community engagement in spatial data projects.

Eugene Chanمشاهده پروفایل

دانشیار

• Consumer Psychology
• Political Ideology and Consumer Behavior
• Marketing Communication
• +۷ مورد دیگر

Eugene Chan is an Associate Professor in the Department of Marketing Management at the Ted Rogers School of Management, Toronto Metropolitan University. He holds a PhD in Marketing from the University of Toronto, a MA in Social Psychology from the University of Chicago, and an AB in Honors Psychology from the University of Michigan, along with an ARCT (Hons) in Piano Performance from the Royal Conservatory of Music, reflecting a multidisciplinary background. His research lies at the intersection of consumer psychology, political ideology, health communication, and sustainability. He employs experimental and survey methods grounded in social science theories to understand how individuals make judgments and decisions in marketplaces and society. Key themes include the influence of political ideology on consumer behavior, strategies for effective marketing and health communication, and promoting environmentally sustainable choices. His work often explores how emotional, moral, and cognitive factors shape consumer decisions. His recent publications span top journals such as Journal of Consumer Psychology , Global Environmental Change , Computers in Human Behavior , and Personality and Social Psychology Bulletin . These studies reveal consistent focus on behavioral interventions, ideological divides, health compliance, and environmental sustainability. Trends indicate a strong emphasis on moral psychology, emotional triggers, and real-world applications in public policy and marketing strategy. Scientific Awards: Emerging Researcher Award, Australian and New Zealand Marketing Academy (2018) Dean’s Award for Excellence in Research by an Early Career Researcher, Monash Business School (2018) He has secured research funding from diverse sources including the National Natural Science Foundation of China, ACR Transformative Consumer Research Grant, IHS Hayek Fund, and the Indiana Commission for Higher Education, supporting projects on fake news mitigation, brand revitalization, moral foundations, and pandemic behavior. He has taught at institutions worldwide, including the University of Toronto, Monash University, and Purdue University, demonstrating international academic engagement. Eugene Chan serves in editorial roles for several journals, including as Associate Editor for Australasian Marketing Journal and International Journal of Consumer Studies , and as Special Issue Editor for Frontiers in Psychology . He also co-authored the 2nd Asia-Pacific edition of the textbook Consumer Behavior , contributing to marketing education. He advises students in consumer behavior and marketing research, though specific advisees are not listed.

Anna Monrealeمشاهده پروفایل

دانشیار

• Privacy-Preserving Data Mining
• Big Data Analytics
• Social Network Analysis
• +۷ مورد دیگر

Anna Monreale is an Associate Professor in the Department of Computer Science at the University of Pisa and a key member of the Knowledge Discovery and Data Mining Laboratory (KDD-Lab), a joint research group with the Information Science and Technology Institute of the National Research Council (ISTI-CNR) in Pisa. Her academic career is rooted in the University of Pisa, where she completed her Bachelor's, Master's, and Ph.D. in Computer Science. Her research focuses on privacy-preserving data analytics, with core interests in big data analytics, social network analysis, spatio-temporal mining, and explainable AI. She is particularly known for her work on privacy-by-design in data mining and evaluating privacy risks in analytical processes. Her research bridges technical innovation with ethical and legal considerations in data science. Her recent publications reveal a strong trend toward explainable AI, privacy in federated learning, and risk assessment in mobility and health data. She actively contributes to developing methods for explaining black-box models, assessing privacy exposure, and balancing privacy, utility, and fairness in AI systems. Privacy by Design Ambassador (2014) ISTI-CNR Young++ Researcher Award (2014) Monreale has advised and co-chaired several international workshops, including PriSMO, PinSoDa, and MoKMaSD, and serves on editorial boards such as Transactions on Data Privacy. She teaches advanced data mining, big data ethics, and database systems across multiple graduate and undergraduate programs. She is involved in major EU projects like SoBigData, XAI, TAILOR, and HumMingBird, reflecting her leadership in data science and AI ethics. She is affiliated with the KDD-Lab, a prominent research group focused on knowledge discovery, social mining, and big data analytics, contributing to both theoretical advances and real-world applications in privacy-aware data science.

James Stewartمشاهده پروفایل

استاد

• Computer-assisted surgery
• Image processing
• Computer graphics
• +۳ مورد دیگر

James Stewart is a Professor at Queen's University's School of Computing. His research focuses on biomedical computing and surgical navigation systems. Education: Ph.D. in Computer Science from Cornell University (1992) Location: Office Goodwin 732 Contact: Phone 613 533-3156 Research Interests Professor Stewart's work bridges computer graphics, image processing, and medical applications. Key areas include: Computer-assisted surgical navigation 3D medical visualization Geospatial data representation Robust geometric computation Human-computer interaction in clinical settings Medical imaging uncertainty analysis Scientific Awards Best Poster Award (2013) for 'Image-guided Osteochondral Autologous Autografting of the Ankle' Publications His publications span multiple domains including: Computer graphics algorithms Medical imaging techniques Geospatial visualization Biomedical engineering applications Surgical navigation systems Robust geometric computation

Anthony Clarkمشاهده پروفایل

استادیار

• Autonomous Robotics
• Evolutionary Robotics
• Computer Vision
• +۷ مورد دیگر

Anthony Clark is an Assistant Professor of Computer Science at Pomona College, where he has been teaching since 2020. Previously, he served as an Assistant Professor at Missouri State University from 2016 to 2020. He directs the ARCS (Autonomous Robotics and Complex Systems) Lab, which focuses on improving the robustness and adaptability of autonomous robots, particularly small-scale systems that can navigate unpredictable terrain and adapt to potential damage. Clark earned his Ph.D. in Computer Science from Michigan State University in 2016, where he worked under Dr. Philip K. McKinley, and his B.S. in Computer Engineering from Kansas State University, graduating magna cum laude. His research centers on making autonomous robots more robust and adaptive through optimization algorithms and multimodal systems. He specializes in evolutionary robotics, computer vision, neural networks, and simulation methods for developing control systems that leverage multiple locomotion mechanisms. His recent work demonstrates strong trends across several domains: developing hybrid locomotion systems (wheel/leg transformations), applying deep learning to terrain classification and pathfinding, using simulation environments for training, and exploring pretraining techniques for evolutionary robotics. His research shows a consistent focus on bridging simulation and real-world applications while addressing challenges in robot adaptability and robustness. Faculty Excellence in Teaching, Missouri State University (2018) Best Paper Award, Workshop on Evolutionary and Reinforcement Learning (2013) Best Paper Award, ALIFE Conference, Behavior and Intelligence Track (2012) Outstanding Reviewer, Elsevier (2018) Master Advisor Certification, Missouri State University (2017) Clark has advised numerous undergraduate and graduate students through the ARCS Lab, with current research involving projects like the Adabot (a robot with multiple locomotion mechanisms) and thermal semantic segmentation for aerial field robots. His teaching portfolio includes courses on data structures, algorithms, neural networks, computer systems, and mobile robotics. He has also served as a Visiting Associate at Caltech's ARC Lab from 2023-2024, working with Dr. Soon-Jo Chung. The ARCS Lab develops simulation environments, optimizes control systems, and fabricates physical robots. Current projects include the Adabot with its geared coaxial shaft mechanism for hybrid locomotion, thermal semantic segmentation using satellite data, and creating dynamic simulation environments with Unreal Engine 5. The lab emphasizes practical applications of theoretical research while training students in both hardware and software aspects of robotics.

Sam S. Ramanujanمشاهده پروفایل

استاد

• Big Data Architecture
• Visual Analytics
• Software Engineering
• +۴ مورد دیگر

Dr. Sam S. Ramanujan is Professor of Computer Information Systems and Analytics at the University of Central Missouri , affiliated with the Harmon College of Business and Professional Studies . He teaches advanced object-oriented programming and software engineering courses, combining over two decades of academic expertise with substantial industry experience in complex system deployment. Doctor of Philosophy in Information Systems (University of Houston, 1995) MBA in CIS and Quantitative Analysis (University of Arkansas, 1989) PGDM in Information Systems (XLRI Institute of Management Studies, 1987) Bachelor of Arts (Hons) in Economics (University of Delhi, 1985) His research spans big data architecture , visual analytics , healthcare IT , and legal aspects of technology . He has published extensively on topics including software maintenance, e-commerce trust models, and cloud-based healthcare systems, with a focus on bridging technical and legal challenges in digital environments. Dr. Ramanujan's academic work shows a consistent focus on software engineering (1995–2017), healthcare IT (2004–2017), and legal-compliance frameworks (2000–2017). His publications demonstrate interdisciplinary expertise in merging technical systems with regulatory requirements . Best Paper Award , Journal of American Academy of Business, Cambridge (2006) He has contributed to pedagogical advancements in distributed computing curricula and collaborates with scholars like S. Kesh and S. Nerur. His industry experience informs real-world applications of his research in software maintenance and offshore operations.

Yoseph Barashمشاهده پروفایل

دانشیار

• Machine Learning
• Computational Biology
• Bioinformatics
• +۴ مورد دیگر

Yoseph Barash is an Associate Professor at the University of Pennsylvania, jointly appointed in the Perelman School of Medicine's Department of Genetics and the School of Engineering and Applied Science's Department of Computer and Information Science. He leads the BioCiphers Lab, integrating machine learning with experimental biology to decode RNA biogenesis and splicing regulation in human disease. Education: B.Sc. in Physics and Computer Science, Hebrew University Ph.D. in Machine Learning, Hebrew University (2006) His research spans Machine Learning , Computational Biology , and Bioinformatics , focusing on predictive models for RNA splicing and its role in diseases like cancer and neurological disorders. He pioneered the splicing code (Barash et al., Nature 2010) and extended it to genetic variations (Xiong et al., Science 2015). Recent publications emphasize RNA splicing variations in cancer, tool development (e.g., MAJIQ V3, MAJIQ-CLIN), and machine learning for drug discovery (e.g., trametinib sensitivity in AML). His work bridges computational innovation with wet-lab validation, enabling novel high-throughput assays. Scientific Awards: Lap-Chee Tsui Publication Award (2010) NSERC EWR Steacie Fellowship Canadian Institute for Advanced Research Fellowship He advises companies in RNA therapeutics and has licensed splicing quantification tools to Pfizer, GSK, and Biogen. His lab collaborates extensively, training students and postdocs in interdisciplinary approaches to RNA biology.