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Didar ZowghiView profile

Researcher

• Artificial Intelligence Ethics
• Data Quality Management
• Requirements Engineering
• +4 more

Didar Zowghi is a Senior Principal Research Scientist and Science Team Leader at CSIRO Data61, Australia's national science agency. His work focuses on advancing ethical AI systems, data quality frameworks, and requirements engineering methodologies. He leads research initiatives addressing challenges in AI governance, diversity/inclusion in technology, and human-centered AI development. Research interests include AI ethics, data completeness in healthcare systems, and the application of machine learning in requirements engineering. His contributions span theoretical frameworks for responsible AI patterns, empirical studies on user perceptions of AI tools like M365 Copilot, and analysis of AI's role in global diplomatic practices. Zowghi has published extensively on topics ranging from blockchain in supply chains to pedagogical innovations in software engineering education. His work often bridges technical systems and societal impacts, emphasizing real-world implementation challenges through collaborative industry-academia projects. Notable outputs include the Responsible AI Pattern Catalogue and studies examining barriers to data quality in IoT platforms. He has pioneered frameworks linking innovation initiatives to occupational skill requirements and developed tools like Elica for dynamic requirements knowledge extraction in agile teams.

A. Alperen GünayView profile

Assistant Professor

• Thermal Engineering
• Nanomaterials
• Energy Conversion Systems
• +3 more

A. Alperen Günay is an Assistant Professor in the Department of Mechanical Engineering at Bilkent University . He previously served as an Assistant Professor at METU (2021-2023) and as a researcher at The University of Tokyo (2019-2021). Günay earned his PhD and MS in Mechanical Engineering from the University of Illinois at Urbana-Champaign under Dr. Nenad Miljkovic. Current Affiliation: Bilkent University Prior Affiliations: METU, University of Tokyo Education: PhD (UIUC), MS (UIUC), BS (METU) Research Focus : Developing green passive thermal devices through nanomaterials and phase change technologies. Key areas include radiative cooling , thermophotovoltaic systems , and nanomaterial-based heat sinks . His work spans energy conversion, thermal management, and optical property characterization. Scientific Awards : TÜBİTAK 2232-B Award Laboratory Leadership : Dr. Günay directs the Thermal Research & Optics Laboratory (TROL), focusing on projects like metal-organic framework systems , passive evaporative cooling , and greenhouse films for year-round thermal regulation .

Rick BusselleView profile

Associate Professor

• Media Effects
• Narrative Engagement
• Social Perception
• +3 more

Rick Busselle is an Associate Professor at Bowling Green State University (BGSU), affiliated with the School of Media & Communication within the College of Arts & Sciences. His research focuses on how mediated narratives influence perceptions of social issues like poverty and crime, emphasizing engagement, perceived realism, and the social construction of reality through media. He holds a B.S. in Journalism from BGSU, an M.A. in Telecommunication, and a Ph.D. in Mass Media, both from Michigan State University. Dr. Busselle’s work appears in journals like Communication Theory and Media Psychology , with a focus on narrative engagement, media effects, and psychophysiological responses. He has served on editorial boards for Media Psychology , The Journal of Broadcasting & Electronic Media , and co-edited Media Psychology . His courses include Media Effects, Quantitative Research Methods, and Strategic Communication. His scholarship bridges narrative theory and audience psychology, exploring how stories shape social realities. Recent publications (2022–2008) highlight themes like epistemic monitoring in stories, narrative persuasion, and the cultivation of perceived realism. His research underscores the interplay between cognitive processes and media influence, with applications in communication studies and journalism. Busselle’s contributions extend to editorial leadership and academic mentorship, shaping discourse in media psychology and communication theory without explicit awards but recognized through peer contributions and publication impact.

Teresa WangView profile

Senior Lecturer

• Entity/User Modeling
• Relational/Structural Machine Learning
• Spatial/Temporal Machine Learning
• +5 more

Dr. Teresa Wang is a Senior Lecturer in Data Science at Monash University's Faculty of Information Technology, specializing in entity/user modeling, relational/structural machine learning, and graph/network analysis. She holds a Ph.D. from the University of Queensland and degrees from Nanjing University. Currently, she directs the Master of Data Science Program and teaches courses like FIT5201 Machine Learning. Her research focuses on social, e-commerce, and health data modeling, with notable projects including the Knowledge Enriched Approach for Effective Personalization (2025–2027) and collaborations on AI in Mental Health and Site Safety. Dr. Wang has co-authored over 59 publications, emphasizing areas like ontology matching and multimodal data analysis. She actively supervises PhD students and contributes to initiatives like the CSIRO Next Generation Graduates Program for clean energy and sustainability. Education: Ph.D. in Computer Science (2017), University of Queensland Master of Computer Science (2013), Nanjing University Bachelor of Software Engineering (2010), Nanjing University Research Interests: Entity modeling, spatio-temporal data analysis, graph mining, recommender systems, and health/medical records mining. She explores applications in social media, e-commerce, and healthcare sectors. Projects: "Knowledge Enriched Approach for Effective Personalization" (2025–2027) "AI for Clean Energy and Sustainability" (2023–2027) "CSIRO Next Generation Graduates Program: AI in Mental Health" (2023–2027) "Large-scale multimodal knowledge management" (2022–2025) Grants & Collaborations: Engaged with CSIRO, Crank Group, and Pola Practice Pty Ltd. Her work aligns with UN SDGs in education and sustainable energy systems. Labs/Teams: Part of the Monash Energy Institute and Monash Data Futures Institute, contributing to interdisciplinary AI and energy research.

Sara NabilView profile

Assistant Professor

• Human-Computer Interaction (HCI)
• E-Textiles
• Smart Materials
• +3 more

Sara Nabil is an Assistant Professor at Queen's University's School of Computing within the Faculty of Arts and Science. She leads the HCI Design Studio and previously held a postdoctoral position at Carleton University's Creative Interactions Lab. Her research focuses on integrating interior design, fashion, and product design with interactive technologies, emphasizing e-textiles, smart materials, and shape-changing interfaces. She holds a PhD from Newcastle University and prior experience as an HCI Lecturer, interior designer, and senior software developer. Education: PhD in Computing, Newcastle University (2019) MSc in Computing BSc in Computing Research interests include designing computational spaces, wearable technology, and e-textile interactions. Her work explores sustainable fabrication methods, user-centered design for smart environments, and bridging traditional crafts with digital technologies. Notable projects include exhibitions like 'Living with Adaptive Architecture' and 'Persuasive Pharmacy Space,' showcasing interactive wearables and spaces. Her recent articles (2023–2025) emphasize e-textile innovations, sustainable design, and human-building interactions. Key themes include smart materials in fashion, modular wearables, and community-driven interaction systems. Awards: None explicitly mentioned. Advising/Grants: No details provided. Labs/Teams: Head of HCI Design Studio and part of iStudio Lab, focusing on interioraction design.

• Populist Communication
• Far-Right Movements
• Critical Discourse Studies
• +5 more

Kurt Sengul is a Macquarie University Research Fellow (MQRF) in the School of Communication, Society and Culture. He holds a PhD in Media and Communications from the University of Newcastle (2022). His research focuses on media populism, far-right movements, and critical discourse analysis, with projects exploring the nexus between media and far-right politics in Australia. He has taught at the University of Sydney and University of Newcastle, specializing in political communication, social media, and digital cultures. Research interests include far-right communication strategies, media populism's impact on democracy, critical discourse studies, and anti-gender movements. His work examines topics like far-right humor, online radicalization via platforms like X/Twitter Spaces, and the discursive construction of victimhood. He has published in journals such as Critical Discourse Studies , Television & New Media , and Communication Research and Practice . Professional roles include serving as NSW Representative for ANZCA and secretary of APSA’s Queer Caucus. Media engagements include commentary for The New York Times , The Guardian Australia , and The Sydney Morning Herald . His forthcoming monograph Far-Right Populism in Australia (Bloomsbury) explores communication and discourse strategies of Australian far-right groups.

Timothy FraserView profile

Researcher

• Climate Change Adaptation
• Disaster Resilience
• Energy Policy
• +5 more

Dr. Timothy Fraser is a Computational Social Scientist serving as Ezra Systems Research Associate in Cornell University's Systems Engineering Program and Coordinator for the Center for Transportation, Environment, & Community Health (CTECH). Holding a PhD in Political Science from Northeastern University (2022), he focuses on climate change adaptation, disaster resilience, and energy policy using big data analytics, GIS, and AI. His work bridges computational methods with societal challenges, emphasizing community engagement and policy impact. Education: PhD in Political Science, Northeastern University (2022) MA in Political Science, Northeastern University BA in International and Global Studies, Middlebury College Research Interests: Fraser’s research integrates computational social science with environmental policy, exploring how social networks and governance structures influence cities' climate adaptation strategies. Key areas include renewable energy adoption, disaster evacuation dynamics, and pandemic response mechanisms. He employs mixed methods such as network analysis, statistical modeling, and fieldwork. Grants & Awards: Fulbright Fellowship (2016), Kyushu University Japan Foundation Doctoral Fellowship (2020) USDOT Multimillion Grant Administrator (2022-2023) Teaching & Mentorship: Fraser teaches statistical methods and research design at Cornell, advising over 30+ students in projects published in leading journals. He coordinates capstone teams and mentors researchers in data science and policy analysis. Labs & Projects: Leads the Climate Action in Transportation dashboard initiative (Gao Labs), developing tools for emissions visualization. Collaborates on UNDP social capital mapping projects in Mexico and Paraguay, applying spatial analysis techniques for vulnerable communities.

Minita SanghviView profile

Associate Professor

• Political Marketing
• Gender Studies
• Consumer Behavior
• +5 more

Minita Sanghvi is an Associate Professor of Marketing at the Department of Management and Business, Skidmore College. Her research focuses on political marketing, transformative consumer research, and gender/race discrimination in marketing contexts. She holds a PhD from the University of North Carolina Greensboro, a Graduate Certificate in Feminist Studies from Duke University, and advanced degrees in retailing, management, and commerce from institutions in the US and India. Her teaching portfolio includes courses such as MB 107 Business and Organization Management, MB 214 Foundations of Marketing, and SSP 100 Sexing Politics. Her work bridges academic scholarship and real-world applications, emphasizing intersectional frameworks in business and consumer behavior analysis. Key research themes include gender dynamics in political campaigns, the role of appearance in political branding, and the impact of intersectionality on marketing strategies. Sanghvi’s publications span monographs like Gender and Political Marketing in the United States and the 2016 Presidential Election and peer-reviewed articles in Journal of Business Research and Journal of Marketing Management .

• Observational cosmology
• Galactic astronomy
• Exoplanet science
• +5 more

David W. Hogg is Professor of Physics and Data Science in the Center for Cosmology and Particle Physics in the Department of Physics at New York University. He serves as Senior Research Scientist in the Astronomical Data Group in the Center for Computational Astrophysics of the Flatiron Institute and maintains an affiliation with the Max-Planck-Institut für Astronomie in Heidelberg. His primary research focuses on observational cosmology, particularly approaches that use galaxies to infer physical properties of the Universe. He also conducts significant research on stellar kinematics in the Milky Way and the measurement and discovery of exoplanets. Across all domains, Hogg develops engineering systems and statistical methodologies that enable large-scale astrophysical projects for both his research group and the broader community. Recent work demonstrates expertise in robust statistical methods, particularly dimensionality reduction techniques like Robust-HMF. His research bridges theoretical statistics with practical applications in major astronomical surveys including Gaia, SDSS-V, and SPHEREx. He frequently explores connections between Bayesian and frequentist approaches to astronomical data analysis, with recent work on nuisance parameter integration, anomaly detection, and robust matrix factorization. Research supported by NYU, NASA, NSF, Moore Foundation, Sloan Foundation Additional support from Max Planck Society, Humboldt Foundation, ERC, Simons Foundation Hogg is actively involved in major astronomical projects including Astrometry.net, Gaia, and SDSS, with long-term comprehensive goals of analyzing all galaxies, stars, and astronomical images. His work emphasizes open science principles, reproducible research practices, and the development of publicly accessible tools for the astronomical community.

Kate FarrahiView profile

Associate Professor

• Machine Learning
• Digital Health
• Human Sensing
• +3 more

Dr. Kate Farrahi is an Associate Professor in the ECS department at the University of Southampton, where she leads research in the Vision, Learning and Control (VLC) Group. Previously, she was a Research Assistant at the Idiap Research Institute and earned her PhD in Computer Science from the Swiss Federal Institute of Technology in Lausanne (EPFL). Her work focuses on the intersection of machine learning and digital health, particularly in developing human sensing methods using vision and wearable technologies. She currently supervises four PhD students in Computer Science and actively accepts new PhD applications. Her research interests span machine learning applications in healthcare, including wearable device analytics, epidemiological modeling via AI, and drug discovery through generative methods. She has been recognized with a Best Paper Award (2022) and contributes to interdisciplinary research groups such as the Institute for Life Sciences and Centre for Machine Intelligence. Her work bridges computational methods with real-world health challenges, emphasizing practical deployment of AI solutions in clinical and public health contexts. Research Groups: Vision, Learning and Control; Institute for Life Sciences; Centre for Health Technologies; Centre for Machine Intelligence Key Collaborations: Cross-disciplinary projects combining computer science with biomedical engineering and public health

• Computer Vision
• Computer Graphics
• Numerical Methods
• +8 more

Richard Szeliski is a Distinguished Scientist at Google DeepMind and Affiliate Professor at the University of Washington's Department of Computer Science & Engineering. He previously led the Interactive Visual Media Group at Microsoft Research and founded the Computational Photography group at Facebook. His research focuses on computer vision, computer graphics, and numerical methods, with specialties in 3D modeling from imagery, computational photography, and neural rendering. Education details are not explicitly listed, but his career trajectory indicates advanced academic training in computer science. Research interests include algorithms for 3D reconstruction, image stitching, and optimization techniques. His recent work emphasizes neural rendering, volumetric representations, and large-scale scene modeling. Key contributions include the widely cited textbook Computer Vision: Algorithms and Applications and foundational papers on multi-view stereo, panorama stitching, and energy minimization in MRFs. Publications span 40+ years, with recent focus on radiance fields (NeRF), 3D scene understanding, and real-time rendering systems. Though no explicit awards are listed, his textbook adoption and industry roles reflect significant academic and industrial impact. He advises through his academic role and has contributed to open-source projects like the Bundle Adjustment Library (BAL). Labs/teams include collaborations with Google DeepMind, prior work at Microsoft Research's Interactive Visual Media Group, and academic partnerships at UW's Graphics & Imaging Lab. His work bridges theory and application, addressing challenges in both academic research and industrial-scale systems.

Yen-Chi ChenView profile

Associate Professor

• Nonparametric statistics
• Topological data analysis
• Missing data
• +7 more

Yen-Chi Chen is an Associate Professor in the Department of Statistics at the University of Washington. He also holds positions as a Data Science Fellow at the UW eScience Institute and as a co-investigator and statistician at the National Alzheimer's Coordinating Center. His academic career spans multiple interdisciplinary fields including statistics, data science, and astrostatistics. Chen's educational background includes a Ph.D. from Carnegie Mellon University, where he received prestigious awards including the Umesh K. Gavasakar Thesis Award (2017) and the William S. Dietrich II Presidential Ph.D. Fellowship Award (2015). His research focuses on nonparametric statistics, topological data analysis, missing data methodologies, cluster analysis, manifold learning, and applications in large-scale structure analysis and astrostatistics. Chen has made significant contributions to the development of statistical methods for analyzing cosmic web structures, GPS data, and causal inference with continuous treatments. His work bridges theoretical statistics with practical applications in astronomy, neuroscience, and public health. Analysis of his recent publications reveals a strong emphasis on developing novel statistical frameworks for complex data structures, particularly focusing on density-based methods, manifold learning, and approaches that address challenges in missing data and causal inference without standard assumptions. ASA Noether Early Career Scholar Award, American Statistical Association (2022) CAREER Award, National Science Foundation (2022-2027) Umesh K. Gavasakar Thesis Award, Carnegie Mellon University (2017) William S. Dietrich II Presidential Ph.D. Fellowship Award, Carnegie Mellon University (2015) Chen has advised numerous graduate students across multiple publications, with a focus on developing new statistical methodologies. His research has been supported by major funding agencies including the National Science Foundation and the National Institutes of Health. He is actively involved in several research groups including the UW Geometric Data Analysis Group, the UW Center for Statistics and the Social Sciences, and the National Alzheimer's Coordinating Center.

M. Laura BeninatiView profile

Associate Professor

• Environmental Fluid Mechanics
• Sediment Transport
• Multi-phase Fluid Dynamics
• +3 more

M. Laura Beninati is an Associate Professor of Mechanical Engineering at Bucknell University. She holds dual B.S. degrees in Architectural and Civil Engineering from Drexel University (1994), M.S. in Civil and Mechanical Engineering from Drexel (1997), and a Ph.D. in Mechanical Engineering from the University of Iowa (2004). Her research focuses on environmental fluid mechanics, sediment transport, turbulence dynamics, and experimental fluid mechanics instrumentation. She teaches courses in fluid mechanics, thermodynamics, and engineering experimentation. Awards: Lindback Grant (2007), Swanson Research Fellow (2005-2007), Amelia Earhart Scholarship (2002-2003) Her experimental studies emphasize vortex dynamics and turbulence interactions in fluid flows, with applications to environmental and aerospace engineering. Research methodologies include advanced fluid dynamics instrumentation and computational modeling.

Xiaowen ZhangView profile

Professor

• Cryptography
• Information Security
• Cybersecurity
• +5 more

Xiaowen Zhang is a Professor of Computer Science at the College of Staten Island (CSI), City University of New York (CUNY), and a Doctoral Faculty Member at the CUNY Graduate Center. His academic work bridges theoretical and applied research in cybersecurity, information systems, and network technologies. Dr. Zhang holds a Ph.D. in Computer Science from the CUNY Graduate Center (2007) and a Ph.D. in Electrical Engineering from Northern Jiaotong University (1999), along with an M.A. from CUNY Queens College, an M.S. from Northern Jiaotong University, and a B.S. from Shanxi University. His research focuses on Cryptography, Information Security, Cybersecurity, Secure Biometrics, RFID Security & Privacy, Information Retrieval, and Wireless Sensor Networks . He explores both foundational cryptographic methods—such as secret sharing schemes and hash functions—and their practical implementations in secure systems, including RFID authentication protocols and data visualization platforms for sensor networks. The analysis of his recent publications reveals a consistent focus on security mechanisms in distributed and wireless environments . His work frequently combines cryptographic theory with system-level implementations, particularly in RFID and sensor networks. There is a strong trend toward privacy-preserving protocols, efficient data retrieval, and secure information sharing , often leveraging mathematical structures like Latin squares and Bloom filters. Dr. Zhang has been actively involved in mentoring students, as evidenced by numerous co-authored publications with graduate and undergraduate researchers. His contributions span journals such as Security and Communication Networks , Journal of Applied Security Research , and International Journal of Security and Networks , as well as major conferences including IEEE LISAT, ACM CODASPY, and IEEE Sarnoff Symposium.

Przemyslaw GrabowiczView profile

Assistant Professor

• fair and explainable machine learning
• data science
• computational social science
• +12 more

Przemyslaw Grabowicz is an Assistant Professor of Computer Science at University College Dublin and an Adjunct Professor at the University of Massachusetts Amherst. He leads the SIMS (Socially Intelligent Media and Systems) Lab and the EQUATE initiative, and is actively involved in the Knowledge Discovery Lab (KDL). His work bridges computer science, social science, and public policy, focusing on responsible AI and digital society. Research Interests: Fair and Explainable Machine Learning Computational Social Science Social Media and Network Science Public Opinion Modeling Algorithmic Bias and Discrimination Prevention Open-World Learning His research develops statistical and machine learning methods to understand and augment public opinion in digital environments, ensuring fairness, transparency, and societal benefit. He emphasizes legal compliance and ethical design in AI systems. Recent Research Trends: His recent publications focus on social media polls, political bias, misinformation, and fairness in machine learning. He investigates how algorithmic systems shape public discourse, especially during elections and global crises, and develops methods to detect and mitigate bias in data and models. Scientific Awards and Recognition: Best Paper Honorable Mention, ICWSM’25 WICI Data Challenge Main Prize (2013) Arnold O. Beckman Research Award Multiple UMass Amherst Interdisciplinary Research Grants Volkswagen Foundation Grants (over €900k total) Advising and Grants: Dr. Grabowicz supervises several PhD students in the SIMS and KDL labs and collaborates with MS students. He has secured significant funding from the Volkswagen Foundation, UMass Amherst, and the University of Illinois, supporting research on political misinformation, media bias, and global agenda setting. He is currently recruiting a postdoc at UCD. Labs and Initiatives: He heads the SIMS Lab and the EQUATE initiative, and contributes to the KDL. His project socialpolls.org explores public opinion through social media, and he maintains an active presence through the Uncommon Good blog on responsible AI.