Matthew Louis Mauriello is an Assistant Professor in the Department of Computer and Information Sciences at the University of Delaware , where he directs the Sensify Lab . He holds a PhD in Computer Science from the University of Maryland (2018) and completed postdoctoral work at Stanford University (School of Medicine, 2020; School of Public Policy & Environmental Engineering Department, 2019). Research interests span Human-Computer Interaction (HCI), Ubiquitous Computing, and User-Centered Design with applications in: Sustainability Human-Building Interaction Wearable Technology Personal Informatics Educational Game Design Mental Health Interventions Recent publications highlight trends in stress monitoring (skin-like biosensors, workplace wellbeing), energy auditing (thermography systems), and educational technology (block-based programming tools for teachers). His work appears in ACM CHI, ACM Human-Computer Interaction, and Building and Environment. Scientific awards include: Best Paper Honorable Mention, CHI 2016 Best Paper Honorable Mention, CHI 2015 Best of WebSci'18 Teaching at University of Delaware encompasses courses like Educational Game Design Operating Systems Advanced Web Technologies Computing for Social Good with a focus on project-based learning and systems thinking.
Adriana Kovashka is an Associate Professor at the University of Pittsburgh , affiliated with the School of Computing and Information and serving as Department Chair . Her academic journey began with BA degrees in Computer Science and Media Studies from Pomona College (2008) and a PhD in Computer Science from The University of Texas at Austin (2014). Joined Pitt’s faculty in January 2015 NSF CAREER awardee (2021) Google Faculty Research Award recipient Dr. Kovashka’s research spans Computer Vision , Machine Learning , and Natural Language Processing , focusing on visual rhetoric, weak multimodal supervision, and domain adaptation. She pioneered techniques for analyzing political imagery, developing robust object detection frameworks, and exploring the intersection of visual and textual persuasion through large-scale annotated datasets. Her recent work emphasizes geographic diversity in vision-language systems, audio-visual fusion for domain generalization, and shape-texture bias mitigation in CNNs. Key publications include groundbreaking studies on symbolic reasoning, multimodal dialogue systems, and ethical AI applications in education. Scientific honors include: NSF CRII Award (2016) NSF CAREER Award (2021) Pitt CRDF Award (2016, 2018) Best Paper at ECV Workshop (2021) Google Faculty Research Award (2016, 2018) Dr. Kovashka actively mentors students in multimodal learning projects and collaborates with interdisciplinary teams on NSF-funded initiatives. She co-organizes workshops like the first CVPR workshop on advertisement understanding and leads research groups exploring human-AI co-learning systems.
Dr. Wei Peng is a Professor in the Department of Media and Information at Michigan State University, specializing in health communication technology design and human-computer interaction. Her research explores behavior change mechanisms through interactive media. Ph.D. in Communication from University of Southern California (2006) Key research areas include: Psychological and social effects of interactive media AI-driven health promotion systems Conversational agents for wellness Digital games for physical activity Mobile health applications Combating health misinformation through technology Her 2024-2021 publications demonstrate expertise in AI ethics, health gamification, and technology-based behavior change. Grant collaborations include: National Science Foundation (NSF) - Sensor-enabled family routines for child obesity prevention Robert Wood Johnson Foundation (RWJF) - Exergame development Scientific recognition includes multiple ICA Top Paper Awards and MSU Teacher-Scholar honors. She actively serves on editorial boards of: Journal of Communication Health Communication Games for Health Journal BMC Public Health Currently advising in AI applications for health misinformation and persuasive technology research.
Xuezhe Ma is an Assistant Professor in the Department of Computer Science at the University of Southern California's Viterbi School of Engineering. Previously, he was a Ph.D. student at Carnegie Mellon University's Language Technologies Institute, where he worked under the supervision of Professor Eduard Hovy. His academic journey includes a Master's degree from Shanghai Jiao Tong University's Center for Brain-like Computing and Machine Intelligence and a Bachelor's degree in Computer Science from the same institution. Ph.D. in Computer Science, Carnegie Mellon University (completed ~2020) M.S. in Brain-like Computing, Shanghai Jiao Tong University B.S. in Computer Science, Shanghai Jiao Tong University Dr. Ma's research spans multiple areas at the intersection of Natural Language Processing and Machine Learning, with particular focus on structured prediction, syntactic and semantic parsing, machine translation, language generation, and deep generative models. His recent work has expanded into vision-language models, large language model architectures, and applications across computer vision tasks. His research combines theoretical foundations with practical implementations, as evidenced by his development of tools like NeuroNLP2 and MaxParser. His publication record shows a clear trajectory from foundational NLP work during his PhD (including papers on dependency parsing and sequence labeling) to more recent contributions in generative models and large language systems. The 15 most recent publications reveal a strong focus on addressing fundamental challenges in generative modeling, context handling, and multimodal integration, with applications spanning literary translation, medical imaging, and news diffusion analysis. AI2 Outstanding Intern Award (2018) Dr. Ma has secured research funding supporting his work in generative models and language technologies, with projects focusing on improving the efficiency and capabilities of large language models. His research group at USC is actively working on next-generation language understanding and generation systems, with particular emphasis on context-aware modeling and multimodal integration. He has established collaborations with industry partners including the Allen Institute for AI and has contributed to open-source projects like Texar. At USC, Dr. Ma leads research in the Information Sciences Institute, directing projects on efficient large language model architectures and multimodal reasoning systems. His lab focuses on developing novel approaches to context handling, model efficiency, and multimodal integration, with applications across diverse domains including healthcare, literary analysis, and news media.
Prof. Bahire Efe Özad is a Professor in the Department of Television and Film Studies at Eastern Mediterranean University's Faculty of Communication and Media Studies. She holds a PhD and multiple master's degrees in education and English language teaching. Her research focuses on media studies, social media impact, communication theory, environmental sociology, cinema analysis, and intercultural communication. She has supervised over 80 PhD and Master's theses, reflecting her extensive academic mentorship. Her notable works include analyses of sacred defense cinema, pandemic governance in Northern Cyprus, and systematic reviews on fake news scholarship. She has conducted impactful studies on marital sustainability during the pandemic, Nigerian election media framing, and digital natives' social media use. Her research spans diverse areas including ICT's environmental impact, romantic relationship dynamics, and blog reader engagement. Prof. Özad has led projects like analyzing communication barriers for African students and exploring original scores in film. She maintains an active academic presence through Google Scholar and has contributed to numerous peer-reviewed journals. Her teaching and research activities emphasize interdisciplinary approaches to media, communication, and social dynamics.
Dr. Jean Goodwin is the SAS Institute Distinguished Professor of Rhetoric & Technical Communication at NC State University's Department of Communication, part of the College of Humanities and Social Sciences. She specializes in science communication ethics, civil argumentation, and the rhetoric of controversial scientific topics such as climate change and GMOs. Her work bridges theory and practice, including NSF-funded initiatives like Teaching Responsible Communication of Science, which develops case studies for STEM graduate students. She also leads the Leadership in Public Science cluster through NC State's Chancellor’s Faculty Excellence Program. Education: B.A. in Mathematics (University of Chicago, 1979), J.D. (University of Chicago, 1984), and Ph.D. in Communication/Rhetoric (University of Wisconsin-Madison, 1996). Her career includes over 25 years of teaching rhetoric and mentoring students across communication subfields. Research focuses on how scientists communicate effectively with non-experts, leveraging discourse analysis and conceptual frameworks like speech act theory. Key themes include trust-building in contentious contexts, ethical advocacy roles for scientists, and historical rhetorical strategies from Cicero to modern policy debates. Her work often intersects with civic engagement and interdisciplinary collaboration, such as organizing conferences for science communication scholars and advising organizations like the AAAS. Major publications explore ethical dimensions of science communication, including climate change advocacy, disinformation detection, and pandemic messaging. Awards include the EB Knight Journal Award (2007) and her distinguished professorship. Current initiatives emphasize translating scholarly insights into practical tools for scientists and fostering dialogue between scientific and public communities through funded research partnerships.
Alin Coman is a Professor at Princeton University 's School of Public and International Affairs, leading the Cognition in Collectives Lab . His research explores how cognition emerges and evolves within social contexts, focusing on collective memory, belief dynamics, and emotion regulation through interactions. Education: Ph.D. from the New School for Social Research Research Focus: Integrating laboratory experiments, field studies, social network analysis, and agent-based simulations, his work demonstrates how macro-level phenomena like collective memories and synchronized beliefs arise from micro-level cognitive processes. Key themes include memory convergence, belief propagation in networks, and socially triggered prediction errors. Article Trends: His recent publications address vicarious memory frameworks, emotion regulation contagion, moral narratives, political belief change, pandemic-related belief dynamics, and the role of social norms in cognitive processes. Methodologies often involve network science and experimental paradigms. Advising: Mentors graduate researchers including Ari Dyckovsky, Gracielle Li, and Naomi Vaida. Lab: The Cognition in Collectives Lab employs a social-interactionist approach to study emergent psychological phenomena across groups and networks.
Dr. Koustuv Saha is an Assistant Professor of Computer Science at the University of Illinois Urbana-Champaign (UIUC), leading the OnCARE lab. He holds a PhD from Georgia Tech and a B.Tech from IIT Kharagpur. His research focuses on computational social science, social computing, and ethical AI applications in mental health and wellbeing. His work bridges computer science with psychology, sociology, and public policy to address societal challenges. Education: PhD in Computer Science (Georgia Tech, 2021), B.Tech in CSE (IIT Kharagpur, 2012). Previous roles include Senior Researcher at Microsoft Research Montreal (FATE group) and industry research experience in Silicon Valley. Research interests include wellbeing sensing technologies, algorithmic fairness, and large language models’ societal impacts. Recent work examines caregiver mental health, deceptive wellness apps, and AI ethics in content moderation. His studies combine causal inference, NLP, and multimodal data analysis. Publications span top venues like CHI, CSCW, ICWSM, and JMIR. Notable awards include Georgia Tech’s Outstanding Dissertation Award (2022) and Snap Research Fellowship (2020). He advises on AI governance and collaborates with policymakers, clinicians, and industry. OnCARE lab explores human-centered AI for societal good, with projects on mental health support systems, ethical tech design, and algorithmic transparency in health contexts. Current focus includes caregiver AI tools, LLM-based empathetic systems, and workplace wellbeing interventions.
Mariam Zachariah serves as a Research Fellow at the Centre for Environmental Policy within the Faculty of Natural Sciences at Imperial College London. She is a core contributor to World Weather Attribution (WWA), an international scientific collaboration conducting rapid climate change attribution analyses for extreme weather events globally. Her work bridges climate science, vulnerability assessment, and policy-relevant research. Her educational foundation includes a PhD from the Indian Institute of Technology Bombay (IITB), where she investigated climate impacts on Indian agriculture. This research focused on drought and extreme temperature effects on crop yields in major agrarian regions, recognizing agriculture's critical role in India's climate-vulnerable economy. Zachariah's research centers on near-real-time attribution of extreme events to quantify human-induced climate change influences. Her expertise spans climate modeling, statistical analysis of extreme weather, and integrating vulnerability frameworks to assess compound impacts on communities. She examines how climate change interacts with socioeconomic factors to exacerbate disasters, particularly in agricultural systems and flood-prone regions worldwide. Analysis of her recent publications reveals a dominant focus on rapid attribution of droughts, floods, and heatwaves across diverse global contexts - from the Horn of Africa to Central Europe and South America. These studies consistently demonstrate climate change as a significant amplifier of event severity, while emphasizing how pre-existing vulnerabilities determine actual impacts. Her work increasingly addresses compound hazards and the intersection of climate change with infrastructure failures and land management. As a key member of the World Weather Attribution initiative, Zachariah collaborates with climate scientists, social scientists, and vulnerability experts in a unique operational framework that delivers scientific assessments within days of extreme events. This work directly informs policymakers, media, and affected communities about climate change's role in contemporary disasters.
Professor George Buchanan is a leading researcher in human-computer interaction and digital libraries at RMIT University . His work bridges information science, digital humanities, and health informatics, focusing on usability in sensitive contexts like healthcare and misinformation. Deputy Dean, Research at RMIT University Former Director, University of Melbourne iSchool Research Interests: Digital information interaction Health and aging informatics Disinformation analysis Mobile interface design Digital library systems Key Contributions: Developed mobile web usability benchmarks, spatial hypertext tools, and thermal feedback interfaces. Currently seeking PhD students for 2025 projects on digital browsing and view change dynamics. Awards: Over twenty best paper awards and Honorary Life Fellow of the Royal Society of Arts. Advising: Accepting Masters/PhD supervision in information interaction and digital health domains.
Bonnie Berger is the Simons Professor of Mathematics at the Massachusetts Institute of Technology and head of the Computation and Biology group at MIT's Computer Science and AI Lab. She holds additional appointments as an Associate Member of the Broad Institute, Faculty member of Harvard/MIT Health Science & Technology, and Affiliated Faculty of Harvard Medical School. Her career has been dedicated to pioneering computational approaches in molecular biology, where she has been instrumental in defining the field. Professor Berger's research focuses on designing algorithms to extract biological insights from large-scale data sets. Her work spans Compressive Genomics, Network Inference, Structural Bioinformatics, Genomic Privacy, and Medical Genomics. She actively collaborates with experimental biologists to maximize the power of computation for biological discovery, developing methods that address the challenges of modern high-throughput biological data. Her recent publications demonstrate a strong trend toward integrating machine learning with structural biology and genomic privacy. The articles show increasing sophistication in using deep learning for protein structure prediction, developing privacy-preserving techniques for genomic data sharing, and creating efficient algorithms for massive biological data sets. Her work bridges theoretical computer science with practical biological applications. Professor Berger's scientific recognition includes: Election to the National Academy of Sciences (2021) ISCB Accomplishments by a Senior Scientist Award SIAM Sonya Kovalevsky Lecture Prize Fellowships in ACM, ISCB, AMS, and other prestigious societies Multiple RECOMB Test of Time Awards NIH Margaret Pittman Director's Award She has mentored numerous students who have gone on to make significant contributions in computational biology, including Ellen Zhong, Yun William Yu, and Hyunghoon Cho. Her lab receives substantial research funding supporting projects in genomic privacy, structural bioinformatics, and compressive algorithms for biological data. Professor Berger serves on the Executive Editorial Board of the Journal of Computational Biology and multiple other editorial boards. The Computation and Biology group at MIT CSAIL, which she leads, is at the forefront of developing computational methods for biological discovery. The group combines expertise in algorithms, machine learning, and biology to tackle fundamental challenges in genomics and structural biology. They are currently organizing the Machine Learning in Structural Biology workshop at NeurIPS 2025, highlighting their leadership in this rapidly evolving interdisciplinary field.
David Evan Harris is a Senior Research Fellow at the International Computer Science Institute (ICSI) and a Chancellor’s Public Scholar at the University of California, Berkeley. He serves as a Continuing Lecturer at the Haas School of Business and Senior Advisor for AI Ethics at the Psychology of Technology Institute. He is affiliated with multiple UC Berkeley centers, including CITRIS, the Center for Latin American Studies, EGAL, and the Business and Public Policy Group. M.S., Sociology, University of São Paulo B.A., Political Economy of Environment & Development, UC Berkeley His research focuses on AI ethics, misinformation, civic technology, social media policy, and global development. He explores deceptive design, digital literacy, and the societal impacts of AI, with a particular emphasis on democratic governance and human rights. His recent publications highlight AI ethics, regulatory challenges in AI governance, and international policy frameworks. Earlier work spans social movements, open knowledge, and poverty visualization. David teaches UC Berkeley courses including AI Ethics for Leaders, Civic Technology, and Futures Thinking. He founded the Global Lives Project in 2004 and previously led research at the Institute for the Future (2008–2018). Fluent in English, Portuguese, and Spanish, he has conducted research in 37 countries.
Heidi Vandebosch is a Professor at the University of Antwerp's Department of Communication Studies. A prominent figure in cyberbullying research since 2005, she combines academic rigor with practical applications through her role as senior member of the MIOS research group and leadership in international COST actions. PhD in Social Sciences from KU Leuven (1999) Postdoctoral grants from FWO and KU Leuven research council Academic career progression from assistant professor (2004) to full professor (since 2016) Research Focus : Cyberbullying prevalence, impact, and interventions; digital health games; media psychology; food literacy promotion through social media. Her work bridges theoretical research with practical implementation, including development of the Friendly ATTAC digital game and Cyberscan anti-bullying tools. Key Projects : Friendly ATTAC (€1.04M IWT SBO grant) Cyber-shoc interdisciplinary research BOF Concerted Research Project on adaptive health interventions Awards & Grants : Multiple prestigious FWO grants, IWT SBO funding, and BOF research support. She chairs expert panels and contributes to national educational policy through the Flemish Educational Board (VLOR). Teaching : Offers courses at all academic levels including Introduction to Communication Studies (1BA), Media Audiences & Effects (2BA), and Health Communication (MA). International Engagement : Active in COST actions, editorial roles at Communications. The European Journal of Communication Research , and advisory positions for media literacy initiatives.
Ullrich Ecker is a Professor in the School of Psychological Science at The University of Western Australia (UWA). He holds roles such as Associate Editor for the Journal of Applied Research in Memory and Cognition and Experimental Psychology , and serves on the ARC College of Experts (2023-2025). His academic background includes a PhD from Saarland University (Germany) and a Dipl.Psych. from the same institution. Ecker’s research focuses on misinformation, memory, and decision-making, with a particular emphasis on designing interventions to counter false information. Education: PhD, Saarland University, Germany (2007) Dipl.Psych., Saarland University, Germany (2003) Research Interests: Ecker’s work addresses the psychological mechanisms underlying misinformation, memory updating, and belief change. He explores how people process and retain false information, particularly in the context of social media and public health. Key areas include the effectiveness of debunking strategies, the cognitive underpinnings of belief persistence, and the design of interventions to enhance truth discernment. His research also intersects with societal challenges like climate change communication and public health misinformation. Awards and Recognition: Best Publication Award from the Institute for Information Literacy at Purdue University (2023) Australian Research Awards – Research Field Leader in Cognitive Science (2023) UWA Vice-Chancellor's Award for HDR Supervision (Special Commendation, 2023) School of Psychological Science Award for Research Impact and Innovation (2022) School of Psychological Science Mid-Career Research Award (2022) Grants and Projects: Ecker leads and collaborates on numerous grants, including an ARC Discovery Project (2024–2027) addressing emerging misinformation threats, and the NHMRC Special Initiative HEAL Grant (2022–2027) focusing on health and environmental change. He has also secured funding from the WA Defence Science Centre, DSTG, and the Worldwide Universities Network. Notable projects include developing AI-driven tools to combat disinformation and studying misinformation’s behavioral consequences. He actively supervises PhD students in misinformation research and is open to new candidates. Teaching and Engagement: Ecker teaches Cognitive Psychology and Psychological Research Communication Skills at UWA. He is involved in community engagement, including chairing events on memory and fact-finding. His industrial collaborations focus on designing communication strategies to counter misinformation in public health and defense sectors.
Dr. Daniel A. Sass is an Associate Dean for Graduate Studies and Associate Professor in the Department of Management Science and Statistics at the University of Texas at San Antonio’s Carlos Alvarez College of Business. He directs the Statistical Consulting Center and focuses on methodological research, including psychometrics, structural equation modeling, and factor analysis. His applied work spans education, public health, and organizational behavior. Education: Ph.D. in Management Science and Statistics, University of Wisconsin-Milwaukee B.A., University of Wisconsin-Milwaukee Research Interests : Dr. Sass specializes in advanced statistical methodologies with applications in education and social sciences. His work emphasizes psychometric validation, measurement invariance, and applied collaborative projects. Key areas include teacher retention, classroom management, and cross-cultural scale adaptation. His research bridges theoretical statistical frameworks with real-world challenges in education and public policy. Publications Trends : Recent work explores pandemic impacts on productivity, educator stress in charter schools, and diabetes management programs. Earlier studies focus on statistical methods like factor analysis and structural equation modeling validation. His articles consistently address practical implications for policy and practice. Advising/Grants : While no advisees are listed, his collaborative projects involve interdisciplinary teams across education, public health, and organizational studies. His Statistical Consulting Center supports UTSA researchers in applying rigorous statistical methods to their work. Labs/Teams : Director of the Statistical Consulting Center, providing methodological support for academic and applied research projects.
