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Dr. Amiangshu Bosu is an Assistant Professor in the Department of Computer Science at Wayne State University. His research focuses on software engineering analytics, with specialization in code review practices, software security, malware detection, and empirical analysis of open-source communities. Dr. Bosu directs the Software Engineering Analytics (SEAL) Lab, where he mentors PhD students in cutting-edge software engineering research. His research interests span both technical and human aspects of software development, including cybersecurity, blockchain systems, mining software repositories, and social network analysis in technical communities. Dr. Bosu's work examines how communication patterns affect software quality and team collaboration. Dr. Bosu's publications demonstrate consistent focus on improving software quality through empirical studies of developer practices. Recent work explores toxicity detection in code reviews, gender bias in open-source communities, and onboarding strategies for new contributors. His NSF CAREER award supports research transforming peer code review environments. Awards: NSF CAREER Award (2024) NSF CRII Award (2019) College of Engineering Research Excellence (2025) Outstanding Graduate Researcher, University of Alabama (2015, 2014) Research Group: Leads the Software Engineering Analytics (SEAL) Lab where he advises multiple PhD students working on empirical software engineering projects funded by NSF grants. Current research includes automated detection of toxic communications and gender discrimination in developer interactions.

• Code Review
• Software Security
• Android Security
• +6 more

Sukwoong Choi is an Assistant Professor at the Department of Information Systems and Business Analytics, Massry School of Business, University at Albany, SUNY. He is also a Digital Fellow at MIT's Initiative on the Digital Economy. His research focuses on innovation and entrepreneurship driven by AI, quantum computing, and algorithms, particularly examining their economic impacts on decision-making, R&D, productivity, and labor markets. Education: PhD from KAIST College of Business. Postdoctoral roles at MIT Sloan/CSAIL, USC (Technology Innovation & Entrepreneurship), and University of Kentucky (Gatton College of Business). Visiting scholarships at UC Berkeley (Haas School) and Northwestern University (Kellogg School). Research Interests : AI's dual role in advancing knowledge while reducing diversity Quantum computing adoption challenges Economic implications of AI in labor and R&D Technology competition networks Key Contributions : Over 15 peer-reviewed publications in top journals like PNAS Nexus, Strategic Management Journal, and California Management Review. Notable awards include the Best Interdisciplinary Paper Award (SMS 2021) and KOSIME 2024 Best Paper. Media coverage includes New York Times, Yahoo Finance, and MIT Sloan. Teaching : Courses in Analytics, Business Intelligence, and Network Analysis at UAlbany, UKY, and KAIST. Consistently high instructor ratings (4.2-4.9/5). Grants : Co-PI of a $19,400 USC grant studying AI's impact on medical decision-making (2022-2023). Professional Activities : Active in academic conferences, editorial reviews, and digital economy initiatives. GitHub contributions focus on research tools and open-source projects.

• Innovation
• Entrepreneurship
• Artificial Intelligence (AI)
• +7 more

Shyam Ranganathan is an Assistant Professor in the Department of Mathematical and Statistical Sciences at Clemson University, with an additional appointment as a Faculty Scholar at the Clemson School of Health Research. He holds a PhD in Mathematics from Uppsala University, an MS in Electrical Engineering from the University of Notre Dame, and a BTech in Electrical Engineering from the Indian Institute of Technology-Madras. His research focuses on interdisciplinary applications of mathematical and statistical methods to address complex problems in environmental science, public health, social systems, and engineering. Key areas include dynamical systems modeling for sustainable development goals, statistical analysis of health outcomes linked to environmental exposures, and biomechanical studies involving movement analysis. He also explores virtual reality applications for mental health interventions and network analysis for policy design. Ranganathan's work bridges theoretical frameworks with real-world data, emphasizing practical policy implications. His publications span journals in mathematics, engineering, environmental science, and social sciences, reflecting his commitment to cross-disciplinary collaboration. While no awards are explicitly listed, his prolific publication record indicates significant scholarly contributions. His roles at Clemson involve both academic teaching and research leadership in health-related initiatives. His advising and grant activities are not detailed here, but his research collaborations suggest involvement in funded projects related to health, environment, and development. He contributes to the Clemson School of Health Research, focusing on health metrics and innovative methodologies.

• Applied Mathematics
• Statistical Modeling
• Environmental Health
• +3 more

Dr. Minjuan Wang is Professor and Program Head of Learning Design and Technology at San Diego State University's School of Journalism and Media Studies within the College of Education. She serves as Editor-in-Chief of the IEEE Transactions on Learning Technologies (TLT) and previously managed programs at the Chancellor's Office of CSU. Her multidisciplinary research focuses on emerging educational technologies including Metaverse learning, Cross-Reality (XR) environments, AI applications in education, and sociocultural aspects of technology-enhanced learning. Dr. Wang's current research includes co-PI responsibilities on NSF's Coupled Natural and Human Systems project through SDSU's Department of Geography. As an internationally recognized scholar, she has delivered approximately 35 keynote addresses at global conferences and authored over 100 peer-reviewed publications that are extensively cited worldwide. Her research explores how immersive technologies transform learning paradigms, particularly examining: Generative AI's role in reshaping pedagogical approaches Cross-reality environments as educational spaces Socio-technical systems in global learning contexts Metaverse ecosystems for collaborative education Analysis of her recent publications reveals strong emphasis on immersive learning technologies, AI-driven educational transformation, and innovative pedagogical frameworks. The research consistently demonstrates interdisciplinary approaches connecting educational theory with technological innovation.

• Educational Technology
• Metaverse Learning
• Cross-Reality Learning
• +3 more

Dr. Hillary Swanson is an Assistant Professor in the Department of Instructional Technology & Learning Sciences at the University of Utah State University, affiliated with the Emma Eccles Jones College of Education and Human Services. Her work bridges science education, technology integration, and cognitive development. She holds a PhD in Science and Mathematics Education from UC Berkeley and a BA in Physics from Colorado College. Her research focuses on how students refine everyday thinking into scientific understanding through theory-building practices, computational modeling, and collaborative learning. Key projects include developing computational microworlds for physics education and co-designing instructional tools with teachers to support responsive teaching strategies. She directs the Learning Dynamics Lab, exploring how technology can scaffold student reasoning and teacher pedagogy. Her publications emphasize theory-building mechanisms, formative assessment integration, and the role of intuitive resources in learning. She has collaborated with institutions like Northwestern University’s CCL and TIDAL labs. Current work includes applying generative AI in qualitative research and designing embodied artifacts for mathematical reasoning.

• Science Education
• Educational Technology
• Cognitive Science of Learning
• +5 more

Benedikt Harrer is a Clinical Associate Professor in the Department of Physics at the University at Buffalo, affiliated with the College of Arts and Sciences. He specializes in physics education research, focusing on gestures in learning, collaborative problem solving, and energy concepts. His work examines how gestures and embodied cognition contribute to classroom interaction and student understanding in STEM fields. Previously, he served at UC Berkeley's Cal Teach program and San José State University. He holds a PhD in physics from the University of Maine (2013) and a Staatsexamen in physics/mathematics from Ludwig-Maximilians-Universität Munich (2009). Education: Staatsexamen LAG, Physics and Mathematics (2009) – Ludwig-Maximilians-Universität, Munich PhD in Physics (2013) – University of Maine Research interests center on the role of gesture in STEM education, particularly in energy dynamics and collaborative learning environments. He investigates how teachers and students use gestures to mediate conceptual understanding, synthesize ideas, and engage in productive disciplinary practices. His studies often involve multimodal analysis of classroom interactions, emphasizing the interplay between verbal and nonverbal communication. Recent publications highlight trends in analyzing gestural pauses, collaborative problem-solving techniques, and energy representation strategies. His work underscores the importance of embodied interaction in fostering conceptual clarity and pedagogical responsiveness. No scientific awards are explicitly noted in the provided texts. His contributions include curricular design and analytical frameworks for studying learning processes, reflecting a focus on translating theoretical insights into practical educational tools.

• Physics Education Research
• STEM Education
• Gestures in Learning
• +3 more

Dr. Tien Nguyen is an Associate Professor in the Department of Computer Science at UT Dallas' Erik Jonsson School of Engineering. His research focuses on software engineering innovations, particularly in machine learning applications for code analysis, vulnerability detection, and automated testing. He develops neural network approaches to enhance software quality and security. Recent publications demonstrate strong emphasis on AI-driven software solutions, including GPT-based test generation, neural vulnerability scanners, and code representation learning. His team's work bridges theoretical computer science with practical developer tools, evidenced by studies on syntactic sugar design and program dependence learning. Dr. Nguyen's lab maintains active industry collaborations, with translational research addressing real-world challenges in code maintenance and cybersecurity. Current projects explore context-aware code analysis and self-improving language models for programming assistance.

• Software Engineering
• Machine Learning
• Neural Networks
• +3 more

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.

• Computational Social Science
• Network Analysis
• Social Simulation Models
• +5 more

Joseph Hundley is an Associate Professor in the Department of Mathematics at the University at Buffalo. His primary research focuses on automorphic forms, L-functions, and representation theory, with significant contributions to the study of Spin L-functions and automorphic representations for groups like GSO₁₀, GSpin, and quasi-split D₄. He has co-authored foundational texts on automorphic L-functions for general linear groups. Education: PhD in Mathematics, Columbia University Research Interests: Hundley's work centers on advanced topics in number theory and representation theory, including Fourier coefficients of automorphic forms, integral representations of L-functions, and applications of the Rankin-Selberg method to orthogonal and unitary groups. His research often intersects with the Langlands program and functoriality conjectures. Recent Research Trends: His publications highlight investigations into p-adic representations, spin L-functions for classical groups, and multiplicity questions in automorphic forms. Ongoing work extends to G₂ groups and multi-variable Rankin-Selberg integrals. Awards: No specific prizes or fellowships are listed, though his contributions have been recognized through prestigious publication venues like the Memoirs of the AMS and Israel Journal of Mathematics. Grants and Advising: While specific grants are not detailed, his collaborative works with researchers like D. Ginzburg and Q. Zhang suggest active involvement in funded projects. He has advised doctoral students in areas tied to his research specializations.

• Automorphic Forms
• L-functions
• Number Theory
• +3 more

Jeffrey Nickerson is a Professor and Steven Shulman '62 Endowed Chair for Business Leadership at the School of Business, Stevens Institute of Technology. His research focuses on collective intelligence, design/creativity processes, and digital innovation. He holds leadership roles in multiple institutional committees including the School of Business Research Committee, University Promotion and Tenure Committee, and Hanlon Advisory Board. His work spans grants such as NSF projects on automation in news production and peer production networks. He actively contributes to professional societies like ACM, AOM, and AAAI. Recent publications explore AI-augmented journalism, organizational data work, and metaverse design principles. His research bridges technology, management, and societal impact. Education details are not explicitly stated in the text. He has advised on grants totaling over $2M and collaborates with institutions like Syracuse University and Columbia. His lab interests include generative AI applications, news production automation, and collaborative work systems. He serves on editorial boards and conference committees, including the ACM Collective Intelligence Conference steering committee.

• Collective Intelligence
• Design and Creativity
• Digital Innovation
• +3 more

Dr. Erin Solovey is an Associate Professor of Computer Science at Worcester Polytechnic Institute (WPI) and a 2024-25 Harvard-Radcliffe Institute Fellow. Her research focuses on Human-Computer Interaction (HCI) and Human-AI Interaction , with expertise in brain-computer interfaces , physiological computing , and accessibility technologies for the Deaf community. She holds affiliations with WPI’s Robotics Engineering , Artificial Intelligence , and Interactive Media & Game Development programs. Education: AB in Computer Science (Harvard, 2001), MS/PhD in Computer Science (Tufts, 2007/2012) Postdoctoral: MIT’s Humans and Automation Lab Her research designs adaptive systems using machine learning to interpret physiological signals (e.g., fNIRS, radar) for applications in education , transportation , and decision-making . Recent work includes ASL-centric survey tools and IndexPen (radar-based text input). She leads the Human-Computer Interaction Lab and directs NSF-funded Research Experiences for Teachers (RET) programs focused on the UN Sustainable Development Goals. Dr. Solovey serves as Deputy Editor of the International Journal of Human-Computer Studies (2019-2024) and Associate Editor for ACM Transactions on Computer-Human Interaction (TOCHI). She has received tenure and promotion (2022), multiple NSF grants , and best paper honors at CHI, TOCHI, and IEEE conferences.

• Human-Computer Interaction
• Human-AI Interaction
• Brain-Computer Interfaces
• +6 more

Giridhar Reddy Bojja is an Assistant Professor of Information Systems & Analytics at the College of Business, Michigan Technological University. His academic office is located in Academic Office Building G018. He holds a strong focus on interdisciplinary research and teaching in data-driven fields. Research Interests: Information Systems Capabilities and Firm Performance Social Media Analytics and Healthcare Applications Econometric Modeling in Technology Impact Design Science Research Methodologies Teaching Specializations: Business Analytics (ML, DL, Text Mining) Generative AI and Its Applications Management Science and Social Network Analysis Research Themes: His work spans AI-driven IoT security frameworks, healthcare data analytics, blockchain-enabled healthcare systems, and organizational impact of IT investments. Recent projects include predictive models for patient outcomes and frameworks for resilient IoT networks. Professional Background: His research has been published in top-tier journals and conferences, with a focus on healthcare IT, cybersecurity, and AI applications. He actively contributes to both theoretical and applied research in information systems.

• Business Analytics
• Machine Learning
• Deep Learning
• +7 more

Carole Rosenstein is a Professor of Arts Management and affiliated Professor of Folklore at George Mason University, Virginia. Her research focuses on cultural policy, cultural democracy, and equity in the arts and culture sector. She holds a PhD in cultural anthropology and combines qualitative and quantitative methodologies in her work. Rosenstein has led major studies for organizations like the National Endowment for the Arts and the Institute of Museum and Library Services. Her fieldwork spans major U.S. cities, including New York, Los Angeles, and Chicago. She was a Rockefeller Humanities Fellow in Cultural Policy at the Smithsonian Center for Folklife and Cultural Heritage. Her research interests include the social life of the arts, cultural policy frameworks, and the intersection of cultural heritage with nonprofit operations. Notable works include Understanding Cultural Policy (2024, 2nd ed.) and studies on inequities in cultural data infrastructure. Rosenstein’s recent articles analyze public funding ethics and transnational policy perspectives on cultural equity. Rosenstein has advised on large-scale cultural policy projects, including studies of outdoor arts festivals and history organizations. Her grants and collaborations reflect a focus on empirical research and actionable policy insights. She contributes to academic discourse through both authored books and peer-reviewed analyses of cultural bureaucracy and institutional practices. Rosenstein’s work bridges academic research and real-world policy, emphasizing how cultural equity can be operationalized in public and nonprofit sectors. Her affiliations include leadership roles at George Mason’s Folklore program and past collaborations with the Urban Institute’s policy research initiatives.

• Cultural Policy
• Arts Management
• Cultural Democracy
• +3 more

Saeed Amal is an Assistant Research Professor at Northeastern University's College of Engineering and Department of Bioengineering. He leads the Amal Lab for Precision Medicine, focusing on AI-driven healthcare solutions. His primary affiliation is with Northeastern's Roux Institute and he holds academic leadership roles in cardiovascular and cancer research. Previously, he was a Postdoctoral Fellow at Stanford University School of Medicine and held industry roles as VP of R&D at Cardiacx Medical (cardiology startup) and Data Scientist positions at companies like General Electric and Dynamic Yield. Education: B.Sc. in Computer Science, Technion - Israel Institute of Technology (2005) M.Sc. in Computer Science (Information Retrieval), University of Haifa (2009) Ph.D. in Computer Science (Machine Learning), University of Haifa (2019) Postdoctoral Research, Stanford University (2021–Present) Research Interests: AI applications in healthcare, including deep learning for medical imaging, NLP for clinical text analysis, and multimodal data fusion for cardiovascular and cancer care. His work emphasizes precision medicine, automated disease diagnosis (e.g., prostate and breast cancer), and improving patient outcomes through AI-driven tools. Key Contributions: Developed AI tools for cardiovascular disease prediction using multimodal data fusion, led initiatives in digital pathology for cancer grading, and pioneered the use of generative AI in Gleason pattern segmentation. His lab has published extensively on machine learning models for adverse event prediction in surgery and healthcare decision-making visualization. Awards: Emerging Visionary Award (Northeastern University NAI, 2025) Grants and Collaborations: Partnered with Santovia Path AI and Prima CARE on AI tools for cancer diagnosis. His work is supported by Northeastern's research initiatives and collaborations with institutions like Stanford University School of Medicine. Labs/Teams: Director of The Amal Lab for Precision Medicine, focusing on AI and multimodal data integration for disease care.

• Artificial Intelligence
• Healthcare Applications
• Deep Learning
• +7 more

Wei Zhu is a Professor and Deputy Chair in the Department of Applied Mathematics and Statistics at Stony Brook University. She holds a Ph.D. in Biostatistics from UCLA (1996), an M.S. in Statistics from UIC (1992), and a B.S. in Mathematics from East China Normal University (1989). Her research focuses on biostatistics, brain image analysis, clinical trial design, and environmental modeling. Key areas include medical imaging algorithms, climate prediction systems, and statistical methodologies for biomedical studies. Her work spans interdisciplinary applications such as predictive analytics for kidney disease outcomes, synthetic data-driven climate forecasting, and cryptocurrency crash prediction frameworks. She has developed machine learning models for medical image segmentation and decision tree frameworks for risk stratification in pandemic contexts. Teaching includes courses like AMS 312 and AMS 572. Zhu’s research portfolio emphasizes translational statistics, with contributions to genomic modeling, financial market dynamics, and public health policy evaluation. Her lab addresses pressing challenges in healthcare analytics, environmental science, and computational biomedicine through rigorous statistical innovation.

• Biostatistics
• Medical Imaging
• Clinical Research
• +5 more