Vittorio Solina is a Researcher at the Department of Mechanical, Energy and Management Engineering (DIMEG) of the University of Calabria, specializing in industrial systems simulation and digital twin technologies. His work spans Industry 4.0/5.0 applications, supply chain optimization, and human-robot collaboration. Affiliation: University of Calabria Academic Role: Researcher (Legge 240/10) Research Focus: Digital twins, simulation modeling, sustainable manufacturing His research emphasizes advanced simulation tools for decision support, including applications in Industry 4.0 , Smart Manufacturing , and Agri-Food Supply Chains . Recent work explores adaptive simulation optimization for Industry 5.0 and 5G-enabled robotics. Key publication trends include: (1) Digital twin integration for supply chain resilience (2024-2025), (2) Simulation automation methodologies (2025), and (3) Human-robot collaboration frameworks (2024).
Joseph A. November is an Associate Professor in the Department of History at the University of South Carolina, affiliated with the McCausland College of Arts and Sciences. His research focuses on the history of biomedical computing, distributed computing, and the intersection of technology and medicine. He holds a Ph.D. from Princeton University (2006), an M.A. from the University of Chicago (2002), and a B.A. from Hamilton College (1997). His work includes the award-winning book Biomedical Computing: Digitizing Life in the United States (2012), which explores the co-development of biomedicine and computing technologies. Current projects include Revolutions@home , examining distributed computing in protein folding research, and a biography of computing pioneer Robert S. Ledley. He has received grants from the NSF, NIH, and the Charles Babbage Institute. Teaching interests span the history of science and technology, including courses on the history of medicine, digital humanities, and the role of games in historical education. He actively contributes to professional organizations like SHOT and the History of Science Society. Awards include the Computer History Museum Prize (2013) and the National Institutes of Health DeWitt Stetten Fellowship (2007-2008). His research bridges historical analysis with contemporary issues in technology and biomedical ethics.
Professor Hutan Ashrafian is a clinician-scientist and surgeon at the University of Leeds Business School, holding dual roles as Professor of Research Impact and Senior Research Fellow at Imperial College London. His expertise spans AI in healthcare, metabolic surgery, and ancient history. He pioneered STARD-AI and QUADAS-AI guidelines for AI diagnostics, collaborated on AI-driven breast cancer screening with Google and NHS, and led global health policy initiatives. Ashrafian’s work bridges medicine, history, and philosophy, including his contributions to understanding historical figures’ medical conditions, such as King Tutankhamun’s epilepsy. He has authored over 550 publications, 12 books, and holds a PhD in computational physiology and an MBA with distinction. Awards include the Hunterian Prize and Wellcome Trust Fellowship. His research also explores AI ethics, quantum physics paradoxes, and art-based medical diagnostics. Education: PhD in Computational Physiology (Imperial College London) MBA (Warwick Business School) MD (University College London) Bachelor of Science in Immunology (University College London) Research Interests: Ashrafian’s work spans: AI in Medicine: Diagnostic algorithms, guideline development (STARD-AI/QUADAS-AI), and ethical frameworks. Metabolic Surgery: Bariatric interventions, gut microbiome, and obesity treatments. Ancient History: Medical analyses of historical figures (e.g., Tutankhamun, Julius Caesar) and art-based pathology identification. Philosophy: AI rights (AIONAI law), temporal paradoxes, and the Simulation Argument. Awards: Royal College of Surgeons Arris and Gale Lectureship Hunterian Prize Wellcome Trust Research Fellowship Advising & Innovation: Supervised >50 PhD students, co-founded Oxford Medical Products (weight loss tech), and serves as CSO at Flagship Pioneering’s Preemptive Health division. He advises on NHS digital transformation and global health policy. Labs/Teams: Leads AI initiatives at Imperial’s Institute of Global Health Innovation and collaborates with Google, NICE, and international institutions on health tech solutions.
Silvia Lindtner is an Associate Professor at the University of Michigan's School of Information and Director of the Center for Ethics, Society, and Computing (ESC). She holds courtesy appointments in the Penny W. Stamps School of Art and Design and the Digital Studies Institute. Her work focuses on the social and cultural study of technology in China and globally, with a focus on data-driven governance, AI ethics, and the intersection of technology and labor. Lindtner has conducted nearly two decades of fieldwork in China, examining innovation ecosystems, digital economies, and the affective dimensions of state control. She is the author of the award-winning *Prototype Nation: China and the Contested Promise of Innovation* (2020) and co-author of *Technoprecarious* (2020). Education: PhD in Information and Computer Sciences from University of California, Irvine; BS/MS in Media Technology and Design from University of Hagenberg, Austria. Research Interests: Science and Technology Studies (STS), China Studies, HCI, Critical Computing, AI Ethics, Data Governance, Labor Studies, and Transnational Digital Economies. She explores how technological systems shape governance, labor practices, and everyday life, particularly in contexts of global inequality and state surveillance. Awards: Joseph Levenson Prize (2021), Francis L.K. Hsu Book Prize (2021), ACM Distinguished Member (2022), and fellowships from the National Committee on US-China Relations (2021-2023) and China-US Scholars Program (2021-2022). Grants: Supported by NSF, IMLS, Intel Labs, Google Anita Borg, and Chinese National Natural Science Foundation. Leads interdisciplinary initiatives including Tech.Culture.Matters research group and Michigan Interactive and Social Computing (MISC) research group. Labs/Teams: Directs the Center for Ethics, Society, and Computing (ESC) and collaborates with the Lieberthal-Rogel Center for Chinese Studies. Current projects include studies on affective control in AI governance and transnational data practices in healthcare and labor.
Arti Singh is an Assistant Professor in the Department of Agronomy at Iowa State University. Her research focuses on plant breeding, soybean diseases, genomics, and phenomics, with a strong emphasis on integrating artificial intelligence and high-throughput technologies into agricultural systems. She leads projects involving AI-driven disease identification, precision agriculture, and crop improvement strategies. Her expertise includes developing machine learning models for real-time weed and insect classification (e.g., WeedNet and InsectNet), deploying drones and ground robots for crop phenotyping, and leveraging genomic data to map traits like flowering time and disease resistance in legumes. Singh collaborates on initiatives like the AIIRA Institute for Resilient Agriculture and the BioTrove biodiversity dataset. Singh’s work spans plant stress phenotyping, digital twin technologies for plant sciences, and multi-sensor phenotyping for early disease detection. Her research bridges computational methods with traditional agronomy, aiming to enhance crop resilience and sustainability in the face of environmental challenges. Her recent projects include optimizing robotic navigation for precision agriculture, improving soybean yield estimation via video analysis, and dissecting genetic architectures of traits in mungbean and soybean using GWAS and genomic tools. She actively contributes to conferences and publishes in high-impact journals, advancing both foundational and applied aspects of agricultural science.
Sean Cao serves as Associate Professor (with tenure) at the Robert H. Smith School of Business, University of Maryland, where he is Director and Co-founder of the AI Initiative for Capital Market Research. He also holds an affiliation as professor at Harvard Business School's D 3 Institute. His academic journey began with a Ph.D. from the University of Illinois at Urbana-Champaign. Dr. Cao's research focuses on the intersection of artificial intelligence and capital markets, with particular expertise in how machine learning transforms financial analysis, corporate disclosure practices, and investment decision-making. His work examines the evolving relationship between human analysts and AI systems, blockchain applications in financial reporting, and the strategic adaptation of corporate communications for machine readership. He has pioneered research on the "AI divide" among investor groups and developed frameworks for human-AI collaborative stock analysis. His publication portfolio spans top journals including Journal of Financial Economics, Review of Financial Studies, Journal of Accounting Research, and Management Science. The research demonstrates consistent thematic progression toward increasingly sophisticated AI applications in finance, with recent work exploring distributed ledger technologies for auditing, machine learning for extracting private information from disclosures, and the economics of greenwashing in ESG funds. His studies frequently combine textual analysis with traditional financial metrics to uncover novel market insights. Fama-DFA Prize from Journal of Financial Economics for best paper in capital markets and asset pricing Michael J. Brennan Award from Review of Financial Studies Deloitte Initiative for AI and Learning award for developing trustworthy AI for social equity PanAgora Asset Management's Dr. Richard A. Crowell Memorial Prize Multiple best paper awards from Midwest Finance Association, Global AI Finance Conference, and Asian Finance Association Dr. Cao has delivered over 200 invited research talks at major institutions including the Central Bank of Japan, Central Bank of Thailand, and U.S. Securities and Exchange Commission. He serves as Guest Associate Editor for Management Science and has co-chaired Review of Financial Studies conferences on FinTech and Machine Learning. His educational initiatives include a widely adopted free AI textbook for finance and accounting that has been implemented at universities worldwide including Indiana University, UT Dallas, and University of Minnesota. As Director of the AI Initiative for Capital Market Research, Dr. Cao leads a multidisciplinary team exploring practical AI applications in finance. The initiative has secured significant funding including a $150,000 grant from GRF CPAs & Advisors. His research group maintains strong industry connections through partnerships with regulatory bodies, financial institutions, and technology companies, facilitating the translation of academic research into practical financial applications.
Aniket (Niki) Kittur is a Professor in the Human-Computer Interaction Institute (HCII) at Carnegie Mellon University's School of Computer Science. His research focuses on AI-augmented cognition, exploring how humans and computational systems can partner to accelerate knowledge acquisition and innovation. With over 100 peer-reviewed publications and 17 best paper awards or honorable mentions, Dr. Kittur has established himself as a leader in human-computer interaction and social computing. Dr. Kittur's research spans multiple interconnected areas focused on enhancing human cognition through technology. His work on crowd-augmented cognition examines how crowds and computation can collectively enhance human intellect. In social computing, he investigates how sociotechnical architectures can motivate and coordinate large groups for complex tasks. His research in data visualization and sensemaking explores how people collect, organize, and make decisions with online information. Most recently, his work has shifted toward LLM-augmented cognition, investigating how humans and large language models can work together in partnership to achieve better decisions and greater creativity than either could alone. Dr. Kittur's publications reveal a consistent trajectory toward increasingly sophisticated human-AI collaboration systems. Early work focused on crowdsourcing complex tasks (CrowdForge, CrowdSynthesis), then evolved to knowledge acceleration systems (Knowledge Accelerator, Fuse), and has recently centered on LLM-integrated cognition (Selenite, InkSpire, BioSpark). His research consistently demonstrates practical impact, with systems influencing products used by millions and receiving coverage in major media outlets including Nature News, The Economist, and The Wall Street Journal. Kavli fellow NSF CAREER award recipient Allen Newell Award for Research Excellence Inductee into the CHI Academy 17 best paper awards or honorable mentions across his publications Dr. Kittur has advised numerous students, including Andrew Kuznetsov, and has secured major research funding from NSF, NIH, Google, Microsoft, Bosch, Toyota, and other organizations. His Skeema browser extension project, which addresses tab overload through innovative project-based organization, has shown remarkable user retention and represents a practical application of his research on knowledge acceleration. His work with industry partners has influenced products used by millions, including Semantic Reader, Google Shopping, and Wikipedia features.
Oscar Westlund serves as Professor at the Department of Journalism and Media Studies within the Faculty of Social Sciences at Oslo Metropolitan University (OsloMet), where he co-leads the OsloMet Digital Journalism Research Group. He maintains a secondary appointment at the University of Gothenburg and acts as Editor-in-Chief of Digital Journalism . His research spans digital journalism, fact-checking, platform dynamics, media management, news consumption, and mobile media. Westlund's scholarly focus centers on journalism safety in digital environments, sociotechnical dimensions of misinformation combat, and platform-induced challenges for news organizations. His work examines professional fragilities of journalists, epistemological foundations of data journalism, and legitimacy paradoxes in public service media-platform relationships. Current projects address disinformation countermeasures through the SCAM initiative (Source Criticism And Mediated Disinformation). Analysis of his 2022-2024 publications reveals dominant themes: journalism safety frameworks (33%), platform-journalism tensions (27%), and fact-checking as sociotechnical practice (23%). Key methodological approaches include cross-national comparative studies, epistemological analysis, and practice theory applied to digital news production. Westlund actively contributes to academic discourse through editorial leadership at Digital Journalism and special issue guest editing. His research group coordinates interdisciplinary collaboration on digital journalism studies, while the SCAM project develops practical methodologies for disinformation detection in democratic contexts. Recent work demonstrates increasing emphasis on mobile news ecosystems and journalist safety cultures. He co-leads the OsloMet Digital Journalism Research Group, which investigates platform impacts on news production, mobile journalism evolution, and epistemological shifts in data-driven reporting. The group maintains strong international partnerships, particularly with Swedish institutions through his University of Gothenburg affiliation.
Sarah Billington is the UPS Foundation Professor of Civil and Environmental Engineering at Stanford University and a Senior Fellow at the Woods Institute for the Environment. Her research program focuses on sustainable building design, human wellbeing, and ethical supply chain practices. Education: PhD, University of Texas at Austin, Structural Engineering (1997) MSE, University of Texas at Austin, Structural Engineering (1994) BSE, Princeton University, Civil Engineering & Operations Research (1990) Her lab employs interdisciplinary methods to study how built environments impact human physical, psychological, and social wellbeing. Current projects include developing tools to quantify nature exposure in buildings, exploring affordable housing's role in wellbeing, and using AI to assess forced labor risks in material supply chains. While no longer active in this area, her group previously pioneered research on sustainable construction materials like bio-based composites and ductile cement-based composites. Her recent publications address topics such as nature integration in architecture, workplace design optimization, and health impacts of building materials. The Billington Lab at Stanford fosters collaborative team science, welcoming partnerships to advance occupant-centric engineering solutions.
Snježana Babić serves as Associate Professor and Head of the Graduate Study Program Informatics - Teaching Major at the Faculty of Informatics in Pula , University of Pula. With a PhD obtained in 2016 and university affiliation since 2017, she teaches across undergraduate and graduate programs focusing on ICT fundamentals, web design, digital competencies, and informatics education methodology. Her educational background includes graduation in 1993 followed by doctoral studies culminating in 2016. Though specific institutions aren't detailed in the text, her career trajectory shows progression from foundational ICT teaching to specialized informatics education leadership. Babić's research centers on educational technology adoption with particular emphasis on programming pedagogy for young learners through the MEMA method. Her work investigates digital competencies across multiple educational contexts, from primary schools to higher education. Recent publications demonstrate rapid adaptation to emerging technologies, with 2025 studies examining ChatGPT integration in Croatian educational settings and cross-cultural applications of programming methods. Analysis of her 15 most recent publications reveals consistent focus on technology acceptance models applied to Croatian educators and students. The research trajectory shows evolution from foundational e-learning systems (2016-2020) to cutting-edge AI and robotics applications (2022-2025), maintaining strong methodological focus on teacher motivation , implementation barriers , and culturally-specific adoption factors . Her teaching portfolio demonstrates deep integration with research interests: Undergraduate: ICT Fundamentals, Web Design and Application Graduate: Digital Competencies in Education, Informatics Education Methodology, Practicum for IT Educators Cross-disciplinary: ICT in Nursing, Healthcare Informatics Babić actively contributes to institutional leadership as program head while maintaining robust research productivity. Her work bridges theoretical technology adoption frameworks with practical implementation challenges in Croatian educational contexts, particularly examining how emerging technologies like humanoid robots and AI assistants can be effectively integrated into teaching practices.
Priyanka Raina is an Assistant Professor of Electrical Engineering at Stanford University, with a courtesy appointment in Computer Science. She leads the Stanford Accelerate research group, focusing on domain-specific hardware architectures and agile hardware-software co-design. Her work emphasizes high-performance, energy-efficient accelerators for emerging technologies. Education: B.Tech. from IIT Delhi (2011), M.S. and Ph.D. from MIT (2013/2018). Postdoctoral experience includes NVIDIA Research (2018) and Amazon Visiting Academic (2023–present). Awards include the Sloan Research Fellowship (2024), NSF CAREER Award (2023), and Terman Faculty Fellowship (2018). Research Interests: Domain-specific architectures, near-memory computing, design productivity, and machine learning acceleration. Her group develops frameworks like AHA (Agile Hardware) for efficient accelerator design and compilers. Awards: Over 10 major awards, including best paper recognitions at VLSI, MICRO, and JSSC. Active roles as Associate Editor for IEEE JSSC and Program Chair for IEEE Hot Chips (2020). Advising & Teaching: Supervises multiple PhD and MS students in hardware design, CGRAs, and ML accelerators. Teaches VLSI design courses (EE271/272/372) and oversees independent studies in embedded systems and chip design. Labs & Collaborations: Affiliated with Stanford PORTAL Center, AHA Center, and SystemX Alliance. Projects include MINOTAUR (edge AI accelerator), Amber (CGRA-based SoC), and EMBER (RRAM macros).
Dean Eckles is an Associate Professor of Marketing at MIT Sloan School of Management and serves as an Associate Director of the MIT Institute for Data, Systems, and Society (IDSS). He is also affiliated with the MIT Schwarzman College of Computing through the Institute for Data, Systems & Society and its Statistics and Data Science Center. Additionally, he leads the analytics research area at the Initiative on the Digital Economy and organizes the annual Conference on Digital Experimentation (CODE@MIT). His educational background includes a BA in philosophy, BS and MS in cognitive science, MS in statistics, and PhD in communication, all from Stanford University. Prior to joining MIT, Eckles worked as a scientist at Facebook, where he contributed to areas including News Feed, messaging, advertising, tools for randomized experiments, and survey methods. He previously held research positions at Nokia and Yahoo. Eckles's research primarily focuses on social influence mediated by interactive technologies, examining how communication technologies mediate, amplify, and direct social influence. His work spans multiple specific areas including social interactions, contagion, and interventions in networks; experimental design and inference in networks; and methods for causal inference. His research often combines social science with advanced statistical methods. His notable publications include research on long ties in social networks and their relationship to economic prosperity, how network structure affects social contagions, and algorithmic transparency in social media platforms. His work has appeared in prestigious journals including PNAS and Nature Human Behaviour, and he has provided expert testimony before the US Senate on algorithmic ranking. Long ties, disruptive life events and economic prosperity (PNAS) Long ties accelerate noisy threshold-based contagions (Nature Human Behaviour) Algorithmic transparency and assessing effects of algorithmic ranking (Senate testimony) Eckles actively shares his research through social media platforms including Bluesky, Twitter, and Mastodon, as well as through his blog and contributions to the Gelman et al. blog. His work bridges academic research with practical applications in technology and policy.
Mohammad Saifur Rahman is the Daniels School Chair in Management and a Professor of Management Information Systems at the Mitch Daniels School of Business, Purdue University. Previously, he was an Associate Professor at the Haskayne School of Business, University of Calgary. His academic journey includes significant leadership roles such as co-chairing the Conference on Information Systems and Technology (CIST) in 2013 and serving as president of the INFORMS eBusiness Society in 2014. Currently, he serves as an associate editor for both Management Science and Information Systems Research (ISR). Ph.D. in Management Information Systems, Krannert School of Management, Purdue University (2008) MBA in Management Information Systems, Southern Illinois University (2004) BS in Computer Science, Southern Illinois University (2002) Rahman's research primarily focuses on the economic implications of digital transformations. His work examines how digitization affects consumer behavior, market structures, and business strategies across various industries. He investigates the value of digital traces in driving consumer behavior and improving decision-making, particularly in omnichannel retail environments. His research on the sharing economy has revealed important insights about economic disparities, showing how platforms like Airbnb provide economic benefits to predominantly white neighborhoods while failing to generate similar spillover effects in predominantly Black or Hispanic neighborhoods. His recent publications reveal a consistent focus on the intersection of technology, economics, and social impact. Rahman's work frequently examines how local market structures interact with digital platforms to create or exacerbate economic inequalities. His research spans multiple disciplines including information systems, economics, marketing, and operations management, with a particular emphasis on empirical studies using real-world data from major companies like Walmart and Cisco. CICP Faculty Commercialization Award (2020) INFORMS Sandy Slaughter Early Career Award (2018) World's Top 40 Business School Professors Under 40 by Poets and Quants (2017) Jay N. Ross Young Faculty Scholar Award (2015) Dean's Award for Outstanding Research Achievement (University of Calgary, 2014) Rahman has secured substantial research funding from organizations including Social Sciences and Humanities Research Council (SSHRC), Adobe Systems ($50,000 grants in 2017 and 2020), Trask Innovation Fund ($21,218), and NSF I-Corps ($50,000). He has advised numerous PhD students and collaborated with industry partners to translate research into practical applications. Rahman co-founded RightFit Analytics, a precision health analytics solution that utilizes AI to learn success patterns in healthcare. He has organized significant academic events including the Krannert-Walmart Data Dive (believed to be the first data dive on a college campus) and the Dawn or Doom Data Dive in cooperation with Cisco. Rahman actively engages with industry through consulting and collaborative research projects. His work with Walmart, Cisco, and other major corporations demonstrates his ability to bridge academic research with practical business applications. He has been particularly active in studying how AI and big data analytics can be leveraged to improve business decision-making while addressing potential negative consequences like algorithmic bias and economic inequality.
Eytan Adar is a Professor of Information and Computer Science at the University of Michigan, holding dual appointments in the School of Information and the College of Engineering's Electrical Engineering and Computer Science department. His work sits at the intersection of human-computer interaction and artificial intelligence, focusing on large-scale systems analysis and novel interface design. Adar's research spans multiple domains including social media analysis (Twitter, Reddit), academic citation networks, meme propagation, information extraction, and political networks. His methodological expertise includes data mining, data visualization, and graph-based network analysis. His work often operates at internet scale, examining language, creativity, social network dynamics, and text production. His recent publications reveal a strong focus on AI-human collaboration, with particular attention to generative AI interfaces, visualization techniques for complex data, and ethical considerations in AI systems. His work shows a consistent pattern of bridging theoretical insights with practical system implementations. Best Paper Award at ProtoAI: Model-Informed Prototyping for AI-Powered Interfaces, IUI'21 Honorable Mention Award at CHI'24 for feminist interaction techniques research Best Paper Award at ICWSM'18 for Wikipedia language edition analysis Best Paper Award at ICML 2016 Workshop for neural language model visualization Best Student Paper at WSDM'09 for web dynamics research Best of CHI at CHI 2008 for web revisitation patterns analysis Adar has advised numerous PhD students who have gone on to prominent positions at organizations including Google, Apple, RAND, Northwestern University, and Stanford. His research is generously supported by the NSF, IARPA, NIH, the Education Department, and major technology companies including Adobe, Microsoft, Facebook, Google, and Yahoo. He is also a founder of the International Conference on Web and Social Media (ICWSM) and has served as Co-General Chair for WSDM and Co-Program Chair for UIST.
Jillian Bohlen is an Associate Professor at the University of Georgia within the College of Agricultural & Environmental Sciences , specifically the Department of Animal and Dairy Science . Her work focuses on dairy cattle reproduction, teaching, and youth development in agricultural sciences. Education: B.S. in Dairy Science, University of Georgia (2003) M.S. in Dairy Science, University of Georgia (2005) Ph.D. in Animal Sciences, Clemson University (2012) Dr. Bohlen's research emphasizes applied reproduction in cattle , including synchronization techniques, ultrasound applications in reproductive programs, and embryo competency. She integrates students into all research projects despite lacking a formal research appointment. Her teaching interests span dairy cattle production , reproductive management , and contemporary agricultural issues , with courses like ADSC 3620 (Dairy Cattle Production), ADSC 4010 (Issues in Animal Agriculture), and ADSC 4410 (Applied Reproductive Management). Scientific awards include: Student Career Success Influencer Award (2024) Russell Award for Excellence in Undergraduate Teaching (2023) UGA Creative Teaching Award (2022) CAES Early Career Teaching Award (2022) Hoard's Dairyman Youth Development Award (2021) Larry Benyshek Teaching Award (2017) She actively promotes agricultural education through programs like the Commercial Heifer Project , Dairy Cattle Judging , and Dairy Quiz Bowl . Additionally, she participates in funded projects related to methane emissions , heat stress mitigation , and antibiotic alternatives in dairy farming.
