Associate Professor Sam Kirshner is a faculty member at the University of New South Wales within the School of Information Systems and Technology Management . His research focuses on behavioral decision making , algorithmic impact on operations , and artificial intelligence applications in business contexts. PhD in Management Science from Queen’s University, Canada Teaching expertise in data visualization, predictive analytics, and AI ethics Co-author of Business Analytics: A Management Approach Member of the Ethical AI Advisory His research explores how psychological distance and construal level theory influence decisions in supply chains, technology management, and consumer behavior. Recent work examines ChatGPT's decision biases , algorithm aversion , and sustainable operations under financial constraints. Key publication trends show focus areas: AI ethics and human-AI collaboration Behavioral supply chain analysis Temporal/spatial psychological distance effects CO2 forecasting with sparse data Consumer behavior in digital platforms Virtual reality and cognitive processing Supervision roles include mentoring 2 PhD students and 6 honors students, contributing to the next generation of scholars in business analytics and technology management.
Professor Dhiraj Murthy holds appointments in the Moody College of Communication , Sociology , and School of Information at the University of Texas at Austin. He earned a Ph.D. in Sociology from the University of Cambridge. His research focuses on social media, digital methods, health communication, and disaster response. He directs the Computational Media Lab , a leading research group with over 20 students, and co-edits the journal Big Data & Society . Notably, he authored the seminal book Twitter: Social Communication in the Twitter Age (2013/2018), which won the ALA CHOICE Prize. Dr. Murthy's work has been funded by NIH, NSF, and other major grants, including studies on e-cigarette marketing, disaster informatics, and AI-driven disinformation detection. He also serves on advisory boards for MediaWell and chairs international social media conferences. Education : Ph.D. in Sociology, University of Cambridge. Grants : Over $5M from NIH, NSF, and UT Austin’s Good Systems initiative for projects like 'AI Technologies to Curb Disinformation' and 'E-cigarette Use Among Mexican American Students.' Labs/Teams : Computational Media Lab (UT Austin), focusing on AI, social media analytics, and health research. Awards : Stanford University’s 2023 Top 2% Global Scientists in Communication & Media Studies and Sociology, ALA CHOICE Prize (2018), and multiple NIH/NSF grants. His work bridges sociology, media studies, and computational methods to address societal challenges like health disparities and misinformation.
Cecilia Mascolo is a Professor of Mobile Systems at the University of Cambridge , specifically in the Department of Computer Science and Technology . She co-directs the Centre for Mobile, Wearable System and Augmented Intelligence and is a Fellow of Jesus College, Cambridge . Her research focuses on mobile systems , machine learning for mobile health , and earable technology . She has been awarded prestigious grants such as the ERC Advanced Research Grant (2019-2025) and the EPSRC Open Research Fellowship (2025-2030). Currently on sabbatical at Harvard University , her work bridges systems and machine learning for health applications. Education: PhD in Computer Science from the University of Bologna, Italy. Previous Affiliation: Faculty at University College London before 2008. Her research spans mobile and wearable systems for health and behavior monitoring, focusing on on-device machine learning , uncertainty-aware models , and audio-based diagnostics . Key areas include federated learning , edge computing , and respiratory disease progression analysis via wearables. She explores earable technology for physiological monitoring, gait analysis, and even toothbrushing tracking using in-ear sensors. Her recent publications highlight advancements in earable-based health monitoring , including heart rate estimation , respiratory rate detection , and ECG analysis using machine learning. She emphasizes longitudinal health data from consumer devices, advocating for scalable diagnostics beyond traditional clinical standards. Scientific Awards: ERC Advanced Research Grant EPSRC Open Research Fellowship Best Paper Award - IEEE Percom 10-Year Impact Award - ACM Ubicomp Computer Laboratory Ring Hall of Fame Best Paper Award Student: Andrea Ferlini - ACM SIGMOBILE Doctoral Dissertation Runner-up She leads the Mobile Systems Research Laboratory , mentoring a team of 15 researchers (postdocs and PhD students), and has graduated over 25 PhD students. Her teaching includes Mobile Health courses at the University of Cambridge, and she serves as Director of Studies for Computer Science at Jesus College.
Barbara J. Evans is a Stephen C. O’Connell Chair Professor of Law and Professor of Engineering at the University of Florida, with joint appointments in the Levin College of Law and Herbert Wertheim College of Engineering. She focuses on data privacy, AI/ML medical software regulation, genomic technologies, and diagnostic testing, and is a key member of the NIH Bridge2AI project. Education : J.D. from Yale Law School, LL.M. in Health Law from the University of Houston, postdoctoral training in clinical ethics at MD Anderson, and a Ph.D. in Earth Sciences from Stanford. Her research bridges law and engineering, emphasizing ethical and regulatory challenges in AI/ML medical applications, genomic data governance, and DIY biotechnology. She has led initiatives like the LawSeq SM project to standardize genomic analysis policies. The 15 most recent works highlight her interdisciplinary focus on AI ethics in healthcare, genomic privacy, and regulatory frameworks for emerging technologies. Key subfields include biomedical data sharing, FDA compliance, and equitable access to health data infrastructure. Scientific Awards : American Law Institute membership, IEEE Senior Membership, Greenwall Foundation Faculty Scholar. Evans has collaborated with institutions like the American College of Medical Genetics and Genomics (ACMG) and contributed to guidelines for genomic medicine. Her grants include NIH funding for Bridge2AI and LawSeq SM projects.
Professor Kim Eun-kyung is a full-time Professor at the College of Pharmacy , Seoul National University , South Korea. She directs patient-oriented research at the intersection of pharmacy, public health and clinical epidemiology, leading projects that range from nationwide pharmaco-epidemiologic cohort analyses to qualitative investigations of pharmacist-led care models. Education Ph.D. & Pharm.D., University of Florida, USA Research Interests Professor Kim’s research program is built on five mutually reinforcing pillars: Population-based patient care research – leveraging large national databases to understand medication utilization and outcomes in real-world settings. Drug safety and patient empowerment – identifying adverse drug reactions and developing interventions that enable consumers and clinicians to report and prevent harm. Access to care and medications in underserved and special populations – examining barriers faced by the elderly, rural residents, patients with rare diseases, and those undergoing high-cost procedures such as hematopoietic stem-cell transplantation. Disease prevention and appropriateness of therapy – evaluating preventive pharmacotherapy (e.g., anti-osteoporosis drugs, vitamin D) and ensuring evidence-based prescribing. Quality improvement in health-care delivery – designing multidisciplinary models that integrate pharmacists into care teams to optimize medication therapy and reduce drug-related problems. Publication Trends Across 2017–2020, Professor Kim has published extensively in International Journal of Environmental Research and Public Health , Clinical Nutrition , Medicina , BMC Public Health , Blood Research , Neuroepidemiology and other peer-reviewed journals. Her work characteristically combines rigorous secondary-data analyses of Korean or US national health surveys with systematic reviews/meta-analyses focusing on drug safety endpoints. Themes include neurological adverse events (trimetazidine-induced parkinsonism), hematologic toxicities (linezolid-induced thrombocytopenia), nutritional and metabolic complications in critical care, and access/utilization of medications in vulnerable populations. Scientific Awards & Honors (None listed in the provided texts) Grants & Research Support While specific grant identifiers are not detailed in the supplied pages, the breadth of large-scale database studies and multi-institutional collaborative projects implies sustained funding from national agencies such as the Korea Health Industry Development Institute (KHIDI) or the Ministry of Health & Welfare. Laboratory & Team Professor Kim leads an active research group located in Yeongeon Campus 17-201. The team integrates graduate students, post-doctoral researchers, pharmacists and biostatisticians working together on pharmacoepidemiology, patient-reported outcomes and health-services research.
Hamza Salih Erden is an Associate Professor (Docent) at the Informatics Institute of Istanbul Technical University in Turkey. His research focuses on energy optimization in data centers, thermal management systems, and computational fluid dynamics applications. With over 34 research outputs and an h-index of 12, he leads projects in energy-grid integration and carbon-aware load management. Research Focus Dr. Erden's work centers on improving energy efficiency in technological infrastructure through: Advanced cooling techniques for data centers Integration of thermal energy storage systems Computational fluid dynamics modeling Demand-response optimization for smart grids AI-driven monitoring of energy systems Publication Trends Recent works (2022-2025) demonstrate strong focus on sustainable energy technologies, particularly optimization of data center operations through thermal management innovations, integration of renewable energy solutions, and AI applications for system monitoring. Economic assessments of energy-saving techniques feature prominently. Awards and Recognition Technical Paper Award (2016) Multiple International Scientific Publication Incentive Awards (2017-2021) Poster Award (2012) Graduate Student Grant (2007) Projects and Funding Leads multiple energy research projects including: Carbon-aware load management in data centers (2025) Grid-integrated energy system modeling for data centers (2021-2023) CFD analysis of CRAH bypass methods (2018-2020) Economizer applications in Turkish data centers (2016-2017)
Prof. Sadettin Emre Alptekin is a full Professor of Industrial Engineering at Galatasaray University, Faculty of Engineering and Technology, where he also serves as Vice Dean. Since joining the university as a research assistant in 2000, he has steadily advanced through the academic ranks, becoming an Assistant Professor (2006–2010), Associate Professor (2010–2023), and finally Professor in 2023. Education: PhD (Dr), Industrial Engineering, Istanbul Technical University, Institute of Science and Technology, 2001–2006 MSc, Industrial Engineering, Galatasaray University, Faculty of Engineering and Technology, 1999–2001 BSc, Industrial Engineering, Istanbul Technical University, Faculty of Management, 1995–1999 Languages: Advanced English (C1), Upper-Intermediate French (B2), Advanced German (C1) Research Interests: Prof. Alptekin’s research focuses on Computer Learning , Fuzzy Sets and Systems , and Decision Support Systems . His work integrates artificial intelligence, machine learning, and soft-computing techniques to solve complex industrial and managerial problems in areas such as supply chain management, quality function deployment, blockchain adoption, and mental-health prediction. Publication Trends: Across more than 50 refereed publications, Prof. Alptekin has consistently explored hybrid intelligent models that combine fuzzy logic, machine learning, and multi-criteria decision-making. Recent articles emphasize deep-learning-based anomaly detection in industrial time-series data, blockchain adoption in supply chains, and machine-learning applications in subjective well-being and mental-health modeling. Scientific Awards & Honors: No specific awards or medals are listed in the provided documents. Research Leadership & Funding: Since 2008 he has been the principal investigator (executive) of 12 nationally funded projects, covering topics such as Industry 4.0 sub-system design, Internet of Things applications, artificial neural networks in organizational decision-making, big-data analytics, and strategic decision processes. Graduate Advising: He has formally supervised at least 8 master’s theses and numerous undergraduate projects. Representative thesis titles include Gaussian-process-regression-based man-hour prediction, machine-learning-driven human-behavior modeling, recommender-system design for e-commerce, thyroid-nodule diagnosis from scintigraphic images, software-effort estimation via neural networks, spreadsheet heuristics for joint-replenishment problems, cross-selling decision systems in insurance, and profitability analyses of Turkish banks under disinflation. Laboratories & Teams: While no dedicated laboratory name is disclosed, his continuous role as Vice Dean and principal investigator implies active leadership of the Industrial Engineering department’s research clusters in intelligent systems and decision support technologies.
Mike Kosek (Dr. rer. nat.) is a Research Fellow at the Chair of Connected Mobility (Department of Informatics) at the Technical University of Munich (TUM). His research focuses on transport protocols, congestion control, internet architecture, and internet measurements. Research Interests: Transport protocol design and analysis Congestion control mechanisms Internet architecture and measurement Network performance optimization DNS protocol behavior and privacy Applications in satellite and aerial communication Recent Research Trends: His publications emphasize QUIC protocol analysis, DNS over QUIC investigations, cross-layer protocol interactions, and satellite communication adaptations. Key methodologies include real-world measurements, protocol design extensions, and dataset creation for reproducibility. Contact: E-mail: kosek@in.tum.de Phone: +49 89 289-18665 Office: 01.05.038, Boltzmannstr. 3, 85748 Garching
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.
Lynn Wu is an Associate Professor at the Wharton School of the University of Pennsylvania, focusing on the intersection of artificial intelligence, analytics, and innovation. She teaches MBA, undergraduate, and doctoral courses on emerging technologies' transformative impact on business and society. Education: B.S. in Finance and Computer Science, MIT M.S. in Computer Science, MIT Ph.D. in Management Science, MIT Sloan Her research explores how AI and digital platforms reshape productivity, workforce dynamics, and innovation strategies, with applications in antitrust policy and startup ecosystems. Key trends in her publications include AI's role in post-IPO innovation, robotics' impact on managerial roles, and social media's ability to mitigate funding disparities. Scientific Awards: Kauffman Best Paper Award (2019) Sandy Slaughter Early Career Award (2019) AIS Early Career Award (2018) ISR Best Published Paper (2014) Best Paper Awards at ICIS (2009), HICSS (2013), etc. She has collaborated with IBM, Google, Meta, and advised the U.S. Department of Justice and World Bank, with her work cited by The New York Times , The Economist , and Harvard Business Review .
Sanjeev Dewan is a Professor of Information Systems and Associate Dean of Masters Programs at the Paul Merage School of Business, University of California, Irvine. He also serves as Faculty Director of the Master of Science in Business Analytics program. Prior to joining UCI in 2001, he held faculty positions at the University of Washington and George Mason University. PhD, University of Rochester MS, University of Rochester Bachelor of Technology, Indian Institute of Technology, Delhi His research focuses on the economics of digital platforms , social and mobile analytics , and the valuation of technology investments . He investigates how information technology creates business value, impacts consumer behavior, and influences firm performance. His work spans electronic markets, Web 2.0 technologies, IT productivity, and the digital divide. The most recent publications reveal a strong emphasis on empirical analysis of digital platforms , including studies on gender bias in open source communities, quality certification in the sharing economy (e.g., Airbnb), personalized ranking in app stores, and mobile health applications. His research frequently uses large-scale datasets to examine behavioral patterns, market dynamics, and the economic implications of IT innovations. Faculty Service Award for 2023-24, UCI Paul Merage School of Business Best Paper Award, INFORMS 2019 e-Business Cluster Faculty Service Award for 2016-17, UCI Paul Merage School of Business Best Paper Award, INFORMS Conference on Information Systems and Technology (2009) INFORMS Service Award (2009) INFORMS Certificate of Appreciation (2008) Beta Gamma Sigma Honor Society (1991) University of Rochester Fellowship (1985–1990) Sanjeev Dewan has advised numerous PhD students who have secured faculty positions at leading institutions such as the University of Wisconsin-Madison, HKUST, Penn State, and the University of Hong Kong. His editorial service includes senior editor roles at Information Systems Research and associate editor at Management Science . He has also chaired tracks at ICIS and served as program co-chair for PACIS. There is no indication of external grant funding in the provided text, but his sustained publication record and leadership roles suggest significant research activity and institutional support. He is actively involved in academic leadership and research dissemination, contributing to major conferences and editorial boards. His work bridges theory and practice, particularly in digital platform ecosystems and analytics-driven decision-making.
Retsef Levi is the J. Spencer Standish (1945) Professor of Operations Management at the MIT Sloan School of Management, affiliated with the MIT Operations Research Center. He co-directs the Leaders for Global Operations (LGO) Program. His work focuses on data-driven decision models for healthcare systems, supply chain optimization, and risk management. Levi holds a PhD in Operations Research from Cornell University and has led industry collaborations with major hospitals and organizations like the FDA and Walmart Foundation. Education: PhD in Operations Research, Cornell University, 2005 Bachelor’s in Mathematics, Tel-Aviv University, 2001 Research Interests: Levi’s research addresses complex decision-making under uncertainty in healthcare, supply chains, and logistics. Key areas include food safety analytics, risk-based sampling, and predictive modeling for zoonotic diseases. He designs algorithms for inventory control, appointment scheduling, and healthcare resource allocation. Articles Overview: Recent work spans AI-driven epidemiological models, supply chain cybersecurity, and agricultural market interventions. His articles emphasize practical applications of operations research in healthcare and public health. Awards: NSF Career Grant INFORMS Optimization Prize (2008) Wagner Prize (2013) Harold W. Kuhn Award (2016) Advising & Grants: Advised 10 PhD students and 34 master’s students. Led multi-million-dollar projects like the Walmart Foundation initiative for China’s food safety. Active in hospital process optimization and FDA risk management contracts. Labs & Teams: Runs MIT’s Food Supply Chain Analytics and Sensing Initiative, collaborating with global partners on predictive risk tools and healthcare analytics.
Dr. Mary Lacity is a Distinguished Professor of Information Systems at the Sam M. Walton College of Business, University of Arkansas, and holds the David D. Glass Endowed Chair. She is also a Visiting Professor at the London School of Economics for Spring 2025. Director of Walton College’s Blockchain Center of Excellence (2014-2019) Former Curators’ Distinguished Professor at University of Missouri Holds visiting positions at MIT, Washington University, and Oxford University Senior Editor for MIS Quarterly Executive Contributing Editor for Journal of the British Blockchain Association Her research focuses on enterprise adoption of emerging technologies, particularly blockchain, metaverse, service automation, and ethical technology use. She has conducted extensive case studies and surveys on automation and Web3 implementation across hundreds of organizations globally. Recent publications include books like Human Privacy in Virtual and Physical Worlds (2024) and Blockchain Fundamentals for the Web 3.0 (2022). She has over 30 books and 26,300 Google Scholar citations (h-index: 68). 2014: Inducted into IAOP’s Outsourcing Hall of Fame 2024: Recognized as top 2% scholar in Business and Management (Stanford) 2024: Top 1% scholar in Business and Management (ScholarGPS) Fellow of the Association of Information Systems She actively contributes to blockchain standards via the Global Standards Mapping Initiative (GSMI) of the Global Blockchain Business Council and the Linux Foundation’s Trust over IP (ToIP). Her work bridges academic research and practical applications in enterprise technology adoption.
Kirk Roberts, PhD, is an Associate Professor in the Department of Health Data Science and Artificial Intelligence at the McWilliams School of Biomedical Informatics, UTHealth Houston. He specializes in Natural Language Processing (NLP), with a focus on clinical information extraction, spatial information extraction, and medical information retrieval. His work bridges computer science, medicine, linguistics, and machine learning to improve accessibility and usability of biomedical data. Education: PhD (2013) and MS (2009) in Computer Science from the University of Texas at Dallas; BS (2005) in Computer Science from Georgia Institute of Technology. Research emphasizes NLP applications for healthcare, including question-answering systems, EHR analysis, and spatial relation extraction. He leads the TREC Clinical Decision Support track and has been recognized with a National Library of Medicine Career Development Award. His contributions span over 20 peer-reviewed publications in journals like JAMIA and conferences such as ACL and AMIA. Key areas include: advancing clinical decision support via NLP, optimizing biomedical literature retrieval, and improving health data dissemination through natural language systems.
Dr. Lachlan D. Urquhart is a Senior Lecturer in Technology Law and Human-Computer Interaction at the University of Edinburgh's School of Law. He co-directs the Scottish Research Centre for Intellectual Property and Technology Law (SCRIPT) and leads the Regulation and Design (RAD) Lab. He is a director of the Centre for Research into Information, Surveillance, and Privacy (CRISP) and contributes to the Designing Responsible NLP Centre for Doctoral Training and the Institute of Design Informatics. Education: LL.B, Hons (Edinburgh); LL.M in IT & Telecoms Law, Distinction (Strathclyde); Ph.D in Computer Science (Nottingham). Research Interests: Focus on socio-technical aspects of designing, regulating, and living with emerging information technologies, including AI ethics, IoT, data privacy, cybersecurity, and responsible innovation. Projects: Principal Investigator of the £1.2m EPSRC 'Fixing the Future: Right to Repair and Equal-IoT' project; Co-Investigator on £9.75m Responsible NLP AI CDT and £3.2m EPSRC Trustworthy Autonomous Systems Governance Node. Visiting Roles: Turing Fellow (2020-22), Research Fellow at Universitá degli Studi di Milano (2022-23), and visiting researcher at Meiji University (2014).
