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Amelia CompagniView profile

Associate Professor

• Healthcare Management
• Public Management
• Innovation Management
• +3 more

Amelia Compagni serves as Associate Professor in the Department of Social and Political Sciences at Bocconi University and Director of CeRGAS (Center for Research on Health and Social Care Management) at SDA Bocconi. Previously Director of the World Bachelor in Business program, she teaches healthcare management and public management across undergraduate, graduate, and PhD programs at Bocconi University alongside MIHMEP and MIMS master programs at SDA Bocconi. Her academic foundation includes a Biology degree specializing in Genetics and Molecular Biology from the University of Pavia, followed by a PhD in Genetics from Vienna's Institute of Molecular Pathology (1995-2000). After a post-doctoral fellowship at Cancer Research UK in London (2000-2004), she transitioned to management through a Master in Healthcare Management, Economics and Policy from SDA Bocconi. Compagni's research centers on healthcare management dynamics and innovation within professional healthcare groups , with expanding focus on digital transformation and AI applications . Her work bridges biological sciences with management perspectives to address systemic healthcare challenges, particularly examining organizational behavior in clinical settings and policy implementation. Recent publications (2024-2025) reveal concentrated exploration of telemedicine efficacy, healthy ageing metrics, AI adoption barriers, and environmental sustainability in healthcare systems. These studies demonstrate interdisciplinary methodology spanning systematic reviews, empirical surveys of healthcare organizations, and patient-centered outcome research published in top-tier journals. Award recognition includes: Excellence in Research Award (Bocconi University, 2024) Excellence in Teaching Innovation Award (2019) Academy of Management Best Reviewers Award (2018) Research Excellence Award (2015) International “Vivisalute” Research Award (2012) SDA Bocconi Best Teacher Award (2010) Through CeRGAS leadership, she directs national and international collaborations analyzing healthcare organization effectiveness, with recent projects examining Lombardy's AI implementation and comparative sustainability models between Italy and England. Her advisory work focuses on translating research into practical management frameworks for healthcare institutions.

Hwanhee HongView profile

Associate Professor

• Bayesian Statistical Methods
• Comparative Effectiveness Research
• Network Meta-Analysis
• +5 more

Hwanhee Hong is an Associate Professor in the Department of Biostatistics and Bioinformatics at Duke University School of Medicine and a member of the Duke Clinical Research Institute. Affiliated with the Biostatistics, Epidemiology, and Research Design (BERD) Methods Core and the B&B Faculty, Dr. Hong maintains an active research program focused on statistical methodology development for clinical applications. Dr. Hong's educational background includes a Ph.D. in Biostatistics from the University of Minnesota (2013), an M.S. in Biostatistics from Harvard University (2010), and a B.S. in Statistics from Chung-Ang University, Korea (2008). Prior to joining Duke, they completed a postdoctoral fellowship at Johns Hopkins Bloomberg School of Public Health under Dr. Elizabeth A. Stuart. Research interests center on Bayesian statistical methods for comparative effectiveness research, network meta-analysis, causal inference, measurement error correction, and data integration across multiple sources. Their work emphasizes adaptive information borrowing to address clinical and public health questions, particularly in developing flexible Bayesian modeling frameworks that synthesize diverse data streams for evidence generation. Analysis of recent publications reveals consistent methodological focus on network meta-analysis techniques, causal inference with error-prone covariates, generalizability assessment, and time-to-event analysis. The research spans applications in pediatrics, cardiology, obesity treatment, and vaccine effectiveness, demonstrating strong translational impact across medical domains. Dr. Hong actively collaborates with biostatisticians, epidemiologists, clinicians, and health policymakers through multiple funded projects, though no formal awards or fellowships are documented in the provided materials. Participant, Faculty Success Program, National Center for Faculty Development & Diversity (2023) Participant, Faculty Curriculum on Anti-Racism, Duke Office of Faculty Advancement (2021) Teaching responsibilities include BIOSTAT 719: Generalized Linear Models. Current grant funding spans eight major projects totaling over $20 million, primarily from NIH and PCORI, addressing pediatric care coordination, mental health interventions, obesity treatment, diabetes management, and advanced biostatistical methodology development. Dr. Hong's laboratory work focuses on computational approaches for data integration, maintaining active collaborations with the Duke Clinical Research Institute and multiple external institutions including Johns Hopkins University and North Carolina State University.

Emma SpiroView profile

Associate Professor

• Social Networks
• Sociology
• Information Integrity
• +3 more

Emma Spiro is an Associate Professor at the University of Washington Information School, with adjunct appointments in the Department of Sociology and Human Centered Design & Engineering. She co-founded the Center for an Informed Public (CIP) and directs the Social Media Lab (SoMeLab) and Data Science and Analytics Lab (DataLab). Her research focuses on online communication, misinformation dynamics, and network structures in both digital and physical contexts. Dr. Spiro’s work explores social networks and computational social science, analyzing how misinformation spreads during crises and elections. Her research has been funded by the National Science Foundation and Army Research Office, and published in top journals like PNAS, Social Networks, and Information, Communication & Society. She holds a Ph.D. in Sociology from UC Irvine and dual B.A.s in Applied Mathematics and Science, Technology & Society from Pomona College. As a Data Science Fellow at UW’s eScience Institute, she bridges technical and social science methodologies to study information integrity. Her affiliations include the UW Center for Statistics & the Social Sciences (CSSS) and the Center for Studies in Demography & Ecology (CSDE). She actively collaborates across disciplines to address strategic misinformation through labs, institutes, and multi-institutional initiatives like the Disinformation Summer Institute.

Vincent RocaView profile

Researcher

• Privacy
• Robust Content Distribution
• Transport Protocols
• +6 more

Vincent Roca is a permanent researcher at Inria , a French national research institute for digital science and technology. Since 2019, he leads the Privatics research team focusing on privacy, previously part of the Planete team (2000-2012) for Internet protocols and applications. His work spans Privacy in smartphones, IoT, and web browsers Design of the ROBERT and CLEA protocols for the French TousAntiCovid app Standardization in IETF working groups, notably on FEC and network coding Co-author of Inria's cybersecurity white book (2019) Instructor of the popular Privacy in the digital world MOOC (14,006 participants) Research Interests include privacy risks in digital technologies, robust content distribution via FLUTE/ALC transport protocols and LDPC-Staircase FEC codes, and network coding for scalable services. His articles focus on privacy in LoRaWAN, contact tracing protocols, GDPR compliance, and FEC optimization. Scientific Awards include the Third Applied Research Price from FIEEC (2014) Knight Medal of the French Order of Merit (2020) Students supervised include PhD candidates in privacy-preserving IoT, secure authentication, and alumni like Samuel Pelissier (LoRaWAN privacy) and Michael Toth (GDPR compliance). Software Contributions include openfec.org (AL-FEC codes) and FLUTE/ALC implementations .

Sebastian von MammenView profile

Professor

• Games Engineering
• Virtual Reality
• Interactive Simulations
• +3 more

Prof. Dr. Sebastian von Mammen is a tenured professor at the University of Würzburg's Institute for Computer Science, where he heads the Games Engineering research group and contributes to the Chair for Human-Computer Interaction. His group leads the Games Engineering academic program. Previously, he completed his habilitation (2012-2016) at the University of Augsburg's Chair of Organic Computing and was a postdoctoral fellow at the University of Calgary. His research spans: Real-Time Interactive Systems : Visual programming, immersion techniques, software engineering Interactive Simulations : Serious games for healthcare/logistics/construction Artificial Life : Self-organisation, adaptive systems, evolutionary computation Artificial Intelligence : Agent-based modeling, procedural content generation Recent publications (2023-2025) demonstrate strong focus on: Virtual reality applications in education (femtoPro optics simulator, BrainBuilder neuroanatomy) Healthcare technology platforms (VIA-VR for medical serious games) Game mechanics analysis (Match-3, Jump'n'Run flow) AI-driven emotion recognition and interactive systems Computational modeling of biological systems He leads the Games Engineering research group and previously participated in the Evolutionary and Swarm Design group (Calgary) and LINDSAY project. His lab develops VR simulations for scientific training and serious games applications.

Paul BrindleyView profile

Senior Lecturer

• Digital Representations of Landscape
• GIS Mapping
• Health Inequality
• +5 more

Dr. Paul Brindley is a Senior Lecturer at the School of Architecture and Landscape , University of Sheffield, specializing in geospatial analysis of human-landscape interactions. His work combines GIS, statistics, and digital data to address urban greenspace equity, rural-urban classification, and health-environment linkages. Senior Lecturer in GIS and Spatial Analysis Key researcher in the NERC-funded Improving Wellbeing through Urban Nature (IWUN) project Co-author of official Rural-Urban Classification for England and Wales Research focuses on: Urban Greenspace Accessibility using GPS and social media data Health Inequality Mapping through epidemiological GIS studies Vague Geographic Objects modeling of subjective spatial boundaries Computational Neighborhood Mapping via web data mining Project leadership includes: 2016-2019: IWUN Work Package 1 (Sheffield health-green space analysis) 2013-2014: Rural-Urban Classification updates for 2011 Census 2015: Real-Time Bus Data Mapping system development Teaching modules: LSC119: The Changing Landscape LSC336: Landscape Planning Toolkits LSC5020: Rural Landscape Planning GIS Workshops Professional contributions: Co-developer of Crime Map Analyst toolkit for non-GIS experts Joint Director of Learning and Teaching Links Member of Creative Spatial Practices initiative

• Artificial Intelligence
• Educational Technology
• Business Process Management
• +5 more

Darko Etinger is an Associate Professor and currently serves as the Dean of the Faculty of Informatics at Juraj Dobrila University of Pula in Croatia. His academic career spans over two decades with significant contributions to the fields of information systems, educational technology, and artificial intelligence. He teaches undergraduate courses including Artificial Intelligence, Business Information Systems, Business Process Management, ICT Fundamentals, Information Systems, Introduction to Artificial Intelligence, and Multimedia Systems. At the graduate level, he teaches Development of IT Solutions, IT Management, Modelling and Simulation, and Project Management. He also supervises doctoral research in Management of Information Technologies in Education. Dr. Etinger's research interests span several key areas in computer science and education technology. He has made significant contributions to understanding how information and communication technologies can support children with special educational needs, as evidenced by his 2024 and 2025 books on the topic. His work also focuses on business process management, educational data mining, and the application of artificial intelligence in educational contexts. His 2024 book 'Introduction to R and RStudio' demonstrates his commitment to data science education. Analysis of his recent publications shows a strong focus on practical applications of technology in education and business. His work spans educational robotics, learning management systems analysis, business process modeling, and the application of large language models in healthcare. He has a particular interest in how technology can be made accessible and beneficial for diverse learner populations, including those with special needs. His research often takes a human-centered approach, examining not just the technology itself but how it's adopted and used by end users. His 2025 bibliometric analysis of metaverse security demonstrates his ability to tackle emerging technological challenges. Associate Professor at Faculty of Informatics, Juraj Dobrila University of Pula Current Dean of Faculty of Informatics Author of multiple publications on educational technology and information systems Supervisor for numerous graduate theses on educational technology topics Active participant in EDIH Adria project as evidenced by 2025 publications Researcher in educational robotics implementation in Croatian schools Dr. Etinger has advised numerous students completing their theses, with a focus on educational technology applications. His research has been published in various international conferences and journals including IEEE Engineering Management Review, Procedia Computer Science, and System Dynamics Review. His current research appears to be heavily focused on the EDIH Adria project, which is a European Digital Innovation Hub initiative focusing on technology transfer and business innovation. He maintains an active research program with publications spanning from 2003 to the present, demonstrating sustained scholarly contribution to his fields of expertise.

Nick CheneyView profile

Associate Professor

• Artificial Intelligence
• Robotics
• Machine Learning
• +7 more

Nick Cheney is an Associate Professor in the Department of Computer Science at the University of Vermont, leading the UVM Neurobotics Lab. He also serves as Graduate Program Director and is affiliated with the Vermont Complex Systems Center, an interdisciplinary hub for data-rich complex systems research. PhD in Computational Biology and Biological Statistics from Cornell University Advised by Hod Lipson and Steve Strogatz His research focuses on bio-inspired machine learning algorithms, particularly in evolutionary computation, deep learning, and reinforcement learning. Key applications span robotics, healthcare diagnostics, and environmental science. The lab's interdisciplinary work has been recognized with prestigious awards including the NSF CAREER Award and SIGEVO Impact Award . Recent publications highlight advancements in morphological computation, continual learning, and cross-domain applications of machine learning. His team develops algorithms for soft robots, medical diagnostics using wearable sensors, and sustainable agriculture systems, often publishing in venues like the Nature Scientific Reports , GECCO , and Soft Robotics . Scientific Awards : NSF CAREER Award SIGEVO Impact Award The lab actively mentors graduate students in Complex Systems and Data Science, with alumni securing positions at institutions like Harvard, UC Berkeley, and Medidata. Collaborative grants with biomedical and environmental researchers demonstrate the lab's commitment to societal impact through machine learning applications.

R. JayakrishnanView profile

Professor

• Transportation Systems Engineering
• Dynamic Traffic Assignment
• Urban Traffic Simulation
• +3 more

R. Jayakrishnan , a Professor in the Department of Civil and Environmental Engineering at the Samueli School of Engineering , University of California, Irvine, is a leading researcher in transportation systems engineering. Ph.D., University of Texas, Austin, Civil Engineering, 1992 M.S., University of Texas, Austin, Civil Engineering, 1987 B.S., Indian Institute of Technology, Madras, India, 1985 His research focuses on dynamic traffic assignment , urban traffic simulation , and real-time information systems to improve congested traffic corridors. He is developing advanced dynamic simulation-assignment models for urban traffic networks. Recent publications highlight his contributions to: Crowdsourced delivery optimization using decomposition heuristics Eco-driving algorithms with V2I communication Multi-furniture placement applications via augmented reality Subscription mobility services cost-benefit analysis Agent-based lane-changing coordination systems These works demonstrate his interdisciplinary approach combining transportation engineering, optimization algorithms, and emerging technologies like AR and connected vehicles.

Daniel HaleView profile

Professor

• Pediatric Endocrinology
• Growth Disorders
• Pubertal Disorders
• +3 more

Daniel Hale is a Professor in the Department of Pediatrics and Chief of the Division of Endocrinology. His work focuses on pediatric endocrine abnormalities, particularly in children with genetic syndromes, growth disorders, and pubertal disorders. He is also active in medical student, resident, and provider education. Education: MD, University of Texas McGovern Medical School (1977) Pediatrics Residency, Medical University of South Carolina (1980) Pediatric Endocrinology Fellowship, Children's Hospital of Philadelphia (1983) Research Trends: Type 2 Diabetes in Youth Genetic Syndromes and Endocrinology Impact of CNS Stimulants on Pediatric Growth Glycemic Control and Complications in Diabetes Chromosome 18 Syndromes Collaborations: Extensive cross-institutional collaborations in diabetes, genetics, and child development. Grants: National Children's Study, GH Trial for Chromosome 18q- Syndromes, DM2 Risk in Mexican Youth, Telehealth Network Grants.

Santiago OntañónView profile

Associate Professor

• Artificial Intelligence
• Machine Learning
• Game AI
• +10 more

Santiago Ontañón is an Associate Professor in the Department of Computer Science at Drexel University's College of Computing and Informatics. He is also a Senior Research Scientist at Google DeepMind, reflecting a strong dual affiliation in both academic and industrial AI research. His work bridges theoretical AI with practical applications in gaming and machine learning. PhD in Computer Science (Artificial Intelligence), cum laude, Autonomous University of Barcelona Postdoctoral Researcher, Georgia Institute of Technology Researcher, Artificial Intelligence Research Institute (IIIA), Barcelona, Spain Dr. Ontañón's research focuses on artificial intelligence, machine learning, and robotics, with a particular emphasis on game AI. His interests span case-based reasoning, reinforcement learning, Monte Carlo tree search, player modeling, and procedural content generation. He has made significant contributions to AI in real-time strategy games and explainable AI systems. His recent publications reflect a consistent trend in AI for games, hierarchical planning, and learning from demonstration. The articles span topics such as reproducible deep reinforcement learning, adaptive player modeling, and integrating domain knowledge into search algorithms, indicating a mature and impactful research trajectory in AI and game technologies. Senior Research Scientist, Google DeepMind Organizer, microRTS AI Competition Advising multiple PhD students in AI and game-related topics He has advised numerous PhD students, many of whom have completed their theses on advanced AI topics in games and reasoning. His research is supported by access to substantial computational resources and collaborative networks in both academia and industry. He actively promotes open science by releasing software, data, and teaching materials. He leads research efforts in AI for games and maintains an active lab focused on game AI, with projects like microRTS, FTL, and Darmok. His team develops systems for reinforcement learning, planning, and natural language understanding in game environments.

• Human-Centered Design
• Digital Ethics
• Social Technology
• +6 more

Thomas Olsson is a **Professor in Human-Centered Design** at Tampere University, affiliated with the Faculty of Information Technology and Communication Sciences and the Computing Sciences department. He leads the *Technology x Social Interaction Research Group* and the *Digital and Sustainability Transitions in Society* research platform. His work focuses on designing ICT systems that prioritize digital ethics, social sustainability, and environmental responsibility. **Research Interests**: Social technologies, sustainable design of ICT, AI-driven recruitment systems, cultural integration through technology, and the ethical implications of digital media. He employs qualitative methods and design-through-research approaches, often collaborating across disciplines like computer science and behavioral/social sciences. Current roles: Academic Director of Digital/Sustainability Transitions Platform; Head of Master's Program in Computing Sciences and Electrical Engineering Key projects: AIdience (AI in Journalism), Trust-M (Migrant Services), Big Match (Team Assembly), Emotions in Digital Media Teaching: Coordinates Human-Technology Interaction studies and develops courses like *Sustainable Design* and *Ethics of Technology* **Lab/Team**: Leads the *Technology x Social Interaction* group (collaboration opportunities available). Active in the *Rajapinta* interdisciplinary research community.

David KurzView profile

Visiting Assistant Professor

• Conservation Science
• Human Dimensions of Wildlife
• Climate Policy
• +5 more

David Kurz is a Visiting Assistant Professor in Environmental Studies at Boston College. He holds a PhD in Environmental Science, Policy, and Management from UC Berkeley, an MPhil in Zoology from the University of Cambridge, and an AB in Ecology & Evolutionary Biology from Princeton University. His interdisciplinary research focuses on the human dimensions of wildlife conservation, climate policy, and socio-ecological systems. Dr. Kurz explores how climate change, urbanization, and land-use shifts impact ecosystems and human communities. Key research projects include studying bearded pig distributions in Borneo, cultural implications of lobster die-offs in the Long Island Sound, and equity in urban green space access. His work bridges natural and social sciences to address challenges in biodiversity conservation and climate resilience. Recent publications highlight topics like wildfire biodiversity overlaps in California, socio-ecological dynamics in Malaysian Borneo, and the impacts of the COVID-19 pandemic on wildlife. He emphasizes mentorship, guiding students toward real-world problem-solving and engaged scholarship. Dr. Kurz’s teaching and research align with Boston College’s commitment to environmental justice and interdisciplinary collaboration.

Rahul SiddharthanView profile

Researcher

• Bioinformatics
• Regulatory Genomics
• Chromatin Structure
• +6 more

Rahul Siddharthan is a computational biologist at The Institute of Mathematical Sciences (IMSc), Chennai , with research interests spanning bioinformatics algorithms, regulatory genomics, chromatin structure, evolutionary biology, and machine learning applications in clinical outcomes. He holds a PhD in Physics from the Indian Institute of Science, Bangalore, and transitioned to biology during a postdoc at the Rockefeller University, New York. At IMSc, he has led the Computational Biology group since 2013 and contributed to a new PhD program in this field. PhD: Physics, Indian Institute of Science, Bangalore Postdoc: Rockefeller University, New York Current Affiliation: IMSc, Chennai Leadership: Computational Biology group (since 2013) Research Interests include: Bioinformatics Algorithms Regulatory Genomics Chromatin Structure Evolutionary Biology Machine Learning in Clinical Data His recent publications focus on machine learning for fetal growth prediction , clustering methods for clinical data , and evolutionary analysis of fungal pathogens . He actively supervises PhD students and collaborates with medical institutions like Apollo Hospitals and Warwick Medical School. Rahul also organizes interdisciplinary workshops such as 'Machine Learning for Health and Disease' at ICTS Bengaluru and 'Aspects of Gene and Cellular Regulation' at IMSc. Advising and Collaborations involve mentoring current PhD students Sankarsan Dutta and Akash Sivaraman, with past advisees including Pavitra S (defended 2025), Chandrani Kumari (submitted 2024), and Rakesh Netha Vadnala (PhD 2023). Key collaborators include Dr. Uma Ram (Seethapathy Clinic), Leelavati Narlikar (IISER Pune), and Ponnusamy Saravanan (Warwick). Technical Contributions include developing algorithms like THiCweed for ChIP-seq motif discovery and ClaID for Candida auris clade identification. His group engages in projects related to chromatin organization , transcription factor interactions , and genomic data analysis .

Nai-Ching ChiView profile

Associate Professor

• Data Science
• Health Technology
• Dementia Care
• +4 more

Dr. Nai-Ching Chi is a tenured Associate Professor at the University of Iowa College of Nursing. She is a nurse scientist and informaticist conducting pioneering research at the intersection of data science, technology, and health, focusing on dementia care, multimorbidity management, pain management, family caregiving, and healthy aging. PhD in Biobehavioral Nursing and Health Informatics (University of Washington) MS in Clinical Informatics and Patient-Centered Technologies (University of Washington) MSN (University of California, San Francisco) BSN (Tzu Chi University, Taiwan) Dr. Chi's research integrates advanced data science and AI to develop digital interventions for vulnerable populations. Notable projects include the PACE-app for dementia caregiver pain management, AI-powered nursing communication tools, and NIH-funded studies on multimorbidity patterns in Alzheimer's patients. Her work informs clinical guidelines and leverages predictive modeling for early risk detection. Recent publications focus on AI-driven pain assessment, machine learning in multimorbidity analysis, usability of caregiving apps, and rural age-friendly ecosystems. Her work spans comorbidity indices, geriatric pain, and health informatics innovations. National Academy of Medicine Emerging Leader Forum nomination NIA Butler-Williams Scholar NIA Aging Initiative MCCs Scholar Hospice and Palliative Nurses Association Emerging Leader Award Dr. Chi mentors students in aging research and technology-driven healthcare. She serves on editorial boards, grant review panels, and university committees, while volunteering in nursing homes and international medical missions.