Xinjie (Cynthia) Ma is an Assistant Professor in the Department of Accounting at the University of Iowa's Tippie College of Business. Previously, she held a Visiting Assistant Professor position at the University of Iowa in 2025. Her research bridges financial accounting with advanced technologies, focusing on corporate disclosure mechanisms, human capital valuation, and AI/NLP applications in capital markets. She earned her PhD in Accounting from Temple University in 2021. Research Expertise : Financial accounting, CSR strategy alignment, human capital analytics, and machine learning applications Publications : 2023 Review of Accounting Studies paper on CSR-performance alignment, 2022 The Accounting Review article on text-based investment opportunity sets Teaching : Instructed graduate Financial Statement Analysis at National University of Singapore (2021-2025), undergraduate Managerial Accounting at Temple University (2019) Academic Affiliation : Tippie College of Business Her recent work analyzes how textual disclosures in 10-K filings inform investment decisions and explores labor demand dynamics through real-time market data. Currently, she's developing machine learning models to predict startup innovation potential and examining managerial communication patterns in earnings calls. Email: xinjie-ma@uiowa.edu
Professor Victor Callan AM is Professor of Leadership and Organisational Change at the University of Queensland Business School within the Faculty of Business, Economics and Law. With over 300 publications to his name, including 179 journal articles, 60 conference publications, and 17 books, he is one of Australia's most recognized researchers in organizational change, leadership performance, and employee training. His influential work has shaped public policy in workforce development, vocational education, and organizational change management. Education: Bachelor (Honours) of Arts, University of New South Wales Doctor of Philosophy, Australian National University Professor Callan's research focuses on two primary areas: organizational change and leadership, with special interest in employees' and leaders' experiences with large-scale change; and employee skills, capabilities and training, examining effective responses to skills development and shortages. His work explores adaptation levels, personal capabilities, communication dynamics, and team processes during organizational transitions. He has pioneered research on maverickism in organizations, investigating how positively deviant change agents drive radical organizational transformations. His recent publications reveal a strong trend toward gender equality research, Indigenous knowledge integration, and maverick leadership. These works span multiple disciplines including organizational behavior, human resource management, vocational education, and leadership studies. His research on workplace gender inequality employs wicked problems frameworks, while his work on Indigenous knowledge holders emphasizes co-creation and positioning as expert researchers. Major Awards and Recognition: Fellow of the Academy of Social Sciences in Australia Fellow of the Queensland Academy of Arts and Sciences Fellow of the Australian Institute of Company Directors Member (AM) of the Order of Australia for significant service to higher education University's Award for Excellence in Higher Degree Research Supervision Two UQ Excellence in Leadership Awards Professor Callan has supervised numerous PhD students across diverse topics including leadership ascension, maverickism, CEO appointments, and organizational change. He has secured substantial research funding, including his 14th Australian Research Council project in 2025 focusing on Indigenous women environmental rangers. His advisory work spans over 100 projects for government departments and international organizations across South Africa, Ghana, Tanzania, Indonesia, Bhutan, Brunei, New Zealand, PNG, and South Pacific countries, addressing employee skills, vocational education, industry closures, and workforce development. He actively contributes to executive education for senior managers globally and has developed strong research, consulting, and industry partnerships. His current teaching focuses on MBA programs and the Bachelor of Advanced Business Honours program at UQ.
Dr. April Nowell is a Professor of Anthropology in the Department of Anthropology at the University of Victoria's Faculty of Social Sciences, specializing in Paleolithic archaeology, cognitive archaeology, and the archaeology of children. Currently on leave, she leads internationally recognized research projects across Europe, the Levant, Australia, and Africa while actively accepting graduate students. She earned her PhD from the University of Pennsylvania and has developed expertise in Neanderthal lifeways, Paleolithic art, and hominin life histories. Her academic journey reflects deep engagement with both theoretical frameworks and fieldwork across diverse geographical contexts. Nowell's research examines how prehistoric societies structured knowledge transmission, childhood development, and symbolic expression. Her groundbreaking work on finger flutings in Australian caves reveals children's roles in Paleolithic storytelling traditions, while her analysis of Levantine wetland ecosystems demonstrates how Pleistocene humans adapted to environmental shifts. She challenges conventional narratives about Neanderthal cognition and has pioneered methodologies for reconstructing prehistoric childhood experiences through skeletal and material evidence. Her recent publications show consistent innovation in archaeological methodology, particularly in digital documentation of rock art and interdisciplinary approaches to human development. Key trends include integrating bioarchaeological data with cognitive models, examining material culture as evidence of social learning, and analyzing environmental archives to understand human dispersal patterns. Her scientific recognition includes: 2023 EAA Book Prize for Growing Up in the Ice Age: Fossil and Archaeological Evidence of the Lived Lives of Plio-Pleistocene Children Nowell secures major research funding including Social Sciences and Humanities Research Council grants supporting her Azraq Basin project in Jordan and Koonalda Cave research in Australia. She mentors graduate students in Paleolithic theory while collaborating with Indigenous communities and international scholars on field projects spanning five continents. Her work bridges academic research and public engagement through TEDx talks and media appearances examining science communication. She directs field programs at Jordan's Azraq Basin wetlands and Australia's Koonalda Cave, working with multidisciplinary teams including geochronologists, bioarchaeologists, and Traditional Owners to investigate Pleistocene human adaptation and cultural transmission.
Prof. Dr. Frank T. Piller is a University Professor and Co-Leader of the Institute for Technology and Innovation Management (TIM) at RWTH Aachen University, where he also serves as Academic Director of the Executive MBA program at RWTH Business School. He leads a research team of approximately 30 doctoral students, 5 postdocs, and over 20 student researchers within the TIME Research Area of the School of Business and Economics. His educational background includes a doctoral degree in Operations Management from the University of Würzburg (1999) and a Habilitation degree from TUM Business School (2004) on "Innovation and Value Co-Creation." Prior to joining RWTH Aachen in 2007, he was a Research Fellow at MIT Sloan School of Management and faculty at TUM Business School. Prof. Piller is recognized as one of the world's leading experts in customer-centered value creation, specializing in mass customization, personalization, and customer co-creation. His current research focuses on how established companies can transform in response to disruptive business model innovations, with particular emphasis on digital transformation (Industry 4.0), AI-augmented innovation, and sustainable business models. He is particularly known for his work on innovation ecosystems, platform-based business models, and stakeholder-oriented technology development. His recent publications demonstrate a clear trajectory toward integrating artificial intelligence with traditional innovation management frameworks, exploring how AI transforms manufacturing systems, innovation processes, and business models. His work increasingly addresses the challenges of digital transformation in established industries while maintaining focus on customer co-creation and mass customization principles. His scientific achievements have been recognized with numerous awards: Co-Creation Award of the PDMA Nomination for "Innovating Innovation" Prize by Harvard Business Review and McKinsey "Lecturer of the Year" by Executive MBA students at TU Munich RWTH Aachen Rector's Prize for Excellent Teaching (since 2010) Grant for innovative "Flipping the Classroom" teaching concept ERC Synergy Grant for SAFER Grid project (2025-2031) Prof. Piller maintains an extensive research network spanning academia and industry. He collaborates with numerous corporations including 3M, Adidas, BASF, EON, J&J, P&G, Siemens, and Vodafone, as well as many technology startups across Europe and North America. As a co-founder, supervisory board member, and investor in innovative startups, he actively transfers research into practice. His research has received significant funding, most notably the prestigious ERC Synergy Grant for the SAFER Grid project. He leads the Technology and Innovation Management Group (TIM) within the TIME Research Area at RWTH Aachen, which comprises over 100 senior and junior researchers working at the intersection of innovation, technology management, marketing, and entrepreneurship. The institute is a leading European research institution for strategic, behavioral, and computer-supported technology and innovation management.
Glenn Tiffert is a Distinguished Research Fellow at Stanford University's Hoover Institution, specializing in modern Chinese history and contemporary US-China relations. He co-chairs Hoover's program on the US, China, and the World and leads Stanford's participation in the NSF SECURE program, a $67 million initiative authorized by the CHIPS and Science Act of 2022. Tiffert is a historian of modern China with expertise in the political and legal history of the People's Republic of China. His research focuses on the construction of China's court system and judiciary, the drafting of the 1954 PRC Constitution, and the suppressed genealogy of the rule of law in China. He has pioneered the integration of computational methods into Chinese historical studies and is currently completing the first archival study in any language of the takeover and reconstitution of a Chinese state organ (the courts) by the Chinese Communist Party. His recent publications reveal a strong trend toward analyzing China's global influence operations, research security challenges, and technological competition between the US and China. Tiffert's work increasingly addresses how authoritarian regimes exploit vulnerabilities in open knowledge ecosystems, particularly examining China's 'sharp power' projection and efforts to reshape global narratives. Co-chairs the Hoover project on China's Global Sharp Power Executive committee member of the Academic Security and Counter-Exploitation Program Participant in multiple Hoover research teams including Taiwan in the Indo-Pacific Region and Semiconductors security working group Testified before the U.S. Senate Select Committee on Intelligence on Chinese malign influence operations Tiffert collaborates extensively with government and civil society partners worldwide to document and build resilience against authoritarian interference with democratic institutions. His work spans academic research, policy development, and public education on the security and integrity of knowledge ecosystems, particularly academic, corporate, and government research.
Dr. Tommaso Gabrieli is an Associate Professor in Real Estate at the Bartlett School of Planning, University College London (UCL), where he has been employed since September 2015. His academic career spans multiple institutions including the University of Reading, City University London, University of Warwick, and the Catholic University of Milan. His educational background includes: PhD in Economics from the University of Warwick (2009) MSc in Economics from the London School of Economics and Political Science (2003) Fellowship of the Higher Education Academy from the University of Reading (2013) As a theoretical economist trained in the ambrosian tradition of social welfare, Gabrieli's research focuses on the economic analysis of urban policy issues. His expertise encompasses economic modeling of real estate markets, financial viability of urban projects, multi-dimensional value measurements, and value-capture mechanisms. He has developed novel interdisciplinary methods bridging urban planning and design with economics, making him one of few economists actively collaborating with urban planning scholars in the UK. His work addresses Sustainable Development Goals including No Poverty, Good Health, Decent Work, Reduced Inequalities, Sustainable Cities, and Climate Action. His recent publications demonstrate a strong focus on urban design governance, value capture mechanisms, and the interface between economic theory and urban planning practice. The research spans theoretical explorations of post-growth planning and practical applications in land value recovery, particularly examining implications for housing affordability, wealth distribution, and community wellbeing in both urban and rural contexts. His work often integrates behavioral economics with spatial planning considerations. Professional recognition includes: Fellow of the Higher Education Academy Gabrieli has extensive experience supervising PhD and MSc dissertations across multiple institutions. His teaching portfolio includes Real Estate Appraisal and Valuation at UCL, where he leads relevant modules for both undergraduate and graduate programs. He has contributed to significant research projects including 'Street Appeal' commissioned by Transport for London and the Horizon 2020-funded 'UrbanMaestro' project worth 1 million Euros. His research impact has been formally recognized by Transport for London. Currently, he leads the 'Future Urban Growth Lab' project, funded by UCL Knowledge Exchange and Innovation Funding, in partnership with the Royal Town Planning Institute and Politecnico of Turin. This project aims to operationalize an urban growth model prototype for use by local authorities in planning future city development, bridging academic research with practical planning applications.
Lappeenranta-Lahti University of Technology LUTFinland
Adeel Tariq is a Post-Doctoral Researcher at the Industrial Engineering and Management department of LUT School of Engineering Sciences , Lappeenranta University of Technology, Finland. He completed his Ph.D. (2019) and MBA (2014) at the School of Management , Asian Institute of Technology, Thailand. Research Focus: Technology and innovation management, digital transformation, sustainable development, knowledge management, and leadership studies. Peer Review: Active reviewer for journals including Leadership & Organization Development Journal , Journal of Intellectual Capital , and European Journal of Innovation Management . Collaborations: Regular co-author with Waqas Tariq, Muhammad Saleem Sumbal, and Marko Torkkeli on topics like digital governance, fintech, and SME sustainability.
Professor Alexander Koller is a leading academic in Computational Linguistics at Saarland University's Department of Language Science and Technology. He holds a courtesy appointment in Computer Science and contributes to the Saarland Informatics Campus - one of Europe's premier computer science research centers. He leads the Computational Linguistics group and serves as speaker for the DFG-funded Research Training Group 'Neuroexplicit Models of Language, Vision, and Action'. PhD in Computer Science (Saarland University) Former positions: University of Potsdam, Columbia University, University of Edinburgh Sabbatical experiences: Meta AI (Paris), Allen Institute for AI (Seattle) His research focuses on computational modeling of meaning and reasoning in NLP, combining neural and symbolic approaches. Key contributions include semantic parsing systems like the AM parser and Alto, neurosymbolic models, and the GIVE Challenge for NLG evaluation. His recent work explores LLMs' limitations in problem-solving and compositional generalization. Recent publications highlight diverse applications across semantic parsing, dialogue systems, and LLM evaluation. Awards include ACL 2020 Best Theme Paper and multiple Outstanding Paper recognitions at ACL conferences. 2025 - AI Action Summit keynote speaker 2023 - ACL Outstanding Paper Awards 2022 - ELLIS Faculty appointment He maintains the DialogOS system for spoken dialogue development and teaches advanced computational linguistics topics. His group includes multiple postdocs and PhD students working across LLMs, dialogue systems, and semantic modeling.
Paul Boersma is a Professor of Phonetic Sciences at the University of Amsterdam within the Faculty of Humanities. His research explores how phonetic, phonological, and morphological phenomena emerge through computational modeling using artificial neural networks and Optimality Theory, with a focus on multi-level constraint interactions and distributional learning. University of Amsterdam Faculty of Humanities Phonetic Sciences Key research areas include: Computational Modeling : Simulations of phonological category emergence from phonetic data Optimality Theory : Gradual Learning Algorithm applications BiPhon Framework : Parallel bidirectional phonology/phonetics models Statistical Learning : Cross-situational and distributional learning mechanisms Recent publications emphasize: 2025: Inclusive speech recognition systems using Whisper model 2025: F0 ratio analysis for creaky voice diagnostics 2024: Prosodic clitics in child speech and checked tones in Shanghai Chinese 2023: Distributional learning in developmental language disorder contexts 2022: Substance-free phonological features and ghost segment phenomena He has also contributed extensively to the Praat software for phonetic analysis, with continuous updates since 1993.
Dan Nguyen, Ph.D., is a faculty member in the Department of Radiation Oncology at UT Southwestern Medical Center, where he is part of the Division of Medical Physics and Engineering. He is a founding member of the Medical Artificial Intelligence and Automation (MAIA) Laboratory, collaborating closely with Dr. Steve Jiang to advance AI applications in radiotherapy. His work focuses on deep learning for treatment planning, dose prediction, auto-segmentation, and adaptive radiotherapy. Ph.D. in Biomedical Physics, University of California, Los Angeles (UCLA), 2017 Mentor: Dr. Ke Sheng Faculty appointment at UT Southwestern since 2017 Dr. Nguyen’s research is centered on applying artificial intelligence to solve critical challenges in radiation oncology. His primary interests include deep learning-based dose prediction, auto-segmentation of anatomical structures, optimization of treatment plans, and real-time adaptive radiotherapy. He has pioneered work in direct aperture optimization, 4π radiotherapy, and uncertainty quantification in AI models. His research bridges the gap between AI innovation and clinical implementation, with a focus on improving plan quality, reducing planning time, and enhancing accessibility for less experienced clinicians. The most recent publications (2023–2025) demonstrate a consistent trend in developing fast, accurate, and robust deep learning models for radiotherapy. Key themes include dose prediction with transfer and meta-learning, adaptive segmentation using test-time optimization, uncertainty assessment in AI predictions, and mathematical modeling of radiotherapy-immunotherapy synergy. These works span high-impact journals in medical physics, AI, and oncology, reflecting interdisciplinary innovation. While no specific scientific awards are listed, Dr. Nguyen’s leadership in the MAIA Lab and extensive publication record in top-tier journals indicate significant recognition in the field of medical physics and AI in medicine. Dr. Nguyen has co-authored numerous studies involving mentoring and collaborative research, particularly with trainees and junior faculty in the MAIA Lab. His work is supported by institutional and likely federal funding, given the scale and scope of AI deployment studies. He has contributed to large-scale collaborative efforts such as OpenKBP-Opt, involving international teams evaluating knowledge-based planning pipelines. The MAIA Laboratory is a multi-investigator research group focused on innovating, developing, and applying artificial intelligence technologies to empower clinicians—especially those with less experience or limited resources—for improved patient care. The lab’s work spans machine learning, deep learning, reinforcement learning, and mathematical modeling in radiation oncology.
Ghassan AlRegib is the John and Marilu McCarty Chair Professor in the School of Electrical and Computer Engineering at Georgia Institute of Technology. He directs the Omni Lab for Intelligent Visual Engineering and Science (OLIVES), the Center for Energy and Geo Processing (CeGP), and previously led Georgia Tech's MENA initiatives (2015-2018). His research spans machine learning, image processing, and seismic interpretation with real-world applications in autonomous vehicles, medical imaging, and subsurface analysis. His research focuses on trustworthy AI systems through three pillars: enhancing interpretability, improving robustness/generalizability, and tackling domain-specific challenges. Key interests include human-in-the-loop frameworks, uncertainty quantification, explainable AI, and physics-driven learning. The OLIVES lab pioneered modern machine learning applications in seismic interpretation and developed open-source datasets for geological fault analysis. Dr. AlRegib's scientific contributions include over 270 publications, multiple U.S. patents, and leadership roles as Technical Program co-Chair for ICIP 2020/2024. His work demonstrates significant impact through awards like the IEEE Fellow designation (2022) and multiple best paper awards at premier conferences. IEEE Fellow (2022) 2023 EURASIP Best Paper Award 2019 ICIP Best Paper Award 2017 Denning Faculty Award for Global Engagement CSIP Research & Service Awards (2003) He has advised numerous PhD students including Dr. Ashraf Alattar (now Auburn professor) and Dr. Zhiling Long (Kennesaw State faculty). His lab structure emphasizes collaborative teams comprising postdocs, senior/junior PhD students, and undergraduates working on high-impact problems from autonomous systems to medical diagnostics. Current research thrusts include trustworthy neural networks, human-in-the-loop frameworks, and deployment of machine learning in seismic interpretation and ophthalmology.
Mark Crowley is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo , with a cross-appointment in the Cheriton School of Computer Science . He is actively involved in the Waterloo Artificial Intelligence Institute (WAII) , the Waterloo Institute for Complexity and Innovation (WICI) , and serves as National Secretary for the Canadian Artificial Intelligence Association (CAIAC) , coordinating the Canadian Conference on AI . Research interests span the theoretical and applied aspects of Reinforcement Learning , Deep Learning , Manifold Learning , and Ensemble Methods . His work addresses challenges in domains with spatial dynamics, multi-agent systems, and uncertainty, particularly in Computational Sustainability (forest fire management, sustainable forestry), Autonomous Driving , Medical Imaging , and Material Design . Recent research focuses on integrating causal modeling with generative representation learning to improve out-of-distribution robustness in motion forecasting applications. Key publications include foundational work on ChemGymRL environments for safe chemical process reinforcement learning, Generative Causal Representation Learning for robust forecasting, and collaborative work on multi-advisor reinforcement learning in multi-agent settings. He co-authored a textbook Elements of Dimensionality Reduction and Manifold Learning (Springer, 2023) with Prof. Ali Ghodsi and Prof. Fakhri Karray. Teaching includes graduate and undergraduate courses in Algorithm Design , Computational Intelligence , Reinforcement Learning , and Data Modeling at the University of Waterloo since 2018. His research group has produced several notable graduates including Benyamin Ghojogh (2021), who continued as a postdoc until 2022.
Laurie Williams serves as a Goodnight Distinguished University Professor in the Computer Science Department within the College of Engineering at North Carolina State University. She co-directs both the NCSU Secure Computing Institute and the NC State Science of Security Lablet, demonstrating deep institutional leadership in cybersecurity research. With over 260 refereed publications, her work establishes her as a prominent figure in software security academia. Her research spans critical areas including software security, agile development practices (particularly continuous deployment), software reliability, and software supply chain security. Williams focuses on practical security solutions addressing modern challenges like malicious dependencies in open-source ecosystems, AI-generated code vulnerabilities, and runtime protection mechanisms. Her work bridges theoretical security principles with industry-relevant applications. Recent publications reveal strong trends toward software supply chain security, with multiple 2024-2025 papers addressing vulnerability exploitability, malicious commit detection, and metrics-driven security control selection. Her research increasingly incorporates machine learning for threat detection while maintaining focus on human factors in secure development practices. IEEE Fellow (2018) National Science Foundation CAREER Award (2004) ACM SIGSOFT Influential Educator Award (2009) Multiple IBM Faculty Awards (2002-2012) NCSU Alumni Association Outstanding Research Award (2015-2016) Williams leads multiple major NSF-funded projects including the $5.7M SaTC Frontiers grant on secure software supply chains and the Science of Security Lablet with $3.6M in DoD funding. Her research emphasizes practical industry impact through collaborations with Cisco and Laboratory for Analytic Sciences. She actively mentors through the NCSU Research Leadership Academy and maintains significant educational outreach in software security. Her laboratory work centers on the Secure Computing Institute and Science of Security Lablet, where her team develops frameworks for vulnerability prediction, supply chain risk assessment, and secure development methodologies. Current projects focus on machine learning integrity, cognitive modeling for security decisions, and empirical analysis of build/deployment logs for anomaly detection.
Mark Jenkinson is a Professor of NeuroImaging at the University of Oxford's Nuffield Department of Clinical Neurosciences and also holds positions at the University of Adelaide's Australian Institute for Machine Learning and the South Australian Health and Medical Research Institute (SAHMRI). He heads the Structural Modelling and Analysis Group at the FMRIB Centre, where his research focuses on multimodal population modeling and structural brain segmentation. Education: DPhil in Robotics Research (University of Oxford, 1999) BSc (Hons I) in Mathematical Physics (University of Adelaide, 1994) BE (Hons I) in Electrical and Electronic Engineering (University of Adelaide, 1993) Professor Jenkinson's research spans two major themes: multimodal modeling of populations to describe disease processes and apply to individual patient diagnoses, and structural segmentation and analysis of brain anatomy and pathology, particularly focusing on sub-cortical structures and lesions. His work integrates advanced computational methods with neuroimaging to develop tools for understanding neurological disorders. As the developer of key components of the FMRIB Software Library (FSL), he has significantly contributed to standard neuroimaging analysis pipelines used worldwide. His recent publications demonstrate a strong focus on deep learning applications in neuroimaging, uncertainty quantification in medical AI, and advanced segmentation techniques. There's a clear trend toward developing more robust, anatomically plausible models that preserve topological structures while improving diagnostic capabilities for conditions like multiple sclerosis, Huntington's, and Parkinson's diseases. Scientific Awards: Highly Cited Researcher (Clarivate Analytics 2018-2021, Thomson Reuters 2014-2016) ISMRM Outstanding Teacher Award (2009, 2014) Teaching Excellence Award, University of Oxford (2012) David Phillips Fellowship from BBSRC (2005-2010) Professor Jenkinson has supervised over 25 doctoral students whose work spans brain segmentation, connectivity analysis, and clinical applications of neuroimaging. His research is supported by significant grants including the Medical Research Future Fund (AU$2m), Wellcome Trust Centre for Integrative Neuroimaging (£11m), and NIH Human Connectome Project (US$30m), reflecting the high impact and translational potential of his work. As head of the Structural Modelling and Analysis Group at FMRIB, Jenkinson leads a team developing the FSL (FMRIB Software Library), one of the most widely used neuroimaging analysis packages globally. His group collaborates extensively with clinical researchers on applications ranging from multiple sclerosis to traumatic brain injury, translating computational advances into clinical practice.
University of Illinois Urbana-ChampaignUnited States
Jodi Schneider is an Associate Professor at the University of Illinois Urbana-Champaign , with affiliate appointments at the Beckman Institute , Health Care Engineering Systems Center , European Union Center , and Center for Health Informatics . She directs the Information Quality Lab and focuses on the science of science through argumentation and evidence analysis. PhD in Informatics (National University of Ireland, Galway) M.S. in Library and Information Science (UIUC) M.A. in Mathematics (UT-Austin) B.A. in Liberal Arts (St. John's College) Her research examines how scientific controversies persist through citation patterns, the role of knowledge brokers in public policy, and information quality in biomedical contexts. She has developed semantic frameworks for micropublications and knowledge maintenance in digital libraries. Recent publications include citation integrity studies in Scientometrics , retraction indexing in STI Conference , and argumentation mining in Human Language Technologies . Collaborative projects span institutions like Harvard Radcliffe Institute and RWTH Aachen . NSF CAREER Award IMLS Early Career Award Senior Member, Association of Computing Machinery Marie Curie Fellow She advises graduate students in information quality and knowledge representation , with funding from the Alfred P. Sloan Foundation , NIH , and European Commission . Her lab develops tools to combat scientific misinformation and improve public health informatics .
