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Julie CaillerView profile

Associate Professor

• Automated Deduction
• Theoretical Computer Science
• Formal Methods
• +6 more

Julie Cailler is an Associate Professor at the University of Lorraine, affiliated with CNRS, Inria, and LORIA in Nancy, France. She is a member of the VeriDis Team and focuses on automated deduction, interactive proof systems, and logic in computer science. PhD in Theoretical Computer Science from the University of Montpellier (2023) Former Associate Professor at the University of Regensburg Her research interests include: Designing concurrent and parallel decision procedures for first-order logic Integration of automated and interactive theorem proving Proof system interoperability and formal verification Recent publications highlight her work on: SC-TPTP format extensions for sequent-based proofs (CADE-30, 2025) Graph Neural Networks for word equation solving (ATVA 2024, 2025) Deskolemization strategies in first-order logic (LPAR 25, 2024) Scientific recognition: Woody Bledsoe Award (2022) Best Newcomer Prover (CASCJ11, 2022) She supervises students in projects related to: Automated theorem prover development Logic programming and deduction modulo theory Formal verification and proof tool integration Julie is actively involved in academic service as: Co-head of GT LVP (Languages and Program Verification) working group PC member for major conferences like FMCAD, FSTTCS, and ITP

• Epidemiology
• Health Services
• Population Health
• +9 more

Maria Inacio is a Research Professor at Flinders University's College of Nursing and Health Sciences and serves as the Director of the Registry of Senior Australians (ROSA) at SAHMRI and Flinders' Caring Futures Institute. She holds a NHMRC Emerging Leadership 2 Fellow and has trained at the Dartmouth Centre for Evaluative Clinical Sciences (MS 2002) and University of California, San Diego (PhD 2013). Her career includes 11 years at Kaiser Permanente developing orthopaedic registries before returning to Australia to establish ROSA. Research Focus : Population health surveillance systems, registry science, and health services research in aged care. She specializes in leveraging existing data to monitor quality/safety in aged care, reducing unwarranted care variations, and improving surgical outcomes. Her work has informed federal policy reforms, including contributions to Australia's Royal Commission on Aged Care. Article Trends : Recent publications emphasize geriatric orthopaedic outcomes data linkage methodologies UV disinfection in infection control mental health-surgery intersections economic evaluations of rehabilitation programs frailty intervention strategies Scientific Recognition : Stanford/Elsevier Top 2% Most Cited Scientist (2022) Hospital Research Foundation Mid-Career Fellow (2020-2023) Australian Academy of Health and Medical Science Mentee (2019-2023) National and international awards including SA Young Tall Poppy Science Award (2020) and US Orthopaedics Research Foundation Clinical Research Award (2018) Leadership : Principal investigator for NHMRC/MRFF grants, editor of Clinical Orthopaedics and Related Research, and former Deputy Medical Editor of the Medical Journal of Australia. She co-leads the ROSA team, which has delivered critical reports to federal health agencies.

Dominik MoritzView profile

Professor

• Data Visualization
• Human-Computer Interaction
• Interactive Systems
• +3 more

Dominik Moritz is a Professor at Carnegie Mellon University's Human-Computer Interaction Institute and concurrently serves as an ML Researcher at Apple. He co-leads the Data Interaction Group, focusing on building interactive visualization systems. His educational background includes a PhD from the University of Washington's Paul G. Allen School and a B.S. from Hasso Plattner Institute. Moritz's research spans interactive visualization systems , scalable data analysis tools , and accessibility-focused design . His work combines database technologies with human-computer interaction to create frameworks like Mosaic for cross-filtering billion-record datasets and Draco for visualization constraint modeling. Projects include Vega-Lite (high-level visualization grammar) and Swift Charts (Apple's charting framework). His publications consistently explore scalability in visualization , perceptual accuracy in data representation , and accessibility tooling , with recent work emphasizing real-time interaction with massive datasets. Awards include multiple Best Paper recognitions at VIS/InfoVis. Fulbright Program German National Academic Foundation Scholar Best Paper Honorable Mention (VIS 2023 ×2) Best Paper (InfoVis 2018) Best Paper (InfoVis 2017) SIGGRAPH Invitation (2016) Moritz mentors PhD students through the Data Interaction Group and has collaborated with Google Research, Microsoft Research, and Open Knowledge Foundation. His systems are widely adopted in Python/JavaScript data science communities.

Margunn AanestadView profile

Professor

• Digital Transformation
• e-Health
• Information Systems
• +6 more

Margunn Aanestad is a Professor in Digital Innovation at the Department of Informatics (IFI), Faculty of Mathematics and Natural Sciences, University of Oslo (UiO). With 25 years of research experience focused on healthcare digitalization, she examines how digital technologies transform organizations and societies at multiple analytical levels. Her work spans healthcare information systems, digital innovation, and information infrastructures across the Nordic region and internationally. Her research interests center on understanding digital transformation through a sociotechnical lens, particularly examining how work practices evolve when based on digital monitoring rather than physical visits, how organizations become 'data-driven' through advanced analytics, and how sector-level ecosystems require new technical and regulatory solutions for data sharing. She investigates information infrastructures as interconnected systems rather than isolated technologies, working at the intersection of Information Systems (IS), Computer Supported Cooperative Work (CSCW), Science and Technology Studies (STS), and organizational theory. Her empirical work primarily focuses on healthcare digitalization, including patient records, collaboration solutions, patient portals, digital home monitoring, and emerging AI applications for personalized medicine. Professor Aanestad leads research within the Digital Innovation (DIN) group at UiO and has been involved in significant projects including KINT (From local breakthroughs in knowledge to integration into medical practice) and CORPUS (New competence requirements in the public sector: The consequences of digitalization for work with different degrees of specialization). She previously held a Professor II position at the University of Agder (2019-2022) and maintains active collaborations with NTNU, BI Norwegian Business School, Diakonhjemmet Hospital, and Copenhagen Business School. Her publication record demonstrates consistent high-impact contributions across information systems, healthcare innovation, and digital governance. Recent work explores critical perspectives on digital solutionism, data governance spaces for personal health information, and the sociotechnical dimensions of implementing data infrastructure in public sectors. She examines how digital technologies create both opportunities for innovation and complex challenges related to governance, inclusion, and sustainability. Professor Aanestad's educational background includes engineering degrees in medical technology (1992) and technical sciences (1994) from Stavanger University College. Before joining UiO as a PhD student in 1998, she worked as a department engineer at Rikshospitalet and as a senior engineer at Telenor. Her career trajectory reflects deep engagement with both technical implementation and theoretical understanding of digital transformation processes.

• Circular strategies
• Sustainable production
• Asset management
• +13 more

Mirka Kans is an Associate Professor at the Department of Supply and Operations Management within the School of Business, Economics and Law at Chalmers University of Technology. Her research focuses on circular strategies and sustainable production, asset management and maintenance, and industrial automation and digitalization. Her work spans several key research areas including predictive maintenance, digital tools for data-driven maintenance and effective decision-making, digital maturity and digital transformation, and Industry 4.0/5.0 applications for both industrial systems and infrastructure. She employs various modeling approaches such as information modeling, business modeling, and ecosystem modeling in her research methodology. Mirka also maintains a strong interest in educational and competence development within these fields. Her publication record shows a pronounced focus on circular economy applications across multiple industries, particularly furniture and wood products, with significant contributions to understanding remanufacturing potential and sustainable business models. She has conducted extensive empirical research on digital transformation in maintenance practices, with particular attention to the Swedish maintenance ecosystem and infrastructure sectors like gravel roads. READY2 (2025-2027): Sustainable, robust and resource-efficient wood manufacturing industry with dynamic maintenance (VINNOVA) READY (2024-2025): Sustainable, robust and resource-efficient sawmill industry with dynamic maintenance CirkuTrä (2023-2028): Strategies for increased circularity in the wood processing industry RE:Furn (2023-2026): Efficient remanufacturing of furniture used in public environments She collaborates extensively with researchers including Jaime Campos, Chamirangika Madushani Hetti Arachchige, Dan Paulin, and Malin Löfving, producing interdisciplinary work that bridges theoretical frameworks with practical industrial applications across multiple sectors including manufacturing, infrastructure, and transportation.

• Programming Languages
• Theory of Computation
• Decentralized Finance (DeFi)
• +3 more

Omry Ross is an Associate Professor at the Department of Computer Science, University of Copenhagen. His research focuses on Programming Languages and Theory of Computation, with significant contributions to decentralized finance (DeFi), blockchain technology, and algorithmic governance. Research Interests: Decentralized Finance (DeFi) and Smart Contract Systems Blockchain Protocol Design and Cryptoeconomics Programming Language Theory and Formal Verification Token Governance in Decentralized Autonomous Organizations (DAOs) Algorithmic Game Theory and Market Mechanisms Recent publications highlight his work in AI moderation of online communities, compliance reporting in DLT systems, and MEV optimization in multi-block scenarios. His research bridges theoretical computer science with practical applications in financial cryptography. Scientific Awards: Nasdaq Nordic Foundation Grant (2021) Omry Ross collaborates extensively with researchers in blockchain and DeFi, including contributions to the Financial Cryptography and Data Security workshops.

• Legal Technology
• Artificial Intelligence in Law
• Legal Informatics
• +3 more

David Colarusso serves as Lecturer and Director of the Legal Innovation and Technology Lab at Suffolk University Law School, where he bridges legal practice with technological innovation. His multidisciplinary background spans public defense, data science, software engineering, and secondary education, with current focus on leveraging technology to enhance access to justice. His educational foundation includes a BA from Cornell University, MEd from Harvard Graduate School of Education, and JD from Boston University Law School. This diverse training informs his unique approach to legal technology challenges. Colarusso's research centers on AI-driven legal applications , accessible court form design , and algorithmic bias detection in legal systems. He pioneered QnA Markup—a programming language specifically for legal professionals—and investigates how machine learning can improve legal document automation while ensuring equitable access. His work consistently addresses the human-technology interface in justice systems. Recent publications reveal strong interdisciplinary trends, with 85% focusing on AI applications in legal contexts and 70% addressing accessibility issues. These works span law, computer science, and human factors research, demonstrating how technical solutions can solve concrete legal access problems. His contributions have earned significant recognition within the legal innovation community: ABA Legal Rebel designation Fastcase 50 Honoree ABA Top Legal Tweeter (2017) Award-winning legal hacker status As Lab Director, Colarusso leads initiatives developing open-source legal technology tools through collaborations with courts, legal aid organizations, and multidisciplinary teams. The LIT Lab's projects emphasize user-centered design principles and open standards to create sustainable solutions for justice system modernization, particularly focusing on vulnerable populations' access to legal resources.

Yuvraj AgarwalView profile

Professor

• Systems and Networking
• Embedded Systems
• Mobile Computing
• +4 more

Yuvraj Agarwal is a Professor at Carnegie Mellon University's School of Computer Science, where he founded and directs the SYNERGY Lab. He previously served as Executive Director of the NSF Expeditions in Variability (2010-2013) and was affiliated with UCSD's Microelectronic Embedded Systems Lab (MESL) and Systems and Networking Group (SysNet). Research Themes : Systems & Networking, Embedded Systems, Mobile Computing, with focus on energy efficiency and privacy. Leadership : Director of SYNERGY Lab, Co-PI in NSF CoDec expedition, Brick Consortium member. His research bridges hardware-software systems with societal impact, including smart building energy optimization using occupancy sensing, mobile privacy tools like ProtectMyPrivacy, and IoT security labeling frameworks . Recent work includes the Computational Decarbonization NSF expedition ($12M over 5 years) to reduce carbon footprints in societal infrastructure. Scientific Awards : 2024: Promoted to Full Professor 2012: UCSD Outstanding Faculty Award for Sustainability 2016: Google Faculty Research Award Advising : Guided 11 PhD students to completion (now in academia/startups) and mentored 10+ MS/undergraduate researchers. Current advisees include 4 PhD students in Carnegie Mellon's Societal Computing program. Grants : NSF Expeditions in Variability (2010-2013), NSF #1564009 (2016), NSF #1526237 (2015), NSF #1513957 (2015), DARPA BRANDEIS program (2015), and Google research funding (2015). Labs & Collaborations : SYNERGY Lab at CMU focusing on IoT and smart campus systems. Key collaborations with the Brick Consortium (Johnson Controls, Schneider Electric), Microsoft Research, Intel Research, and academic institutions including UCSD and UMass Amherst.

Marco Antonio CasanovaView profile

Professor

• Database Systems
• Conceptual Modeling
• Semantic Web
• +5 more

Marco Antonio Casanova is a Full Professor at the Department of Informatics and Coordinator of the Central Planning and Evaluation Office of the Pontifical Catholic University of Rio de Janeiro (PUC-Rio). He has held significant leadership positions at PUC-Rio including Graduate Program Coordinator (2005-2007) and Director of the Department of Informatics (2007-2011). His research interests concentrate on database conceptual modeling, construction of database management systems, and applications of Large Language Models. Dr. Casanova's work focuses on technologies that facilitate the dissemination and interpretation of data on the Web, with particular emphasis on techniques for designing databases to facilitate interoperability. His academic journey began with a degree in Electronic Engineering from the Military Institute of Engineering (1974), followed by an M.Sc. in Informatics from PUC-Rio (1976), and culminated with an M.Sc. (1978) and Ph.D. (1979) in Applied Mathematics from Harvard University. His recent publications (2023-2025) demonstrate a strong focus on the intersection of Large Language Models with database technologies, particularly in developing advanced Text-to-SQL and Text-to-SPARQL systems. His research spans both theoretical database concepts and practical applications across various domains including engineering, healthcare, and cultural heritage. Dr. Casanova has been particularly active in exploring how LLMs can enhance traditional database query interfaces while addressing real-world challenges in complex database environments. Scientific Recognition: Recipient of the Scientific Merit Award from the Brazilian Computer Society (2012) CNPq Level 1B Productivity Grant recipient Dr. Casanova maintains an active research program with numerous collaborations across Brazil and internationally. His work bridges theoretical database research with practical applications, particularly in the evolving landscape of AI-enhanced database systems. He has contributed significantly to the field of semantic technologies, knowledge graphs, and natural language interfaces to databases, with a recent emphasis on leveraging Large Language Models to solve longstanding database interoperability challenges. His laboratory and research team at PUC-Rio focus on developing innovative approaches to database management that incorporate cutting-edge AI techniques while maintaining strong theoretical foundations in database systems.

• Catalysis
• CO₂ Valorization
• Kinetic Modeling
• +4 more

Dr. Sofia Angeli is a Group Leader at the Institute of Catalysis Research and Technology (IKFT), Karlsruhe Institute of Technology (KIT), Germany, since March 2024. Previously, she held roles as Senior Scientist/Group Leader (2021–2024) and Postdoctoral Researcher (2017–2019) at KIT. Her research focuses on catalysis for energy transition, CO₂ valorization, kinetic modeling, and digitalization of catalytic processes. She leads interdisciplinary projects integrating experimental and computational methods to advance sustainable chemical processes. PhD in Chemical Engineering (2016): Aristotle University of Thessaloniki, Greece. Thesis: Hydrogen production via intensified methane steam reforming processes. M.Sc. in Advanced Materials (2012): Aristotle University of Thessaloniki. Diploma in Chemical Engineering (2009): Aristotle University of Thessaloniki. Research Interests : Sofia’s work spans kinetic modeling, CO₂ conversion, catalytic pollutant removal, and digital tools for catalysis research. She develops novel catalysts for methane reforming and designs data management systems like Adacta and CaRMeN to streamline reaction mechanism analysis. Her projects often address industrial challenges in emissions reduction and renewable energy. Her recent publications emphasize catalytic processes for energy sustainability (e.g., methane oxidative coupling) and automated modeling frameworks. She collaborates widely, contributing to journals like Chemical Engineering Journal and ACS Catalysis . Advising & Teams : As a Group Leader, she oversees researchers in catalysis and data-driven processes. Her team works on cutting-edge projects supported by KIT’s infrastructure and interdisciplinary networks. Labs/Teams : Active in the IKFT and the Deutschmann Group, focusing on catalyst design and process intensification.

Wen LiView profile

Assistant Professor

• Software Security
• Software Engineering
• Network Security

Wen Li is an Assistant Professor at the School of Computing , Utah State University. Their research focuses on software security , software engineering , and network security , with significant contributions to analyzing multilingual software systems. Recent work highlights include: Characterization of multilingual software and language selection patterns Security analysis of cross-language interactions and runtime vulnerabilities Development of fuzzing frameworks like Pyrtfuzz and POLYFUZZ Investigation of dynamic information flow and memory management in complex systems Research trends demonstrate expertise in software testing, language interoperability, and security verification across programming environments.

Sai Mounika ErrapotuView profile

Assistant Professor

• Cybersecurity
• Privacy Preservation
• Smart Grid Security
• +6 more

Sai Mounika Errapotu is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Texas at El Paso (UTEP). She leads the Cyber Physical Systems Privacy and Security Enhanced Computing (CyPSEC) Lab, focusing on developing practical security and privacy solutions for hardware and software systems in distributed networks, IoT, and smart grids. Her research integrates cryptography, differential privacy, and optimization to address emerging challenges in cyber-physical systems. Education: Ph.D. in Electrical and Computer Engineering (University of Houston, 2018), B.Tech. in Electronics and Communication Engineering (Jawaharlal Nehru Technological University, 2013). Postdoctoral work: AI, Networking Technologies, and Security Lab, University of Houston (2018–2019). Her research interests span cybersecurity, privacy-preserving protocols, trust modeling, and optimization in smart grids, IoT, and wireless networks. She emphasizes application-specific solutions that balance security, privacy, and scalability. Recent articles highlight advancements in intrusion detection via GANs and neural networks, smart home IoT security protocols, and privacy-preserving techniques in healthcare and transportation systems. Major Grants: $782,500 ARL grant for GAN-based intrusion detection, $1.1M DOE NNSA consortium for power systems, and $140K PNNL grant for healthcare synthetic data. Awards: Miguel Izquierdo Teaching Excellence Award (2021), Rising Stars Award, and Best Dissertation Award (2018). Advising highlights include mentoring students like Humaira (CPS Rising Star), Nicholas Lopez (M.S. grad in IoT security), and Ismael Holguin (LLNL intern). The CyPSEC Lab actively publishes in IEEE and NAPS conferences, addressing vulnerabilities in protocols like DNP3 and smart home IoT systems. Labs/Teams: CyPSEC Lab focuses on bridging theory and practice in CPS security, collaborating with industry partners and national labs.

James H. Cross IIView profile

Professor

• Software Engineering
• Computer Science
• Program Visualization
• +3 more

James H. Cross II is a Professor in the Department of Computer Science and Software Engineering at Auburn University's College of Engineering, with prior affiliations at the University of Nevada Las Vegas' Business School and Drexel University's College of Medicine. His research focuses on software engineering education, program visualization, reverse engineering, and educational technology. Key Roles : Software Engineering Educator, Java Pedagogy Innovator, Program Visualization Researcher His work emphasizes enhancing code comprehension through dynamic data structure visualizations (e.g., jGRASP IDE), reverse engineering methodologies, and interdisciplinary applications in software maintenance and curriculum development. Recent trends in his publications (2019–2024) include FAIR data principles, ontological frameworks, and token-based incentives for scholarly contributions. Notable collaborations include T. Dean Hendrix, Larry A. Barowski, and David A. Umphress. Affiliated with institutions like Auburn University, University of Nevada Las Vegas, and Drexel University's College of Medicine, his career spans software engineering research, educational tool development, and academic leadership.

• Quantum Information Theory
• Quantum Optics
• Quantum Computing
• +3 more

Dr. Daniel Malz is an Assistant Professor at the Department of Mathematical Sciences, University of Copenhagen. His research focuses on quantum many-body systems, quantum optics, and quantum computing, with affiliations to research groups QA, QMATH, and QfL. His work bridges theoretical physics and mathematical modeling, addressing topics like superradiance, entanglement dynamics, and quantum state preparation. Key research interests include quantum information theory, non-Markovian dynamics, and the development of efficient quantum simulation techniques. His recent publications explore advanced topics such as photonic cluster states, tensor network simulations, and cross-platform quantum network verification. Much of his work addresses foundational questions in quantum mechanics while maintaining practical relevance for quantum technologies. His contributions span both theoretical derivations and numerical methods, with a focus on bridging classical and quantum many-body dynamics.

Anna RogersView profile

Associate Professor

• Natural Language Processing
• Artificial Intelligence
• Machine Learning
• +4 more

Anna Rogers is an Associate Professor of Data Science at the IT-University of Copenhagen , affiliated with the NLPnorth research group. Her work focuses on Natural Language Processing (NLP) , Artificial Intelligence , and Large Language Models (LLMs) , with a particular emphasis on ethical data use, peer review innovation, and transformer model analysis. She leads projects addressing AI transparency, medical QA hallucinations, and generative AI applications. Her research explores topics including: LLM behavior and evaluation Data governance in NLP Peer review systems optimization Transformer model robustness Medical AI applications Key Projects : PlagAIrism : Tracking LLM training data origins Pioneer Centre for AI : Pre-registered replication studies TinyGPT : Efficient NLP models AIInterviewer : Large-scale qualitative data collection Publications span ACL , EMNLP , and specialized NLP workshops, addressing topics from BERT analysis to AI content farms.