Yasmina Abdeddaïm is an Associate Professor at Université Gustave Eiffel and affiliated with ESIEE Paris. She works within the Laboratoire d'Informatique Gaspard-Monge (Softwares, Networks and Real-time team) and serves as Head of the Master in Artificial Intelligence and Cybersecurity (AIC) program. Her research focuses on real-time systems, critical systems, and scheduling algorithms. University: Université Gustave Eiffel Role: Head of Master AIC program Laboratory: Laboratoire d'Informatique Gaspard-Monge Team: Softwares, Networks and Real-time Her research spans real-time systems , mixed-criticality scheduling , energy-harvesting systems , and probabilistic schedulability . Recent publications analyze compilation optimization impacts on timing variability and propose new models for real-time deep neural networks over GPUs. She employs formal methods like timed automata for scheduling verification. Her teaching includes courses on Real-time Systems , Model Checking , Critical Application Development , and Artificial Intelligence . She is based at Cité Descartes, Champs-sur-Marne, France, with office contact details provided.
Rüdiger Lunde is a Professor at Technische Hochschule Ulm , currently serving as Dean of Studies for Information Systems since September 2019. He previously chaired the Examination Board for programs including INF, CTS, TI, ICS, DSM, MD, and IS from 2014 to 2019. His primary research areas include Software Engineering , Intelligent Systems , and Model-Based Systems Engineering , with a focus on automated safety analysis and technical system simulation. Current Role: Dean of Studies for Information Systems Prior Role: Chair of Examination Board (2014–2019) His research leverages the smartIflow framework for safety tasks such as Failure Mode and Effects Analysis (FMEA) and Fault Tree Analysis (FTA). He has contributed to formal verification methods using Computation Tree Logic (CTL) and explored temporal reasoning across varying time scales. Recent trends in his work include: Automated safety analysis in technical systems Integration of SysML for artifact generation Model decomposition techniques for complex systems Scientific awards: Best Paper Award at International Workshop on Applications in Information Technology (IWAIT-2015) Contact: Ruediger.Lunde@thu.de | Room: A306a | Consultation hours: By appointment via email.
Marianna Nicolosi Asmundo is an Associate Professor of Mathematical Logic (MAT/01) at the Department of Mathematics and Computer Science (DMI) of the University of Catania. She earned her PhD from the same university in 2003 and serves as a proposing member of CINUM - Interdepartmental Center for Humanistic Computing. Teaches undergraduate and graduate programs in Mathematics Master's Degree Programs in Computer Science Textual Sciences for Digital Professions (Department of Humanities) Her research spans automatic deduction, tableaux-based deductive systems, decision procedures in elementary set theory and non-classical logic, interactive theorem proving, knowledge bases, ontologies, and reasoning services for the semantic web. Recent publications emphasize ontology interoperability, blockchain-based knowledge representation, and set-theoretic reasoning frameworks. She contributes to ontologies for cultural heritage (Saint Gall monastery modeling, archaeological Sicilian landscapes) and blockchain applications. Collaborates extensively with researchers like D. Cantone and D.F. Santamaria on description logic systems. Active member of CINUM - Interdepartmental Center for Humanistic Computing Supervises thesis projects on semantic web and blockchain ontologies
Kinan Dak Albab is an Assistant Professor at the Faculty of Computing and Data Sciences (CDS) at Boston University, where he joined in summer 2024. His research spans systems, cryptography, and programming languages, focusing on building practical tools for data privacy and compliance-by-construction. He has developed influential systems such as Sesame, K9db, and DP-PIR, which have been published in top venues like SOSP, OSDI, and USENIX Security. PhD in Computer Science, Brown University MS in Computer Science, Boston University (2020) BS in Computer Science, American University of Beirut (2015) Kinan's research centers on data privacy , secure computation , and systems security . He designs tools that allow developers to build applications that are privacy-compliant by construction. His work leverages systems design, cryptographic protocols, and language-level enforcement to reduce developer burden while ensuring strong privacy guarantees. He is particularly interested in GDPR compliance, private information retrieval, and usability of secure systems. His publications span high-impact areas including end-to-end privacy enforcement (Sesame), database systems with built-in privacy (K9db), and efficient private information retrieval (DP-PIR). These works combine systems performance with strong theoretical foundations, enabling real-world deployment in domains like wage gap analysis and public policy. Presidential Award for Excellence in Teaching, Brown University (2025) Teaching Excellence Award, Boston University (2020) Vivli and Microsoft datatheon Outstanding Graduate Submission (2019) Hariri Institute Graduate Fellow (2017–2020) Mark Sawaya Excellence Award, AUB (2015) 1st Place, ACM Lebanese Collegiate Programming Contest (2015) Kinan has advised and collaborated on real-world secure computation deployments, including a project with the Boston Women's Workforce Council and the Greater Boston Chamber of Commerce to measure wage gaps across over 100 companies. His work contributed to the formation of the startup nthparty and has been cited in the White House’s National Strategy on Privacy-Preserving Data Sharing, the UN Handbook on Privacy-Preserving Computation, and the European Commission’s report on Technological Enablers for Privacy. He is the lead developer of the JIFF framework for secure multi-party computation on the web and has created tools like Carousels for resource estimation in secure programs. He leads the ETOS group and is affiliated with multiparty.org , an initiative focused on advancing privacy-preserving technologies through open-source tools and real-world applications.
Jie Ding is an Associate Professor at the University of Minnesota's School of Statistics with graduate faculty appointments in Electrical Engineering, Computer Science, and the Data Science Program. He serves as a core faculty member of the Data Science and AI Hub and holds an Amazon Scholar position with the Amazon AGI Team focusing on foundation model training. His educational background includes a Ph.D. in Engineering Sciences from Harvard University (2017), postdoctoral work at Duke University (2018), and a B.S. from Tsinghua University where he participated in both the Math & Physics Academic Talent Program and Electrical Engineering program. Ding's research sits at the intersection of artificial intelligence, statistics, and scientific computing, with focus areas including Agentic AI for autonomous data science workflows, AI Foundations for interpretability and trustworthiness, Scalable Modeling for broader AI accessibility, Decentralized and Collaborative AI systems, and AI Safety addressing privacy and security concerns. He developed the STAT 8931 Generative AI course with open-source materials available at genai-course.jding.org . His recent publications demonstrate strong activity across multiple AI subfields, particularly in value alignment (MAP framework), AI safety mechanisms, federated learning innovations, and statistical foundations for modern AI systems. The breadth of venues (ICML, ICLR, NeurIPS) indicates significant impact across the AI research community. NSF CAREER Award (2024) Army Early Career Program (Young Investigator) Award (2023) Cisco Research Award (2022-25) AWS Cloud Credits for Research (2021-22) Meta/Facebook Faculty Research Award (2021-22) UMN Thank-A-Teacher Teaching Award (2019-20) Ding leads the Agentic AI for Data Science Benchmark initiative, collaborating with University of Minnesota colleagues and Minnesota industry partners to evaluate AI agent capabilities across healthcare, insurance, retail, energy and other sectors. His research group actively recruits PhD students interested in AI/Statistics intersections, with focus on developing theoretically grounded yet practically impactful AI systems.
Nadia Naffi is an Assistant Professor in the Department of Teaching and Learning Studies at the Faculty of Education, Laval University, where she also holds the Chair in Educational Leadership (CLE) on innovative teaching practices in a digital context funded by National Bank. She serves as Co-head of the Education and Empowerment axis of the International Observatory on the Societal Impacts of AI and Digital Technology (OBVIA), and has held leadership roles including chairing the first integration of the Institutional Committee for Innovation in Teaching at Laval University. Naffi's research focuses on digital empowerment in the face of AI risks, with particular emphasis on combating disinformation, deepfakes, and cyber scams through educational strategies. Her work spans multiple domains including educational technology, AI ethics, media literacy, and digital resilience across different age groups from youth to seniors. She has developed innovative approaches to designing inclusive learning experiences that harness AI and digital technologies in ethical, critical, and responsible ways. Her recent publications reveal a clear trend toward addressing societal challenges posed by generative AI, with particular focus on deepfakes, disinformation, and cyber resilience. The research spans educational settings, healthcare contexts, and broader societal implications, demonstrating an interdisciplinary approach that connects technical understanding with pedagogical innovation and policy development. Her work consistently emphasizes the human dimension of technology adoption and the need for critical digital literacy across all age groups. Concordia Public Scholar (2017-2018) Winner of SSHRC 'I have a story to tell' competition Winner of ACFAS 'My Thesis in 3 minutes' competition President's Media Outreach Award (2016-2017) Governor General of Canada Gold Medal – Person and Society 2018 2019 SALTISE Award for Teaching Excellence and Innovation John F. Lemieux Young Alumni Medal Naffi has secured significant research funding including a $425,000 National Bank Teaching Leadership Chair and multiple grants from SSHRC, FRQSC, and other organizations totaling over $1.5 million. Her research projects address critical issues such as seniors' cyber resilience against deepfakes, AI-health transformation, digital inequalities during pandemic, and educational responses to disinformation. She has also developed practical resources including bilingual guides for online course transition and the 'Abécédaire de l'IA' educational tool. As Co-head of OBVIA's Education and Empowerment axis, Naffi leads a multidisciplinary team focused on understanding and addressing the societal impacts of AI through education. Her work connects academic research with practical applications through collaborations with government agencies, educational institutions, and community organizations. The Digital and AI Bootcamp she developed represents one practical initiative bringing together educational advisors to explore innovative digital technologies including virtual reality and AI in teaching contexts.
Jack Powers serves as Professor and Chair of Media Arts, Sciences and Studies at Ithaca College's Roy H. Park School of Communications, where he teaches entertainment media business and researches children's media effects. With extensive industry experience including film production and network consulting, he bridges academic theory with professional practice. His educational background includes: PhD in Mass Communications (Media & Behavior concentration) from Syracuse University MA in Journalism/Mass Communication from The Ohio State University BA in Communications and French from University of Mount Union Powers' research spans entertainment industry dynamics, media effects on children, and emerging media technologies. His work examines Hollywood entry strategies, streaming economics, documentary ethics, and digital behavior patterns - particularly how new technologies impact dating, adolescent development, and social discourse. He emphasizes practical application through industry connections and production experience. His recent publications reveal evolving focus from children's media effects toward industry business models and technology impacts, with increasing attention to ethical implications of social media, streaming disruption, and production innovation. Current scholarship addresses writers' room pedagogy and filmmaking's technological transformation. Powers actively integrates professional practice into academia, currently producing a $1 million feature film employing Park School students. His teaching philosophy emphasizes "learning is doing" through required LA internships, London study abroad, and hands-on production via ICTV's 20+ television shows. He maintains direct industry access through regular Hollywood consulting for major networks and production companies. He oversees student development through extensive industry connections, with alumni employed at Disney, ESPN, MLB Network, HBO, Netflix, and numerous major productions. Personal media interests include Taylor Sheridan works, Game of Thrones, and directors like Tarantino and Scorsese, reflecting his professional engagement with contemporary media trends.
Prof. Dr. Thomas Farrenkopf is a full-time Professor in the Department of Business Informatics at the Technische Hochschule Mittelhessen , serving as Dean of Studies . He leads the Business Informatics Bachelor program and specializes in digitalization, multi-agent systems, and AI-driven decision support. Expertise Areas : Industry 4.0, Smart Factory, Semantic Web, full-stack software development Contact : thomas.farrenkopf@mnd.thm.de Research Focus : His work bridges knowledge-based methods with practical applications in artificial intelligence, particularly through multi-agent systems for traffic modeling and business simulations. He developed AGADE Traffic (a knowledge-based traffic simulator) and ATHOS (a domain-specific language for multi-agent simulations), focusing on scalability and complexity reduction. Recent studies explore individual preferences' impact on traffic policies and agent-based feedback mechanisms in business contexts. Academic Contributions : With over 15 publications since 2013, his research spans agent-based modeling, semantic web applications, and smart manufacturing - notably improving throughput times in toolmaking by 90% through Industry 4.0 implementations. Teaching & Supervision : Actively supervises Bachelor's Practical Projects (BPP), providing guidance for internship-related academic work through structured evaluation processes and electronic reporting systems. Collaborations : Works with international researchers like Johannes Nguyen, Simon T. Powers, and Michael Guckert, publishing in venues such as SN Computer Science , Lecture Notes in Computer Science , and Journal of Artificial Societies and Social Simulation .
Jeffrey R. O'Connell, DPhil is an Associate Professor in the Department of Medicine at the University of Maryland School of Medicine, with a secondary appointment in Epidemiology & Public Health. He has held his position at the University of Maryland since 2002, initially as an Assistant Professor (2002-2008) before being promoted to Associate Professor in 2009, a position he continues to hold. Additionally, he maintains a research appointment at the USDA Animal Genetics Improvement Laboratory where he has worked since 2007. Dr. O'Connell's educational background includes a BS in Mathematics from the University of Delaware (1979), an MS in Mathematics from Drexel University (1984), an MS in Computer Science from Drexel University (1993), and a D.Phil in Mathematical Biology from Oxford University (2000). His academic journey reflects a strong foundation in mathematics and computational methods that underpins his research career. Dr. O'Connell's research focuses on developing, implementing and applying methods to analyze genomic data in large pedigree and population data. His primary area has been human genetics, which expanded to animal genetics in 2007 with his appointment at the USDA Animal Improvement Laboratory. He is the developer of MMAP (Mixed Models for Analysis of Pedigree/Populations), a comprehensive software package implementing analysis options for genome-wide association, variance components estimation, linkage analysis, genotype imputation, genomic prediction, haplotyping, and mega analysis. His work extensively utilizes large pedigree data such as the Old Order Amish and Holstein cattle. Dr. O'Connell collaborates with numerous research consortia including the Genetics of Liver Disease (GOLD), the Genetic Factors for Osteoporosis (GEFOS), the Cohorts of Heart and Aging Research in Genetic Epidemiology (CHARGE) musculoskeletal, adiposity, and lipid groups, and the Gene-by-Lifestyle Interaction consortium. He is also a member of the TOPMed whole genome sequencing effort and has been heavily involved in developing analytical tools for cloud-based computing to run genome-wide association and rare variant analysis, generalized linear mixed models for binary and threshold traits, and multi- and correlated trait models for analysis of large omics data sets. His research has resulted in numerous high-impact publications spanning statistical genetics, genomic analysis methods, and applications to both human and animal genetics. His work bridges computational methodology development with practical applications in genetic epidemiology and animal breeding.
Dr. Shravan Ravi Narayan is an Assistant Professor in the Computer Science department at The University of Texas at Austin. His research focuses on secure systems, program verification, and hardware-based security, with groundbreaking work in Software Fault Isolation (SFI), WebAssembly security, and Spectre attack mitigation. He teaches courses like CS361S (Network Security and Privacy) and CS380S (Theory and Practice of Secure Systems). 2023 - Distinguished paper award at ASPLOS 2022 - Mozilla research award 2022 - IEEE Cybersecurity Award for Practice 2022 - NSA Best Scientific Cybersecurity Paper Honorable Mention 2021 - Google V8 research award His publications highlight innovations in hardware-assisted isolation (HFI), sandboxing runtime design (WaVe), and browser security frameworks like RLBox. His work bridges systems security, programming languages, and hardware architecture to create practical, verifiable security solutions. He actively recruits exceptional PhD candidates with expertise in security, programming languages, or computer architecture and collaborates with industry leaders like Firefox and Fastly.
Dr. Tanushree Roy serves as an Assistant Professor in the Department of Mechanical Engineering at Texas Tech University's Whitacre College of Engineering and is an Affiliate Faculty member at the National Wind Institute. Her research pioneers resilient human-centric smart city infrastructures through the integration of control theory, mathematical modeling, and machine learning to address critical challenges in safety, security, and resource optimization for urban systems. Her academic foundation includes: Ph.D. in Mechanical Engineering from The Pennsylvania State University (2022) M.S. in Mathematics from University of Central Florida (2015) M.E. in Electrical Engineering from Indian Institutes of Engineering Science and Technology, India (2011) B.Tech in Applied Electronics and Instrumentation from Maulana Abul Kalam Azad University of Technology, India (2009) Dr. Roy's research centers on cybersecurity , fault diagnostics , and socio-technical systems with specialized applications in smart transportation networks and battery energy storage systems. She develops innovative frameworks that merge human-centric sensing with technical measurements to combat cyberattacks and physical faults in cyber-physical-social systems, emphasizing safety-critical resilience for urban citizens. Her methodology uniquely combines model-based control with data-driven machine learning to address challenges like social data integrity, human behavior modeling, and multi-scale anomaly characterization. Analysis of her 15 most recent publications (2021-2025) reveals dominant trends in cyberattack detection for connected vehicles, thermal fault tolerance in battery systems, and socio-technical traffic modeling. Key technical approaches include Koopman operator theory for secure estimation, control barrier functions for safety certification, and redundancy-based data fusion techniques. These works consistently bridge theoretical control systems with practical smart city implementation, demonstrating strong interdisciplinary connections between transportation engineering, energy systems, and cybersecurity. No scientific awards are documented in the provided information. Dr. Roy actively mentors three PhD students—Sanchita Ghosh (since 2022), Faysal Ahamed, and Soumyoraj Mallick (both since 2024)—alongside undergraduate researcher Mercedes Hernandez. Her research is executed through the Smart Human-centric Automation Resilience (SHARE) Lab, which has secured projects including the secure autonomous mobility testbed and participates in workforce development via Texas Tech's Engineering Research Internship Experience (ERIE) program for high school students. The SHARE Lab operates at the intersection of transportation and energy systems, maintaining two primary research thrusts: resilient human-centric transportation networks and safeguarding battery energy storage infrastructure. Current projects include SUMO-based cyberattack validation for connected vehicle platoons, self-learning voltage estimation under sensor attacks, and thermal fault-tolerant battery management. The lab maintains active collaborations with national conferences (ACC, CCTA) and industry partners to advance real-world implementation of resilient smart city technologies.
Alexey Gotsman is a tenured Research Professor at the IMDEA Software Institute in Madrid, Spain, where he leads research at the intersection of software verification and distributed computing. He also works part-time as a visiting academic at Amazon Web Services. His educational background includes a Ph.D. from the University of Cambridge, where he was previously a postdoctoral fellow. His research spans theoretical foundations and practical implementations of distributed systems, with particular emphasis on fault tolerance, consensus algorithms, and consistency models. His research interests focus on the theoretical and practical aspects of distributed systems, including Byzantine fault tolerance, state machine replication, distributed transactions, and consistency models. His work bridges the gap between formal verification techniques and real-world distributed systems implementations, with numerous publications in top-tier venues like PODC, DISC, and NSDI. His recent publications show a clear progression from theoretical foundations to practical implementations, with increasing focus on real-world applications, performance considerations, and fault tolerance in large-scale distributed systems. The research demonstrates strong connections between formal methods and practical system design, particularly in the areas of consensus protocols, replication strategies, and transaction processing. Best paper award at OPODIS'23 Best paper award at DISC'18 Best paper award at CONCUR'12 EAPLS Best Dissertation Award Runner-up prize in the BCS Distinguished Dissertation Competition ERC Starting Grant 'RACCOON: A Rigorous Approach to Consistency in Cloud Databases' (2017-2022) Ramón y Cajal Fellowship (2017-2022) Alexey actively mentors PhD students including Alejandro Naser Pastoriza, Fedor Ryabinin, and Antonio José Fernández Pinto, while his alumni have gone on to faculty positions at institutions like University of Paris 7 and University of Colorado Boulder, as well as industry roles at companies like ARM and Informal Systems. He has received significant funding including an ERC Starting Grant and served on program committees for numerous top conferences including POPL, DISC, and PODC. He currently co-organizes the International Symposium on Distributed Computing (DISC) and has been instrumental in organizing workshops focused on consistency in distributed systems. His research group at IMDEA Software Institute focuses on developing rigorous approaches to consistency in cloud databases and distributed systems, with active projects spanning theoretical analysis, protocol design, and practical implementation of fault-tolerant distributed systems.
Sarah Neuwirth is a tenured Professor for Computer Science at Johannes Gutenberg University Mainz (JGU) and a Visiting Researcher at the Jülich Supercomputing Centre. She manages JGU's High Performance Computing (HPC) division, coordinates regional/national HPC activities, and represents JGU in NHR, Gauss-Allianz, and HPC committees. Education : PhD (Dr. rer. nat.) in Computer Science (2018), Heidelberg University Diplom in Computer Science (2012), University of Mannheim Bachelor of Science in Computer Science (2010), University of Mannheim Research Interests : Parallel File and Storage Systems Modular Supercomputing (resource disaggregation/virtualization) Performance Engineering High Performance Computing Networking Reproducible Benchmarking Parallel I/O Publications Trends : Her work focuses on HPC performance modeling, parallel I/O optimization, modular supercomputing, network characterization, and reproducible benchmarks. Key themes include resource disaggregation, automated workflows, and data-intensive distributed applications. Scientific Awards : 2023 PRACE Ada Lovelace Award for HPC ZONTA Science Award 2019 Grants & Leadership : She leads the High Performance Computing division at JGU, participated in European DEEP projects, and serves on SC conference committees.
Ajitha Rajan is a Professor (Personal Chair of Software Testing and Verification) at the School of Informatics, University of Edinburgh. Previously, she was a post-doctoral researcher at Oxford University's Computer Science Department and Laboratoire d'Informatique de Grenoble (LIG) in France. She earned her PhD in Computer Science from the University of Minnesota in August 2009 under the supervision of Prof. Mats Heimdahl. Her research spans two main directions: Automated Software Testing Techniques covering test input generation, test oracles, and coverage metrics; and Biomedical Artificial Intelligence focusing on cancer survival models, interpretability for biological sequences, and medical images. Her work bridges software engineering and biomedical applications, particularly in the development of trustworthy AI systems for healthcare. Professor Rajan leads several significant research projects including a Royal Society Industry Fellowship (2022-2025) on AutoTest for autonomous vehicle perception safety, the H2020 European Project KATY (2021-2025) on AI for genomics and personalized medicine where she serves as Edinburgh Lead PI, and an EPSRC Trustworthy Autonomous Systems Node project (2020-2024). Her recent publications demonstrate strong activity across software testing, explainable AI, and biomedical applications, with numerous papers accepted to top conferences in 2025 including ML for Healthcare, IJCAI, and ESEM. Among her scientific recognitions, she received the Best Reviewer Award at ISSTA'25. Her work has been consistently published in leading venues including ICSE, ICASSP, and Communications Biology. Professor Rajan actively mentors PhD students working on diverse topics from automated testing of speech recognition systems to explainable AI for medical image analysis and cancer immunotherapy. She teaches undergraduate courses in Software Testing, Computer Programming, and Embedded Systems, and has been instrumental in establishing several fully funded PhD positions through Centres for Doctoral Training at the University of Edinburgh.
Pierre Picard is a Professor of Economics at École Polytechnique , where he is also a member of the Haut Collège . He holds a PhD in Economics and is a graduate of HEC-Paris. His academic career includes leadership roles such as President of the Risk Theory Society (2005) and President of the European Group of Insurance Economists (EGRIE) (2009). Education: PhD in Economics, HEC-Paris Affiliations: CREST, Risk Theory Society, EGRIE His research focuses on insurance economics , risk management , and contract theory , with applications to catastrophic risks, health insurance, and parametric insurance. Recent publications analyze pandemic business interruption insurance, nuclear liability insurance, and optimal health insurance under ex post moral hazard. Key trends in his work include modeling insurance markets with adverse selection, designing parametric insurance for technology adoption in developing countries, and exploring the role of policy dividends in market equilibrium. He has co-authored multiple papers with A. Louaas, J.-M. Bourgeon, and J. Pinquet. Scientific Awards and Leadership: Junior member, Institut Universitaire de France (1991-1996) President, Risk Theory Society (2005) President, European Group of Insurance Economists (2009) Co-Editor, Annals of Economics and Statistics (past) Co-Editor, Geneva Risk and Insurance Review (past) At École Polytechnique, he teaches courses in Corporate Finance , Microeconomics , and General Insurance at the Master’s level. He also instructs on Topics in Insurance Economics at ENSAE’s Engineering Cycle program.
