جست‌وجوی استاد و پژوهشگر

Alexey Gotsmanمشاهده پروفایل

استاد پژوهشی

• Distributed Systems
• Software Verification
• Consensus Algorithms
• +۵ مورد دیگر

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.

Brigitte Pientkaمشاهده پروفایل

استاد

• Type theory
• Programming languages
• Logical frameworks
• +۷ مورد دیگر

Brigitte Pientka is a Full Professor in the School of Computer Science at McGill University, where she leads the Computation and Logic group. She received her PhD from Carnegie Mellon University in 2003, and previously studied at the University of Edinburgh and Technical University of Darmstadt. Her educational background includes: PhD from Carnegie Mellon University (2003) Studies at the University of Edinburgh Studies at Technical University of Darmstadt Dr. Pientka's research focuses on developing theoretical and practical foundations for building and reasoning about reliable, safe software systems. She combines theoretical research on logical foundations of computer science in programming languages and verification with system building. Her work spans logics (classical and non-classical), type theory, theorem proving, logic and functional programming, and logical frameworks. She has made significant contributions to the field of contextual types and mechanized metatheory. Her recent publications demonstrate a strong trend toward modal type theory, contextual types, and session types, with applications to functional programming, verification, and meta-programming. She has made significant contributions to the Beluga system, which explores how to combine functional programming with dependently-typed, higher-order data specified in the logical framework LF. Her work often bridges theoretical foundations with practical implementations for mechanized reasoning. Dr. Pientka has received several notable awards: Humboldt Fellowship Test of Time Award @ PPDP'18 for 'Programming with proofs and explicit contexts' Best student paper award at ICLP'03 She is actively involved in mentoring and academic service, having served as PC Chair for ICFP'24, CPP'23 and CPP'24, and as General Chair for POPL'20. She is an Executive Editor of Logical Methods in Computer Science and serves on the editorial boards of the Journal of Functional Programming and ACM Transactions of Computational Logic. She leads the Computation and Logic group at McGill University, which focuses on developing theoretical and practical foundations for reliable software systems through research in logical frameworks, type theory, and programming language design.

• Mindfulness-Based Interventions
• Implementation Science
• Clinical Psychology
• +۵ مورد دیگر

Rebecca Crane is a Professor at Bangor University's School of Psychology and Sport Science , directing the Centre for Mindfulness Research and Practice since its founding in 2001. She teaches internationally in Mindfulness-Based Cognitive Therapy (MBCT) and Mindfulness-Based Stress Reduction (MBSR) , focusing on implementation integrity in practice settings. Principle Fellow: Higher Education Academy Fellow: British Association of Mindfulness-Based Approaches Member: Health Professions Council Research Interests center on translating mindfulness evidence into clinical practice, with specific attention to: Implementation processes in UK healthcare Teaching competency assessment (MBI:TAC) Training level-outcome correlations Adaptations for diverse populations Climate crisis integration into mindfulness frameworks Recent publications analyze intervention fidelity (2025), teacher assessment reliability (2024), and adaptations for socio-environmental challenges (2023). Articles show increasing focus on assessment criteria standardization , virtual delivery effectiveness , and systemic transformation through mindfulness. Co-Editor: Essential Resources for Mindfulness Teachers (2021) Principal Investigator: LIGHTMind depression trial (2023) Keynote speaker: International Conference on Mindfulness (2023) Her teaching legacy includes founding Bangor's Mindfulness Master's program (2003) and delivering MBI:TAC training to over 30 international participants (2021). She emphasizes relational mindfulness and social justice in all professional engagements.

• Logic-in-memory
• Machine learning
• Nanocomputing
• +۷ مورد دیگر

Marco Vacca is an Associate Professor in the Department of Electronics and Telecommunications (DET) at Politecnico di Torino and a member of the Interdepartmental Center PIC4SeR - PoliTO Interdepartmental Centre for Service Robotics. His work bridges electronics, nanotechnology, and computing architecture with a focus on innovative solutions to the memory wall problem. His research spans Logic-in-memory computing, Machine learning hardware acceleration, and Nanocomputing with specific emphasis on circuit architectures for probabilistic computing, magnetic devices, hybrid technologies integration, and CAD tools for emerging technologies. Dr. Vacca leads research in RISC-V extensions, hardware accelerators for AI, and autonomous robot systems for agricultural applications through the VLSILAB research group. Recent publications reveal a strong trend toward solving fundamental computing challenges through nanoscale innovations, particularly in memory-centric architectures, molecular field-coupled computing, and novel transistor technologies. His work demonstrates how logic-in-memory approaches can overcome traditional von Neumann limitations while improving energy efficiency for AI workloads. Editorial board member of ELECTRONICS (2021-2023) Program committee member for Design, Automation and Test in Europe Conference (DATE) 2020-2021 Dr. Vacca supervises PhD student Alessandro Varaldi working on 'Hardware AI Accelerators for Automotive Applications' and has led significant research projects including 'Device for Storage and Processing Data and Related Method' (2020-2021) and 'Quantum Computing and Quantum Communication: State of the Art and Applications in the Telco Sector' (2020). His grant portfolio shows strong industry and competitive funding support. As a core member of the VLSILAB research group, Dr. Vacca contributes to advancing VLSI theory and design applications with particular focus on implementing Big Data, Machine Learning, and Neural Networks in specialized hardware architectures that push the boundaries of conventional computing.

Kirsti Kletteمشاهده پروفایل

استاد

• Learning and education
• Pedagogy
• Classroom research
• +۵ مورد دیگر

Kirsti Klette is Professor at the Department of Teacher Education and School Research within the Faculty of Education at the University of Oslo. She serves as Centre Director at the Nordic Centre of Excellence Quality in Nordic Teaching (QUINT), launched in autumn 2018. Her academic career spans over two decades, beginning as Associate Professor at Lillehammer University College in 1994, then at the University of Oslo Faculty of Education in 1998, and becoming full Professor in 2002/2004. She held a Visiting Fulbright Professorship at Stanford University (2007-2008) and has directed numerous national research programs including UTDANNING 2020 (2009-2014). Professor Klette's research focuses on classroom teaching and learning through video methodology, instructional quality, and teacher education. Her work examines the relationship between teaching practices and student outcomes across Nordic educational contexts. She leads major projects including Linking Instruction and Student Achievement (LISA), Linking Instruction and Student Experiences (LISE), and the Synthesizing Research on Teaching Quality (SYNTEQ). Her methodological expertise in video research has established her as a leading figure in educational research methodology. Analysis of her recent publications (2022-2024) reveals consistent focus on classroom observation systems, teacher education coherence, and Nordic educational practices. Her work spans multiple subject areas including mathematics, social studies, and language arts, with particular attention to how instructional quality can be measured and improved. She frequently collaborates with international researchers, contributing to global understanding of teaching quality across different educational systems. Professor Klette has made significant contributions to educational policy and practice, particularly in teacher education reform and classroom observation methodology. Her research bridges educational theory and classroom practice, with implications for teacher preparation, professional development, and educational assessment systems.

Ross Horneمشاهده پروفایل

مدرس ارشد

• Security protocols
• Privacy-preserving technologies
• Concurrency theory
• +۷ مورد دیگر

Ross Horne is a Senior Lecturer in the Department of Computer & Information Sciences at the University of Strathclyde, Glasgow, United Kingdom. He is a member of the StrathCyber and Mathematically Structured Programming research groups. Education: PhD (University of Southampton, 2012), BA (Oxford University, 2005) Prior Appointments: Research Fellow at University of Luxembourg (2018-2023), Senior Research Fellow at Nanyang Technological University (2015-2018), Associate Professor at Kazakh-British Technical University (2012-2015) Research Interests: Dr. Horne's work focuses on security and privacy protocols for digital systems, particularly addressing threats in payment technologies, ePassports, and decentralized identity management (e.g., Solid protocol). His theoretical contributions bridge concurrency theory, proof theory, and logic through applications to security verification and process calculi. Developed formal models for unlinkability in EMV payment protocols Created intuitionistic logical frameworks for process equivalence Explored graphical proof systems beyond formulaic representations Investigated legal-compliant AI for space systems (CubeSat anomaly detection) Scientific Contributions: He has published extensively in top venues including ACM CCS, IEEE CSF, LICS, and CONCUR. His 2017 CONCUR best paper introduced intuitionistic characterizations of bisimilarity. Principal Investigator for EU COST Action on Distributed Knowledge Graphs Co-developed privacy models adopted in Luxembourg parliamentary responses Advising: Currently accepting PhD students with strong mathematical and computer science skills for research in security/privacy of emerging systems. Former student Semen Yurkov completed a thesis on privacy-preserving smart card payments. Interdisciplinary Work: Collaborates with space lawyers through the Interdisciplinary Master Program in Space Resources. Projects include AI for CubeSat reliability and legal-compliant software certification frameworks.

Amy G Froelichمشاهده پروفایل

دانشیار

• Statistics Education
• Psychometrics
• Educational Assessment
• +۳ مورد دیگر

Amy G Froelich serves as Associate Professor and Director of Undergraduate Studies in the Department of Statistics at Iowa State University, where she has taught over 3,000 students since joining in 2000. Her academic leadership includes curriculum development for undergraduate statistics programs and oversight of degree requirements. Ph.D. in Statistics, University of Illinois, Urbana-Champaign (2000) B.S. in Secondary Mathematics Education, University of Illinois, Urbana-Champaign (1994) Dr. Froelich specializes in statistics education, psychometrics, and educational assessment with particular expertise in categorical data analysis and probability instruction. Her research develops innovative teaching methodologies for introductory statistics courses and focuses on training future secondary mathematics teachers through specialized curriculum design. She investigates how electronic assessments and resampling techniques enhance student learning outcomes in statistical reasoning. Her publication record (2008-2018) demonstrates consistent contributions to statistics pedagogy, emphasizing practical classroom applications, assessment design, and teacher preparation. Key themes include the development of engaging activities (e.g., M&M's weight analysis, iPod randomness testing), psychometric methods for educational measurement, and curriculum reforms for mathematics educators. Waller Education Award from the American Statistical Association (2010) Multiple teaching and advising awards at Iowa State University Dr. Froelich has secured significant research funding from the National Science Foundation, U.S. Department of Agriculture, and U.S. Department of Education to support her statistics education initiatives. As Director of Undergraduate Studies since 2018, she mentors students through curriculum development projects and advises on academic pathways in statistics. Her co-authorship of Business Statistics and Analytics in Practice (9th ed., 2019) extends her impact to textbook development.

Brigitte Pientkaمشاهده پروفایل

استاد

• Programming Languages
• Verification
• Type Theory
• +۶ مورد دیگر

Brigitte Pientka is a Professor at McGill University's School of Computer Science , where she leads the Computation and Logic group . She earned her PhD from Carnegie Mellon University in 2003 and previously studied at the University of Edinburgh and Technical University of Darmstadt. Education PhD in Computer Science, Carnegie Mellon University (2003) University of Edinburgh Technical University of Darmstadt Research Interests Her work focuses on the theoretical and practical foundations for building reliable software systems, combining logic, type theory, and verification with system-building. Key areas include: Type Theory and Dependent Types Logical Frameworks and Mechanized Metatheory Session-Typed Concurrency and Linear Logic Metaprogramming and Contextual Type Systems Theorem Proving and Formal Verification Functional Programming and Language-Based Security Professional Roles She has served as: PC Chair for ICFP'24 and CPP'24 General Chair for POPL'20 Executive Editor of Logical Methods in Computer Science Steering Committee Member for LICS, POPL, and ESOP Scientific Awards Dr. Pientka has received: Test of Time Award at PPDP'18 Humboldt Fellowship for research at MPI-SWS, Germany Labs & Teams She actively develops the Beluga programming language , a tool for mechanizing meta-theory proofs and type-driven program manipulation.

Nirupam Guptaمشاهده پروفایل

استادیار

• Distributed Machine Learning
• Federated Learning
• Privacy-Preserving Algorithms
• +۴ مورد دیگر

Nirupam Gupta is an Assistant Professor at the Department of Computer Science (DIKU), University of Copenhagen. His research focuses on robustness, privacy, and fairness in distributed machine learning systems, with particular emphasis on federated learning and Byzantine fault tolerance. He actively contributes to the design of secure, resilient, and privacy-preserving algorithms for collaborative AI systems. He teaches courses in Privacy in Machine Learning (PriMaL) Machine Learning B (MLB) both offered in hybrid formats with full remote participation support. His latest book, Robust Machine Learning: Distributed Methods for Safe AI , provides foundational insights into the field. Key research themes in his work include: Byzantine-Robust Optimization Differential Privacy in Federated Systems Personalization under Adversarial Conditions Secure Aggregation Techniques Contact: nigu@di.ku.dk

Debabrota Basuمشاهده پروفایل

استادیار

• Machine Learning
• Reinforcement Learning
• Bandit Algorithms
• +۶ مورد دیگر

Debabrota Basu is a tenured faculty member (Inria Starting Faculty Position - ISFP) at the Scool team (previously called SequeL) of Inria Centre at University of Lille in France. He teaches postgraduate-level courses on privacy, responsible machine learning, and research methods in AI at École normale supérieure-PSL University, Université de Lille, and Centrale Lille. He is also a member of the ELLIS Society (European Laboratory for Learning and Intelligent Systems) and the Paris unit of ELLIS. Dr. Basu earned his PhD in Computer Science from the Department of Computer Science, School of Computing, National University of Singapore, advised by Stéphane Bressan and Pierre Senellart. Prior to that, he obtained a B.E. degree with Honours in Electronics and Telecommunication Engineering from Jadavpur University. Before joining Inria, he was a postdoctoral researcher at Chalmers University of Technology's Data Science and AI Division. Dr. Basu's research focuses on constructing algorithms for developing efficient, robust, private, and ethical learning machines that solve real-world problems. His methodological approach blends statistics, machine learning, and optimization. His application interests span sustainable agro-ecology, medical and pharmaceutical applications, energy-efficient autonomous systems, and algorithmic audits. Recent collaborations include the Inria-Indian Statistical Institute associate team SeRAI for developing Sequential Testing and Learning Algorithms for Verifiably Robust and Responsible AI, and the Inria-INRAE collaboration on Resilient Agricultural Decision Making under Environmental Risks. His publication record demonstrates expertise in bandit algorithms, reinforcement learning, and privacy-preserving machine learning. Recent work shows a strong theoretical foundation with practical applications, particularly in pure exploration bandits, differential privacy mechanisms, constrained optimization, and fairness verification. His research bridges the gap between theoretical guarantees and real-world deployment challenges across multiple domains. Dr. Basu has received notable recognition for his contributions: Best Student Paper Award at ACM EAAMO 2022 for 'On Meritocracy in Optimal Set Selection' Young researcher (JCJC) grant from the French National Research Agency (ANR) in 2022 in 'Artificial Intelligence and Data Science' He leads the project 'RL under Real-life Constraints: Regrets and Algorithms' and supervises PhD students and postdoctoral researchers. His research is supported by multiple projects including REPUBLIC ('Vers l'IA responsable avec l'apprentissage par renforcement sous contraintes') and 'Foundations of robustness and reliability in artificial intelligence.' Dr. Basu actively collaborates with institutions worldwide, including establishing the RELIANT associate team with Kyoto University for investigating structured multi-armed bandit problems.

• Bayesian Methods
• Stochastic Processes
• Time Series Analysis
• +۳ مورد دیگر

Tevfik Aktekin is a Professor in the Department of Decision Sciences at the Paul College of Business and Economics, University of New Hampshire. His research focuses on Bayesian inference and stochastic modeling in service systems and business analytics. Education : Ph.D. in Decision Sciences (George Washington University), M.B.A. in Management Decision Making (George Washington University), B.S. in Mechanical Engineering (Yildiz Technical University). His work applies Bayesian state-space models to multivariate count data, with applications in call center staffing, product modification cycles, and public health analysis. He has published in journals like Annals of Applied Statistics , Bayesian Analysis , and European Journal of Operational Research . The 15 most recent articles highlight trends in sequential Bayesian learning for dynamic systems (e.g., bike-sharing, web traffic), time series of non-Gaussian data, and stochastic optimization under uncertainty. These works bridge statistical theory with practical applications in business and health.

Drazen Prelecمشاهده پروفایل

استاد

• Behavioral Economics
• Neuroeconomics
• Decision-Making Psychology
• +۵ مورد دیگر

Drazen Prelec is a Professor of Management Science and Economics at the MIT Sloan School of Management , with appointments in the Department of Economics and Department of Brain and Cognitive Sciences . His work bridges psychology, neuroscience, and economics to study decision-making mechanisms. Education: AB in Applied Mathematics (Harvard College), PhD in Experimental Psychology (Harvard University) Prelec's research focuses on behavioral economics and neuroeconomics , particularly in areas like risky choice, time discounting, self-control, and consumer behavior. He develops normative decision theory while investigating its empirical limitations using behavioral and fMRI methods. Two major projects include: Self-Signaling : Examines non-causal motivation where individuals favor actions diagnostic of favorable outcomes over causal ones Bayesian Truth Serum : Creates scoring systems to reward honest judgments in domains without objective truth criteria His recent publications span topics in crowd wisdom , temporal discounting , and neuroeconomic modeling , with applications to consumer neuroscience, political forecasting, and behavioral ethics. Guggenheim Fellowship Junior Fellow, Harvard Society of Fellows Prelec contributes to understanding how credit card usage activates brain reward centers to increase spending, and explores honesty biases in social interactions. His work integrates computational models with empirical neuroscience to address foundational questions in decision theory.

Uri Hassonمشاهده پروفایل

استاد

• Neuroscience
• Natural Language Processing
• Cognitive Science
• +۷ مورد دیگر

Uri Hasson is a Professor at the Princeton Neuroscience Institute, Princeton University, focusing on the neural basis of brain-to-brain human communication, natural language processing, and language acquisition in real-world contexts. His lab challenges traditional experimental models by using deep learning to decode cognition during natural stimuli. Research Highlights: Investigates neural alignment in speaker-listener interactions. Develops computational tools to model language processing in everyday conversations. Explores shared principles between biological and artificial neural networks. Recent Article Trends: 2025–2023 publications emphasize deep language models matching neural responses, event segmentation via Bayesian surprise, and multibrain convergence during storytelling. Key keywords: Neuroscience, Natural Language Processing, Deep Learning, Cognitive Modeling . Awards: NIH Pioneer Award Lab & Collaborations: The Hasson Lab integrates neuroimaging (ECoG, fMRI) with large-scale datasets and AI to study real-life cognition. Collaborations span psychology, computational neuroscience, and machine learning.

Dimitri Mavrisمشاهده پروفایل

استاد

• Advanced Design Methods
• Aircraft Conceptual and Preliminary Design
• Air-Breathing Propulsion Design
• +۴ مورد دیگر

Dimitri Mavris is a Professor at the School of Aerospace Engineering , Georgia Institute of Technology, holding distinguished titles including Boeing Chair in Advanced Aerospace Systems Analysis and S.P. Langley Distinguished Professor . He directs the Aerospace Systems Design Laboratory (ASDL) and serves as Executive Director of the Professional Master’s in Applied Systems Engineering (PMASE) . Education B.S., Aerospace Engineering, Georgia Institute of Technology (1984) M.S., Aerospace Engineering, Georgia Institute of Technology (1985) Ph.D., Aerospace Engineering, Georgia Institute of Technology (1988) Dr. Mavris specializes in advanced design methods , aircraft preliminary design , and non-deterministic design theory , focusing on multi-disciplinary optimization and system of systems architecting . His work spans propulsion systems, space exploration, and sustainable aviation technologies. Recent research trends include machine learning for aerospace safety , hybrid-electric propulsion analysis , and digital twin applications in energy systems. His lab produces 100+ annual publications, reflecting leadership in MBSE , UAS certification , and lunar operations modeling . Scientific Awards Class of 1934 Distinguished Professor Award (2024) NSF CAREER Award (1997) Fellow of AIAA (2009-present) NASA Blue Marble Award (2017) SGA Faculty of the Year (2012-2013) As an advisor to Georgia Tech's AIAA student chapter, Dr. Mavris mentors 1,484 alumni (300 Ph.D., 1,184 M.S.) and leads industry partnerships with FAA , Airbus , and Siemens . His labs include the Vertical Lift Research Center and Strategic Energy Institute , with global initiatives like the ICAS presidency (2023-2024).

Gian-Gabriel Garciaمشاهده پروفایل

استادیار

• Health Policy
• Personalized Medicine
• Medical Decision-Making
• +۵ مورد دیگر

Gian-Gabriel Garcia is an Assistant Professor and Harold E. Smalley Early Career Professor at the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Institute of Technology, with a dual role as Pillar 1 Co-lead in Data Science, Machine Learning, and Artificial Intelligence at the Children's Healthcare of Atlanta Pediatric Technology Center. His work bridges predictive analytics and decision-making frameworks in healthcare contexts. Education : PhD and MS in Industrial and Operations Engineering (University of Michigan), BS in Industrial Engineering (University of Pittsburgh) Research focuses on responsible AI for healthcare, emphasizing health equity , stochastic optimization , and machine learning applied to concussion management, opioids, maternal health, and cardiovascular disease. His methodologies integrate dynamic programming and simulation to address stakeholder acceptability. Key article themes include concussion diagnostics , responsible AI in diabetes care, and interpretable policies for chronic disease management. His work frequently leverages Markov decision processes and stochastic modeling . Scientific Awards National Science Foundation Graduate Research Fellowship INFORMS Bonder Scholarship for Applied Operations Research in Health Services SMDM Lee B. Lusted Prize INFORMS Minority Issues Forum Paper Competition First Prize INFORMS Minority Issues Forum Poster Competition First Prize Garcia also contributes to undergraduate mentorship and serves as Vice President of Communications (co-chair) for the INFORMS Minority Issues Forum, alongside council membership in the INFORMS Health Applications Society.