جستجوی استاد راهنمای دانشگاهی

Jop Briëtمشاهده پروفایل

پژوهشگر

• Theoretical Computer Science
• Quantum Information Theory
• Combinatorics
• +۳ مورد دیگر

Jop Briët is a Researcher at the Department of Algorithms and Complexity at Centrum Wiskunde & Informatica (CWI) in the Netherlands. His work focuses on theoretical computer science, quantum information theory, combinatorics, and tensor analysis. He has held grants including the Veni Innovational Research Grant from NWO and a Rubicon fellowship. He has authored over 50 publications in leading venues, exploring topics such as Grothendieck inequalities, quantum computing, and additive combinatorics. His research interests span the interplay between combinatorics and computational complexity, with particular emphasis on tensor analysis, probabilistic methods, and algorithm design. Recent work includes studies on Szemerédi’s theorem with random differences and the application of quantum query algorithms to entanglement-based problems. Awards: Outstanding paper award TQC (2020), Andreas Bonn medal (2013), Stieltjesprijs (2011). Professional Activities: Editor for ERCIM News, Board Member of Koninklijk Wiskundig Genootschap, and frequent invited speaker at workshops on quantum computing and combinatorics. Grants: Veni Grant (2014), Rubicon Fellowship (2012). Current teaching includes courses on Additive Combinatorics and Quantum Information Processing, reflecting his commitment to bridging foundational theory with advanced applications in computing and mathematics.

Catherine F. Eubanksمشاهده پروفایل

استاد

• Psychotherapy Process Research
• Therapeutic Alliance
• Alliance Rupture and Repair
• +۷ مورد دیگر

Catherine F. Eubanks is a Professor in the Department of Psychology at Adelphi University, affiliated with the Gordon F. Derner School of Psychology. She is based in the Hy Weinberg Center and can be reached at 516.877.4810 or via email at ceubanks@adelphi.edu. Education: PhD, Stony Brook University (2008) Her research centers on identifying therapist skills and characteristics that lead to positive outcomes in psychotherapy, with a particular emphasis on the negotiation of alliance ruptures across different theoretical orientations. She investigates how such skills can be enhanced through training, aiming to bridge the gap between research and clinical practice. Her work integrates quantitative, qualitative, and case study methodologies to maintain both scientific rigor and clinical relevance. Dr. Eubanks has developed and refined the Rupture Resolution Rating System (3RS), an observer-based coding measure designed to evaluate alliance rupture and repair processes in therapy. The 3RS is transtheoretical and applicable across various therapeutic modalities, serving both as a research instrument and a training tool for therapists to improve their sensitivity to therapeutic process and identity-, goal-, or need-based differences between patient and therapist. She teaches advanced doctoral courses such as Advanced Topics in Mental Health, Supervision Theory & Practice, Doctoral Thesis Supervision series, and seminars on psychotherapy integration and psychological research. There are no scientific awards listed in the available information. Dr. Eubanks advises doctoral students through ongoing thesis supervision, contributing to the training of future clinical psychologists. Although specific grant funding is not mentioned, her research program suggests engagement with scholarly and potentially sponsored research activities. The Rupture Resolution Rating System (3RS) represents a key component of her research lab or conceptual research team, functioning as both an analytical framework and a pedagogical instrument in therapist development.

Corrado Mauriniمشاهده پروفایل

استاد

• Fracture Mechanics
• Damage Mechanics
• Computational Mechanics
• +۵ مورد دیگر

Corrado Maurini is a Professor in Mechanics at Sorbonne University , Paris, France. He leads two international master programs: Mécanique des Solides (Solid Mechanics) and Computational Mechanics .

• Human-AI Interaction
• Explainable AI
• Ethical AI
• +۵ مورد دیگر

Chiara Natali is a PhD Student in Computer Science at University of Milan-Bicocca (2022-present) and a Visiting Research Fellow at the Dalle Molle Institute for Artificial Intelligence USI-SUPSI, supported by a Swiss Government Excellence Research Fellowship. She serves as a Lecturer for Interaction Design Lab and Human-Computer Interaction courses at University of Milano-Bicocca, and as a Tutor for Advanced Data Management and Decision Support Systems and Human-System Interaction courses across multiple Italian universities. Her educational background includes: MA in Politics, Philosophy and Public Affairs at University of Milan (2020-2022) Master's in Digital Communication Strategy at IED, Milan (2019-2020) BSc in International Politics and Government at Bocconi University, Milan (2016-2019) Natali's research centers on the complex relationship between humans and AI systems, with particular focus on Human-AI Interaction, Explainable AI (XAI), Ethical AI, and her signature concept of Frictional AI. She investigates the multidirectional effects of AI on human cognitive faculties, examining the tension between Augmentation and Deskilling. Her work explores how intentional design friction can serve as a debiasing strategy against Automation Bias, promoting more thoughtful human-AI collaboration while preserving human agency and critical thinking. Her publication record reveals a strong emphasis on practical applications of XAI in high-stakes domains like healthcare, with particular attention to medical decision-making processes. Her research consistently addresses the challenge of designing AI systems that support rather than replace human expertise, exploring how explanations impact accuracy in hybrid decision-making and how to measure technology dominance in AI-supported environments. Her significant contributions have been recognized with: Best Paper Award at the World Conference on Explainable Artificial Intelligence (2024) Best Doctoral Consortium Award at CEUR Workshop Proceedings (2023) Natali actively shapes her field through academic service, serving as PUBLICITY & PROCEEDINGS CHAIR for HHAI 2025 and organizing multiple workshops on Human-Centred Machine Learning, Algorithmic Authority, and Frictional AI. She also contributes to gender equality in STEM as a Science Ambassador for her institution's Gender Equality Plan and previously served as PhD co-representative at the Department Board. Her interdisciplinary approach extends into creative domains, where she is developing an Interactive AI Opera on 'The Garden of (Un)Earthly AI's' funded by the University of Edinburgh's Generative AI Laboratory, and has curated projects exploring Human-AI Music Co-Creation and live-coding music performances.

• K-12 Computing Education
• Social Justice in Computing
• Physical Computing
• +۳ مورد دیگر

Gayithri Jayathirtha is an Assistant Professor in the College of Education at the University of Illinois at Urbana-Champaign, specializing in Curriculum & Instruction. Her research focuses on integrating social justice into K-12 computing education through electronic textiles and pedagogical frameworks. She holds a Ph.D. and Master's in Learning Sciences from the University of Pennsylvania, along with a B.S. in Computer Science Engineering from Bangalore University, India. Research Interests: Jayathirtha explores how electronic textiles can bridge technical and societal dimensions in computing education. Her work emphasizes critical engagement, equity, and teacher roles in reshaping curricula to include sociopolitical implications of technology. Key areas include computational thinking assessment, collaborative debugging, and justice-centered learning. Publications: Since 2017, she has published extensively in ACM and IEEE conferences, focusing on topics like teacher identity in social justice, student problem-solving with e-textiles, and portfolio assessments for computational thinking. Notable works include redesigning introductory computing programs to address colonialism and bias, as well as frameworks for politicized trust in classrooms. Scientific Contributions: Jayathirtha has co-authored studies on bugs as catalysts for peer collaboration, the invisibility of everyday computing systems, and strategies for equitable K-12 computing education. Her research often involves partnerships with educators to develop and test innovative teaching methods. Professional Impact: Through her publications and presentations at RESPECT, SIGCSE, and ICLS conferences, Jayathirtha advocates for expanding computing education beyond technical skills to include societal implications. Her work provides practical tools for teachers to integrate critical perspectives into curricula.

Gregory Lewkowiczمشاهده پروفایل

استاد

• Digital Law
• Artificial Intelligence
• Global and Transnational Law
• +۴ مورد دیگر

Gregory Lewkowicz is a Professor at the Université libre de Bruxelles (ULB) , Director of the Perelman Center's Smart Law Hub , and a Senior Research Fellow at the University of Nice Sophia Antipolis in Economic Law and Artificial Intelligence. He also teaches at Science Po Paris Law School and the University of Paris II Panthéon-Assas , and is a recurring professor at HEC-Paris for digital transformation programs. Expertise: Digital law and technology, global/transnational law, legal professions Research Focus: Interactions between law and digital technologies (SMART Law), algorithmic law, AI in legal analysis, and transformations of legal professions Leadership: Director of "Penser le droit" collection at Bruylant Publishing , in charge of the Brussels Bar Observatory , and member of AI4Belgium advisory board His recent articles explore trends in algorithmic governance , trustworthy AI , legal argumentation , and digital transformation of legal systems. He has contributed extensively to Brussels School scholarship , focusing on its sociological and philosophical foundations. Gregory Lewkowicz directs research programs on AI ethics , smart city regulations , and global corporate accountability . He is affiliated with the Institute for Artificial Intelligence for the Common Good (FARI) and the Equality Law Clinic (ELC) .

Massimo Franceschettiمشاهده پروفایل

استاد

• Mathematical Engineering
• Networked Control Systems
• Information Theory
• +۷ مورد دیگر

Massimo Franceschetti is a Professor in the Department of Electrical and Computer Engineering at the University of California, San Diego (UCSD), with faculty affiliation at Calit2. His research spans mathematical engineering, focusing on control, communication, computation, and sensing, particularly in complex networks and systems. He integrates tools from statistical physics, wave propagation, and information theory to analyze and design networked systems. Born in Naples, Italy, he studied at the University of Naples Federico II and the University of Edinburgh (European exchange program), graduating in 1997. He earned his M.Sc. (1999) and PhD (2003) from Caltech, where he received the Walker von Brimer Award and the C.H. Wiltz Prize for outstanding research and thesis. After postdoctoral work at UC Berkeley (2003-2004), he joined UCSD as faculty and held visiting positions at Vrije Universiteit Amsterdam, EPFL (Switzerland), and the University of Trento (Italy). He became an IEEE Fellow in 2018 and was nominated a Guggenheim Fellow in 2019. His research includes networked control systems , stochastic geometry , electromagnetic information theory , and social dynamical systems . Recent work explores non-invasive emotional contagion in social networks, quantum limits on information entropy, and the physics of wave propagation. His publications bridge information theory , machine learning , and network science , often applying percolation theory and random walks to explain scaling laws and wireless signal behavior. Scientific accolades include the S.A. Schelkunoff Transactions Prize , IEEE Communications Society Best Tutorial Paper Award , and the IEEE Ruberti Young Researcher Prize . He co-authored two books: Random Networks for Communication (2007) and Wave Theory of Information (2018). His students have pursued careers in academia (e.g., IIT-Bombay, Notre Dame) and industry (e.g., Google, IBM, Tesla). He teaches courses on network science , information theory , and control systems , emphasizing data-driven analysis and the physical foundations of communication. His group’s work impacts cyber-physical systems , quantum network coding , and epidemic modeling on networks .

Moe Mojtahediمشاهده پروفایل

مدرس ارشد

• Construction Management
• Urban and Regional Planning
• Operations Research
• +۸ مورد دیگر

Dr Moe Mojtahedi is a Senior Lecturer at the School of Built Environment, University of New South Wales (UNSW). He earned his PhD in 2014 from the School of Civil Engineering at the University of Sydney. As a certified Project Management Professional (PMP) and Professional Engineer (PEng) accredited by Engineers Australia, Dr Mojtahedi bridges academic research with practical application in construction management and disaster risk reduction. PhD (University of Sydney, 2014) MEngSc (University of New South Wales) B.E. (Industrial), Professional Engineer (Australia) His research focuses on the intersection of construction management , urban resilience , and disaster risk reduction , particularly examining: Climate change adaptation in infrastructure Post-disaster recovery frameworks Lean construction methodologies Decision support systems for risk management Evacuation planning optimization Resilient hospital infrastructure Recent publications analyze trends in disaster science using computational modeling, prefabricated construction for industrial buildings, and AI/ML applications in aged care facility evacuation. His 2025 ChemistryOpen article explores sustainable reaction media for chemoselective processes, demonstrating interdisciplinary reach. Scientific recognition includes: Research Excellence Awards (Engineers Australia, 2012 & 2013) Best Conference Paper (ICES, Salford, 2017) Elsevier Outstanding Contribution Award (International Journal of Project Management, 2017) Learning and Teaching Excellence (UNSW, 2017) As a supervisor, he guides 7 PhD candidates and has mentored 4 graduates, including Mahmoud Ershadi (project management office effectiveness) and Kamyar Kabirifar (construction waste management). He contributes to policy discussions on aligning National Construction Code with UN Sendai Framework and advocates for disaster science integration in built environment practices. His media contributions examine hospital flood risks and climate change adaptation in Australia.

Elvira Nadia La Roccaمشاهده پروفایل

دانشیار

• Criminal Law
• Criminal Procedure
• Anti-Mafia Legislation
• +۳ مورد دیگر

Elvira Nadia La Rocca serves as Associate Professor at Sapienza University of Rome in the Department of Legal and Economic Studies. She teaches Criminal Procedure (4th year, 1st semester), Criminal Enforcement Law (2nd year, 1st semester), and Anti-Mafia Legislation (2nd year, 2nd semester) within the Law program (Course code 33465). Her office hours are held on Wednesdays from 15:00-18:00 and Mondays from 10:00-13:00, with remote consultation available via her institutional email. Professor La Rocca's research focuses on criminal law and procedure, with particular expertise in confiscation law, penitentiary systems, and judicial administration. Her work examines the intersection of procedural efficiency and fundamental rights, analyzing contemporary reforms like the Cartabia Reform of Italy's criminal justice system. She investigates how legal frameworks balance crime prevention with constitutional protections, especially regarding asset confiscation, prison conditions, and procedural guarantees for defendants. Her recent publications demonstrate consistent scholarly output examining evolving criminal justice mechanisms. The articles reveal a methodological trend analyzing European and international legal developments through Italian jurisprudence, with particular attention to Constitutional Court rulings. Her work bridges theoretical legal concepts with practical judicial applications, often addressing tensions between procedural streamlining and fundamental rights protection in criminal proceedings. Professor La Rocca leads research on critical contemporary issues including 'The administration of justice during the health emergency: from inexorable quiescence to the creation of a functional and virtuous paradigm' and 'The predictability of judicial decisions in the era of emergency criminal justice: perspectives and assessments after thirty years of validity of the Code of Criminal Procedure.' These projects address systemic challenges in maintaining judicial functionality during crises while preserving legal certainty and procedural fairness.

R K Bansalمشاهده پروفایل

استاد

• Detection Theory
• Information Theory
• Universal data compression
• +۵ مورد دیگر

R K Bansal is a Professor in the Department of Electrical Engineering at Indian Institute of Technology Kanpur (IIT Kanpur). He has been actively contributing to the fields of Detection Theory and Information Theory for several decades with a strong academic background including a PhD from University of Connecticut (1987). His research interests include: Universal data compression with applications Sequential detection of a change in distribution Robust detection Ergodic theory and large deviation theory applications Stochastic processes Dr. Bansal's recent publications primarily focus on data compression algorithms, particularly variations of the Lempel-Ziv algorithm, and detection theory applications. His work demonstrates a strong theoretical foundation with practical applications in information processing and analysis, showing consistent research activity from the 1980s through 2013. He has received significant recognition for his teaching excellence: Letter of commendation from Director on best teaching (2011) Outstanding tutor for Mathematical Statistics (BSO209) based on student feedback (1998-II) Consistently high teaching evaluations exceeding institute averages Dr. Bansal has advised students and maintained active research in his specialized areas, though specific names of current advisees are not mentioned in the available information. His research has been published in prestigious venues including IEEE Transactions on Information Theory. His laboratory is located in room 202 ACES (Advanced Centre for Electronic Systems) at IIT Kanpur, serving as the base for his research activities in detection theory and information theory applications.

• Information Theory
• Coding Theory
• Algorithm Design
• +۳ مورد دیگر

Sidharth Jaggi is a Professor at the School of Mathematics, University of Bristol, with over 19 years of experience in Information and Data Sciences through the lens of Information Theory. His work emphasizes fundamental performance limits and algorithm design for systems under adversarial threats. Education: B.Tech, M.Phil, PhD Research interests focus on adversarial communication, information-theoretic security, coding theory, and sparse data estimation. He leads the CAN-DO-IT team (Codes, Algorithms, Networks – Design and Optimization for Information Theory), integrating theoretical tools into practical applications like secure distributed computing and robust data storage. Recent publications highlight advancements in adversarial channels , group testing , and privacy-preserving coding . Trends include covert communication under spectral constraints, causal feedback benefits, and efficient algorithms for high-dimensional problems. Current projects include "Information Theory for Interactive Distributed AI" (2024–2029), exploring interactive systems under adversarial constraints.

Lenka Garsholمشاهده پروفایل

دانشیار

• Language Acquisition
• Language Learning
• Multilingualism
• +۵ مورد دیگر

Lenka Garshol is an Associate Professor at the Department of Foreign Languages and Translation at the University of Agder. She serves as the subject coordinator for English in teacher education and is a member of the International Society for the Linguistics of English (ISLE) and the Learner Corpus Association (LCA) . Her research interests include: Language Acquisition Language Learning Multilingualism Code-switching and Code-mixing Game-based Learning She leads the Games and Active Learning Methods in Education (GAME) project, focusing on digital tools and games in language education. Garshol's publications emphasize English language teaching , error analysis in learner English, and the use of digital tools for pedagogy. Her collaborative work spans topics like artificial intelligence in language subjects , foreign language policy , and subject-verb agreement patterns . She contributes to editorial work for journals such as the Nordic Journal of Language Teaching and Learning (NJLTL) and has co-authored book chapters on teacher education reforms and digital competence development.

Igor Di Marcoمشاهده پروفایل

پژوهشگر

• Computational Physics
• Condensed Matter Theory
• Strongly Correlated Materials
• +۵ مورد دیگر

Igor Di Marco is a Researcher at Uppsala University's Department of Physics and Astronomy, specializing in Materials Theory. He has maintained continuous research activity at Uppsala since 2009, initially as a postdoctoral fellow and subsequently as a researcher, with a temporary leave in 2017 to lead a group at the Asia-Pacific Center for Theoretical Physics in South Korea. Dr. Di Marco earned his PhD in condensed matter theory from Radboud University of Nijmegen in 2009. His academic trajectory has focused on computational approaches to understanding complex quantum materials, particularly those exhibiting strong electron correlations. His research centers on computational physics and condensed matter theory , with emphasis on developing methods to determine electronic and magnetic properties of strongly correlated materials . Dr. Di Marco is one of the principal developers of the all-electron DFT code RSPt (a Sweden-USA-France collaboration), which utilizes the full-potential linearized muffin-tin orbitals method. His expertise spans density-functional theory (DFT) , dynamical mean-field theory (DMFT) , and their integration (DFT+DMFT). Current research extends to X-ray absorption spectroscopy (XAS) and resonant inelastic X-ray scattering (RIXS) . Analysis of his recent publications reveals a consistent focus on electronic correlations in quantum materials, particularly in kagome metals, van der Waals magnets, and complex alloys. His work bridges theoretical method development with practical materials applications, frequently examining magnetic properties and electronic structure calculations across diverse material systems. Dr. Di Marco has made significant contributions to computational methodologies for strongly correlated electron systems, including the development of the DFT+DMFT framework within RSPt featuring full self-consistency over electron density and self-energy. His research projects have addressed magnetic properties of transition metals, excitation spectra of metal oxides, theoretical frameworks for lanthanides, and prediction of novel 2D materials.

• Building Permit Processes
• Digital Building Permits
• Building Information Modeling
• +۴ مورد دیگر

Judith Fauth is a researcher at the Technical University of Munich's Chair of Computing in Civil and Building Engineering, where she pioneers digital transformation in building permit processes through Building Information Modeling (BIM) and digital twin technologies. Her work bridges civil engineering, computer science, and public policy to streamline regulatory compliance across international contexts. Her research expertise spans Building Permit Processes , Digital Building Permits , Ontology Engineering , and Process Modeling , with emphasis on developing standardized frameworks for global permit system benchmarking. She investigates how semantic technologies and digital twins can automate regulatory compliance while accommodating regional variations in construction law and administrative practices. Analysis of her 2023-2025 publications reveals three dominant trends: (1) integration of digital building permits with digital building logbooks for lifecycle data management, (2) development of ontologies like OBPA for automated permit reviews, and (3) creation of taxonomies and process models (e.g., PACE-BP framework) enabling cross-national comparisons of permit systems. This work increasingly incorporates sustainability metrics and stakeholder-specific KPIs. Within TUM's research infrastructure, Dr. Fauth contributes to the BIM Lab and Digital Twinning research groups, collaborating on projects involving Gaia-X-based data frameworks and semantic modeling of the built environment. She teaches practical software development skills through the SoftwareLab course, preparing engineering students for digital construction workflows.

Geoffrey Goodhillمشاهده پروفایل

استاد

• Computational Neuroscience
• Neural Development
• Zebrafish Behavioral Modeling
• +۵ مورد دیگر

Geoffrey Goodhill is Professor of Neuroscience and Professor of Developmental Biology at Washington University School of Medicine, where he directs the Center for Theoretical & Computational Neuroscience. His laboratory bridges experimental and theoretical approaches to study brain development. Goodhill earned his BSc in Mathematics and Physics from the University of Bristol (1986), MSc in Artificial Intelligence from the University of Edinburgh (1988), and PhD in Cognitive Science from the University of Sussex (1992). His postdoctoral training included a Medical Research Council Fellowship and a Sloan Theoretical Neuroscience Fellowship at the Salk Institute. His research focuses on computational principles of brain development, particularly using larval zebrafish to investigate neural coding development, behavioral emergence, and alterations in Autism Spectrum Disorders. Key projects examine neural coding and spontaneous activity patterns zebrafish behavioral development autism-related circuit dysfunction calcium imaging analysis methods historical work on axon guidance mechanisms His recent publications show a clear trajectory from molecular gradient studies toward complex systems neuroscience using zebrafish models. Scientific recognition includes: Paxinos-Watson Prize (2012) Elspeth McLachlan Plenary Lecture (2019) Keynote at Computational Neuroscience Meeting (2020) Sloan Theoretical Neuroscience Fellowship (1995) The Goodhill Lab maintains an interdisciplinary team with backgrounds in biology, mathematics, physics and engineering. Current research analyzes human video data for early autism detection while continuing zebrafish neural circuit investigations. The lab has received consistent funding for its innovative approaches to developmental neuroscience questions.