جست‌وجوی استاد و پژوهشگر

Aleksandar Kosticمشاهده پروفایل

مدرس

• Philosophy of Architecture
• Design Theory
• Architectural Design
• +۵ مورد دیگر

Aleksandar Kostic is a Lecturer in the Department of Architecture and Built Environment at South East Technological University (SETU), where he also serves as Lead Researcher. He holds a PhD from University College Dublin, awarded in 2022, and is actively contributing to the academic and professional architecture community. PhD in Design Theory, University College Dublin (2022) His research lies at the intersection of philosophy and architectural design, with a strong focus on design theory, epistemology, ethics, and aesthetics. He explores fundamental questions such as aporia (intellectual impasses) in design, the influence of Platonic philosophy, and the ethical responsibilities of architects. His work emphasizes critical thinking and philosophical inquiry in architectural practice and education. The trends in his publications reveal a consistent engagement with philosophical concepts applied to architectural problems. From examining 'aporetic' design challenges to analyzing Plato’s views on expertise, his research bridges abstract thought and practical design. Recent works continue this trajectory, addressing ethical values, non-material aspects of design, and the role of contradiction in innovation. Nomination for MIES EU Award for Architecture (2009) Aleksandar Kostic advises PhD students and is actively involved in research dissemination through publications, peer-review, and conference organization. He serves on the steering committee of the All Ireland Architecture Research Group and is a member of the Centre for Platonic Studies at Trinity College Dublin and the Royal Institute of the Architects of Ireland. His peer-review activities include journals such as She JI and Building Material . He is a key member of the Architecture Research Group at SETU and collaborates across disciplines, particularly with philosophy. His upcoming activity includes organizing the 'Ethics in Architecture' conference in 2025, highlighting his leadership in integrating ethical discourse into architectural research.

Willemijn van Dolenمشاهده پروفایل

استاد

• Consumer Behavior
• Marketing Strategy
• Social Media Analysis
• +۵ مورد دیگر

Prof. Willemijn van Dolen is a Professor in the Section of Marketing at the Faculty of Economics and Business, University of Amsterdam. Her research focuses on consumer behavior, marketing strategies in digital environments, and the psychological impacts of communication in service encounters. She has extensively studied topics such as visual influence in consumer decisions, corporate greenwashing detection, and the role of humor in service interactions. Her academic career includes notable contributions to understanding online consumer behavior through multimodal datasets and AI frameworks. She has published widely on social media analytics, CSR communication, and child helpline effectiveness, bridging psychological insights with practical marketing applications. Prof. van Dolen’s work emphasizes empirical investigations into customer engagement, ethical consumption, and the interplay between digital platforms and human decision-making. Her research demonstrates a consistent focus on real-world applications, from optimizing brand posts on Instagram to analyzing CEO communication during global crises. Her studies often employ interdisciplinary methods, combining marketing theory with data science and behavioral economics. Despite her prolific output (over 50+ publications), no specific scientific awards are highlighted in the provided texts.

• Education Policy
• Social Capital
• School Choice
• +۵ مورد دیگر

Prof. M. Danish Shakeel is a Professor and Director of the E. G. West Centre for Education Policy at The University of Buckingham, UK. He is also a Research Fellow at Harvard University's Program on Education Policy and Governance. His research focuses on K-12 education policy, particularly in the U.S., with expertise in systematic reviews, meta-analyses, and the political economy of education. Key areas include civic outcomes of private schooling, social capital, charter schools, and non-cognitive traits. His work has been featured in prestigious journals like Journal of School Choice and Education Next , and widely cited in media outlets such as Wall Street Journal and Washington Post . He collaborates globally, presenting at conferences like the American Political Science Association and Association for Education Finance and Policy. Prof. Shakeel advises prospective doctoral students on rigorous quantitative methods and policy-oriented research. His guidance includes structured abstracts, empirical methodology focus, and policy implications. Students pursuing a PhD must demonstrate advanced econometric skills and secure their own funding. His research has influenced philanthropic investments and policy discourse, highlighting gains in U.S. student achievement and the role of charter schools in improving outcomes for marginalized groups.

Kuiyi Shenمشاهده پروفایل

استاد

• Asian Art History
• Chinese Art
• Japanese Art
• +۱۲ مورد دیگر

Kuiyi Shen is Professor of Asian Art History, Theory, and Criticism at the University of California, San Diego (UCSD), where he also serves as Vice Chair and Director of the PhD Program in the Department of Visual Arts. He is affiliated with the Division of Arts and Humanities and maintains an active research, teaching, and curatorial practice focused on Chinese and Japanese art, particularly modern and contemporary Chinese art and Sino-Japanese artistic exchanges. BA in Fine Arts, Shanghai Normal University MA and PhD in Art History, The Ohio State University Shen's research centers on the evolution of Chinese art in the modern era, with emphasis on ink art, unofficial art movements, and the interplay between tradition and modernity. His work explores how political, social, and transnational forces have shaped artistic expression in China, particularly during transformative periods such as the late Qing, Republican era, and post-Cultural Revolution decades. He is deeply engaged in the study of literati painting, Buddhist art, and mass visual culture, including posters and illustrated magazines. The 15 most recent publications and exhibition catalogs reflect a consistent focus on modern and contemporary Chinese ink art, unofficial art practices, and cross-cultural dialogues. Key themes include the reinvention of tradition, the role of Japan in modern Chinese art, and the emergence of independent artistic voices during politically repressive periods. His scholarly output spans academic monographs, co-edited volumes, and curatorial projects that bridge East and West. Notable scientific achievement: 2013 ICAS Book Prize in Humanities for Arts of Modern China Shen has advised numerous exhibition projects and served on international juries, including the Guggenheim Museum and the International Awards for Art Criticism. He has held academic positions at Ohio University, SUNY Buffalo, Rice University, and the University of Oregon before joining UCSD. He is Managing Editor of Brill’s Modern Asian Art and Visual Culture book series, underscoring his leadership in the global academic community. His teaching includes courses on Chinese and Japanese art, landscape painting, and contemporary art and mass culture. Shen has curated or consulted on over 20 major exhibitions worldwide, including A Century in Crisis (Guggenheim), Blooming in the Shadows (China Institute), and Light before Dawn (Asia Society), demonstrating his dual expertise in scholarship and curatorial practice.

John C. Doyleمشاهده پروفایل

استاد

• Control Theory
• Dynamical Systems
• Network Science
• +۴ مورد دیگر

John C. Doyle is the Jean-Lou Chameau Professor of Control and Dynamical Systems, Electrical Engineering, and BioEngineering at the California Institute of Technology (Caltech), where he holds appointments in the Division of Engineering and Applied Science with primary affiliation in the Control and Dynamical Systems Department. His research bridges theoretical foundations with applications across biological, technological, medical, and ecological networks. He earned a BS and MS in Electrical Engineering from MIT (1977) and a PhD in Mathematics from UC Berkeley (1984), followed by consultancy at Honeywell Systems and Research Center (1976-1990). MIT: BS & MS in Electrical Engineering (1977) UC Berkeley: PhD in Mathematics (1984) Doyle's research centers on universal laws and architectures in complex systems, emphasizing robustness-efficiency tradeoffs, speed-accuracy tradeoffs (SATs), diversity-enabled sweet spots (DeSS), bowtie/hourglass structures, and evolvability. His work pioneers System Level Synthesis (SLS) for control systems with sparse, local, saturating, delayed, noisy, quantized, and distributed (SLSDNQD) components, integrating control theory, computation, communication, and machine learning to address challenges from neural networks to infrastructure resilience. Key concepts include virtualization, horizontal transfer, and virality in multiscale systems. Analysis of his publication trends reveals consistent interdisciplinary impact across neuroscience (brain connectivity modeling), systems biology (metabolic oscillations), network science (internet topology), and physics (turbulence, earthquakes), with recurring themes of robust-efficiency limits and architectural principles governing complex networks. His work demonstrates exceptional translation from abstract theory to practical tools like the Matlab Robust Control Toolbox and Systems Biology Markup Language (SBML). His scientific recognition includes: 1990 IEEE Baker Prize (ranked among top 10 most important mathematics papers 1981-1993) Three IEEE Automatic Control Transactions Awards (1998, 1999, 2021) ACM Sigcomm Paper Prize (2004) and Test of Time Award (2016) IEEE Control Systems Field Award (2004) Multiple early-career honors including IEEE Centennial Outstanding Young Engineer (1984) Doyle has mentored generations of students whose contributions include foundational software tools adopted globally. His research has secured sustained funding from NSF, NIH, and other agencies supporting theoretical advances in control frameworks and their applications to biomedical systems, network infrastructure, and environmental modeling. The SBML initiative exemplifies his group's impact in standardizing computational biology research. He leads a highly collaborative research ecosystem at Caltech that integrates engineers, biologists, neuroscientists, and computer scientists to develop universal principles for complex networks. Current efforts focus on translating theoretical insights into health technologies, resilient infrastructure, and climate-responsive systems through the application of robust-efficiency frameworks to emerging challenges in cyber-physical and biological domains.

Luca Iocchiمشاهده پروفایل

استاد

• Cognitive Robotics
• Task Planning
• Multi-Robot Coordination
• +۶ مورد دیگر

Luca Iocchi is a Full Professor at Sapienza University of Rome, where he teaches in the Master in Artificial Intelligence and Robotics program. He is affiliated with the Department of Computer, Control, and Management Engineering and the Faculty of Engineering of Information, Computer Science and Statistics. Iocchi serves as an Associate Editor for Artificial Intelligence Journal and has been the scientific coordinator of Spoke of PNRR project FAIR (Future AI Research). His educational background includes: Master in Engineering in Computer Science (Laurea in Ingegneria Informatica) cum Laude, Sapienza Università di Roma, 1995 PhD in Engineering in Computer Science (Dottorato in Ingegneria Informatica), Sapienza Università di Roma, 1999 Professor Iocchi's research focuses on cognitive robotics, task planning, multi-robot coordination, robot perception, robot learning, human-robot interaction, and social robotics. His work has significant applications in security, surveillance, and environmental monitoring. He has published over 200 referred papers with an h-index of 46 (Google Scholar). His research bridges theoretical AI with practical robotic systems operating in real-world environments, with a particular emphasis on developing intelligent systems that can interact effectively with humans. His recent publications show a strong trend toward multi-agent reinforcement learning, trust modeling in human-AI teams, UAV coordination, and planning systems. There's a clear focus on making robotic systems more reliable, efficient, and capable of operating in complex real-world scenarios like healthcare facilities and smart cities. His work increasingly integrates formal planning approaches with machine learning techniques. Professor Iocchi has received numerous scientific awards: 1999 Top Paper Award WebNet'99 2006 Best Paper Award RoboCup 2006 2008 Best Robotics Demo Award AAMAS 2008 2014 Best Paper Award For Engineering Contribution RoboCup 2014 2017 RoboCup@Home SSPL 2017 - 3rd place 2018 Canada-Italy Innovation Award 2019 Best Paper Award For Engineering Contribution RoboCup 2019 As an academic advisor, Iocchi has directed the PhD Program in Engineering in Computer Science from 2020 to 2023. He has been Principal Investigator for numerous research projects including SciRoc (European Robotics League), AI4EU (European AI project), BUBBLES, AIPlan4EU, ROSITA, Trust Your Agents, and FAIR. His research has been supported by EU H2020 programs, national grants, and industry collaborations, demonstrating strong connections between academia and practical applications. Professor Iocchi is actively involved with the Cognitive Cooperating Robots Lab (LabRoCoCo) and is a key member of the RoboCup Federation, having served as Vice-President from 2019 to 2024. He has played a significant role in benchmarking domestic service robots through RoboCup@Home and the European Robotics League Service Robots (ERL-SR), which he helped establish. His leadership in organizing international scientific robot competitions has been instrumental in advancing the field of service robotics.

Elisa Kreissمشاهده پروفایل

استادیار

• Natural Language Processing
• Psycholinguistics
• Human-Computer Interaction
• +۳ مورد دیگر

Elisa Kreiss is an Assistant Professor in the Department of Communication at UCLA, affiliated with the College of Letters & Science. She leads the Coalas Lab (Computation and Language for Society Lab), focusing on advancing understanding of how communicative context shapes language use through natural language processing, psycholinguistics, and human-computer interaction. Her work addresses challenges in image accessibility for visually impaired users, supported by grants from Google, NSF, and Stanford initiatives. Education: Ph.D. in Linguistics, Stanford University (advised by Christopher Potts) Research Interests: Her research bridges AI ethics, image accessibility, and human-centered evaluation of machine learning systems. Key themes include: Generating context-aware image descriptions for accessibility Ethical implications of vision-language models Interpretable AI through causal reasoning Awards: Google Research Awards National Science Foundation Grant Stanford Human-Centered AI Initiative Support Stanford Community Impact Award (2022) Lab & Advocacy: Directs the Coalas Lab, emphasizing inclusive research environments. Advocates for diversity in STEM and accessible technology design.

Monica Lamمشاهده پروفایل

استاد

• Artificial Intelligence
• Privacy-Preserving Technologies
• Compiler Design
• +۴ مورد دیگر

Monica Lam is the Kleiner Perkins, Mayfield, Sequoia Capital Professor in Stanford University's School of Engineering and holds a courtesy professorship in Electrical Engineering. She leads the Stanford Open Virtual Assistant Laboratory and has pioneered work in virtual assistants, privacy protection, and compiler design. Her research includes the Almond virtual assistant, privacy-preserving IoT systems, and the ThingTalk programming language. She co-authored the seminal 'dragon book' on compilers and co-founded Tensilica (now part of Cadence). Education: Bachelor of Science (Honors), Computer Science, University of British Columbia, 1980 Master of Science, Computer Science, Carnegie Mellon University, 1982 Doctor of Philosophy (PhD), Computer Science, Carnegie Mellon University, 1987 Research Interests: Dr. Lam's work focuses on conversational AI with privacy guarantees, compiler optimization for parallel computing, and open-source virtual assistant ecosystems. She is a leader in decentralized systems, having developed frameworks like SociaLite for large-scale graph analysis and Musubi for mobile social networking without centralized platforms. Article Trends: Recent publications emphasize multimodal interactions, multilingual dialogue systems, and LLM-driven applications in areas like question answering, persuasive chatbots, and adaptive assistants. Her work bridges foundational AI research (e.g., semantic parsing) with real-world deployments (e.g., privacy-compliant IoT). Awards & Honors: Member of the National Academy of Engineering ACM Fellow Popular Science's Best of What's New Award (Security, 2019) Advising & Grants: Lam oversees the Open Virtual Assistant Initiative, a collaborative project to build open-source semantic models. Her NSF CNS grant (CNS Core) focuses on federated privacy systems. She has advised over 50 students in AI and systems research, though specific names are not listed in the provided texts. Labs & Teams: Directs the Stanford Open Virtual Assistant Laboratory, collaborates with the Stanford NLP group, and maintains ties to industry through former startup Tensilica's legacy in embedded processors.

James Malazitaمشاهده پروفایل

دانشیار

• Game Studies
• Platform Studies
• Feminist Technoscience
• +۷ مورد دیگر

James Malazita is Associate Professor of Science & Technology Studies and Associate Director of the Games and Simulation Arts and Sciences (GSAS) program at Rensselaer Polytechnic Institute (RPI). He is affiliated with the Department of Science and Technology Studies in the School of Humanities, Arts, and Social Sciences, and contributes to the GEM (Games and Experiential Media) research group. Education: Ph.D. in Communication, Culture, and Media, Drexel University (2014) BS/MS in Digital Media, Drexel University (2009) Malazita's research lies at the intersection of game studies, platform studies, feminist technoscience, and social justice in computing. He critically investigates how game engines like Unreal shape technological and cultural infrastructures, particularly through the lenses of gender, race, and power. His forthcoming book, Enacting Platforms: Feminist Technoscience and the Unreal Engine (MIT Press, July 2024), offers a groundbreaking feminist and critical analysis of one of the most influential game development platforms. His work also extends to digital humanities, critical design, and the politics of computer science education. His recent publications reveal a strong thematic focus on the co-production of technology and society, with recurring interests in epistemic cultures, disciplinary formation, localization, and critical pedagogy. These works span journals in game studies, design, digital humanities, and STS, reflecting an interdisciplinary approach that bridges technical systems and humanistic critique. Scientific Support and Affiliations: Supported by NEH Office of Digital Humanities Supported by NEH Division of Educational Programs Supported by Popular Culture Association Supported by New Jersey Historical Commission Supported by Red Hat Inc. Supported by Rensselaer’s Teaching and Learning Collaboratory Member of GEM (Games and Experiential Media) ORCID: 0000-0003-3206-3682 Malazita advises graduate students in STS and Games, with former advisees placed at Yale, NYU, and UT Austin. He teaches courses in game studies, human-centered design, interpretive methods, and critical technology studies. His current course includes STSO 2610: DSIS Studio II (Spring 2024). His research raises fundamental questions about the material and cultural limits of platforms, the analyst-platform relationship, and the future of the web as shaped by game technologies.

Jiaxin Linمشاهده پروفایل

استادیار

• Computer Systems
• Networking
• Computer Architecture
• +۵ مورد دیگر

Jiaxin Lin is an Assistant Professor in the Department of Electrical and Computer Engineering at Cornell University , affiliated with the Computer Systems Laboratory . She earned her Ph.D. in Computer Science from UT Austin (2025) , preceded by an M.S. from University of Wisconsin-Madison and a B.S. from ShenYuan Honors College at Beihang University. Her research focuses on co-designing software and hardware systems to enable high-performance data center communication, particularly through: Programmable network interface controllers (SmartNICs) Terabit network system stacks Cache/memory interconnects Compilers for in-network computing Chip-to-chip interconnects Her work addresses challenges in portability across heterogeneous SmartNICs, demonstrated through the development of the Alkali compiler framework (NSDI '25). Key themes include hardware abstraction, data center scalability, and network-compute co-design. Scientific Awards: Google Junior Faculty Award (2025) MIT EECS Rising Star (2024) Google Ph.D. Fellowship (2021) Meta Ph.D. Fellowship (2021)

Shiqing Maمشاهده پروفایل

استادیار

• Security and Privacy
• Trustworthy Machine Learning
• Software Engineering
• +۳ مورد دیگر

Shiqing Ma is an Assistant Professor in the Manning College of Information and Computer Sciences at the University of Massachusetts Amherst. Previously, he held a faculty position at Rutgers University from 2019 to 2023. He earned his Ph.D. in Computer Science from Purdue University (2019) and B.E. from Shanghai Jiao Tong University (2013). His research focuses on secure, intelligent, and transparent computing systems, particularly at the intersection of security, AI, and software systems. Key areas include integrating machine learning into software systems, ensuring algorithmic security through program analysis, and developing novel system architectures. Professor Ma's work has been recognized with prestigious awards, including the NSF CAREER Award (2023), and distinguished paper awards at USENIX Security (2017) and NDSS (2016). He actively contributes to the academic community through editorial roles and program committees in security, privacy, and software engineering. His research explores topics like backdoor attacks, AI safety, and bias mitigation in large language models. Recent articles emphasize defense mechanisms against adversarial attacks, watermarking techniques, and automated debugging systems for machine learning pipelines.

Prakash Muraliمشاهده پروفایل

دانشیار

• Quantum Computing
• Quantum Architecture
• Resource Estimation
• +۳ مورد دیگر

Prakash Murali is an Associate Professor in the Department of Computer Science at Cambridge University, specializing in quantum computing, quantum architecture, and resource estimation. He previously worked as a quantum architect at Microsoft, where he contributed to the Azure Quantum Resource Estimator. He earned his Ph.D. in Computer Science from Princeton University in 2021, with a dissertation recognized by the ACM SIGARCH/IEEE CS TCCA Outstanding Dissertation Award. His research focuses on bridging the gap between quantum algorithms and hardware through compiler and architecture innovations. His awards include the ACM SIGARCH/IEEE CS TCCA Outstanding Dissertation Award (2022), Communications of ACM Research Highlights (2022), and the IBM PhD Fellowship (2021). He leads a research group comprising PhD students (e.g., Sanaa Sharma and Dmitry Filippov), MPhil candidates, and undergraduate researchers. Key contributions include the TriQ compiler framework for quantum systems and the TimeStitch technique for decoherence mitigation. His work has been adopted in industry compilers and has influenced quantum benchmarking practices.

David I. Augustمشاهده پروفایل

استاد

• Compilers
• Computer Architecture
• Parallel Processing
• +۴ مورد دیگر

David I. August is a Professor of Computer Science at Princeton University, affiliated with the Department of Electrical Engineering. He earned his Ph.D. from the University of Illinois at Urbana-Champaign in 2000. His research focuses on compilers and computer architecture, emphasizing synergistic design between compilers and microarchitecture. He leads the Liberty Research Group, which explores topics such as automatic parallelization, memory profiling, and speculative execution. August joined Princeton in 1999 as a lecturer, advancing to full professor in 2012. He has served as program chair for MICRO 2009 and on committees for ISCA, PLDI, and ASPLOS. His notable accolades include the IEEE Fellow designation, Best Paper Awards at PLDI and CGO, and teaching awards from Princeton's School of Engineering. His work spans compiler optimizations, hardware-software co-design, and security architectures like TrustGuard. Recent research includes GPU scheduling (GhOST), memory profiling frameworks (PROMPT), and instruction prefetching (PDIP). He advises over 20 graduate students, many now leading roles at tech companies and academia. August teaches courses such as COS-126 (Intro to CS), COS-375 (Computer Architecture), and graduate seminars. His projects often bridge theory and practice, with tools like NOELLE and Liberty Research Group initiatives advancing compiler infrastructure and parallelism extraction.

Josef Dickمشاهده پروفایل

استاد

• Numerical Integration
• Quasi-Monte Carlo Rules
• Number Theory
• +۵ مورد دیگر

Professor Josef Dick serves as a Professor and Deputy Head in the School of Mathematics & Statistics at the University of New South Wales (UNSW). With a distinguished career in computational mathematics, he has established himself as a leading researcher in numerical integration methods and quasi-Monte Carlo theory. His work bridges theoretical mathematics with practical computational applications across various scientific domains. Dr. Dick earned his PhD in Mathematics from UNSW in 2004 and his MSc in Mathematics from the University of Salzburg in 2001. His academic journey reflects a strong foundation in both theoretical and applied mathematics, which has informed his subsequent research contributions. Professor Dick's research primarily focuses on numerical integration and quasi-Monte Carlo rules , employing techniques from number theory , abstract algebra (particularly finite fields), discrepancy theory , wavelet theory , and statistics . His work provides rigorous analysis of practical algorithms for computational problems, with implementations often provided in Matlab to bridge theory and application. His research has successfully addressed point distributions on the unit cube for numerical integration, completely uniformly distributed sequences for Markov chain quasi-Monte Carlo algorithms, and explicit constructions of uniformly distributed points on the sphere. Analysis of his recent publications (2022-2025) reveals a consistent focus on advancing quasi-Monte Carlo methods, with increasing integration of machine learning techniques and applications to complex computational problems. His work demonstrates strong interdisciplinary connections between pure mathematics, computational science, and practical engineering applications, particularly in uncertainty quantification and high-dimensional numerical integration. Discovery project from Australian Research Council (2012-2014): "Mathematics in the round - the challenge of computational analysis on spheres" Queen Elizabeth II Fellowship from Australian Research Council (2010-2014): "Algebraic methods for Markov Chain Monte Carlo and quasi-Monte Carlo" UNSW Vice Chancellor Fellowship (2006-2009) Professor Dick has supervised numerous PhD and Honours students working on topics including Quasi-Monte Carlo methods, Discrepancy Theory, Markov chain Monte Carlo, and Uncertainty Quantification. His research has been supported by significant grants from the Australian Research Council, including serving as Chief Investigator on multiple projects. Beyond his research, he serves as an Editor for the Journal of Complexity and Journal of Approximation Theory, demonstrating his leadership in the mathematical community. He teaches courses in Algebra and Mathematical Computing for Finance at UNSW.

Tom Leinsterمشاهده پروفایل

استاد

• Category Theory
• Metric Geometry
• Algebra
• +۳ مورد دیگر

Tom Leinster is a mathematician at the University of Edinburgh, specializing in category theory, metric geometry, and their applications to areas such as algebra, topology, and mathematical biology. His research focuses on the concept of magnitude, a measure for metric spaces and enriched categories, as well as entropy and diversity. He has authored influential books including *Basic Category Theory* and *Entropy and Diversity: The Axiomatic Approach*. Leinster's work bridges foundational mathematics with interdisciplinary applications, emphasizing the interplay between abstract structures and concrete problems. His research interests span category theory, metric geometry, algebraic topology, and mathematical biology. Key contributions include foundational work on magnitude and its connections to geometric measure theory, entropy characterization, and categorical frameworks for diversity measurement. Leinster also engages in mathematical education and ethics, advocating for responsible research practices. Notable publications include recent advancements in magnitude homology of Euclidean sets, extremal magnitude in metric spaces, and entropy modulo primes. His work often highlights interdisciplinary applications, such as biodiversity quantification and information-theoretic foundations.