Dr. Ku Cheng Yeaw is a Senior Lecturer at the Division of Mathematical Sciences, School of Physical and Mathematical Sciences, Nanyang Technological University (NTU). He holds a PhD from Queen Mary, University of London (2005) and has held prior academic positions at the California Institute of Technology (Harry Bateman Research Instructor, 2005–2008) and the National University of Singapore (Visiting Fellow/Lecturer/Senior Lecturer, 2008–2016). His research focuses on combinatorics, graph theory, and discrete mathematics, with notable contributions to eigenvalue analysis, intersecting families, and extremal set theory. He has an extensive publication record spanning over two decades, addressing topics such as hypergraphs, permutation patterns, and spectral properties of graphs. Dr. Ku has not been explicitly noted for awards or student advisement in the provided text.
Antonio Guimarães is a postdoctoral researcher at the IMDEA Software Institute in Madrid, Spain. His research focuses on practical aspects of Fully Homomorphic Encryption (FHE), including verifiable FHE, fast bootstrapping algorithms, and efficient homomorphic evaluation of cryptographic primitives. He holds a Ph.D. in Computer Science from the University of Campinas (2019-2023), where he also completed his MSc (2017-2019) and Computer Engineering degree (2012-2016). During his Ph.D., he was a visiting student at Aarhus University (2022-2023). His work emphasizes privacy-preserving technologies and verifiable computation, with applications in secure cloud computing and encrypted machine learning. Education: Ph.D. in Computer Science, University of Campinas (2019-2023) Visiting Ph.D. Student, Aarhus University (2022-2023) MSc in Computer Science, University of Campinas (2017-2019) Computer Engineering, University of Campinas (2012-2016) His research interests include advancing FHE efficiency, developing verifiable computation frameworks for encrypted data, and exploring practical implementations of post-quantum cryptographic algorithms. He has presented work at venues such as CRYPTO, ASIACRYPT, and CHES, and contributed to open-source cryptographic libraries like MOSFHET and HELIOPOLIS. His recent projects focus on homomorphic evaluation of neural networks and optimizing FHE for real-world applications. His publications highlight contributions to bootstrapping algorithms, verifiable computation over approximate arithmetic, and privacy-preserving machine learning. These works emphasize balancing cryptographic security with computational efficiency. Grants and Collaborations: Collaborations include projects on secure transciphering for MPC and high-performance seismic data processing in cloud environments. His work often bridges theoretical cryptography with practical software implementations. Labs/Teams: His research is conducted within the IMDEA Software Institute’s cryptography group, focusing on applied cryptography and privacy-preserving technologies.
Yong Kiam Tan is a research scientist at the Institute for Infocomm Research (I²R), A*STAR, Singapore, and holds a joint appointment as a Nanyang Assistant Professor at the College of Computing and Data Science, Nanyang Technological University (NTU), Singapore. He earned his PhD in Computer Science (Pure and Applied Logic) from Carnegie Mellon University, advised by Prof. André Platzer, under the A*STAR National Science Scholarship. His research lies at the intersection of formal methods, interactive theorem proving, and automated reasoning, with applications in hybrid systems, compiler verification, and cybersecurity. He has made significant contributions to the CakeML and KeYmaera X projects, focusing on verified compilation, deductive verification of differential equations, and formalized mathematics. The 15 most recent publications reflect a strong trend in formally verified automated reasoning, certified algorithms, and applications in both classical and emerging domains such as neural networks and cryptography. His work consistently appears in top-tier venues like POPL, PLDI, CAV, and ITP, emphasizing end-to-end verification from logic to executable code. Distinguished Paper Award at CAV 2024 Best Paper and Best Repeatability Evaluation Award at HSCC 2022 Best Tool Paper Award at FM 2019 Peter Landin Prize at IFL 2015 CMU SCS Distinguished Dissertation Award 2022 Singapore NRF Fellowship Class of 2024 He actively advises students and researchers at NTU and A*STAR, collaborates internationally with experts such as Magnus Myreen, André Platzer, and Jakob Nordström, and has secured competitive funding including the NRF Fellowship. He has served on program committees for CPP, ITP, TACAS, and PLDI Artifact Evaluation, demonstrating active engagement in the research community. He leads a research team working on verified tools for automated reasoning and hybrid systems, with current members including Wei-Lin Wu, Joe Watt, Shuhan He, and several student researchers. His group maintains verified proof checkers in CakeML and contributes extensively to the Archive of Formal Proofs (AFP) in Isabelle/HOL.
Aseem Rastogi is a Senior Principal Researcher at Microsoft Research India specializing in programming languages, type systems, program verification, and software security. He is a core designer and developer of F*, a language for program verification, and has made significant contributions to Project Everest, which builds verified secure communications components including cryptographic libraries and parsers. Dr. Rastogi earned his PhD from the University of Maryland, College Park under Michael Hicks and completed his M.S. at Stony Brook University with Rob Johnson. His research spans formal methods, programming language theory, and practical security applications, with recent work focusing on integrating Large Language Models with formal verification techniques. His publication record demonstrates expertise across multiple domains including concurrent separation logic, secure multi-party computation, and verified systems programming. Recent work shows a clear trend toward applying LLMs to traditional verification challenges, with publications on memory safety, Rust compilation error fixing, and loop invariant generation. Dr. Rastogi has served on numerous conference program committees including as PC co-chair for ISEC 2024 and Diversity, Equity, and Inclusion co-chair for POPL 2024. He has organized workshops such as VeriCrypt and taught F* at multiple summer schools, demonstrating strong commitment to academic community building. As part of Project Everest, he collaborates across Microsoft Research labs to develop verified security-critical components. His work on EverParse has hardened attack surfaces through formally proven parsers, while CrypTFlow enables secure medical image analysis through privacy-preserving machine learning techniques.
Aymeric Fromherz is a researcher at Inria Paris, affiliated with the Prosecco Team, focusing on formal methods for secure systems. His work bridges programming languages, computer security, and computational law, with significant contributions in verified systems and cryptographic software. Research Interests: His research spans formal verification, programming languages (especially Rust), dependent types, separation logic, and the application of formal methods to legal computation via the Catala language. He develops high-assurance software with a focus on memory safety, concurrency, and correctness. Publications Trends: His recent publications (2020–2025) reflect a strong trend toward verified systems: from memory allocators (StarMalloc) and cryptographic primitives (HACL×N, EverCrypt) to legal verification (CUTECat, Catala). These works emphasize correctness, performance, and practical deployment, often in top-tier venues like POPL, ICFP, OOPSLA, and S&P. Scientific Awards: ACM SIGSAC Dissertation Award A.G. Milnes Dissertation Award Distinguished Artifact Award (ESOP 2025) Best Tool Paper Award (ESOP 2024) Spotlight Paper at ICLR 2021 Advising and Grants: He collaborates closely with researchers across institutions, mentoring students and co-developing tools and frameworks. His involvement in the Everest Project indicates long-term, large-scale funding for high-assurance software. He has contributed to grant-funded efforts in verified cryptography and formal legal systems. Labs and Teams: He is a core member of the Prosecco team at Inria, which specializes in computer security and formal methods. He was previously part of the Everest Project at Carnegie Mellon University, a multi-institution effort to build verified, industrial-grade cryptographic software.
Guinevere F Eden is a tenured Professor in the Department of Pediatrics at Georgetown University and serves as Director of the Center for the Study of Learning (CSL) . Her research focuses on the neuroscience of developmental dyslexia , using behavioral measures and brain imaging techniques like functional/structural MRI to study reading disabilities and remediation strategies. Primary appointment: School of Medicine - Pediatrics Collaborations: Wake Forest School of Medicine and Gallaudet University Professional roles: Past-President of the International Dyslexia Association , editorial board member for journals including Annals of Dyslexia , Dyslexia , and Human Brain Mapping Her work explores neural correlates of learning disabilities , bilingual reading differences, and neurobiological impacts of instruction modes. Supported by NIH and NSF grants, she investigates brain plasticity during reading remediation and cross-linguistic neural representations. Recent publications highlight cerebellar activation patterns in combined reading/math disabilities, gray matter differences in bilingual populations, and functional neuroanatomy of arithmetic in mono- and bilingual cohorts. Her research bridges pediatric neuroscience and educational interventions . As a leader in Interdisciplinary Program for Neuroscience (IPN) , she mentors students through neuroimaging studies on language processing, skill acquisition, and sensory experience effects on brain development. CSL teams collaborate with institutions to advance understanding of developmental cognitive neuroscience and translational clinical applications.
Charles Burnett is Professor of the History of Islamic Influences in Europe at the Warburg Institute, University of London. His distinguished academic career has focused on documenting, editing, and translating scientific and philosophical texts that were transmitted from Arabic into Latin during the Middle Ages. Professor Burnett received his BA in Classics from Cambridge University in 1972 and completed his PhD in Modern and Medieval Languages at the same institution in 1976. His academic journey included positions as Junior Research Fellow at St John's College, Cambridge (1976-79), Senior Research Fellow at the Warburg Institute (1979-82), and Leverhulme Research Fellow at the University of Sheffield (1982-84, 1985), with an intervening year as Member of the Institute for Advanced Study, Princeton (1984-85). He was appointed Lecturer at the Warburg Institute in 1985 and promoted to Professor in 1999. Burnett's research encompasses several interconnected domains: Transmission of Knowledge : The transfer of scientific and philosophical texts from the Arab world to medieval Europe, particularly through Arabic-Latin translations Medieval Astronomy and Astrology : Critical editions of works by Abu Ma'shar and other key figures, examining both theoretical frameworks and practical applications History of Numerals and Arithmetic : Studies on the introduction and adoption of Hindu-Arabic numerals in European mathematical practice Palaeography : Analysis of manuscript traditions, including the writing of numerals and magical texts Magical Practices : Investigation of divinatory techniques such as scapulimancy and geomancy across cultural boundaries Jesuit Cultural Exchange : Examination of cultural transmission between Europe and Japan during the "Christian Century" His scholarly output includes numerous monographs, critical editions, and over 200 articles. Major publications include "Magic and Divination in the Middle Ages" (1996), "Arabic into Latin in the Middle Ages" (2009), and "Numerals and Arithmetic in the Middle Ages" (2010). Burnett's work reveals how medieval translators adapted Arabic scientific knowledge for European contexts, transforming both the content and the institutional frameworks for scientific learning. Professor Burnett has supervised numerous doctoral students whose research extends his scholarly legacy. His current supervisees include Beatrice Bottomley, Arianna Dalla Costa, and Dimitrios Roussos. Former students such as Helena Avelar and Juan Acevedo have established themselves as significant scholars in medieval intellectual history. Beyond traditional academic venues, Burnett has shared his expertise through media appearances including BBC's "In Our Time" and documentaries for Arte and the Japanese Broadcasting Corporation. His research continues to illuminate the complex processes through which scientific knowledge traversed cultural and linguistic boundaries during the medieval period.
Pasi Luukka is a Full Professor (tenured) at the LUT Business School, Lappeenranta University of Technology (LUT University), Finland, where he is affiliated with the Department of Business Studies. His research bridges computational intelligence, fuzzy systems, and business decision-making, with a strong emphasis on practical applications in finance, innovation, and industrial performance. His research interests include: Fuzzy Logic and Soft Computing Multiple-Criteria Decision Making (MCDM) Machine Learning and Feature Selection Real Option Valuation under Uncertainty Financial Forecasting and Trading Strategies Innovation and Knowledge Management His recent publications (2022–2025) show a strong trend in enhancing fuzzy classification methods (e.g., fuzzy k-NN), developing aggregation operators (OWA, Bonferroni), and applying fuzzy logic to real-world problems such as stock market prediction, R&D investment analysis, and water-energy nexus modeling. His work frequently appears in top-tier journals like Expert Systems with Applications , Information Sciences , and Fuzzy Sets and Systems . He has received recognition through a substantial body of peer-reviewed publications and active collaboration with leading researchers in fuzzy systems and decision science. Pasi Luukka advises several graduate students, including Mahinda Mailagaha Kumbure and Christoph Lohrmann, and has contributed to numerous research projects involving real options, innovation evaluation, and intelligent systems. He has served as a peer reviewer for journals such as Decisions in Economics and Finance , Group Decision and Negotiation , and Soft Computing . He is a key member of a research group focused on intelligent decision support systems, fuzzy logic applications, and computational methods in business and finance. The team actively publishes and collaborates on interdisciplinary projects involving energy, finance, and industrial systems.
Jan Stoklasa is a Full Professor in the Department of Business Studies at LUT Business School, LUT University, Lappeenranta, Finland. He also holds the position of Assistant Professor in the Department of Applied Economics at Palacký University, Olomouc, Czech Republic, since 2015. His research lies at the intersection of fuzzy logic, decision sciences, and behavioral economics. His primary research interests include Fuzzy Logic , Multi-Criteria Decision Making (MCDM) , Linguistic Modeling , Uncertainty in Evaluation , and Behavioral Operations Research . He investigates how human cognition, emotions, and risk attitudes influence expert and consumer decisions, particularly under uncertainty. His work integrates computational intelligence with practical applications in energy systems, supply chain management, and business analytics. Recent publications (2023–2025) demonstrate a strong trend in developing advanced fuzzy-based decision support methods, including fuzzy TOPSIS with OWA operators, possibilistic pay-off methods for real options, and q-rung orthopair fuzzy models for crisis management. He also explores residential demand response behavior using agent-based modeling and causal maps for knowledge development assessment. Scientific Awards and Recognition: While specific awards are not listed in the text, his extensive publication record in top-tier journals such as Information Sciences , Fuzzy Sets and Systems , Applied Energy , and Expert Systems with Applications indicates significant recognition in his field. He actively serves as a peer reviewer for journals including Fuzzy Sets and Systems , Applied Soft Computing , and Journal of Business Research . Advising and Grants: Although no formal list of students is provided, his collaborative publications with multiple co-authors suggest active supervision and mentoring. He is likely involved in research grants related to energy systems, decision support, and cognitive modeling, given the applied nature of his work. His collaborations with researchers like Pasi Luukka and Mikael Collan indicate participation in funded projects. Labs and Research Teams: Jan Stoklasa is associated with research groups focusing on computational intelligence, decision support, and energy systems at LUT University. His work on fuzzy systems and cognitive maps suggests involvement with interdisciplinary teams bridging computer science, management, and behavioral sciences.
Tonje Amland is a Research Fellow at the Department of Special Needs Education, University of Oslo (UiO), affiliated with the CREATE Centre for Research on Equality in Education. Her work focuses on developmental psychology, early cognitive development, and mathematical learning difficulties. She has held roles including Postdoctoral Researcher (2023–present), University Lecturer (2022–2023), and Doctoral Research Fellow (2018–2022). Academic Background: PhD: Department of Special Needs Education, UiO (2018–2022) MSc Child Development, Institute of Education, UCL (2014–2015) BA in Languages, University of Bergen (2008–2010) Research Interests: Her research examines numeracy development, mindset in mathematics, home learning environments, and children with high learning potential. Methodological expertise includes structural equation modeling and meta-analysis. Teaching: Courses include SPED4400, SPED4010, and SNE4200. She mentors students in special needs education and developmental psychology. Labs/Groups: Active in CREATE, Literacy and Numeracy in Context (LiNCon), and the NumLit project. Her work bridges educational practice and cognitive science to address learning disparities.
Chris Brzuska is an Associate Professor at Aalto University's Department of Mathematics and Systems Analysis, part of the School of Science. His research focuses on cryptography, security protocols, and formal verification of cryptographic systems. He has contributed to key areas including post-quantum cryptography, white-box security, obfuscation, and game-based security models. His work often involves rigorous analysis of cryptographic primitives and protocols, emphasizing practical security and formal proofs. Brzuska's recent research includes studies on LWE assumptions, garbling schemes, TLS security, and resistance against side-channel attacks. He has authored or co-authored over 30 publications in top-tier conferences and journals, such as CRYPTO, EUROCRYPT, and ASIACRYPT. His work bridges theoretical foundations and applied cryptography, addressing real-world security challenges in protocols like TLS and messaging frameworks.
Dr. Matt Skerritt is a Lecturer in Applied Mathematics at the School of Science, RMIT University, located at City Campus, Australia. His research focuses on Applied Mathematics, Pure Mathematics, and Numerical and Computational Mathematics. He specializes in optimization algorithms, number theory, and computational methods, with notable contributions to the Douglas-Rachford method, Giuga’s primality conjecture, and algorithm extensions like the PSLQ algorithm. He also explores educational tools using software such as Mathematica and Maple, emphasizing computational learning and pedagogy. His work bridges theoretical mathematics with practical applications in computational science and education. Research interests include the dynamics of iterative methods, integer relations, and primality testing, alongside the development of educational resources for computational mathematics. His publications span topics like geometric algorithms, numerical analysis, and symbolic computation, reflecting a commitment to advancing both theoretical and applied mathematical research.
Anu Laine is a Senior University Lecturer in mathematics education at the University of Helsinki , affiliated with the Faculty of Educational Sciences and the Department of Education . She also serves as Vice-Dean (Academic Affairs) at the Faculty of Educational Sciences. Her research focuses on mathematics education, emphasizing non-standard problem-solving and affective factors in learning from student, teacher, and teacher education perspectives. Her research projects include initiatives like Future Problem-Solvers! (Finnish Flagship Programme) and studies on mathematics motivation in primary education across Europe. She supervises bachelor, master, and PhD theses and teaches mathematics education courses. Key funding sources include the Research Council of Finland and private foundations. Her publications highlight systematic reviews on mathematical word problem-solving interventions, psychometric assessments of learning disabilities, and the interplay between teaching environments and student motivation. Notable works include analyses of teacher beliefs, student motivation profiles, and cross-cultural comparisons of problem-solving practices in primary education. Laine’s work integrates cognitive, emotional, and pedagogical dimensions of learning, with a focus on fostering mathematical competence and addressing educational equity through innovative teaching strategies. She is actively involved in curriculum development and teacher training initiatives.
Dr. Erin Anne Maloney is an Associate Professor in the Department of Psychology at the University of Ottawa, Faculty of Social Sciences, and holds the Canada Research Chair in Academic Achievement and Well-Being. Her research integrates cognitive psychology, developmental psychology, and education, with a focus on math anxiety and its impact on learning. University: University of Ottawa School: Faculty of Social Sciences Department: Department of Psychology Rank: Associate Professor Canada Research Chair in Academic Achievement and Well-Being Research Interests: Her work centers on the cognitive and emotional factors affecting math learning, particularly math anxiety, parental and teacher influences, and numerical cognition. She investigates how anxiety interferes with arithmetic fluency, word-problem solving, and cognitive reflection, with implications for educational practice and policy. Publication Trends: Her recent publications (2019–2022) reflect a strong interdisciplinary focus on math learning, involving collaborations across psychology, education, and cognitive science. Key themes include the home math environment, language in math, teacher anxiety effects, and methodological rigor in online research. Scientific Awards: Canada Research Chair in Academic Achievement and Well-Being Advising and Grants: Dr. Maloney mentors students and leads research funded by major Canadian agencies including the Social Sciences and Humanities Research Council (SSHRC), the Natural Sciences and Engineering Research Council (NSERC), the Government of Canada, the Province of Ontario, and the University of Ottawa. She advocates for supporting girls and women in STEM and promotes accessibility and equity in education. Labs and Teams: While specific lab names are not mentioned, her collaborative work with researchers across North America suggests active participation in interdisciplinary research teams focused on math cognition, education, and emotional well-being.
Dr. Daniel Han is a researcher at the University of New South Wales (UNSW), affiliated with the School of Mathematics and Statistics and the Department of Mathematics and Statistics. His work focuses on interdisciplinary research at the intersection of mathematics, neurosciences, and cell biology, with a particular emphasis on stochastic processes and random walks. His current research interests include applying mathematical models to neurodegenerative diseases and healthcare challenges, such as telemedicine in rural aged care. Dr. Han's profile can be found at his UNSW webpage . His research spans diverse topics, including biomarker development for Parkinson’s disease, intercultural competence through virtual exchange, and moduli spaces in algebraic geometry. He has contributed to both theoretical and applied domains, publishing widely in journals across mathematics, neurology, and education. His recent work highlights the application of mathematical frameworks to real-world problems in healthcare and education.
