Kees Dorst is a Professor of Transdisciplinary Innovation at the TD School of the University of Technology Sydney. He bridges philosophical understandings of design with practical applications, focusing on tackling complex societal challenges through designerly thinking. His research develops methodologies for strategic transformation and networked problem-solving in public sectors. Professor of Transdisciplinary Innovation, UTS Director, Designing Out Crime Research Centre International keynote speaker and advisor on design thinking Research Interests Dorst specializes in: Transdisciplinary innovation for societal challenges Design thinking and co-evolutionary processes Reframing complex problems in public policy Design cognition and metacognition Urban environment design for safety Recent Research Trends show increasing focus on: Hypercomplex problem-solving frameworks Strategic transformation through design Cognitive models in design processes Public sector innovation methodologies Teaching & Leadership includes: Bachelor of Creative Intelligence and Innovation Master of Creative Intelligence and Strategic Innovation Founding the Designing Out Crime Research Centre International design research symposium leadership
Professor Maciej Dunajski is a University Professor of Mathematical Physics at the Faculty of Mathematics, University of Cambridge, and a Senior Lecturer at Clare College Cambridge. His career spans institutions including Oxford and Cambridge, with roles ranging from Tutorial Fellow to Senior Research Associate. He holds a DPhil from the Mathematical Institute, Oxford, and was awarded the title of Professor by the President of Poland in 2011. University Professor of Mathematical Physics, Faculty of Mathematics, University of Cambridge (2021–present) University Reader in Mathematical Physics, University of Cambridge (2020–2021) Fellow at Clare College Cambridge (2003–present) Author of Solitons, Instantons & Twistors (Oxford University Press, 2009) His research focuses on Twistor Theory , Integrable Systems , and Differential Geometry , with significant contributions to self-dual gravity, Einstein-Weyl structures, and geometric solutions to nonlinear equations. His work bridges mathematics and theoretical physics, including applications to quantum gravity and black hole thermodynamics. Dunajski's recent publications highlight advancements in conformal geometry, null Kähler structures, and higher-dimensional relativity. His collaborations span researchers like K. P. Tod, R. Penrose, and L. Mason. He is based in Room B2.14 at DAMTP, Cambridge, and maintains an active research group in high-energy physics.
Professor Danilo Mandic is a leading academic in Machine Intelligence and Signal Processing at Imperial College London's Department of Electrical and Electronic Engineering. He holds roles including President of the International Neural Network Society and Distinguished Lecturer for IEEE Computational Intelligence and Signal Processing Societies. His research spans Statistical Learning, Wearable Sensing (Hearables), Financial Signal Processing, and Tensor Networks for Big Data. Key contributions include pioneering in-ear physiological sensing and developing quaternion-based adaptive filters. He has authored over 600 publications, including seminal monographs on neural networks and complex-valued signal processing. Education: PhD in Nonlinear Adaptive Signal Processing from Imperial College (1999). Professional accolades include the 2019 Dennis Gabor Award and multiple IEEE Best Paper Awards. His labs include the Financial Signal Processing & Machine Learning Lab and collaborations with the Centre for Neurotechnology. He advises numerous students and leads projects on AI ethics, graph signal processing, and biomedical applications. His work emphasizes translating research into educational curricula via participatory sensor-based learning.
Dr. Katrin Leschke is an Associate Professor in Mathematics at the University of Leicester and Deputy Director for Postgraduate Research (PGR) in the College of Science and Engineering. She holds a Royal Society Short Industry Fellowship (2022–2023). Her research focuses on surface theory, integrable systems, and applications of discrete geometry to machine learning, engineering, and chemistry. She has held research positions at TU Berlin, University of Massachusetts Amherst, and University of Augsburg, where she earned her habilitation. She serves as an external examiner at the University of Manchester and participates in committees like European Women in Mathematics and the London Mathematical Society's SLAM committee. Education: Diplom and PhD in Geometry from TU Berlin Habilitation from University of Augsburg Her work bridges pure mathematics with applied fields, emphasizing geometric visualization and collaborations across disciplines. Key research areas include minimal surfaces, Darboux transformations, and non-axisymmetric turbine design optimization. She is affiliated with the Creative Computing Research Group and AIDAM, fostering interdisciplinary innovation. Notable contributions include studies on integrable systems linking CMC surfaces, isothermic surfaces, and constrained Willmore surfaces, alongside applications in engineering fluid dynamics. Awards highlight her industry-academia collaboration excellence.
Professor Farookh Hussain is a distinguished academic at the School of Computer Science , University of Technology Sydney , specializing in Artificial Intelligence , Cloud Computing , and Software Engineering . His research spans diverse sectors including agriculture, manufacturing, healthcare, and transportation. Affiliated with the Australian Artificial Intelligence Institute (AAII) , he leads impactful work in business intelligence and carbon credit systems. Key research areas: AI applications, blockchain for provenance, carbon credit analytics Active in Masters/PhD supervision and cloud computing education Research Highlights : Developed KACINO framework for carbon dynamics modeling Created hybrid cybersecurity frameworks for supply chain risk management Advanced chatbot dialogue breakdown solutions through systematic reviews Proposed hypercomplex knowledge graph recommenders Published extensively on carbon credit price prediction and blockchain storage methods Contributions to water demand forecasting and collaborative robotics adoption Grant Activities : Secured funding from Hampton Capital Asset Management , Innovation Connections , and Science and Industry Endowment Fund Projects include LLM-driven text-to-SQL conversion , blockchain for melanoma data , and AI for storm water management
Guandong Xu is a Professor in the School of Computer Science at the University of Technology Sydney (UTS), where he has been employed since 2012. He also serves as the Director of the UTS-Providence Smart Future Research Centre, which focuses on disruptive technology for sustainability, and leads the Data Science and Machine Intelligence Lab dedicated to research excellence and industry innovation in data science and artificial intelligence. Dr. Xu holds a PhD in Computer Science from Victoria University, Australia, along with MSc and BSc degrees in Computer Science and Engineering. After holding various research positions at European and Australian universities, he joined UTS in 2012 and was promoted to Associate Professor in January 2017, then to Professor in January 2019. His research spans data mining, machine learning, social computing, recommender systems, text mining, predictive analytics, and user behavior modeling. He has published over 240 papers in these areas with increasing citations from academia. His recent work demonstrates a strong focus on integrating large language models with recommendation systems, causal inference in recommendation, multimodal learning, and fairness in AI systems. His publications reveal sophisticated graph-based approaches and addressing challenges in dynamic recommendation scenarios, particularly through temporal modeling and hypergraph structures. Dr. Xu has received numerous prestigious awards including the Digital Disruptors Winner for ICT Research Project of the Year (2021), eBay's Leaders' Choice Award (2021), and was elected Fellow of Institution of Engineering and Technology (IET), UK (2021) and Fellow of Australian Computer Society (ACS) (2022). He has shown strong academic leadership as founding Editor-in-Chief of Human-centric Intelligent Systems Journal, Assistant Editor-in-Chief of World Wide Web Journal, and founding Steering Committee Chair of the International Conference of Behavioural and Social Computing Conference. He has supervised over 25 high degree research students and secured over $8 million in research funding from ARC, government, and industry sources, including projects like 'Smart Personalized Privacy Preserved Information Sharing in Social Networks' and 'A Secured Smart Sensing and Industry Analytics Facility for Industry 4.0.' Dr. Xu directs the Data Science and Machine Intelligence Lab at UTS, which aligns with UTS research priority areas in data science and artificial intelligence. The lab focuses on research excellence and industry innovation across academia and industry, with particular emphasis on developing advanced techniques for recommendation systems, knowledge graphs, and multimodal learning applications.
Cinzia Cerroni is a Full Professor at the University of Palermo , affiliated with the Department of Mathematics and Computer Science under the School of Basic and Applied Sciences . She serves as Delegate for the Coordination of the University Orientation and Tutoring Center (COT) since November 4, 2021, and holds regular office hours in Room 105 of her department. Research focuses on the history of mathematics , algebraic structures , and mathematical education Key contributions to cryptographic history , non-Archimedean geometries , and gender representation in STEM Active in teacher collaboration projects and interdisciplinary education Her 15 recent publications span topics from tessellations and bicomplex numbers to wartime impacts on mathematical collaboration and educational methodologies. Subfields include group theory , historical algorithms , geometric patterns , and cryptographic theory . Contact: cinzia.cerroni@unipa.it | Phone: +3909123891092
Professor Danilo P. Mandic, affiliated with Imperial College London, UK, is a leading researcher in signal processing, machine learning, and biomedical signal analysis. His work spans quaternion algebra, tensor networks, and neural networks for real-world applications. 2025: Published 11+ works on EEG/PPG analysis, quantum learning, and tensor-based LLM compression 2024: Active in interpretable transformers, graph learning for financial data, and hearable devices Research focuses on hypercomplex signal processing, graph neural networks, and medical AI applications. Recent work explores quaternion calculus for signal processing, tensor network structures for LLMs, and hearable device optimization. Key publication trends include: 2025 emphasis on quantum-aware learning, 2024 graph-based time series clustering, and 2023 foundational work on graph CNNs and matched filtering approaches. Collaborates extensively with Dongpo Xu, Sayed Pouria Talebi, Clive Cheong Took, and Tobias Reichenbach on projects involving ear-EEG, ECG enhancement, and financial sentiment analysis.
Prof. SEHER ASLANCI is a Professor of Mathematics Education at ALANYA ALAADDİN KEYKUBAT UNIVERSITY, Faculty of Education. Her academic journey includes roles such as Vice Dean (2022–2023) and Department Head (2017–2018). She holds a Doctorate in Geometry from Atatürk University (2011). Research focuses on differential geometry (tensors, Riemannian structures) and mathematics education (bibliometric analyses of pedagogical methods like inquiry-based learning and realistic mathematics education). Publications span 20+ years, emphasizing geometric structures and educational methodologies. Awards include TUBITAK's UBYT grants (2009, 2011, 2014). Administrative roles include Scientific Research Commission membership (2020–2021) and Mevlana Exchange Program coordination (2016–2017). Education: Integrated PhD (Geometry), Atatürk University, 2011 Mathematics Teaching Programme, Atatürk University, 1999–2004 Awards: Encouragement of International Scientific Publications (TUBITAK UBYT-2014) Encouragement of International Scientific Publications (TUBITAK UBYT-2011) Encouragement of International Scientific Publications (TUBITAK UBYT-2009) Research themes blend pure geometry (tensor bundles, complex structures) with applied educational studies (bibliometric trends in tech-enhanced learning). Recent work explores heat flux control systems and deformations in geometric structures.
Gregor Weihs is Vice-Rector for Research at the University of Innsbruck, holding a full professorship in Photonics at the Institute for Experimental Physics. He directs the Cluster of Excellence Quantum Science Austria and previously served as Austrian Science Fund (FWF) Vice-President and interim President. His academic journey includes roles at Stanford University, the University of Tokyo, and the University of Waterloo, where he held a Canada Research Chair in Quantum Photonics. Education: MSc (1994, University of Innsbruck), PhD (2000, University of Vienna) awarded 'sub auspiciis praesidentis.' He completed habilitation in Experimental Physics in 2005 at the University of Vienna. Research focuses on quantum photonics, semiconductor optics, and foundational quantum mechanics. Key projects include entangled photon pair generation from nonlinear waveguides, quantum dots, and semiconductor microcavities. He explores quantum communication, many-body interference, and hypercomplex quantum mechanics testing. Awards: Wilhelm Exner Medal, ERC Starting Grant, Canada Research Chair Leadership: Department Head of Experimental Physics (2013–2021), Faculty Council Chair, IQOQI Events Director His work bridges theory and experiment, with contributions to integrated quantum devices and precision tests of quantum foundations.
Harry Millwater is the Samuel G. Dawson Endowed Professor and Associate Chair for Research in the Mechanical Engineering Department at the University of Texas at San Antonio's Margie and Bill Klesse College of Engineering and Integrated Design. With over three decades of academic and research experience, he has established himself as a leading expert in structural mechanics and computational methods. Dr. Millwater's primary research focuses on fracture mechanics, probabilistic structural analysis, sensitivity analysis, and computational mechanics. His work bridges theoretical developments with practical applications in structural reliability, fatigue analysis, and digital twin technologies. He has pioneered methods using hypercomplex variables for sensitivity analysis, which have significantly advanced the field of computational mechanics and structural engineering. His extensive publication record shows a clear evolution from foundational work in probabilistic structural analysis to cutting-edge research in hypercomplex automatic differentiation applied to structural mechanics. Recent publications demonstrate a strong focus on developing arbitrary-order sensitivity analysis methods using hypercomplex mathematics, with applications spanning structural dynamics, fracture mechanics, additive manufacturing, and uncertainty quantification. His scientific recognition includes multiple U.S. Air Force Research Lab Summer Faculty Fellowships awarded in consecutive years (2005-2007). These prestigious awards reflect the practical impact of his research on aerospace engineering applications. Dr. Millwater's research has been supported by significant funding from defense and aerospace sectors, particularly the Air Force Office of Scientific Research. His work on probabilistic methods for risk assessment of airframe digital twin structures represents a major contribution to modern structural integrity assessment. He has also contributed to educational initiatives focused on improving STEM education at Hispanic-serving institutions. His laboratory work centers on computational mechanics, with emphasis on developing and implementing advanced numerical methods for structural analysis. The ZFEM (Complex Variable Finite Element Method) framework appears to be a cornerstone of his research program, enabling high-precision sensitivity calculations that have broad applications across engineering disciplines.
Marija V. Paunović is an Assistant Professor at the Faculty of Hotel Management and Tourism, University of Kragujevac. She holds a PhD in Applied Mathematics and has academic affiliations with institutions in Belgrade and Novi Sad. Education : BSc in Mathematics (Belgrade), Master in Economics (Belgrade), PhD in Technical Sciences (Novi Sad), PhD in Computer Science (Belgrade) Her research focuses on Applied Mathematics, particularly in Fixed Point Theory, Fractional Calculus, Fuzzy Mathematics, Uncertainty Theory, and Decision Theory. Recent work explores fractional differential equations, fuzzy metrics, and multivalued contractions. Select publications (2024–2019) span topics like Darbo fixed point extensions, Wardowski contractions, fuzzy metrics in image processing, and credibility measures. Keywords include Fixed Point Theory, Fractional Calculus, Fuzzy Logic, Nonlinear Analysis, and Mathematical Modeling.
Scott Kaschner is an Assistant Professor in the Department of Mathematics and Actuarial Science at Butler University, College of Liberal Arts and Sciences. His work bridges pure mathematics, applied mathematical biology, and mathematics education. He is actively engaged in research and undergraduate teaching, with a diverse portfolio of scholarly output. Education: Ph.D. in Mathematics, Department of Mathematical Sciences, IUPUI, 2013 M.S. in Theoretical Mathematics, University of Akron, 2008 B.S. in Theoretical Mathematics, University of Akron, 2003 His research interests span Complex Dynamics , particularly Julia sets, rational maps, and bicomplex analysis; Mathematical Virology , including modeling of coronavirus and respiratory syncytial virus (RSV) replication; and Mathematics Education , with focus on student success in introductory courses, assessment design, and interdisciplinary co-teaching. His work reflects a strong interdisciplinary approach, combining deep mathematical theory with real-world applications in biology and pedagogy. The 15 most recent publications reveal a consistent trajectory across three domains: foundational work in complex dynamics and operator theory, applied modeling in virology, and scholarship of teaching and learning in mathematics. The keywords and sub-fields reflect a sophisticated blend of pure and applied mathematics, with increasing engagement in biological modeling and educational research. Scientific Awards: No awards explicitly mentioned in the text. Scott Kaschner has advised or collaborated with numerous students and researchers, particularly evident in his co-authored papers in virology and mathematics education. His involvement in the NSF GK-12 program as a fellow indicates a long-standing commitment to STEM outreach and pedagogical development. He has secured research support through collaborative grants, especially in virology and education. He co-authored an open textbook on linear transformations, contributing to accessible educational resources. He is involved in interdisciplinary research teams, particularly in virology (with Christopher Stobart and others) and mathematics education (with Aubrey Neihaus and others). His work on virus modeling suggests collaboration with biologists, and his educational research involves partnerships across disciplines. These teams reflect a commitment to collaborative, cross-cutting scholarship.
Mojtaba Nayyeri is a Researcher at the University of Stuttgart, working within the Analytic Computing group under the KI institute. His office is located at Universitätsstraße 32, Room 2.302, 70569 Stuttgart, Germany, with contactable phone number +49 711 685 88105. His research centers on Knowledge Graph Embeddings, where he pioneers mathematical frameworks including hypercomplex spaces, stochastic processes, and differential equations to model structured knowledge. This work bridges Artificial Intelligence, Machine Learning, and Natural Language Processing, with significant contributions to semantic web technologies and knowledge representation systems. Nayyeri's publication record (2020-2023) reveals a consistent trajectory toward geometric and topological innovations in knowledge graph representation. He has developed ultrahyperbolic embeddings for heterogeneous structures, neural Itô processes for stochastic trajectory modeling, and hypercomplex space integrations for temporal knowledge graphs, demonstrating how non-Euclidean geometries outperform traditional methods in capturing hierarchical and relational complexities. He actively contributes to the Analytic Computing research group at the University of Stuttgart, which specializes in advanced computational methodologies for knowledge-intensive systems and large-scale data analysis.
Sandra Ricardo is an Assistant Professor at the University of Trás-os-Montes and Alto Douro (UTAD), Portugal, with a strong academic foundation in Mathematics, holding a PhD from the University of Rouen, France, and a Master’s from the University of Coimbra, Portugal. She is actively engaged in research and educational projects with international impact. PhD in Mathematics, National Institute of Applied Sciences of Rouen, University of Rouen, France (2008) Master's in Mathematics, University of Coimbra, Portugal (2000) Her research interests include Mathematics Education, History of Mathematics, Special Matrices, k-Bronze Fibonacci Numbers, and Mechanical Control Systems. She emphasizes innovative teaching strategies and the integration of historical context into mathematical instruction. Her work bridges theoretical mathematics with practical applications in education and biomedical signal analysis. The most recent publications reflect a dual focus: one stream on advanced algebraic structures such as quaternion Gaussian Bronze Fibonacci numbers and matrix theory, and another on pedagogical innovations in teaching fractions, statistics, and problem-solving in early education. These works highlight her commitment to both pure mathematical research and transformative educational practices. Sandra is involved in significant international projects: TeachersMOD (Erasmus+, EACEA): Modernizing elementary school teacher training in Kurdistan (2023–2025) Mais Conhecimento Melhor Futuro (Calouste Gulbenkian Foundation): Enhancing math, Portuguese, and digital literacy in Guinea-Bissau (2022–2023) These initiatives aim to improve educational access and quality in underserved regions, focusing on curriculum development and teacher capacity building. Sandra has advised and collaborated on numerous research projects, particularly in mathematics education reform and control theory. While no formal list of advisees is provided, her publications indicate strong mentorship and collaborative leadership. She has not received publicly listed scientific awards in the provided text. She contributes to academic outreach through the CIIE (Center for Research in Educational Innovation) and LabDERE (Laboratory of Digital Experimentation and Research in Education), promoting digital tools and innovative pedagogies in educational settings.
