Univ.-Prof. Dr.-Ing. habil. Sven Klinkel is a Professor at RWTH Aachen University , affiliated with the College of Civil Engineering and the Department of Structural Mechanics and Structural Dynamics . He holds leadership roles as Chair of the Senior Council, Faculty Council, and Doctoral Committee. Current research focuses on structural engineering , computational mechanics , and seismic analysis . Key projects include carbon-reinforced concrete structures , isogeometric analysis , and digital fabrication . Recent publications address nonlinear systems , topology optimization , and naturally shaped timber . Contact: dekanat@fb3.rwth-aachen.de
Fosca Giannotti is a Full Professor at Scuola Normale Superiore in Pisa, Italy, and leads the Pisa KDD Lab - Knowledge Discovery and Data Mining Laboratory, a joint research initiative of the University of Pisa and ISTI-CNR. Founded in 1994, the Pisa KDD Lab is one of the earliest research labs focused on data mining. Giannotti is a pioneering scientist in mobility data mining, social network analysis, and privacy-preserving data mining. Her educational background includes a Master Degree in Computer Science from the University of Pisa (1982) with 110/100 cum laude. She has held numerous visiting positions including at MCC in Austin, CWI Amsterdam, UCLA, and the Barabasi Lab at Northeastern University. Giannotti's research focuses on social mining from big data, encompassing smart cities, human dynamics, social and economic networks, ethics and trust, and diffusion of innovations. She has authored more than 300 papers and coordinated tens of European projects and industrial collaborations. Her current work increasingly centers on Explainable AI (XAI), as evidenced by her prestigious ERC Advanced Grant for the XAI project focused on "Science and technology for the explanation of AI decision making." Her recent publications reveal a strong emphasis on trustworthy AI, with research spanning privacy-preserving techniques, fairness in machine learning, human-AI collaboration frameworks, and medical applications of explainable AI. The breadth of her work demonstrates how data mining principles are being applied across diverse domains from social sciences to healthcare. ERC Advanced Grant for XAI project Premio Internazionale Tecnovisionarie 2021 Intelligenza Artificiale Giannotti has coordinated numerous significant projects including SoBigData (the European research infrastructure on Big Data Analytics and Social Mining), XAI, TAILOR (Foundations of Trustworthy AI), HumanE-AI-Net, and AI4EU. As former coordinator of SoBigData, she led an ecosystem of ten cutting-edge European research centers providing an open platform for interdisciplinary data science. She leads the Pisa KDD Lab, which serves as a hub for research on knowledge discovery and data mining. The lab has been instrumental in developing techniques for mobility data analysis, social network mining, and privacy-preserving data analytics, with applications ranging from smart cities to pandemic response.
Erin Wolf Chambers is a Professor in the Department of Computer Science and Engineering at the University of Notre Dame, with a concurrent appointment in the Department of Applied and Computational Mathematics and Statistics. She holds the Snyder Family Mission Collegiate Professorship. Previously, she was at Saint Louis University (SLU) as a Professor in Computer Science and Mathematics. Her research focuses on computational topology and geometry, combinatorial algorithms, and improving STEM education inclusivity. She earned her Ph.D. in Computer Science from the University of Illinois Urbana-Champaign in 2008. Dr. Chambers teaches courses such as Topological Data Analysis and Algorithms. She has been recognized with the Rev. Edmund P. Joyce Award for Excellence in Undergraduate Teaching and serves as an editor for the Journal of Computational Geometry and Journal of Applied and Computational Topology. She is actively involved in initiatives like SafeToC and the Society for Computational Geometry. Her research includes NSF-funded projects, with notable contributions in topological data analysis, geometric algorithms, and educational equity. Over 40 publications span topics like Reeb graphs, medial axis analysis, and plant root morphology. She advises students on cutting-edge interdisciplinary research and advocates for fostering inclusive academic environments.
Adrian Bejan is the J.A. Jones Distinguished Professor of Mechanical Engineering at Duke University, renowned for developing the Constructal Law of design and evolution in nature. His research spans thermodynamics, heat transfer, fluid dynamics, and evolutionary design across biological, geophysical, and technological systems. Education Background: S.B. Massachusetts Institute of Technology (1972) Sc.M. Massachusetts Institute of Technology (1972) Sc.D. Massachusetts Institute of Technology (1975) His work establishes fundamental principles governing flow systems evolution, from river basins to social organizations. The Constructal Law explains why similar patterns emerge in nature, technology, and social structures through evolutionary optimization for access and movement. Recent publications explore universal patterns in roof designs, brachistochrone phenomena, and freedom as a physical principle. Research consistently demonstrates how evolutionary design maximizes flow efficiency in diverse systems. Major Honors: Kimberly-Clark Distinguished Lectureship Award (2023) Turkish Academy of Sciences Prize (2020) Humboldt Research Award (2019) Benjamin Franklin Medal (2018) Ralph Coats Roe Medal (2017) 15 honorary doctorates worldwide He teaches Advanced Topics in Mechanical Engineering, Convective Heat Transfer, and Constructal Theory courses. International collaborations extend his flow optimization principles to aerospace design, energy systems, and social dynamics.
James Maurelle is an Assistant Professor of Studio Art at Clark University, with affiliations in the Visual and Performing Arts department. He holds an MFA from the University of Pennsylvania and a BFA from the San Francisco Art Institute. His practice bridges sculpture, video, and sound art, emphasizing labor-creativity correlations and jazz-influenced composition processes. Key research interests include material transformation, interdisciplinary methods, and cultural narratives through industrial materials. Educational Background: M.F.A., University of Pennsylvania (Weitzman School of Design), 2015 B.F.A., San Francisco Art Institute (Film & Design), 2013 Postgraduate Apprenticeship, The Fabric Workshop (Philadelphia), 2015– Research Interests: Explores labor's intersection with creativity, using tools and materials as instruments. Jazz structures underpin his work ethic, with materials (wood, metal, blood) serving as 'staff paper' for compositions. Recent projects investigate industrial progress, cultural heritage, and material symbolism through installations and performances. Recent Exhibitions/Trends: Focused on durational performances (e.g., 24-hour installations) and site-specific works. Recent shows include POSSIBLE FUTURES (2024) and MOVEMENT at Clark University, emphasizing sound and spatial interventions. Material choices increasingly incorporate organic elements like blood, soil, and vegetation, reflecting ecological and bodily themes. Awards: 2022 Pew Fellowship 2024–2023 Higgins School Major Grants Skowhegan Fellowship (2015) Teaching & Grants: Currently teaches Studio Art at Clark University and has held lectures at Penn State and Rutgers. Recent grants fund experimental material projects and community-based installations. Active residencies include Vermont Studio Center (2024) and Windgate ITE (2022). Labs/Teams: Collaborates with institutions like the Center for Art in Wood and the Fabric Workshop. Leads interdisciplinary projects blending sculpture, sound, and performance.
Viktoriya Ozornova is a Researcher at the Max Planck Institute for Mathematics in Bonn, specializing in algebraic topology with a focus on abstract homotopy theory and higher category theory. Her work explores foundational questions in (∞,n)-categories and their applications to mathematical physics. She collaborates extensively with researchers such as Martina Rovelli, Emily Riehl, and others on topics including model structures, categorical equivalences, and homotopy coherence. Her research has been published in leading journals like Advances in Mathematics , Algebraic & Geometric Topology , and Transactions of the American Mathematical Society . She co-organized workshops on infinity categories and Picard groups of topological modular forms (TMF). She has supervised students including Julian Brüggemann (PhD) and mentored numerous bachelor and master theses on topics ranging from elliptic curves to homotopy theory. Ozornova has taught at institutions including the University of Bochum and Bonn, covering courses in topology, analysis, and number theory. Her pedagogical contributions include designing online curricula for engineering mathematics and organizing seminars on advanced topics like Lie groups and braid theory.
Joanne Mulligan is a Professor at the Macquarie School of Education, Macquarie University, specializing in mathematics and STEM education across early childhood to secondary levels. Her research focuses on early mathematical development, pedagogy, assessment, and curricula, with expertise in educational psychology and teacher education. She has led major projects like the $2.3m Opening Real Science (ORS) Project and currently oversees ARC-funded initiatives exploring spatial reasoning and interdisciplinary learning. Research Interests: Mathematics Education, STEM Education, Cognitive Development, Early Childhood Learning, Teacher Professional Development. Key Projects: Connecting Mathematics Learning with Spatial Reasoning (2017–2020), Enriching Mathematics and Science Learning (2018–2020), and the ORS Project (2013–2017). Contributions: Developed programs like PASA and PASMAP, impacting national and international curricula. Active in global organizations such as ICME and ICMI. Research Trends Mulligan’s recent work emphasizes interdisciplinary approaches, spatial reasoning, and data modeling in early education. Her articles highlight pedagogical frameworks for integrating mathematics and science, enhancing teacher training, and fostering student engagement through collaborative and inquiry-based methods. Grants & Collaborations ARC Discovery Projects: Focus on spatial reasoning (2017–2020) and interdisciplinary learning (2018–2020). Collaborations: International Spatial Reasoning Study Group (IOSTEM), Deakin University, and CSIRO. Labs & Teams Associated with the Centre for Research in Mathematics and Science Education (CRiMSE) and the MQ Learning Sciences Laboratory (MQSL). Her work bridges research and practice, influencing curriculum design and teacher education nationally and globally.
Alex Alvarado is a Full Professor in the Signal Processing Systems department at Eindhoven University of Technology (TU/e), leading the Information and Communication Theory Lab (ICT Lab). He is also affiliated with TU/e's Center for Wireless Technology in Eindhoven. His academic career includes roles as a Senior Research Associate at University College London (2014–2016), Marie Curie Intra-European Fellow (2012–2014), and Newton International Fellow (2011–2012) at the University of Cambridge. Alvarado is a Senior Member of the IEEE and has held editorial and committee positions in major conferences like OFC and ECOC. Alvarado holds an Electronics Engineer degree (2003) and MSc (2005) from Universidad Técnica Federico Santa María, Chile, followed by a Licentiate of Engineering (2008) and PhD (2011) from Chalmers University of Technology, Sweden. His research focuses on high-speed secure data transmission in optical and wireless systems, emphasizing energy-efficient algorithms and theoretical limits of telecommunication systems. Key areas include communication theory, information theory, optical fiber systems, and nonlinear interference mitigation. His recent articles explore advanced modulation formats, machine learning applications for channel estimation and decoding, and innovations in free-space optics and MIMO systems. This work contributes to UN Sustainable Development Goals related to affordable and clean energy, industry innovation, and responsible consumption through energy-efficient communication solutions. Scientific Awards: ERC Starting Grant (2018) NWO VIDI Grant (2016) 2015 Journal of Lightwave Technology Best Paper Award 2015 IEEE Exemplary Reviewer Award 2018 and 2023 Asia Communications and Photonics Conference Best Paper Awards 2019 Optoelectronics and Communications Conference Best Paper Award Alvarado's advising contributions include supervising 12 research works. His grants include NWO VIDI and ERC Starting funding. He leads projects like NESTOR (Next-gen optical networks) and LaiQa (Quantum Key Distribution). His lab, the ICT Lab, drives theoretical and applied research in communication systems.
Petra Schwer is a full professor of Geometry at Heidelberg University, holding the position since February 2024. Previously, she was a professor at Otto von Guericke University Magdeburg (2018–2024) and the Karlsruhe Institute of Technology (2014–2018). She has also held research and academic positions at institutions including the University of Münster and UC Davis. Education: She earned her PhD in Mathematics from Westfälische Wilhelms-Universität Münster in 2009, supported by a stipend from the Studienstiftung des deutschen Volkes. Prior to that, she received her Diplom in Mathematics from the University of Bonn in 2005. Research Interests : Her work focuses on the interplay between geometric structures and group theory, particularly in metric spaces of nonpositive curvature, polyhedral complexes, and Coxeter groups. She explores geometric and combinatorial aspects of buildings, including Bruhat-Tits buildings and their generalizations, using methods from geometric group theory and metric geometry. Key Contributions : Recent publications include studies on folded galleries in affine buildings, the geometry of Coxeter groups, and the application of cube complexes in computational geometry. These contributions highlight her expertise in nonpositive curvature and geometric group theory. Grants and Funding : Dr. Schwer has secured grants such as DFG projects on buildings and symmetric spaces, collaborative grants in mathematical complexity reduction, and initiatives like the Young Investigator Network exploring geometric data analysis. Students and Advising : She has advised doctoral and master’s students including Isobel Davies, Marco Lotz, and Anna Michael (OVGU); Julia Heller and Annette Karrer (KIT). Her teaching includes advanced topics in geometry and group theory.
Prof. Mastroddi Franco is a Full Professor at the Department of Mechanical and Aerospace Engineering (DIMA) of Sapienza University of Rome, affiliated with the Faculty of Civil and Industrial Engineering. His expertise spans aerospace engineering, aeroelasticity, and multidisciplinary design optimization. He contributes to training programs such as the 2nd-level Master's in 'Satellites and Orbiting Platforms' and 'Energy Efficiency and Renewable Energy Sources'. His research focuses on fluid-structure interactions, sloshing dynamics in aircraft tanks, and sustainable aircraft design. He has led studies on green aviation technologies, launch vehicle aerodynamics, and numerical modeling techniques like Smoothed Particle Hydrodynamics (SPH). Research Interests: Aeroelastic Stability and Response Hydrogen-Powered Aircraft Systems Neural Network Applications in Fluid Dynamics Green Energy Integration in Aviation Reduced-Order Modeling for Complex Systems Publications highlight contributions to sloshing dynamics, hybrid aircraft design, and computational methods for hypersonic systems. Awards: None explicitly mentioned. Grants and advisory roles include participation in the 'Premio Liviu Librescu' thesis award committee (2010). He collaborates on projects involving structural damping models and multi-objective optimization for aerospace systems.
Ronald Graham is a Professor in the Computer Science and Engineering Department at the University of California San Diego (UCSD), affiliated with the Jacobs School of Engineering. He also serves as Chief Scientist at the California Institute for Telecommunications and Information Technology (Calit2). Graham’s career spans academia and industry, including a 37-year tenure at Bell Labs and leadership roles at AT&T Labs. He is renowned for contributions to combinatorics, Ramsey theory, scheduling algorithms, and discrete mathematics. His Erdős number of 1 underscores his collaborative ties to Paul Erdős, a legendary mathematician. Education: Graham earned his PhD in Mathematics from UC Berkeley in 1962. Research Interests: Graham’s work focuses on combinatorics, graph theory, number theory, computational geometry, scheduling theory, and quasi-randomness. He has also explored recreational mathematics, notably through his book Magical Mathematics (2011), which intertwines card tricks with mathematical principles. His research has influenced internet infrastructure design, including foundational work on routing algorithms and the development of Akamai Technologies. Notable Achievements: Graham has received the Steele Prize for Lifetime Achievement (2003), Euler Medal (1994), and Polya Prize in Combinatorics (1972). His concept of “Erdős numbers” revolutionized academic collaboration tracking, later adapted into Hollywood’s “Six Degrees of Separation” game. Advising & Grants: Graham mentors students and faculty, inspiring future generations through teaching and mentorship. The UCSD CSE Department established the Ronald L. Graham Chair in Computer Science in 2015 to honor his legacy, funded by an $18.5M alumni donation. Labs & Collaborations: As Calit2’s Chief Scientist, Graham advises on strategic directions, emphasizing interdisciplinary research in information technology and communications. His work bridges theoretical mathematics and applied computing, shaping global technological advancements.
Herna Viktor is a Full Professor and Director of the School of Electrical Engineering and Computer Science at the University of Ottawa. She holds a Ph.D. and has extensive administrative leadership experience within the university's Faculty of Engineering. Research Interests : Dr. Viktor specializes in Artificial Intelligence (AI) with a focus on data-driven discovery across diverse domains. Her work emphasizes applications in healthcare (e.g., medical outcome prediction), cybersecurity (e.g., threat detection via semi-supervised learning), finance (e.g., stock market analysis with temporal Transformers), and computational biology (e.g., protein structure generation using diffusion models). She also explores advanced machine learning techniques like lifelong learning, ensemble methods, and interpretability measures. Her research integrates geometric deep learning, quantum computing, and hybrid models to address complex problems in structural proteomics and molecular dynamics. Recent Articles : Her recent publications (2023–2025) highlight trends in protein generation via diffusion models, adversarial robustness of NLP systems, and financial time series predictions. She consistently bridges theoretical AI advancements with real-world applications in medicine, cybersecurity, and quantum computing. Advising & Grants : Currently supervises Paul Kiyambu Mvula . While no grants are explicitly listed, her research demonstrates significant interdisciplinary impact. Her work on SCUT-DS and DynaQ reflects ongoing engagement with imbalanced data and online learning challenges. Labs/Teams : No specific lab or team is mentioned, but she collaborates on projects involving hybrid quantum neural networks and molecular dynamics simulations.
Karin Nachbagauer is a Professor of Applied Mathematics at the University of Applied Sciences Upper Austria, affiliated with the Faculty for Engineering's Mechanical Engineering Department. She holds a Hans Fischer Fellowship at the TUM Institute for Advanced Study (since 2020). Her research focuses on multibody system dynamics, numerical mathematics, optimal control, and inverse dynamics, with applications in mechanical engineering and robotics. She earned her PhD in Engineering Sciences (2012) and Diploma in Industrial Mathematics (2009) from Johannes Kepler University Linz. Notable awards include the 2020 Best Paper Award for optimal control research and 2019 Excellence in Teaching Award. Her work emphasizes adjoint gradient methods for optimization problems, parameter identification in multibody systems, and time-optimal control applications. Current projects include the VRoboCoop initiative for human-robot collaboration and IOMMS for innovative optimization in multibody systems. Publications span journals like Journal of Computational and Nonlinear Dynamics and Multibody System Dynamics , with over 80 peer-reviewed articles. She actively participates in international conferences and serves on editorial boards.
Lawrence Sass is a Professor and Chair of the Computation Group in the Department of Architecture at MIT's School of Architecture + Planning. His research focuses on design innovation using digital fabrication, particularly in low-cost housing and construction automation. He pioneered methods to reduce home construction steps through computational tools, including the concept of Snap Assembly building systems showcased at MoMA in 2008. His work has inspired startups in digitally fabricated housing. B.Arch from Pratt Institute (1990) Master’s (1994) and PhD (2000) from MIT Research interests include sustainable construction techniques, 3D printing in architecture, and material optimization. He co-founded LuBan3D, a software system enabling large-scale 3D modeling with affordable tools. Current projects explore AI and robotic systems for home production. Awards include the prestigious MacVicar Faculty Fellow recognition. His teaching includes courses like Design Computation (4.500) and Tiny Fab (4.501), emphasizing computational methods in architectural design. Collaborations include work with Singapore-based researcher Prof. Lujie Chen on large-scale fabrication software. His lab focuses on integrating digital tools into physical production workflows, aiming to democratize construction through accessible fabrication technologies.
Sandra Zilles is a Professor and Canada Research Chair (Tier 1) in Computational Learning Theory at the University of Regina's Department of Computer Science. She holds adjunct appointments at the University of Waterloo and collaborates with the Alberta Machine Intelligence Institute (Amii). Her research focuses on theoretical computer science and artificial intelligence, particularly interactive learning models, formal language theory, and heuristic search algorithms. Her research integrates computational learning theory, formal language theory, and discrete artificial intelligence structures. Key interests include: Machine teaching with limited data Learnability of pattern languages and automata Graph-theoretic approaches in AI Her work bridges theoretical frameworks with applications in medical imaging, bioinformatics, and game theory. Zilles has received numerous honors including: NSERC Canada Research Chair (Tier 1, 2022-2029) Royal Society of Canada College membership Best Paper Awards (KI 2012, ALT 2003, COLT 2002) She mentors over 50 students and postdocs through her research group. Current projects explore symbolic automata, collaborative learning, and geometric teaching models. Her lab maintains international collaborations with institutions in Germany, Canada, and the US.
