Örs Legeza is a physicist and scientific advisor at the Wigner Research Centre for Physics of the Hungarian Academy of Sciences in Budapest, leading the Strongly Correlated Systems Research Group. He holds a visiting professorship at Philipps University Marburg, Germany, and has held fellowships at institutions like ETH Zurich and LMU Munich. His research focuses on developing tensor network state (TNS) methods for strongly correlated quantum systems, with applications in condensed matter physics, quantum chemistry, and nuclear structure calculations. Education: PhD from Budapest University of Technology and Economics (1997). He has collaborated with European institutions such as FAU Erlangen-Nuremberg and has been an Alexander von Humboldt awardee. His work bridges quantum information theory and computational mathematics to advance simulations of complex quantum systems. Research interests include quantum phase transitions, magnetic properties in solids, and ultracold atomic systems. His methods push computational boundaries for larger systems, integrating techniques like density matrix renormalization group (DMRG) and matrix product states (MPS). Notable awards include the 2021 Academy Prize and 2018 Humboldt Research Award. Recent articles explore quantum crystal imaging, tensor network algorithms, and nuclear structure calculations. His work emphasizes interdisciplinary approaches to quantum many-body problems.
Yuan Tian is an Assistant Professor in the School of Computing at Queen's University, Faculty of Arts and Science. She holds a PhD in Information Systems from Singapore Management University (2017) and a B.Sc. in Computer Science from Zhejiang University (2012). Her research focuses on integrating heterogeneous data sources to enhance software engineering practices, including data mining, recommender systems, and social network analysis. Prior to Queen's, she was a data scientist at Living Analytics Research Centre (LARC), SMU. She has held visiting positions at Carnegie Mellon University, INRIA Paris, and SAIL Canada. Research Interests: Data Mining Software Engineering Social Network Analysis Information Retrieval Recommender Systems Computer Security Recent Research Trends: Her work emphasizes AI-driven solutions for software bug management, code translation, vulnerability detection, and developer behavior analysis. Notable contributions include leveraging LLMs for technical debt repayment and enhancing code vulnerability detection via Graph Neural Networks. Awards: SMU Presidential Doctoral Fellowship (2015-2016) Best Paper Award at SANER 2017 Grants & Advising: No formal advisees listed, but active in collaborative projects with industry and academic partners. Labs/Teams: Previously associated with SOAR Group at SMU and currently leads research in Queen's School of Computing.
Dr. Emanuele Pelucchi is a Research Professor and Head of the Epitaxy and Physics of Nanostructures (EPN) group at Tyndall National Institute, University College Cork. His research focuses on quantum technologies, epitaxial growth (MBE/MOVPE), quantum dot physics, and photonic integration. He leads a world-class MOVPE facility, pioneering developments in site-controlled quantum dots and entangled photon emitters. Pelucchi's work has resulted in over 129 international publications with an h-index of 28 (Scholar), including contributions to Nature Photonics and NanoLetters. He has held a Science Foundation Ireland Principal Investigator grant since 2006, establishing his group at Tyndall in 2007. His expertise spans semiconductor nanostructures, including III-V materials and quantum optics. Pelucchi actively reviews for top journals and chairs international conferences, contributing to the field's academic discourse. His MOVPE laboratory is recognized as a key resource for III-V materials, serving as a secondary supplier to the UK National Centre for III-V Materials. Pelucchi's research bridges fundamental physics and applied photonics, driving advancements in quantum information processing and optoelectronic devices.
Yi Zheng is an Associate Professor in the Department of Mechanical and Industrial Engineering at Northeastern University, where he directs the Nano Energy Laboratory. He previously held positions at the University of Rhode Island before joining Northeastern in 2019. His research focuses on nanoscale thermal transport, renewable energy systems, photon-based cooling, and sustainable materials derived from biomass. Zheng serves on editorial boards for Scientific Reports and Journal of Photonics for Energy , and actively participates in conferences like ASME IMECE. He holds a PhD in Mechanical Engineering from Columbia University (2015), with earlier degrees from Columbia and Tsinghua University. Education: Ph.D., Mechanical Engineering, Columbia University (2015) M.S., Mechanical Engineering, Columbia University (2011) B.S., Mechanical Engineering, Tsinghua University (2009) Research Interests: Prof. Zheng’s work bridges nanotechnology and energy systems, emphasizing novel materials for thermal management, radiative cooling, and sustainable energy harvesting. His lab develops biomass-derived composites for solar desalination, thermophotovoltaics, and smart cooling paints. Key projects include ultra-dark solar absorbers, phase-change material-based thermal devices, and recyclable cellulose-based materials. Grants & Awards: 2024 ASME Rising Star Award 2019 NSF CAREER Award 2025 NASA Glenn Faculty Fellow 3M Non-Tenured Faculty Award (2022) Labs/Teams: The Nano Energy Laboratory at Northeastern collaborates internationally on projects like photonics-enabled biosensors and adaptive radiative cooling systems. Recent innovations include self-cleaning cellulose composites and cooling paints for urban heat reduction.
Professor Peter Wells is an Associate Professor at the University of Southampton, with a joint appointment at Diamond Light Source. His research focuses on operando spectroscopy, heterogeneous catalysis, and nanoparticle design. He coordinates the CHEM3054 module on Inorganic Materials Chemistry and holds a Fellow accreditation from the Higher Education Academy. Education: MChem in Chemistry (University of Surrey, 2003) PhD in tailored metal nanoparticle preparation and characterization (University of Southampton, 2007) His research integrates advanced X-ray techniques (e.g., X-ray absorption spectroscopy) with computational methods like DFT simulations to study catalyst dynamics. Key areas include stabilizing structural changes in palladium nanoparticles and designing nanoparticle catalysts for sustainable chemical production from waste biomass. He collaborates with the UK Catalysis Hub and serves on peer-review panels for Diamond Light Source and the Swiss Light Source. Active Research Projects (EPSRC): Core Equipment 2024 (£1.26M, PI) Nitridic and Carbidic Pd Nanoparticles for Directed Catalysis Peter supervises multiple PhD students in Chemistry and actively mentors researchers through collaborative grants. His work bridges experimental and theoretical approaches to catalysis, emphasizing real-time structural analysis under operational conditions.
Pedro Vilaça is a **Professor and Head of the Department of Energy and Mechanical Engineering** at **Aalto University's School of Engineering**, Finland. Previously, he worked at the Instituto Superior Técnico (Técnico), University of Lisbon, Portugal (1995–2013). His research focuses on **welding technology**, **solid-state manufacturing**, **non-destructive testing (NDT)**, **hydrogen-related materials science**, and **materials safety**, with applications in energy and aeronautics sectors. He leads R&D teams and has collaborated globally, contributing to 142+ publications (h-index 32 via Scopus). **Research Interests**: Advanced welding techniques (e.g., friction stir welding), hydrogen embrittlement in steels, supercapacitor materials, and smart composites. He has pioneered methods for **zero-material-loss welding** and **self-sensing metallic materials**. **Key Projects**: Led initiatives like **THEWFuelCells** (fuel cell welding innovations) and **EARLY/Vilaca** (hydrogen damage assessment). His work aligns with **UN Sustainable Development Goals**, emphasizing renewable energy storage and industrial sustainability. **Awards**: 2011 Eng. Cruz Azevedo Award for outstanding research in Mecânica Experimental. **Collaborations**: Active in international networks, including the International Institute of Welding and European research consortia. He has organized conferences, reviewed patents, and advised doctoral students globally. **Recent Articles**: Focus on corrosion-resistant materials, piezoelectric composites, and hydrogen-induced failure in steels. His 2023–2025 work emphasizes energy storage innovations and advanced joining technologies. **Grants**: Principal investigator for projects funded by Business Finland, EU EIT, and Academy of Finland. **Labs/Teams**: Oversees Aalto’s mechanical engineering research teams and collaborates with institutions like Helmholtz-Zentrum Geesthacht.
Connor Myant is Reader in Digital Manufacturing Systems at Imperial College London's Dyson School of Design Engineering, where he leads the Advanced Manufacturing Group. He holds a PhD from Imperial College (2010) and teaches courses in Solid Mechanics and Design for Additive Manufacture. His research advances multi-material 3D printing technologies with applications in medical devices, energy-absorbing structures, and functional composites. Current projects focus on open-source 5-axis printing platforms and stiffness-matched implants. Publication themes include: Medical device customization Nanocomposite material development Biomechanical optimization Industrial 3D printing systems
Vladimir Bulović is a Professor of Electrical Engineering and Computer Science at MIT, holding the Fariborz Maseeh Chair in Emerging Technology. He serves as Founding Director of MIT.nano, a 20,000 m² nanofabrication and prototyping facility. His research focuses on nanoscale materials, renewable energy, and optoelectronics, with emphasis on scalable solar technologies and printed electronics. Education: B.S.E. and Ph.D. in Electrical Engineering from Princeton University. Research Interests: Development of thin-film photovoltaics (perovskites, organic PVs), energy-efficient optoelectronics, and advanced manufacturing techniques. His work bridges nanotechnology with real-world applications, such as transparent solar cells and flexible electronics. Key innovations include vapor transport deposition (VTD) for perovskite solar cells and scalable printed electronics. Publications: Over 250 articles (45,000+ citations) focus on perovskite materials, semiconductor fabrication, and optoelectronic device optimization. Recent trends emphasize machine learning-driven materials design and stability enhancement strategies for photovoltaics. Awards: MacVicar Fellowship (2018), Top 1% Highly Cited Researcher (2018) Advising & Grants: Co-founded Ubiquitous Energy, Kateeva, and QD Vision. Led projects on grid-edge solar solutions and MIT-Eni Solar Frontiers Center. Served as Associate Dean for Innovation and Director of MIT’s Innovation Initiative (2013–2018). Labs/Teams: Directs the Organic and Nanostructured Electronics Lab and oversees MIT.nano’s interdisciplinary research programs.
Julian Jauk is a Researcher at the Institute for Architecture and Media, TU Graz. His work focuses on innovative material systems, digital fabrication, and sustainable architectural design. He explores the integration of clay composites, mycelium-based materials, and knitted structures with advanced manufacturing techniques like 3D printing. Key research themes include lightweight ceramic structures, biocomposite materials, and computational design methodologies. His research emphasizes material-driven innovation, structural optimization, and environmental sustainability. Notable projects include MyCera (clay-mycelium composites) and ClayKnit (3D-printed clay-knitted hybrids). He also investigates mixed reality tools for architectural sketching and kinetic architectural prototypes. Publications from 2021–2024 highlight trends in bio-based materials, additive manufacturing, and material-property analysis. His work bridges traditional craftsmanship with cutting-edge digital fabrication, aiming to redefine sustainable building practices.
Josh McDermott is a Professor in the Department of Brain and Cognitive Sciences at MIT and an Associate Investigator at the McGovern Institute. He holds roles as Associate Department Head and Principal Investigator of the Laboratory for Computational Audition. His work bridges psychology, neuroscience, and engineering to study auditory perception, with a focus on sound interpretation, hearing impairment treatments, and machine hearing systems. Education includes a B.A. from Harvard (summa cum laude), an MPhil from University College London, and a PhD from MIT. Postdoctoral training included NYU and the University of Minnesota. Research interests encompass computational principles of sound perception, natural sound statistics, music cognition, and machine hearing. Key areas include sound localization, auditory scene analysis, and the role of generative models in perception. Recent publications highlight advancements in auditory neural networks, cross-cultural music perception, and noise schema processing. Awards include the Troland Research Award, BCS Excellence in Advising, and NSF CAREER Award. Advising includes over 20 graduate students and postdocs, with notable contributions to auditory neuroscience and machine learning. Major grants support projects on auditory models and sensory systems. The lab develops tools like cochleagram generation and headphone screening software. The Laboratory for Computational Audition operates at MIT, focusing on biological and computational approaches to hearing. Collaborations span engineering, psychology, and neuroscience to advance understanding of auditory processing.
Dr. Thalia Dominguez Bucio is a Senior Research Fellow at the Optoelectronics Research Centre (ORC), University of Southampton, within the Faculty of Engineering and Physical Sciences. She is a key member of the Silicon Photonics research group and actively contributes to the Horizon Europe PIXEurope project, advancing integrated photonic technologies. Her work focuses on silicon nitride as a material platform for next-generation photonic integrated circuits. Her research interests center on integrated photonics , silicon nitride platforms , nonlinear optics , and CMOS-compatible fabrication . She investigates low-loss photonic devices, efficient coupling mechanisms, and high-speed electro-optic modulators, with applications in optical communications and signal processing. Recent publications (2024) demonstrate a strong trend toward high-efficiency grating couplers , broadband wavelength conversion via intermodal four-wave mixing, and monolithic integration for low-power operation. These works reflect a cohesive research direction focused on enabling scalable, high-performance photonic integrated circuits using advanced silicon nitride technology. Speaker, Advanced Silicon Nitride Integration for CMOS Photonic Circuits, 2023 She currently supervises PhD students Qian Zhang and Lifeng Bao , and is accepting new PhD applicants. Her research is supported by major EU-funded initiatives like Horizon Europe. She is part of the Photonic Systems, Circuits and Sensors Group and the broader Silicon Photonics team at the ORC, fostering interdisciplinary collaboration in photonics research and development.
Dr. Hossein Alizadeh Otorabad is a Research Fellow at the Department of Engineering, School of Computing and Engineering, University of Huddersfield. He joined the Institute of Railway Research (IRR) in 2019 and was promoted to Research Fellow in 2022. His work focuses on finite element analysis, railway engineering, and thermal dynamics in wheel-rail interactions. BSc in Solid Mechanics, Tehran Polytechnic University MSc in Applied Mechanics, Khajeh Nasir Toosi University (2002) PhD in Railway Engineering (2018), focusing on wheel-flat fatigue crack initiation His research expertise spans Railway Engineering , Finite Element Analysis , and Thermal Modeling , with a particular focus on wheel-flat dynamics and fatigue analysis. He has contributed to studies on dynamic load effects in railway crossings, temperature evolution during wheel flat formation, and elasto-plastic behavior in railway wheels. Recent publications show a strong emphasis on Railway Systems (2018-2024), covering topics like: Dynamic load prediction in crossings Thermal analysis of wheel-rail sliding Contact mechanics in flatted wheels Fatigue life evaluation under transient loads His work aligns with UN Sustainable Development Goals for sustainable infrastructure and transportation systems. Scientific Recognition: h-index of 31 (Scopus metrics) 16+ citations for elasto-plastic wheel analysis Contributions to key railway engineering conferences At IRR, he conducts FE analysis, laboratory/field testing of railway assets, hammer testing, and signal processing. He previously received funding from Iran's Ministry of Science for sabbatical research at TU Delft's Material Science and Engineering department.
Dr. rer. nat. Thomas Hermann is a faculty member at Bielefeld University's Faculty of Engineering, leading the Ambient Intelligence Group and coordinating the Computer Science program. He specializes in sonification, auditory data science, and smart environments. Head of Ambient Intelligence Working Group Computer Science Program Coordinator Member of multiple academic advisory boards His research focuses on interactive sonification for biomedical applications, quantum systems, and smart environments. Key projects include ECG sonification for cardiac diagnosis, real-time auditory feedback in swimming, and sonic interfaces for AR cooperation. Recent publications span 2025 with Python-based sonification tools ( pya AGen ), quantum system sonification, and ST-elevation myocardial infarction monitoring. He contributes to open-access supplementary materials and interdisciplinary workshops. As a researcher , Hermann develops practical sonification frameworks like Panson for facial behavior analysis, CardioScope for portable ECG monitoring, and Base Cube One for smart environments. His work bridges academic research with industry applications.
Gianni Dal Maso is a Professor of Mathematical Analysis at the International School for Advanced Studies (SISSA) in Trieste, Italy. He has been a faculty member at SISSA since 1985, first as Associate Professor and then as Full Professor since 1987. He has held several leadership positions at SISSA including Head of the Sector of Functional Analysis and Applications (1993-1998, 2001-2010), Deputy Director (2010-2015), and Coordinator of the Mathematics Area (2016-2020). His educational background includes: 1973-1977: Undergraduate student in Mathematics at the University of Pisa and Scuola Normale Superiore 1977: Degree in Mathematics with honors at the University of Pisa (thesis: "Gamma-limits of set functions," advised by Ennio De Giorgi) 1977: "Diploma" in Mathematics from the Scuola Normale Superiore 1977-1981: Post-graduate Research Fellowship in Mathematics ("Perfezionamento") at the Scuola Normale Superiore Dal Maso's research focuses on the Calculus of Variations, with particular emphasis on semicontinuity and relaxation problems, Gamma-convergence, and more recently, free discontinuity problems and their applications to mechanics. His work bridges pure mathematical analysis with practical applications in material science, particularly in plasticity and fracture mechanics. He has developed mathematical frameworks for understanding crack propagation, material failure, and the behavior of solids under stress, contributing significantly to both theoretical foundations and practical modeling approaches in these areas. His extensive publication record shows a clear evolution from foundational work in Gamma-convergence (culminating in his influential book "An Introduction to Gamma-Convergence" in 1993) toward increasingly sophisticated models of material behavior, particularly in fracture mechanics and plasticity. Recent work demonstrates continued innovation in handling complex discontinuities, non-local effects, and multi-scale phenomena in material science applications. Among his notable scientific recognitions: 1982: Stampacchia Prize, awarded by the Scuola Normale Superiore 1990: Caccioppoli Prize, awarded by the Italian Mathematical Union 1996: Medaglia dei XL per la Matematica, awarded by the Accademia Nazionale delle Scienze detta dei XL 2003: Prize of the Minister for the Cultural Heritage for Mathematics and Mechanics, awarded by the Accademia Nazionale dei Lincei 2005: Prize Luigi and Wanda Amerio, awarded by the Istituto Lombardo Accademia di Scienze e Lettere Dal Maso has supervised 42 PhD students at SISSA, demonstrating a strong commitment to academic mentorship. His research has been significantly supported by multiple National Research Projects (PRIN) in Italy, and notably by an ERC Advanced Grant "Quasistatic and Dynamic Evolution Problems in Plasticity and Fracture" (QuaDynEvoPro) from 2012-2017, where he served as Principal Investigator. This major project focused on nonlinear evolution problems in plasticity and fracture, with three main research directions: plasticity with hardening and softening, quasistatic crack growth, and dynamic fracture mechanics. His scholarly activities extend to editorial service, with membership on the boards of numerous prestigious journals including Archive for Rational Mechanics and Analysis, SIAM Journal on Mathematical Analysis, and Journal of Convex Analysis. He has also been active in the mathematical community through membership in scientific committees and academies, including the Accademia Nazionale dei Lincei since 2014.
Jean Provost is a Full Professor in the Department of Engineering Physics at Polytechnique Montréal , with affiliations to the Montreal Heart Institute , IVADO , and the Institute of Biomedical Engineering . His research focuses on ultrasound imaging , cardiac and cerebral vascular imaging , and superresolution image reconstruction using machine learning and optimization . Based on 96 publications, his work emphasizes ultrasound localization microscopy , neural network applications , and microvascular hemodynamics . Education : Ph.D. (Columbia University), MPhil (Columbia University), M.Sc.A. (École Polytechnique Montréal), Engineering Degree (École Centrale Paris), License (Université Paris XI), B.Eng. (École Polytechnique Montréal) Research trends from 15 recent articles include: 3D and dynamic ultrasound localization microscopy for microvascular mapping Deep learning for image reconstruction and neural network pruning Machine learning-driven aberration correction and superresolution imaging Acoustoelectric and cavitation-based imaging techniques Applications in cardiac diagnostics and dementia detection Supervision includes 2 Ph.D. and 8 Master's theses completed at Polytechnique Montréal (2023), covering topics like optical ultrasound detection , microbubble modulation , and spatiotemporal sampling .
