Kim Rasmussen is the Challis Professor of Civil Engineering at the University of Sydney's School of Civil Engineering. He holds a MScEng from the Technical University of Denmark and PhD/DEng from the University of Sydney. His roles include former Head of School (2005–2016), Deputy Dean (2016–2022), and Interim Dean (2018). His research focuses on structural mechanics, particularly steel/cold-formed/stainless-steel structures, 3D-printed metals, and fracture mechanics. Major projects include: midrise cold-formed steel structures, reliability of 3D-printed metal frameworks, and fracture analysis of steel connections. He collaborates internationally with institutions like Imperial College London and Stanford University. Awards include the 2016 Shortridge Hardesty Award and 2020 Lynn Beedle Award. His work advances sustainable and efficient structural designs, with over 20 years of ARC funding. Current students research topics like additive manufacturing and structural reliability.
Jakub Vohryzek is a postdoctoral researcher at the Computational Neuroscience (CNS) Group at University Pompeu Fabra in Barcelona, supervised by Prof. Gustavo Deco. His work focuses on spacetime connectomics and whole-brain modeling, particularly in neurodegenerative disorders and psychedelic neuroscience. He holds a DPhil from the University of Oxford, where he studied under Prof. Morten Kringelbach. Research Interests: Spacetime connectomics Psychedelic-induced brain state transitions Neurotwin models for personalized medicine Cognitive and clinical applications of whole-brain dynamics Current projects include developing neurotwin models under a European grant for neurodegenerative treatments, investigating brain state dynamics in mindfulness therapy, and modeling psychedelic effects on Alzheimer’s disease. His recent work emphasizes low-dimensional brain network interactions and functional hierarchy perturbations. His research has explored connectivity profiles, oscillatory restoration in dementia, and algorithmic agent approaches to neuropsychiatric disorders. He collaborates on open-science initiatives like Brainhack and advocates for inclusive conference design.
Dr. Troy Michael Bordun is an Assistant Professor in the English Department within the Faculty of Indigenous Studies, Social Sciences and Humanities at the University of Northern British Columbia, where he teaches film and television studies. He holds a PhD in Cultural Studies from Trent University, an MA from Brock University, and a BA Honours from the University of Toronto. His academic journey includes prior teaching positions as a contract instructor at Concordia University (Film Studies, Sociology, Art History, Communication Studies), Trent University (Cultural Studies, Sociology), and Bishop's University (English and Film Studies), where he received Trent University's part-time teaching award. Dr. Bordun's research spans film and media studies, celebrity studies, porn studies, and comics studies, with particular expertise in contemporary superhero comics, continental philosophy, and online pornography. His work examines genre theory, spectatorship, and the intersections of cinema with gender, sexuality, and power structures. His scholarship demonstrates a consistent theoretical sophistication, drawing on phenomenological approaches, affect theory, and continental philosophy to analyze cinematic experiences. His publications reveal a thematic trajectory connecting extreme cinema, pornography studies, and superhero narratives. The articles show his ability to bridge theoretical frameworks with close readings of specific films, often focusing on how cinematic form engages with philosophical concepts. His work consistently addresses how film genres function as sites for ethical and political critique, particularly regarding gender representation and power dynamics. Genre Trouble and Extreme Cinema: Film Theory at the Fringes of Contemporary Art Cinema (2017) SSHRC Explore Grant recipient Research Strategic Initiatives Grant (UNBC) Editorial board member for Comics Studies: Theory and Practice and Porn Studies Co-Chair of Comics Studies Special Interest Group (Society for Cinema and Media Studies) Dr. Bordun actively supervises graduate students in English and is available as a media expert on film and television studies. His current research includes developing a manuscript linking contemporary superhero comics and continental philosophy, an edited collection about the Invincible transmedia franchise, and ongoing research on online pornography, labor, platforms, and celebrity.
He Zhu is an Assistant Professor at Rutgers, The State University of New Jersey, affiliated with the Department of Computer Science. His research focuses on programming languages, compilers, wireless communications, IoT systems, and 5G network protocols. He received the PLDI 2019 Distinguished Paper Award for his contributions to formal methods in programming systems. His work addresses challenges in vehicle-to-everything (V2X) communication, resource allocation in sidelink networks, network security, and dynamic authorization frameworks for IoT devices. Key research interests include optimizing 5G NR (New Radio) protocols for vehicular environments, developing efficient data aggregation techniques for user equipment, and enhancing service layer mechanisms for IoT systems. He leads projects funded by the NSF, such as 'Formal Symbolic Reasoning of Deep Reinforcement Learning Systems,' and has contributed to advancements in beam management, RACH protocols, and energy-efficient DRX configurations in wireless networks. His office is located in Core 315. Notable Awards: PLDI 2019 Distinguished Paper Award Grants: NSF Grant: Formal Symbolic Reasoning of Deep Reinforcement Learning Systems His research group explores intersections between compiler design, distributed systems, and network architecture, with applications in smart mobility, edge computing, and secure IoT communication. He actively contributes to standards development for 5G and future generations of wireless networks.
Alexander D Maloney serves as the Kathy and Stan Walters Endowed Professor of Quantum Science and Director of the Institute for Quantum and Information Science at Syracuse University's College of Arts and Sciences, Department of Physics. His leadership bridges theoretical physics and quantum information science through institutional and research initiatives. His academic foundation includes a Ph.D. in Physics from Harvard University (2003) with dissertation "Time-Dependent Backgrounds of String Theory," complemented by dual B.Sc. and M.Sc. degrees in Physics and Mathematics from Stanford University (1998). Maloney's research centers on quantum gravity and information theory, exploring black hole physics through string theory frameworks. His work connects quantum field theory, cosmology, and information paradox resolution, with particular focus on wormhole geometries, resurgence phenomena, and holographic dualities. This interdisciplinary approach examines how quantum information principles shape spacetime structure. Recent publications reveal evolving emphasis on Narain ensemble statistics, modular invariance applications, and quantum cosmology in reduced dimensions. His 2020-2025 output demonstrates methodological progression from semiclassical gravity to non-perturbative quantum gravity techniques, increasingly integrating machine learning concepts with theoretical frameworks. His scientific recognition includes: James McGill Professor at McGill University (2023) Sir William Macdonald Chair in Physics at McGill University (2020) Maloney secures major research funding including NSERC Discovery Grants (2015-2020, 2020-2025) and Simons Foundation's "It from Qubit" collaboration (2015-2022). He actively shapes academic discourse through search committee leadership, journal reviewing (Journal of High Energy Physics since 2007), and international conference organization at Aspen Center for Physics and Institute for Advanced Study. As Director of Syracuse's Institute for Quantum and Information Science, he cultivates collaborative research environments exploring quantum gravity applications to quantum computing and cosmological modeling.
Eilif B. MULLER is a Professor in the Department of Neurosciences at Université de Montréal, Principal Investigator of the Architectures of Biological Learning Lab (ABL-Lab) at CHU Sainte-Justine Research Center, and Associate Faculty at Mila (Quebec AI Institute). His work bridges neuroscience and artificial intelligence, focusing on understanding how sensory perception is learned in the neocortex through biophysical simulations and deep learning models. He holds affiliations with IVADO (Institute for Data Valorization) and contributes to strategic initiatives like the UNIQUE Québec Center. His research integrates empirical neurophysiology with computational models, exploring dendritic processing and synaptic plasticity to inform both biological understanding and AI advancements. Teaches NSC-6044 and NSC-6045 (Neuroscience Colloquia) at Université de Montréal. Leads projects on neocortical learning mechanisms and their implications for neurodevelopmental disorders. Recipient of grants from CRSNG (Natural Sciences and Engineering Research Council), FRSQ (Health Research Fund), and institutional funding. Publications span topics in computational neuroscience, neural network modeling, and interdisciplinary AI-neuroscience research. Collaborates extensively across institutions to advance large-scale brain simulations and data-driven models.
Dr. Weihua Zhuang is a University Professor and University Research Chair in the Department of Electrical and Computer Engineering at the University of Waterloo. She holds prestigious fellowships from IEEE, Royal Society of Canada, and other organizations. Her research focuses on future communication networks, including 6G, network virtualization, autonomous vehicles, and smart grids. She has led groundbreaking work on MAC protocols like VeMAC for vehicular networks and has contributed extensively to AI-driven network management. Education : Doctorate in Electrical Engineering, University of New Brunswick, Canada (1993) M.Sc. and B.Sc. in Electrical Engineering, Dalian Maritime University, China Research Interests : Dr. Zhuang's work spans wireless networking, IoT, autonomous systems, and smart infrastructure. She explores solutions for network architecture evolution, machine learning applications in communication systems, and service customization for dynamic environments. Her recent projects include digital twin-driven networks, cross-modal transmission strategies, and AI-native slicing for 6G. Awards : Women's Distinguished Career Award (IEEE VTS, 2021) R.A. Fessenden Award (IEEE Canada, 2021) Fellowships from IEEE, RSC, CAE, EIC Grants & Professional Activities : She led the Tier I Canada Research Chair in Wireless Communication Networks (2010–2024) and has held roles such as IEEE VTS President (2023–2024). Her grants include the NSERC Discovery Accelerator Supplements and PREA awards. She edits journals like IEEE Transactions on Vehicular Technology and co-chairs major conferences. Labs & Teams : Her research group focuses on network architecture, AI-driven protocols, and vehicular communication. Collaborations include projects on 6G, satellite-terrestrial integration, and edge computing for autonomous systems.
Dr. Jacqueline McCleary is an Assistant Professor of Physics at Northeastern University's College of Science, specializing in observational cosmology with a focus on galaxy clusters and dark matter. She leads research using weak gravitational lensing to study cosmic structures, collaborating on projects like the COSMOS-Web (JWST), SuperBIT (balloon telescope), and LoVoCCS surveys. Her work leverages multi-wavelength data from space, stratospheric, and ground-based observatories. Education: M.S. in Astronomy (New Mexico State University), M.S. and Ph.D. in Physics (Brown University), Postdoctoral Fellow at NASA's Jet Propulsion Laboratory. She transitioned to Northeastern as an ADVANCE Future Faculty Fellow before becoming a tenure-track faculty member in 2022. Research Interests: Dark matter interactions, galaxy cluster dynamics, gravitational lensing techniques, and next-generation observational platforms. Her team develops advanced algorithms and instrumentation for high-resolution imaging. Recent Contributions: COSMOS-Web has enabled unprecedented observations of distant galaxies using JWST, while SuperBIT's stratospheric flights provide diffraction-limited data. Key publications focus on lensing surveys, data reduction techniques, and dark matter-halo relationships. Awards: Recognized as a Northeastern ADVANCE Future Faculty Fellow. Media Engagement: Regularly comments on space exploration, asteroid risks, and cosmic phenomena for public outlets.
Dori Bejleri is an Assistant Professor in the Department of Mathematics at the University of Maryland, College Park. Prior to this, he was a Benjamin Peirce and NSF postdoctoral fellow at Harvard University (2019–2023) and an NSF postdoctoral fellow at MIT (2018–2019). He earned his PhD in 2018 from Brown University under Dan Abramovich's supervision. His research focuses on algebraic geometry, particularly moduli spaces and birational geometry, with connections to number theory, enumerative geometry, combinatorics, and geometric representation theory. His work is supported by NSF grant DMS-2401483. He has organized several academic events, including the JHU-UMD Algebra and Number Theory Day (2024) and the Perspectives on Moduli in Algebraic Geometry conference (2025). Bejleri has taught graduate courses such as Rationality Questions in Algebraic Geometry (Spring 2022), Birational Geometry of Algebraic Varieties (Fall 2020), and Moduli Spaces in Algebraic Geometry (Fall 2019). His research spans topics like wall-crossing phenomena in moduli spaces, compactifications of elliptic surfaces, and motivic Hilbert zeta functions. He has also contributed to the study of stable log pairs and geometric representation theory. His teaching and research reflect a commitment to advancing foundational questions in algebraic geometry while engaging with interdisciplinary connections. His academic contributions include organizing seminars and mentoring students through advanced topics in geometry and topology.
Mark Kramer is a Professor in the Department of Mathematics & Statistics at Boston University. He belongs to the Applied Mathematics research group, focusing on mathematical, statistical, and machine learning approaches to characterize brain activity. His work bridges data-driven neuroscience with computational methods, exploring topics like biophysical models of neurons, field models of neural populations in epilepsy, and theoretical questions about brain rhythms. His research interests include: Biophysical modeling of single-neuron dynamics Neural population activity in pathological states Machine learning for detecting abnormal brain rhythms Analysis of cross-frequency coupling and coherence Kramer has developed educational resources like Case Studies in Neural Data Analysis using both MATLAB and Python. These materials teach practical data analysis techniques for spike trains and field data, emphasizing hands-on implementation over theoretical mathematics. He has received funding from NIH and NSF for computational neuroscience projects. His recent publications focus on epilepsy research, sleep spindle analysis, and neural signal processing. The work spans from developing statistical frameworks to understanding network dynamics in seizure termination and exploring phase consistency in neural data. Notably, his coherence studies revealed non-intuitive coupling patterns between brain regions, demonstrating that low-amplitude rhythms can be more informative than dominant ones.
Dr. Graeme Peter Desmond Wilkin is a Lecturer in Pure Mathematics at the University of York, where he serves as Undergraduate Admissions Officer for the Department of Mathematics. He completed his undergraduate studies at the University of Melbourne and earned his PhD from Brown University in 2006. Prior to joining York, he held academic positions at Johns Hopkins University, the University of Colorado, and the National University of Singapore. His educational background includes: Undergraduate studies at the University of Melbourne PhD from Brown University (2006) Dr. Wilkin specializes in the topology and geometry of moduli spaces that arise in gauge theory, with particular focus on Higgs bundles and quiver varieties . His research employs diverse techniques from differential geometry, geometric analysis, algebraic geometry, and representation theory, with special emphasis on Morse theory and geometric flows . His work has significant connections to theoretical physics, particularly in areas related to quantum field theory and string theory. Analysis of his recent publications reveals a consistent focus on the geometric and topological properties of moduli spaces, with increasing attention to the analytical aspects of Morse theory on singular spaces. His research demonstrates strong connections between pure mathematics and theoretical physics, particularly in how geometric structures relate to physical phenomena. While maintaining a strong theoretical foundation, his recent work shows growing interest in computational aspects of these complex geometric structures. Dr. Wilkin actively supervises graduate students and has secured multiple research grants. His current project "Geometry of very stable and wobbly bundles" runs from October 2024 to September 2025. Previous projects include "Algebraic and Analytic Methods in Gauge Theory" and "Geometry and Topology of Singular Spaces." Principal Investigator on "Geometry of very stable and wobbly bundles" (2024-2025) Principal Investigator on "Algebraic and Analytic Methods in Gauge Theory" (2024) Researcher on "Geometry and Topology of Singular Spaces" (2018-2019) He is an active member of the "Geometry and Analysis" research group at the University of York and frequently participates in international conferences and collaborative research projects across multiple countries. His upcoming activities include organizing the "New Frontiers in Gauge Theory, Topology and Physics" conference scheduled for September-October 2026.
Camilo Mora is a Professor in the Department of Geography at the University of Hawaii at Manoa, where he maintains an active research laboratory and teaches courses on environmental issues, biogeography, and data analysis. His academic journey began with a BSc in Marine Biology from Universidad del Valle in Colombia (1999), followed by a PhD in Biology from the University of Windsor, Canada (2005). He completed postdoctoral fellowships at the University of Auckland (2005), Scripps Institution of Oceanography (2006-2008), and Dalhousie University (2008-2010). BSc, Marine Biology, Universidad del Valle, Colombia (1999) PhD, Biology, University of Windsor, Canada (2005) Postdoctoral Fellow, University of Auckland (2005) Postdoctoral Fellow, Scripps Institution of Oceanography (2006-2008) Postdoctoral Fellow, Dalhousie University (2008-2010) Mora's research spans interconnected lines focused on understanding biodiversity patterns and their modification by human activities, with particular emphasis on climate change impacts. His lab specializes in big data analytics applied to diverse environmental challenges including heatwaves, disease transmission, marine ecosystems, and even unconventional topics like Bitcoin's environmental footprint. The Mora Lab operates on a 'divide and conquer' approach to tackle large research questions by breaking data gathering into individual parts that can be concatenated into central databases. Mora has received the CSS Excellence in Research award (2014) for his significant contributions to environmental science. His influential publications include groundbreaking work on the global risk of deadly heat (2017), the projected timing of climate departure from historical variability (2013), and the finding that over half of known human pathogenic diseases can be aggravated by climate change (2022). CSS Excellence in Research (2014) Highly cited publications in Nature and Nature Climate Change Research featured in major international media outlets Development of innovative research methodologies for large-scale analyses Mora leads an active research group that engages students in the full scientific process from idea generation to publication. His approach to mentoring involves creating yearly classes where graduate students, professors, and international advisors collaborate to tackle significant research questions, with papers typically completed within a single semester. His Carbon Neutrality Challenge project, spearheaded by his daughter Asryelle Mora, provides a practical mechanism for individuals to offset carbon emissions through tree planting. The Mora Lab maintains a distinctive approach to environmental research, working on seemingly diverse topics from reef fishes to Bitcoin, united by their reliance on big data analytics. This interdisciplinary methodology has produced impactful research across multiple domains of environmental science and climate change impacts, establishing Mora as a significant contributor to our understanding of humanity's environmental challenges.
Mia Liljeström is a Staff Scientist at the Department of Neuroscience and Biomedical Engineering, Aalto University. She holds a Doctoral Degree in Engineering and Technology from Aalto University (2010) and a Master's Degree in Engineering and Technology from Helsinki University of Technology (2002). Doctoral Degree: Aalto University, 2010 Master's Degree: Helsinki University of Technology, 2002 Her research focuses on Magnetoencephalography (MEG) , Functional Connectivity , and Brain Networks . She explores Transcranial Magnetic Stimulation (TMS) , Functional MRI , and Neural Networks to map language-critical brain areas and study cortical dynamics. Recent work includes automated speech artefact removal from MEG data and test-retest reliability of brain connectivity metrics. Mia actively participates in conferences like MEG Nord and has presented invited talks on language processing and large-scale brain networks. Her publications emphasize MEG-informed TMS, cortical beta modulation, and brain stimulation precision. She contributes to the UN Sustainable Development Goal of Quality Education through neuroimaging research.
Prof. Raphaële Clément is affiliated with the Materials Research Laboratory at the University of California, Santa Barbara. Her research focuses on using NMR spectroscopy to investigate ionic conduction mechanisms in battery materials, bridging atomic-level structural insights with macroscopic electrochemical performance. Her work integrates solid-state NMR , pulsed field gradient NMR , and first-principles calculations to understand ion diffusion processes in systems like Li/Na-ion conducting rocksalt halides and polymeric ionic liquids. This multiscale approach connects local structural features to material synthesis and processing conditions. Notably, her 2022 publication on disordered battery materials highlights the interplay between crystallinity, ion dynamics, and electrolyte functionality. While specific awards or student advisement details are not mentioned in the provided text, her methodologies emphasize the synergy between experimental and computational analysis in advancing energy storage technologies.
Dr. Julian Sahasrabudhe is a researcher at the Department of Pure Mathematics and Mathematical Statistics (DPMMS) , University of Cambridge, affiliated with the School of Mathematics . His work focuses on combinatorics, number theory, and graph theory, with a emphasis on extremal problems and probabilistic methods. His recent research explores Erdős covering systems, Littlewood polynomials, and monochromatic subgraphs. Publications from 2018–2024 highlight applications of probability generating functions, arithmetic progressions, and density analysis in combinatorial structures. Contact details: jdrs2@cam.ac.uk , Room C2.08, Tel: 01223 337974. Personal homepage .
