Gabriel Hanssen Kiss is currently an Associate Professor at the Department of Computer Science (IDI), Norwegian University of Science and Technology (NTNU), and Senior Engineer at the Operating Room of the Future, St Olavs Hospital. He holds a PhD in Engineering from K.U. Leuven, Belgium, with a focus on visualization and automated polyp detection in virtual colonoscopy, and a computer science engineer diploma from Technical University of Cluj-Napoca, Romania. Education: PhD in Engineering (K.U. Leuven), Computer Science Engineer (Technical University of Cluj-Napoca) Affiliations: NTNU (Associate Professor), St Olavs Hospital (Senior Engineer) His research focuses on medical image processing and visualization, extended reality (XR) systems, and ultrasound technology. Key subfields include volumetric data visualization, image registration/fusion, and XR applications in both medical and non-medical domains. Recent publications highlight AI-driven echocardiography, LiDAR-GNSS data fusion for localization, and mixed reality in surgical training. Collaborative work spans AI applications in transesophageal echocardiography for left ventricular function, 3D segmentation models, and augmented reality systems for medical education. He works with teams at NTNU and St Olavs Hospital, focusing on systems like the Operating Room of the Future (FOR).
Lieven Vandenberghe is a Professor at the University of California, Los Angeles (UCLA) with joint appointments in the Electrical and Computer Engineering Department and the Department of Mathematics . He received his PhD in Electrical Engineering from K.U. Leuven, Belgium, in 1992. Vandenberghe has held visiting professor positions at K.U. Leuven and the Technical University of Denmark, and his career at UCLA began in 1997 after postdoctoral work at K.U. Leuven and Stanford University. His research focuses on optimization , systems and control , and signal processing . He co-authored the influential textbook Convex Optimization (2004) with Stephen Boyd and edited the Handbook of Semidefinite Programming (2000). His recent publications emphasize large-scale convex optimization algorithms, first-order methods, and applications to power systems and signal processing. Key contributions span semidefinite programming , operator splitting , and chordal graph techniques for sparse optimization. He has supervised numerous PhD and MS students, including Xin Jiang (2022), Jinchao Li (2015), and Martin Skovgaard Andersen (2011). Vandenberghe also developed software tools like CVXOPT and CHOMPACK for convex and sparse matrix optimization.
Gary K. Nave Jr. is an Assistant Teaching Professor in Mechanical Engineering at Colorado School of Mines (2022-present), where he teaches dynamics and robotics while developing an advanced dynamics course. Previously, he was a Postdoctoral Scholar at Northwestern University (2020-2022) studying pain dynamics in Sickle Cell Disease, and a Postdoctoral Research Associate at University of Colorado Boulder's BioFrontiers Institute (2018-2020) researching collective insect behavior. He holds a Ph.D. in Engineering Mechanics from Virginia Tech (2018) and a B.S. in Engineering Science and Mechanics from the same institution (2012). His research focuses on interdisciplinary modeling at the intersection of Engineering, Applied Mathematics, Physics, and Biology. Key areas include: Collective behavior in biological systems (honey bee swarms, fire ant towers) Dynamics of physiological systems (pain mechanisms in Sickle Cell Disease) Fluid-structure interactions (flying snakes, vibrating cylinders) Biomimetic design (maple seed dispersal) His publications demonstrate strong trends in nonlinear dynamics applications to biological systems, with recent work emphasizing medical informatics, swarm intelligence, and biomechanics. Analysis of his research output shows consistent focus on phase space structures, collective behavior modeling, and interdisciplinary approaches combining engineering principles with biological phenomena. Nave has mentored multiple students including: Hadley Tallackson (undergraduate) on honeybee swarm modeling High school students April, Jackson, and Sloan through STEM Research Experience programs He has collaborated with research teams at Northwestern University's Department of Engineering Science and Applied Mathematics, University of Colorado Boulder's BioFrontiers Institute, and Virginia Tech's Biological Transport program. His experimental work includes x-ray CT analysis of honeybee swarms and wind tunnel testing of biomimetic structures.
Prof. Dr. Dietmar Graeber is a Professor of Energy Economics at Ulm University of Applied Sciences (THU), where he has worked since 2017. He leads the Smart Grids Research Group and the Transfer Center for Energy Economics , while overseeing the Energy Economics B.Sc. program . He is also a board member of the Institute for Energy Technology and Economics (IEE) , the Smart Grids Platform Baden-Württemberg , and participates in the Center for Energy Research and Technology , Center for Digitization, Analytics, and Data Science Ulm , and HAW Doctoral Center in Baden-Württemberg . Focuses on quantitative methods in energy systems , particularly distributed flexibilities , sector integration , and European energy market design . Coordinates multiple national and international research projects , including collaborations with ENTSO-E. Teaches in Bachelor and Master programs , with lecture materials available via Moodle . Research trends highlight innovations in TSO-DSO interaction , small PV participation in balancing markets , capacity trading , and smart meter applications for grid services. His work emphasizes market coupling , data-driven solutions , and privacy-preserving flexibility .
Ian J. Cero is an Assistant Professor in the Department of Psychiatry at the University of Rochester School of Medicine and Dentistry , focusing on suicide prevention and behavioral research. His work spans clinical trials, social network analysis, and mental health policy. Research Areas: Suicide prevention, PTSD, eating disorder treatment, digital health interventions Methodology: Randomized controlled trials, sentiment analysis, categorical data analysis, causal inference Collaborative Work: Military mental health, school-based interventions, inflammatory biomarkers, equity in risk screening Recent publications highlight his contributions to implementing behavioral interventions in crisis centers, leveraging social networks for prevention, and examining stress-inflammation interactions in suicide risk. His work integrates clinical practice with computational approaches.
Dr. Guangze Yang is an NHMRC Emerging Leadership Fellow at the School of Chemical Engineering within the Faculty of Sciences, Engineering and Technology at The University of Adelaide. His research program bridges fundamental nanomaterial science with practical applications in healthcare and industrial biotechnology, with a strong emphasis on translational potential. He leads a research group focused on developing advanced nanomaterials with high therapeutic and industrial value. Dr. Yang's research interests center on the design and development of advanced nanomaterials for drug delivery, biomimetic systems, and sustainable technologies. His work specifically focuses on engineering polymeric and lipid nanoparticles with high drug-loading capacity, targeted delivery, and controlled release properties. He also investigates microfluidic-based nanoparticle synthesis and advanced drying techniques to improve stability and scalability. Beyond drug delivery, his research explores biofunctional materials including peptides, proteins, and stimuli-responsive systems, examining how material properties influence cellular interactions, immune responses, and therapeutic efficacy. His work extends to environmentally sustainable approaches in resource industries through biomolecules for mineral processing. Analysis of Dr. Yang's recent publications reveals a strong focus on biomimetic and bioinspired nanomaterials, with particular emphasis on cell membrane-coated nanoparticles, peptide-based designs, and sustainable processing techniques. His work demonstrates a consistent progression toward increasingly sophisticated delivery systems with multi-functional capabilities, integrating computational approaches with experimental validation. The research spans both biomedical applications and sustainable industrial processes, reflecting his interdisciplinary approach. NHMRC Emerging Leadership Fellowship (2025-2029) for Innovative Chemoimmunotherapy for Metastatic Castration-Resistant Prostate Cancer Dr. Yang actively mentors students and early-career researchers, contributing to the development of the next generation of scientists in nanotechnology and biomaterials. His NHMRC Fellowship project represents significant competitive funding that supports his innovative work in cancer therapy. He maintains active collaborations with both academic and industry partners, facilitating the translation of fundamental research into practical applications. His research program demonstrates a strong balance between fundamental scientific inquiry and applied technological development. Dr. Yang's research group operates at the intersection of chemical engineering, nanotechnology, and biomedical science, utilizing advanced synthesis techniques, characterization methods, and biological evaluation to develop next-generation nanomaterials. The group maintains strong connections with clinical partners to ensure relevance to real-world medical challenges, while also working with industry to address sustainability challenges in resource processing.
Hubert Klahr is an apl. Prof. (Associate Professor) and Research Group Leader at the Max Planck Institute for Astronomy in Heidelberg, Germany. He leads multiple research groups focused on Planet Formation and Exoplanets, Star Formation, and the Theory of Planet and Star Formation within the Department of Planet and Star Formation. His research centers on computational physics applied to the formation of the solar system and exoplanets, with particular emphasis on turbulence in protoplanetary disks. Klahr employs multidimensional self-gravitating magneto hydro dynamical simulations of turbulent gas and embedded particles using massive parallel computers to investigate fundamental questions about solar system formation, star formation processes, and the role of turbulence in planet formation. His specific research interests include determining how Earth came to life, how massive and small stars form, the nature of turbulence in planet formation, the initial mass function of planets, planetary formation distances from stars, and the prevalence of Earth-sized planets in habitable zones. His recent publications (2024-2025) focus on advanced computational modeling of protoplanetary disks, planet-disk interactions, radiation hydrodynamics, and planetesimal formation mechanisms. Key research themes include vertical shear instability, three-temperature radiation hydrodynamics, spiral arm formation in disks, and dust evolution in protoplanetary environments. Prof. Klahr has engaged with the public through lectures such as 'Lucy: Eine Reise zu den Fossilien unseres Sonnensystems' (Lucy: A Journey to the Fossils of Our Solar System), where he discussed the Lucy mission to Trojan asteroids that serve as relics of the early solar system.
Helga Molbæk-Steensig is a Research Associate in the Department of Law at the European University Institute (EUI) in Florence, Italy. She is actively engaged in the ELOQUENCE project, focusing on the ethical and legal dimensions of generative AI. Her research spans human rights, public international law, empirical legal studies, and the impact of technology on justice systems. She has contributed to major reform debates at the European Court of Human Rights and has published widely on judicial independence, the margin of appreciation, and fair trial rights in the age of artificial intelligence. Research Interests: Her work emphasizes empirical legal methods , quantitative research design , and mixed-methods analysis in international human rights law. She investigates how courts like the ECtHR navigate legitimacy under political pressure, how AI affects fair trial rights, and how pandemics challenge fundamental rights protections. Her scholarship critically engages with methodological issues in legal research, particularly case-law sampling and doctrinal interpretation. The recent publications highlight a strong trajectory in AI and law , human rights in crisis contexts , and institutional legitimacy . Themes include algorithmic accountability in healthcare, judicial deference, dynamic interpretation, and the politicization of enlargement in the Western Balkans. Her editorial work supports early-career researchers in navigating academic publishing ethics and challenges. Scientific Contributions: Co-authored entries in the Companion to The European Convention on Human Rights (Brill, 2023) Contributed to Human Rights and Artificial Intelligence (Oxford University Press, 2023) Published in European Journal of International Law , Leiden Journal of International Law , European Health Law Journal , and Utrecht Journal of International and European Law Regular contributor to leading blogs such as EJIL:Talk! , Strasbourg Observers , and Verfassungsblog Teaching and Academic Engagement: She has taught courses on legal philosophy, fundamental rights, and populism at the University of Copenhagen and delivered guest lectures at the University of Messina and Leipzig University. Her international outreach includes summer schools on human rights and transitional justice in Sarajevo and Leipzig. She mentors early-career scholars and advocates for methodological rigor and ethical publishing practices. Labs and Research Groups: She is affiliated with the ELOQUENCE project at EUI, which investigates generative AI’s legal and ethical implications. She also contributes to the Human and Fundamental Rights Working Group and the Expert Knowledge and Authority in Transformative Times initiative, reflecting her interdisciplinary approach to law, technology, and democracy.
Rajiv Sethi is a Professor of Economics at Barnard College, Columbia University, and an External Professor at the Santa Fe Institute. He is currently a Joy Foundation Fellow at the Radcliffe Institute for Advanced Study at Harvard University, with prior visiting positions at Microsoft Research and the Institute for Advanced Study in Princeton. He contributes to CORE (Curriculum Open-Access Resources for Economics), promoting open-access economics education. Ph.D. in Economics, New School for Social Research B.S. in Mathematics, University of Southampton His research centers on information and beliefs , particularly how stereotypes influence interactions in the criminal justice system. In collaboration with Brendan O’Flaherty, he analyzed victim-offender dynamics, judicial bias, and prosecutorial behavior, culminating in the 2019 book Shadows of Doubt: Stereotypes, Crime, and the Pursuit of Justice . With Muhamet Yildiz, he studies communication under differing perspectives, exploring public disagreement , information seeking , and correlated biases in social groups. His work spans game theory , behavioral economics , inequality , and prediction markets . Rajiv’s recent publications show a consistent trend in analyzing social and economic inequality , information processing , and structural bias across domains—from climate-conflict dynamics to urban crime and financial speculation. His interdisciplinary approach integrates economics with cognitive science, sociology, and public policy. Joy Foundation Fellow at the Radcliffe Institute for Advanced Study Founding Associate Editor, Collective Intelligence Editorial Board, American Economic Review and Economics and Philosophy Rajiv Sethi has advised on public policy, particularly in criminal justice reform and pandemic economic resilience. He has been involved in national efforts on pandemic response and advocated for equitable economic policies, including Federal Reserve reforms and universal testing. He has collaborated widely with scholars such as Brendan O’Flaherty, Muhamet Yildiz, Sam Bowles, and Glenn Loury. While no formal students are listed, his mentorship is evident through collaborative research and public intellectual engagement. He has received research grants from Barnard College and major fellowships, supporting interdisciplinary work on justice, inequality, and collective decision-making. Rajiv is affiliated with the Santa Fe Institute , a hub for complex systems research, and contributes to initiatives like CORE and Collective Intelligence , emphasizing open science and collaborative knowledge production. His work on prediction markets and public discourse reflects active engagement with real-world policy debates, especially around elections, policing, and climate.
Guillaume Haeringer is a Professor at the Bert W. Wasserman Department of Economics and Finance within the Zicklin School of Business at the City University of New York (CUNY). He holds a Ph.D. in Economics from Universite Louis Pasteur (Strasbourg, France) and has dedicated his career to the study of market design, game theory, and blockchain technologies. His research focuses on matching mechanisms, strategic behavior in markets, and the economics of digital currencies. Education: Ph.D., Economics, Universite Louis Pasteur DEA Analyse Economique, Universite Louis Pasteur Maitrise d'Econometrie, Universite Louis Pasteur His recent work includes publications on gradual college admission processes, monotone strategyproofness, and the microeconomics of cryptocurrencies. He has contributed to journals such as the Journal of Economic Theory , Games and Economic Behavior , and the Journal of Economic Literature . His research is supported by multiple PSC-CUNY grants, including projects on matching markets and school choice dynamics. Professor Haeringer has received prestigious awards such as the ICREA Academia Research Prize (2013), Fundacion Ramon Areces research award (2009), and a Marie Curie fellowship (2000). He actively contributes to academic service through committee memberships and editorial roles, including associate editor at the Journal of Public Economic Theory . Current projects explore school choice under uncertainty and self-selection mechanisms.
Luca Bergamasco is a Fixed-term Tenure-Track Assistant Professor at the Department of Energy (DENERG) , College of Electrical and Energy Engineering , Politecnico di Torino. His academic career spans multiple teaching roles across Electrical, Energy, Mechanical, Aerospace, and Automotive Engineering colleges, with a focus on computational heat transfer and solar energy technologies. Faculty of Electrical and Energy Engineering Member of Mechanical, Aerospace, and Automotive Engineering College Dr. Bergamasco's research centers on thermal engineering and industrial energy systems , combining machine learning with traditional thermal analysis. Key projects involve optimizing phase change materials for energy storage and developing neural network models for industrial applications. His recent publications (2023-2025) reveal a strong emphasis on thermal conductivity enhancement , CO2 reduction , and machine learning integration in energy systems. Collaborative work with Alessandro Ribezzo on metal wool-phase change composites demonstrates practical applications of his research. Teaching activities include Advanced Solar Energy Technologies and Computational Heat and Mass Transfer courses at both PhD and Master's levels. He actively supervises PhD students and contributes to courses like Machine Learning for Energy Applications .
Marcin Bownik is a Professor in the Department of Mathematics at the University of Oregon, part of the College of Arts and Sciences. He has been at the University of Oregon since 2003, progressing from Assistant Professor (2003-2008) to Associate Professor (2008-2014) and finally to Professor (2014-present). He has also held visiting positions at the Institute of Mathematics of the Polish Academy of Sciences (2009-2010, 2016-2017, 2023-2024). Education: Ph.D. in Mathematics, Washington University in St. Louis, 2000 (Thesis Advisor: Richard Rochberg) M.A. in Mathematics, Washington University in St. Louis, 1997 Magister in Mathematics, University of Warsaw, Poland, 1995 Marcin Bownik's research focuses on Harmonic Analysis, Wavelets, and Frames . His work spans several interconnected areas including non-isotropic function spaces such as anisotropic Hardy, Besov, and Triebel-Lizorkin spaces; construction of wavelets with arbitrary dilations; theoretical aspects of wavelets and frame wavelets; the structure of shift-invariant spaces in L 2 (R n ); Gabor systems; and weighted norm inequalities. His recent publications demonstrate continued innovation in anisotropic analysis, frame theory, and applications to operator theory. His work often bridges pure mathematics with applications in signal processing and geometric analysis. Bownik serves as editor for several prestigious journals including the Journal of Fourier Analysis and Applications (2019-present), Applied and Computational Harmonic Analysis (2020-present), and Dissertationes Mathematicae (2020-present). He has organized numerous conferences and special sessions on Wavelets, Frames, and Related Expansions, demonstrating his leadership in the field. Ph.D. Students: Kenneth Hoover (2007) - Dimension functions of rationally dilated wavelets John Jasper (2011) - Infinite dimensional versions of the Schur-Horn theorem Li-An Daniel Wang (2012) - Multiplier theorems for anisotropic Hardy spaces Joey Iverson (2016) - Frames generated by actions of locally compact groups Martin Hiserote (2019) - A characterization of anisotropic H 1 (R N ) by smooth homogeneous multipliers Bownik maintains an active teaching schedule at the University of Oregon, regularly teaching advanced courses in Real Analysis, Complex Analysis, and specialized topics in Harmonic Analysis. His teaching spans from undergraduate calculus courses to graduate-level seminar courses in his research specialty areas.
Najmeh Bazmohammadi is an Assistant Professor at the Faculty of Engineering and Science , Aalborg University , specializing in Electric Power Systems and Microgrids . Her teaching portfolio includes PhD courses on Microgrids: Modelling, Control, and Energy Management and Advanced Optimization and Control in Power and Energy Systems . Research Interests : Microgrid control, energy management systems, battery degradation, digital twins, renewable energy integration, and hybrid energy systems. Projects : Co-investigator in the HECATE project (Hybrid Electric Regional Aircraft) and supervisor for a Digital Twin framework in Microgrids project. Collaboration : Works with Professors Josep M. Guerrero and Juan C. Vasquez on maritime, space, and rural electrification projects. Publications : 72+ publications since 2012, focusing on microgrid optimization, energy storage, and control systems. Expertise : Model predictive control, multi-carrier energy systems, and resilience strategies for remote and space-based communities.
Enric Boix is an Assistant Professor at the University of Pennsylvania , affiliated with The Wharton School and the Statistics and Data Science Department . His research focuses on the mathematical foundations of deep learning, including neural network training dynamics, inductive bias, adversarial robustness, and AI safety. Undergraduate: Princeton University (advised by Emmanuel Abbe) PhD: MIT EECS (advised by Guy Bresler and Philippe Rigollet) Postdoctoral: MIT Mathematics & Harvard CMSA Current work investigates theoretical aspects of AI, such as: Feature learning in neural networks Model distillation and fine-grained expert architectures Chain-of-thought reasoning in LLMs Inductive bias in ResNets and Transformers NTK approximation validity and optimization dynamics Adversarial prompt vulnerabilities His publications span top conferences like NeurIPS, ICLR, and EMNLP, emphasizing mathematical rigor in understanding deep learning phenomena. Awards include: NSF Graduate Research Fellowship Siebel Fellowship Apple AI/ML Fellowship He has collaborated extensively with researchers including Mikhail Belkin, Emmanuel Abbe, and Philippe Rigollet, focusing on theoretical advancements to improve AI efficiency and trustworthiness.
Ioannis Remediakis is an Assistant Professor at the Department of Materials Science and Technology, University of Crete, with a research focus on electronic structure theory and first-principles simulations of low-dimensional materials. His work bridges quantum mechanics and macroscopic properties, targeting applications in nano-chemistry (e.g., metal nanoparticles, heterogeneous catalysis) and nano-physics (e.g., 2D semiconductors, nanostructured solids). He is affiliated with the Institute for Electronic Structure and Laser at FORTH, enhancing his interdisciplinary collaboration. Education: B.S., M.S., and Ph.D. in Physics from the University of Crete (1997, 1998, 2002), with Ph.D. research conducted at Harvard University. Affiliations: University of Ioannina, Technical University of Denmark (DTU), University of Crete (since 2008), FORTH. Research Themes: Surface and edge energetics, catalytic mechanisms, stability of 2D materials, and machine learning for nanoparticle morphology. His recent publications highlight trends in perovskite sensors, high-entropy alloys, transition metal dichalcogenides, and polymer nanocomposites. These works emphasize computational modeling, environmental applications, and energy-related materials. Despite no explicit scientific awards listed, his extensive publication record underscores significant contributions to materials science and nanotechnology.
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