Yuanzhu Chen is a Professor in the School of Computing at Queen’s University, affiliated with the Faculty of Arts and Science. He previously served as Professor and Department Head at Memorial University of Newfoundland (2005–2021). His research focuses on computer networking, mobile computing, complex networks, and applied machine learning, emphasizing wireless innovation beyond traditional wired systems. He holds a PhD from Simon Fraser University (2004) and a B.Sc. from Peking University (1999). Education: PhD in Computing Science (Simon Fraser University, 2004); B.Sc. in Computer Science (Peking University, 1999). Earlier roles include Post-doctoral Researcher at Simon Fraser University (2004–2005) and leadership positions at Memorial University, including Department Head (2019–2021). Research Interests: Network Coding and Opportunistic Routing Mobile and Wireless Network Protocols Complex Network Analysis Machine Learning Applications Indoor Positioning Systems Social Network Dynamics Selected Awards: Recipient of Queen’s University President's Award for Distinguished Teaching. Lab Affiliation: Director of the Wireless Networking and Mobile Computing Lab (WineMocol). Active in collaborative projects involving smartphone sensors, community-based environmental monitoring, and stock market prediction using web data.
Titu Andreescu is a retired Associate Professor in the Science/Mathematics Education Department at the University of Texas at Dallas (UTD), affiliated with the School of Natural Sciences and Mathematics. He holds a Ph.D., M.S., and B.A. in Mathematics from the University of West Timisoara, Romania. His research focuses on enhancing mathematics education through problem-solving initiatives, particularly via AwesomeMath—a program encompassing summer camps, correspondence courses, and journals for gifted students. He specializes in Diophantine Analysis, particularly quadratic equations and their applications in advanced mathematics. Andreescu has authored numerous publications, including textbooks like Complex Numbers from A to Z and contributed to Olympiad problem design for competitions such as the IMO and W.L. Putnam. He has received prestigious awards, including the Edith May Sliffe Award and led the U.S. IMO team to historic victories, including a first-place finish in 1994. His professional roles include directing the Mathematical Olympiad Summer Program (MOSP) and serving as a coach for national teams in Romania and the U.S. Key projects include keynote speaking at international math camps and consulting for competitions. He has secured grants totaling over $800,000 for mathematics education initiatives, including funding from Akamai Technologies and the U.S. Army Research Office.
Trine Mygind Korsby is an Assistant Professor at the Department of Anthropology, University of Copenhagen, Faculty of Social Sciences. Her research is centered on the anthropology of transnational crime, with a focus on human trafficking, sex work, pimping, and criminal livelihoods. She conducts long-term ethnographic fieldwork in Romania, Italy, Portugal, and Denmark. Her primary research interests include: Anthropology of the body, desire, and labor Morality, perpetration, and ethnographic unease Skills and social relationships in criminal economies Collaborative concept-work and experimental research methods Her recent publications (2023–2025) reflect a deep engagement with the lived realities of traffickers and victims, the ambiguities of fieldwork in criminal settings, and the moral complexities of perpetration. Themes such as agency, visibility, time, and freedom recur across her work, particularly in urban and transnational contexts. She has received significant recognition, including: Marie Skłodowska-Curie Global Fellowship (2022) Elite Research Travel Grant from the Danish Ministry of Higher Education and Science (2013) Individual Postdoc Grant from the Independent Research Fund Denmark (2015) Korsby is affiliated with the Centre for Global Criminology and was a visiting scholar at UC Berkeley (2013) and a postdoc at Stanford University (2016–2018). In 2023–2024, she was selected for the UCPH Forward program for research leadership. Her current project, TRAFFICKER, explores the social relationships of convicted human traffickers and their integration of legal and illegal work, with a research stay at CUNY Graduate Center (2024–2025). She has co-edited a special issue on transnational street economies in Migration & Society (2023) and has contributed to public discourse through media appearances and articles challenging simplistic narratives about traffickers and victims.
Dr. Genevieve Cezard is a Research Fellow in the Cardiovascular Epidemiology Unit at the University of Cambridge and a fellow of the Big Data for Complex Diseases driver programme (HDR UK). Her work leverages linked electronic health records across 70 million UK residents to investigate population health, with emphasis on health inequalities, disease associations, and multimorbidity development. Her educational trajectory began as a statistician at the University of Edinburgh (2010), leading to a PhD from the University of St Andrews (2016) focused on ethnic health disparities in Scotland. Subsequent research established methods to characterize multimorbidity trajectories based on core diseases. Genevieve's research spans: Long-term health impacts of diabetes and chronic conditions Social determinants of disease trajectories Population-level vaccine effectiveness analysis Epidemiological modeling of multimorbidity Health record linkage methodologies Disparities in healthcare access by demographics She currently leads a fellowship project examining diabetes complications during the COVID-19 era (2020-2027), analyzing health consequences across diverse subgroups using integrated GP/hospital records from England, Scotland, and Wales. Scientific recognition includes: Competitive St Leonard’s PhD studentship (University of St Andrews) Prestigious HDR UK Big Data for Complex Diseases Fellowship As lead analyst for England on the first UK-wide study of under-vaccination using individual-level health records, her findings directly informed national public health interventions. Current work focuses on identifying diabetes-related disease trajectories to optimize clinical follow-up protocols across the UK healthcare system. She collaborates within HDR UK's Molecules to Health Records Driver Programme, utilizing cross-institutional health data infrastructure.
Myrto Mavraki is an Assistant Professor in the Department of Mathematics at the University of Toronto, with affiliations to both the St. George and Mississauga campuses. She specializes in arithmetic geometry and dynamical systems, particularly the theory of unlikely intersections and canonical heights in families of rational maps. Institution: University of Toronto School: Faculty of Arts and Science Department: Department of Mathematics Rank: Assistant Professor Her research focuses on deep connections between arithmetic geometry and dynamical systems. Key areas include equidistribution, variation of canonical heights, preperiodic points, and unlikely intersections in families of maps, especially on the projective line and in elliptic surfaces. These topics lie at the heart of modern arithmetic dynamics and have strong ties to Diophantine geometry and number theory. The most recent publications show a sustained focus on canonical height variation, equidistribution, and the geometry of post-critically finite and preperiodic loci in parameter spaces. Collaborations with leading mathematicians such as Laura DeMarco, Harry Schmidt, and Hexi Ye reflect her central role in current developments in arithmetic dynamics. Her work combines algebraic, analytic, and arithmetic techniques to solve deep conjectures and establish foundational results. Her research is supported by an NSERC Discovery Grant and an Early Career Supplement (2024–2029), and previously by an NSF grant (DMS-2200981). She has mentored or collaborated with several prominent researchers and is likely supervising graduate students, though none are explicitly named. She does not list formal awards, but her publication record in top journals and prestigious fellowships indicate high recognition in the mathematical community. Mavraki held the Benjamin Peirce Fellowship at Harvard (2020–2023), a highly competitive postdoctoral position, and prior positions at the University of Basel and Northwestern University. She earned her PhD from the University of British Columbia under Dragos Ghioca.
Professor Dahlia Malkhi is a leading academic and researcher in distributed systems and blockchain technology. She currently holds a faculty position at the University of California, Santa Barbara (UCSB), where she heads the Foundations of Financial Technology (FfTech) research lab. Her work focuses on reliability, security, and consensus mechanisms in distributed systems, with a recent emphasis on blockchain innovations like HotStuff, which underpins Diem, Aptos, and other blockchains. She has held influential roles at industry leaders such as Chainlink Labs, Diem Association, VMware, and Microsoft Research. Education: Ph.D. in Computer Science from The Hebrew University of Jerusalem. Past roles include CTO of Diem Association (2019–2022), Principal Researcher at VMware (2014–2019), and Partner Principal Researcher at Microsoft Research (2004–2014). Research Interests: Blockchain consensus algorithms (e.g., HotStuff, Flexible Paxos), Byzantine Fault Tolerance (BFT), secure multi-party computation (FairPlay), and distributed database systems (CorfuDB). Her work bridges academic theory with industrial applications, emphasizing practical scalability and security. Awards: ACM Fellow (2011), IEEE TCDP Outstanding Technical Achievement Award (2021), IBM Faculty Award (2003/2004). She has also held leadership roles in conferences like Usenix ATC and program chairs for multiple distributed systems events. Advising & Grants: Advises projects at Space Computer, Lyquor Labs, and Chainlink Labs. Her research labs and collaborations include work on BBCA-Chain, Lumiere, and BFTBrain, advancing consensus mechanisms in decentralized systems. Labs/Teams: Leads UCSB’s FfTech lab, co-founded VMware Research, and contributed to foundational blockchain projects like DiemBFT and Espresso Systems. Her work impacts technologies such as NSX-T control planes and distributed financial infrastructure.
Yong-Bin Kang is a Senior Data Science Research Fellow at the ARC Centre of Excellence for Automated Decision Making and Society (ADM+S) at Swinburne University of Technology, affiliated with the School of Social Sciences, Media, Film and Education. He holds a PhD in AI from Monash University and leads numerous transdisciplinary research projects applying artificial intelligence to address complex societal challenges. Education: PhD in Faculty of IT, Monash University, Australia Dr. Kang's research focuses on Responsible AI and Society, with specific interests in developing Societal-AI platforms that integrate social data with ethical principles. His work spans healthcare, humanitech, education, financial planning, environmental health, and justice domains. He investigates how AI can enhance decision-making processes while promoting societal well-being, with particular attention to ethical implementation and human-centered approaches. His expertise encompasses AI, natural language processing, machine learning, and decision-making optimization. Analysis of Dr. Kang's recent publications reveals a strong trajectory toward socially responsible AI applications across diverse domains. His work consistently bridges technical AI capabilities with social implications, particularly focusing on ethical frameworks, community-centered design, and addressing societal inequalities through technology. The publications demonstrate increasing collaboration across disciplines including criminology, environmental science, mental health, and education. Dr. Kang is actively involved in significant research funding initiatives, with multiple ongoing projects that address critical societal challenges through AI. His supervision availability includes Doctorate (PhD) candidates, indicating his commitment to mentoring the next generation of researchers in AI and data science fields. Current Flagship Areas: Digital Capability Innovative Society Manufacturing Futures Sustainable Development Goals: Good Health and Well Being (SDG 3) Industry, Innovation and Infrastructure (SDG 9) Affordable and Clean Energy (SDG 7)
JuHyun Lee is an Associate Professor of Architecture and Computational Design in the School of Built Environment at the Faculty of Arts, Design and Architecture (ADA), University of New South Wales (UNSW) Sydney, where they also hold the prestigious title of Scientia Academic. With a professional background in architecture and construction (1998-2002), they have held academic positions across Australia including a five-year post-doctoral fellowship at the University of Newcastle (2012-2017) and a senior research fellowship at the University of South Australia (2018), following earlier research and teaching roles in South Korea (2003-2011). Lee specializes in architectural design computing, design cognition, and urban complexity, integrating computational methods, cognitive science, and architectural theory to advance architectural intelligence and human-centered design. Their research spans architectural visualization, analysis and design methods, algorithm/protocol design, and data visualization with computational approaches. They have established a strong research program examining the intersection of language, culture, and design cognition, particularly focusing on cross-cultural design communication between Australia and Korea. Lee's recent publications demonstrate a clear trajectory toward increasingly sophisticated integration of computational methods with architectural design theory, particularly in the areas of shape grammar, space syntax, and machine learning applications. Their work shows consistent focus on practical applications of computational design methods to real-world architectural problems, with growing emphasis on cross-cultural collaboration and intelligent design systems. The research portfolio reveals a deepening engagement with AI and machine learning techniques applied to architectural design assessment and generation. Scientia Academic at UNSW Sydney Associate Fellow of the Higher Education Academy (AFHEA, 2020) As an educator, Lee develops cutting-edge courses in computational design and Building Information Modeling (BIM), integrating experiential learning and industry engagement. They have secured over $11 million in research funding, including multiple ARC Discovery Projects and an Australia-Korea Foundation grant. Lee co-directs the Advanced Architectural Analytics Laboratory (A 3 LAB), leading interdisciplinary research on design automation, spatial analysis, and machine learning applications in architecture, while also leading cross-cultural initiatives like the Australia-Korea Architects' Network (AKAN). Lee supervises multiple HDR students working on culturally sustainable urban design, socio-spatial patterns in public housing, and computational layout generation. Their research has significant implications for improving design communication across cultural boundaries and developing more coherent, clear, and accessible built environments through computational design approaches.
Seth Herzon is the Milton Harris '29 Ph.D. Professor of Chemistry at Yale University, with joint appointments in the Departments of Pharmacology and Therapeutic Radiology at the Yale School of Medicine. He is also a Member of the Yale Cancer Center and co-founder of Modifi Biosciences, which was acquired by Merck in Fall 2024. Herzon joined Yale in 2008 after completing his PhD at Harvard University and an NIH postdoctoral fellowship at the University of Illinois, Urbana-Champaign. Her research focuses on organic synthesis with an emphasis on the molecular mechanisms of action of DNA-damaging compounds, particularly anticancer and microbiome-derived natural products. His laboratory has made significant contributions to understanding colibactin, a gut microbiome metabolite that induces colorectal cancer, and has developed novel chemotherapies targeting DNA repair defects in tumors. His work spans synthetic chemistry, chemical biology, and translational medicine, with projects ranging from total synthesis of complex natural products to developing antibacterial agents. His recent publications reveal a strong trend toward microbiome-cancer interactions, particularly focusing on colibactin's role in carcinogenesis, alongside continued innovation in synthetic methodology and therapeutic development for drug-resistant cancers. His work bridges fundamental chemistry with clinical applications, particularly in cancer therapeutics. Among his numerous accolades are the NSF CAREER Award, Searle Scholar Award, Packard Fellowship, Sloan Fellowship, Arthur C. Cope Scholar Award, and the 2024 Yale Cancer Center Class of '61 Cancer Research Award. He served as Associate Editor for The Journal of Organic Chemistry from 2018-2023 and was a member of the United States Defense Science Study Group from 2018-2019. Herzon has mentored numerous PhD students and postdoctoral researchers who have gone on to successful careers in academia and industry. His laboratory at Yale continues to be at the forefront of chemical research with significant translational impact, particularly in cancer drug discovery. The lab maintains active collaborations with researchers across Yale, including in pharmacology, radiobiology, and cancer biology.
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.
William Sulis is an Associate Clinical Professor in the Department of Psychiatry and an Associate Member of the Department of Psychology at McMaster University, where he also directs the Collective Intelligence Lab (CILab). With a unique interdisciplinary background spanning mathematics, physics, and psychiatry, Dr. Sulis bridges the gap between theoretical science and clinical practice. His educational journey is exceptionally diverse: B.Sc. (Hon) in Mathematics with minor in Theoretical Physics, Carleton University (1976) M.D., University of Western Ontario (1980) M.A. in Mathematics, University of Western Ontario (1984) Ph.D. in Mathematics, University of Western Ontario (1989) FRCPC in Psychiatry (1984) Ph.D. in Theoretical Physics, University of Waterloo (2014) CRCPC in Geriatric Psychiatry (2015) Dr. Sulis's research explores the intersection of complex systems theory with psychological and psychiatric phenomena. His work on Collective Intelligence investigates how group dynamics emerge from individual interactions, while his research on Temperament and Psychobiology examines the continuum between normal personality variations and mental illness. He has made significant contributions to understanding Synchronization in Complex Systems and developed the concept of Transient Induced Global Response Synchronization (TIGoRS) , which has implications for neural coding and information processing. His theoretical work extends to Quantum Foundations and Process Algebra Theory , where he proposes novel approaches to quantum mechanics. Analysis of his recent publications reveals a consistent thread connecting complex systems theory with psychological and psychiatric applications. His work increasingly focuses on bridging the gap between temperament theory and clinical psychiatry, using mathematical and computational approaches to understand mental illness. Simultaneously, he continues to develop theoretical frameworks in quantum physics through process algebra models, demonstrating remarkable interdisciplinary range. Dr. Sulis has received several prestigious awards including The Governor General's Medal for having the highest overall grade point average in his graduating class, the Henry Marshall Tory Scholarship, and multiple Harry Stevenson Southam Scholarships. Throughout his career, Dr. Sulis has mentored numerous students across disciplines, supervising research projects spanning collective intelligence, semantic space modeling, network dynamics, and temperament studies. His Collective Intelligence Lab has served as a hub for interdisciplinary research connecting computer science, psychology, and psychiatry. Dr. Sulis has also been actively involved in professional organizations, serving as President of The Society for Chaos Theory in Psychology and the Life Sciences (1996-1998) and holding editorial positions for several journals including "Dynamical Psychology" and "Nonlinear Dynamics in Psychology and the Life Sciences." As Director of the Collective Intelligence Lab at McMaster University, Dr. Sulis fosters research exploring how complex adaptive systems can model cognitive and social phenomena. The lab serves as an intellectual nexus where mathematics, computer science, psychology, and psychiatry converge to address fundamental questions about intelligence, both individual and collective.
Avi Wigderson is the Herbert H. Maass Professor in the School of Mathematics at the Institute for Advanced Study, Princeton. He is a leading authority in theoretical computer science, particularly computational complexity theory. Wigderson organizes the Computer Science and Discrete Mathematics (CSDM) program at the Institute, fostering interdisciplinary research at the intersection of mathematics and computer science. Wigderson earned his Ph.D. (1983), M.A. (1982), and M.S.E. (1981) from Princeton University. Prior to his current position, he held appointments at The Hebrew University of Jerusalem (1986-2003), Princeton University (1990-1992), Mathematical Sciences Research Institute, Berkeley (1985-1986), IBM Research (1984-1985), and University of California, Berkeley (1983-1984). Wigderson's research spans computational complexity theory, randomness and computation, algorithms and optimization, circuit complexity, proof complexity, quantum computation and communication, and cryptography. His work explores fundamental questions like whether mathematical creativity can be automated (P vs NP problem), the security of electronic commerce, the role of randomness in computation, and the potential of quantum mechanics to enhance computation. He has made significant contributions to understanding the power and limitations of efficient computation. Analysis of Wigderson's recent publications reveals a strong focus on optimization, complexity theory, and their mathematical foundations. His work connects diverse areas including non-commutative algebra, geometric complexity, graph theory, and quantum computing. A recurring theme is exploring whether fundamental computational problems like P vs NP can be addressed through optimization techniques such as gradient descent. His research shows increasing interdisciplinary connections between theoretical computer science, mathematics, and physics. ACM A.M. Turing Award (2023) Abel Prize (2021) Donald E. Knuth Prize (2019) Gödel Prize (2009) American Mathematical Society's Levi L. Conant Prize (2008) Rolf Nevanlinna Prize (1994) Yoram Ben-Porat Presidential Prize for Outstanding Researcher (1994) Bergman Fellowship (1989) Member, American Academy of Arts and Sciences Member, National Academy of Sciences While specific details about Wigderson's students are not provided in the source material, his extensive lecture series, workshops, and program organization suggest significant mentorship activities. His book "Mathematics and Computation" published by Princeton University Press serves as an educational resource for students and researchers. Wigderson has organized major programs at the Institute for Advanced Study including "Lower Bounds in Computational Complexity" (2018) and "Pseudorandomness" (2017), creating research opportunities for numerous scholars. Wigderson leads the Computer Science and Discrete Mathematics (CSDM) program at the Institute for Advanced Study, which brings together researchers from mathematics and computer science to explore fundamental questions in computation. His work with collaborators across multiple institutions has established connections between theoretical computer science and diverse fields including quantum information theory, algebraic geometry, and optimization. Recent projects focus on non-commutative optimization and its applications to computational complexity problems.
Gil Serrancoli Masferrer is an Associate Professor in the Department of Mechanical Engineering at the School of Engineering of East Barcelona (EEBE), part of the Polytechnic University of Catalonia (UPC). He is affiliated with the InSup - Research Group in Surface Interaction in Bioengineering and Materials Science and the LAM - Multimedia Applications and ICT Laboratory. His work focuses on biomechanics, computational modeling, and telerehabilitation systems development for clinical applications. Dr. Serrancoli's research spans multisolid dynamics, dynamic optimization, movement simulation, and telerehabilitation systems. His expertise lies in applying computational techniques to solve complex problems in orthopedics, gait analysis, and rehabilitation engineering. His work bridges mechanical engineering with biomedical applications, particularly in musculoskeletal modeling and simulation of orthopedic procedures. He has developed novel computational frameworks for estimating internal musculoskeletal loading and muscle adaptation in various conditions, including hypogravity environments. His recent publications demonstrate a strong focus on in-silico modeling of orthopedic procedures, particularly knee osteotomies (proximal fibular osteotomy versus high tibial osteotomy), with detailed analysis of joint pressure redistribution. He has also pioneered the application of machine learning techniques, particularly recurrent neural networks, to biomechanical problems including cycling biomechanics and running dynamics prediction. His work consistently integrates computational efficiency with clinical relevance. Technical Award - OpenSim+ Advanced Workshop March 2024 Accésit del XLV Congreso de la Sociedad Ibérica de Biomecánica y Biomateriales European Society of Biomechanics Travel Award OpenSim Virtual Workshop - Technical Award OpenSim Visiting Scholar 2017 Enginyers BCN 2018 Dr. Serrancoli leads several competitive R&D projects including 'Muvity: a novel physical telerehabilitation system' for vulnerable populations and 'Simulaciones predictivas in silico para cirugías ortopédicas' (Predictive in-silico simulations for orthopedic surgeries). He collaborates extensively with researchers across Europe, particularly with Jordi Torner, Josep Maria Font Llagunes, and Joan Carles Monllau, and has secured funding from national and regional programs including Plan Estatal de Investigación Científica y Técnica y de Innovación. He is actively involved in the BIOMEC - Biomechanical Engineering Lab and the TecSalut - Research Group in Health Technologies, where he contributes to the development of innovative solutions for healthcare challenges, particularly in the areas of telerehabilitation and computational biomechanics for orthopedic applications.
Aleksandr (Sasha) Aravkin is Associate Professor in the Department of Applied Mathematics and Adjunct Associate Professor of Health Metrics Sciences, Mathematics, and Statistics at the University of Washington. He serves as Director of Mathematical Sciences at the Institute for Health Metrics and Evaluation (IHME), where he leads the Mathematical Sciences and Computational Algorithms team and contributes to strategic direction for applying mathematical sciences to analytic challenges. Dr. Aravkin earned his PhD in Mathematics (Optimization) and MS in Statistics from the University of Washington in 2010, following a BSc in Mathematics and Computer Science in 2004. His educational background forms the foundation for his interdisciplinary research approach. His research expertise spans large scale optimization, machine learning, data science, convex and variational analysis, algorithm design, robust statistics, inverse problems, and uncertainty quantification . These methodologies are applied across diverse domains including health metrics, computational medicine, tracking and navigation, seismic imaging, computational finance, and neuroscience. Dr. Aravkin has pioneered approaches for fusing physics-based and data-driven models, enabling innovative solutions to complex problems. Dr. Aravkin's publication record demonstrates a strong focus on health metrics and Global Burden of Disease studies, with recent work emphasizing meta-analytic approaches for risk-outcome relationships. His research spans epidemiological modeling, health effects of various exposures, and forecasting disease burden across populations. The publications reveal a consistent pattern of high-impact work in top journals including The Lancet and Nature Medicine, often addressing critical public health questions through rigorous statistical and mathematical frameworks. At IHME, Dr. Aravkin has led significant projects including the Burden of Proof Studies (2019-2024) which analyzed 153 risk-outcome pairs, and COVID-19 Modeling (2020-2023) where his team developed forecasting models and excess mortality estimation methods. He has also been instrumental in developing the Evidence Score model, requiring novel algorithmic approaches. His work bridges theoretical mathematical sciences with practical applications to improve global health policy and practice.
Martin Nilsson Jacobi serves as President and CEO of Chalmers University of Technology, holding the position of the institution's fourteenth President since September 2023. He simultaneously maintains his academic standing as Professor of Complex Systems at the university, demonstrating his dual commitment to academic leadership and scholarly work. Professor Nilsson Jacobi's research portfolio spans theoretical physics, complex systems theory, and ecological applications. His work bridges multiple disciplines, creating innovative approaches to understanding natural systems through mathematical and computational frameworks. His research trajectory shows an evolution from theoretical physics to complex ecological systems, with particular emphasis on spatial patterns, ecosystem stability, and marine conservation strategies. His scholarly output demonstrates consistent productivity across multiple domains. The most recent publications (2020-2022) focus on complex ecological communities, spatial coherence in heterogeneous landscapes, and species-area relationships, while earlier work (2010-2015) explored self-assembly systems, hierarchical dynamics, and theoretical approaches to complex systems. This progression reflects his ability to apply fundamental theoretical concepts to increasingly complex real-world ecological challenges. Lifetime member of the Swedish Royal Academy of Engineering Sciences (IVA) Professor Nilsson Jacobi has held significant leadership roles beyond his current presidency, including serving as chairman of the Faculty Senate and Head of Department at Chalmers. His international research experience includes collaborations with Los Alamos National Laboratory and the Nordic Institute for Theoretical Physics (NORDITA), highlighting his global scientific engagement. He has successfully secured research funding through multiple projects supported by the Swedish Research Council and the European Commission, demonstrating his ability to lead substantial research initiatives.
