Anne-Sophie Chauvin is a Senior Lecturer and Researcher at École Polytechnique Fédérale de Lausanne (EPFL), School of Basic Sciences, within the Institute of Chemical Sciences and Engineering and the Supramolecular Chemistry Laboratory. She actively engages in supramolecular and inorganic chemistry, focusing on f-element (lanthanides and actinides) coordination polymers and luminescent bioprobes for biological and technological applications, including invisible inks and dye-sensitized solar cells. PhD in Bioinorganic Chemistry from University Paris V-René Descartes (thesis on Nitrile Hydratase mimetics) Postdoctoral work at University of Geneva on chiral alcohol configuration analysis Habilitation à Diriger des Recherches (HDR) from University René Descartes (2006) Her research spans Lanthanide and Actinide Chemistry , Luminescence , Coordination Polymers , Metallacages , and Photovoltaic Materials . Recent publications emphasize catalytic spiro stereocenter formation, actinide coordination polymers, and photoredox-enabled biomolecule functionalization. She has supervised PhD students including Andrei Andreichenko , Julien Andrès , Steve Comby , and Aurélien Willauer . Recognitions include Fellowship of the Royal Society of Chemistry (FRSC) and membership in the Swiss Chemical Society (SCS). Current roles include teaching General and Analytical Chemistry to first-year Pharmacy and Biology students at the University of Lausanne (UNIL), overseeing practical sessions, and serving on the EPFL School of Basic Sciences Faculty Council.
Professor Jörn Steuding holds the Professorship for Number Theory at the University of Würzburg since 2006, where he is affiliated with the Institute of Mathematics within the Faculty of Mathematics and Computer Science. His academic career includes a Ramon y Cajal research position at Universidad Autónoma de Madrid (2004-2006), postdoctoral work at the University of Frankfurt under Professors W. Schwarz and J. Wolfart (1999-2004), and completion of his habilitation at Frankfurt in 2004. His educational background includes a PhD from the University of Hannover in 1999 under Prof. G.J. Rieger, where he also served as an assistant from 1996-1999, and undergraduate studies in mathematics at Hannover from 1991-1995. Professor Steuding's research spans multiple areas of number theory, with particular focus on Zeta and L-functions (including zero distribution, universality properties, and connections to Random Matrix Theory), Diophantine analysis (covering approximation theory, equations, and the abc conjecture), elliptic curves and modular forms , algebraic number theory (including arithmetically equivalent fields), and elementary number theory with applications to primality testing and factorization. His work often bridges theoretical foundations with historical perspectives, as evidenced by his research on the Hurwitz brothers' contributions to complex continued fractions. His publication record demonstrates consistent contributions to leading journals in number theory, with research trends showing evolution from foundational work on Riemann zeta function zeros to broader investigations of L-functions in the Selberg class, Diophantine problems over quadratic fields, and historical aspects of number theory. His publications appear in prestigious journals including Mathematische Annalen, Acta Arithmetica, and the Bulletin of the American Mathematical Society. Professor Steuding has authored significant monographs including Diophantine Analysis (CRC Press/Chapman-Hall, 2005), Value distribution of L-functions (Springer Lecture Notes in Mathematics 1877, 2007), and Elementary Number Theory: A Gentle Introduction to Higher Mathematics (Springer Spektrum, 2015, co-authored with N. Oswald). He serves as the Erasmus Coordinator for his department alongside Dr. Jens Jordan, facilitating international academic exchanges. His research collaborations span multiple institutions, with notable co-authors including N. Oswald, M. Technau, H. Nagoshi, and L. Pankowski. Professor Steuding leads the Number Theory team at the University of Würzburg, maintaining an active research group focused on contemporary problems in analytic and algebraic number theory. His work continues to explore connections between classical number theory and modern mathematical physics through Random Matrix Theory applications.
Ryan Caverly serves as an Associate Professor in the Department of Aerospace Engineering and Mechanics at the University of Minnesota, Twin Cities, holding the prestigious McKnight Land-Grant Professorship. His research bridges theoretical control frameworks with practical aerospace and robotics applications, focusing on dynamic modeling and system control. Education: BS in Honours Mechanical Engineering from McGill University MS in Aerospace Engineering from the University of Michigan PhD in Aerospace Engineering from the University of Michigan Professor Caverly's research centers on input-output stability, robust control of nonlinear systems, and computationally efficient modeling of flexible structures. His work spans aerospace vehicles, spacecraft, and robotic manipulators, emphasizing theoretical rigor alongside real-world implementation challenges in structural flexibility and control precision. Recent publications reveal strong emphasis on predictive control for orbital mechanics, hypersonic vehicle dynamics, and cable-driven systems. His work consistently integrates convex optimization, state estimation, and structural dynamics to solve complex problems in solar sail technology, UAV navigation, and hypersonic flow measurement. Scientific Awards: McKnight Land-Grant Professor Caverly leads multiple externally funded projects including NASA-sponsored research on solar sail momentum management, UAV state estimation with Honeywell, hypersonic bow shock measurements with the Air Force, and deployable space structure control. His grants portfolio demonstrates significant industry and government collaboration in aerospace innovation. He directs the Aerospace, Robotics, Dynamics, and Control (ARDC) Lab, which specializes in the intersection of dynamic modeling and control theory for flexible multi-body systems, with particular focus on cable-driven mechanisms and lightweight aerospace structures.
Dr. Alexandra Piotrowski-Daspit is an Assistant Professor in the Biomedical Engineering department and Internal Medicine – Pulmonary and Critical Care Medicine at the University of Michigan Medical School. She is a chemical/biological engineer with expertise in polymeric biomaterials for gene therapies, focusing on in vivo behavior of delivery vehicles and strategies to optimize biodistribution. Education: Ph.D. in Chemical/Biological Engineering Her research bridges polymer chemistry, gene delivery, and translational medicine, emphasizing in utero interventions and pulmonary targeting. Key areas include nanoparticle surface engineering, macrophage decoys, and computational pharmacokinetic modeling. Recent publications highlight systemic in utero gene editing for cystic fibrosis, poly(amine-co-ester) nanoparticle tunability, and mucosal vaccination platforms. She also explores miRNA therapies for congenital diaphragmatic hernia and triplex-forming PNAs for CFTR correction. PhRMA Foundation Awardee (2024) Her work involves interdisciplinary collaborations, DEI initiatives, and translational projects from postdoc foundations in W. Mark Saltzman’s lab. Labs like Saltzman and SCGE teams support her research.
Hassan Z. Ashtiani is an Associate Professor in the Department of Computing and Software within the Faculty of Engineering at McMaster University. His academic profile shows consistent engagement in both teaching and research activities, with evidence of active participation in major machine learning conferences and journals through 2025. Dr. Ashtiani's research focuses on the theoretical foundations of machine learning, with particular expertise in privacy-preserving algorithms, Gaussian mixture models, and adversarial robustness. His work bridges statistical learning theory with practical algorithm design, often addressing fundamental questions about sample complexity and computational efficiency in learning systems. A significant portion of his recent work explores the intersection of differential privacy with statistical learning, developing methods for private density estimation and distribution learning. Analysis of his publication record reveals a strong trend toward increasingly sophisticated theoretical frameworks for private and robust learning. His work consistently appears in top-tier venues including NeurIPS, ICML, COLT, and ALT, with recent contributions extending into agnostic private density estimation and robust learning with tolerance. The research demonstrates progression from foundational work on nearest neighbor search and clustering algorithms toward more complex problems in private learning of high-dimensional distributions. Dr. Ashtiani teaches across multiple levels of computer science education, including undergraduate courses in Automata and Computability (COMPSCI 2AC3) and Principles of Programming (COMPSCI 2S03), as well as graduate-level courses such as Fundamentals of Machine Learning (COMPSCI 4ML3) and Theoretical Foundations of Unsupervised Learning (CAS 775). His teaching portfolio shows consistent involvement in machine learning education since at least 2019, with evidence of teaching multiple sections each academic year. His scholarly impact is reflected in mentions across 3 news outlets, reference in 1 policy source, engagement from 7 X users, and 90 readers on Mendeley, suggesting growing recognition of his contributions to theoretical machine learning.
Jamie Morgenstern is an Associate Professor at the Paul G. Allen School of Computer Science & Engineering , University of Washington . She was previously an assistant professor at Georgia Tech and a Warren Center Fellow at University of Pennsylvania . Expertise: Ethics & Fairness, Human-Centered AI, Machine Learning Education: PhD in Computer Science from Carnegie Mellon University (2015) Her research examines the social impact of machine learning and ensuring ML models do not exacerbate societal inequalities. She investigates robustness to human-generated training data, fairness in clustering and active learning, and algorithmic equity in recommendation systems. Recent publications focus on interactive ML systems , fairness constraints , and privacy-preserving methods across conferences like NeurIPS, ICML, and AIES. Key subfields include multimodal learning , membership inference attacks , and data equity . Scientific Awards: NSF Career award for "Strategic and Equity Considerations in ML" Simons collaboration project Simons Award for Graduate Students in Theoretical Computer Science (2014-2016) NSF GFRP fellowship Microsoft Research Graduate Women's Scholarship Spotlight presentation at NeurIPS 2015 Mentoring: She advises current PhD students Rachel Hong , Jie (Claire) Zhang , and Yuanyuan (Chloe) Yang . Former advisees include Daniel Jiang (MS), Bhuvesh Kumar (PhD), and Angel (Alex) Cabrera (BS). Grants: Funded by NSF Career award and Simons collaboration projects. Previously supported by Simons, NSF, and Microsoft Research fellowships. Labs & Collaborations: Collaborates with researchers like Michael Kearns , Aaron Roth , and Avrim Blum . Affiliated with the Allen School's Artificial Intelligence research group.
Kent Yagi is an Associate Professor in the Physics Department at the University of Virginia, specializing in theoretical astrophysics, gravity, and cosmology. His research focuses on using gravitational waves from compact objects like black holes and neutron stars to probe fundamental physics, including testing General Relativity in strong-field regimes and determining the equation of state of nuclear matter. Position: Associate Professor (2023-present), previously Assistant Professor (2017-2023) Education: Ph.D. in Physics from Kyoto University (2012) Prior positions: Postdoctoral Research Scholar at Princeton University (2015-2017), Postdoctoral Research Associate at Montana State University (2012-2015) Yagi's research centers on theoretical modeling of neutron stars and gravitational wave physics. He is particularly known for discovering the 'I-Love-Q' universal relations among neutron star observables that are insensitive to the equation of state. His work enables testing strong-field gravity and probing nuclear physics through gravitational wave observations. He also investigates binary pulsar systems as precision laboratories for testing gravitational theories beyond General Relativity. His research has significant implications for multi-messenger astronomy, connecting gravitational wave observations with electromagnetic counterparts to extract fundamental physics. The field has evolved rapidly since the first gravitational wave detection in 2015, and Yagi's theoretical predictions have helped shape how we interpret these observations to test gravity and nuclear physics in extreme conditions. NSF CAREER Award (2023) Sloan Research Fellowship (2019) IUPAP Young Scientist Prize (2019) Mead Honored Faculty (2018-2019) Yagi leads an active research group at UVA with multiple graduate and undergraduate students. His group collaborates with researchers across departments, including high energy physicists, nuclear physicists, astronomers, and researchers at the National Radio Astronomy Observatory. Current research directions include multi-band gravitational wave tests of general relativity, constraining nuclear matter parameters with GW170817, and developing parameterized post-Einsteinian gravitational waveform models for various modified gravity theories. The group has received multiple student research fellowships and awards, demonstrating strong mentorship and training of the next generation of physicists.
Stefano Grivet-Talocia is a Full Professor at the Department of Electronics and Telecommunications at the Polytechnic University of Turin, where he also serves as Director of the Doctoral School and President of the Doctoral School Council. He is a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory, the University Committee for Research, Technology Transfer and Services to the Territory, and the Commission for the Promotion of Library, Archive and Museum Heritage. His academic career spans over two decades at Politecnico di Torino, where he has established himself as a leading researcher in electromagnetic modeling and signal integrity. Grivet-Talocia earned his Laurea degree (summa cum laude) in Electronic Engineering in 1994 and his Ph.D. in Electronic and Communication Engineering in 1998, both from the Polytechnic University of Turin. Between 1994 and 1996, he conducted research at NASA/Goddard Space Flight Center in Greenbelt, Maryland. His educational background laid the foundation for his expertise in electromagnetic modeling, wavelet analysis, and signal processing. His research focuses on behavioral modeling, electromagnetic compatibility, macromodeling, model order reduction, numerical modeling, passivity, power integrity, signal integrity, transmission lines, and wavelets . Grivet-Talocia is particularly renowned for his work on passive macromodeling of interconnect structures, development of the TOPLine technique for transmission line simulation, and pioneering contributions to passivity enforcement algorithms. He has co-authored the first book entirely dedicated to Macromodeling (2016) and developed innovative approaches to waveform relaxation and wavelet-based signal processing. His recent publications (2024-2025) demonstrate continued leadership in model order reduction, with significant contributions to data-driven modeling of linear and nonlinear systems, power integrity analysis, and electromagnetic compatibility. His work spans both theoretical advances in numerical methods and practical applications in circuit design, with strong industry relevance particularly for semiconductor and electronic design automation companies. IEEE Fellow (2018-present) Three Intel SRS Grants (2022-2024) Three IBM SUR Grant Awards (2007-2009) Best Associate Editor Award - IEEE Transactions on Components, Packaging and Manufacturing Technology (2020) Multiple Best Conference Paper Awards (2006-2020) URSI Young Scientist Awards (1999) Ranked among the "top 2% worldwide researchers" (Stanford) since 2019 Grivet-Talocia actively supervises doctoral students including Michele Cusano, Sara Paknezhad Panahi, Antonio Carlucci, and Kun Zhao. He has secured numerous research grants from competitive national calls (PRIN) and commercial contracts with industry partners including Intel, IBM, Nokia, Hitachi, Infineon, and Cadence. His technology transfer activities include co-founding the spin-off IdemWorks (2007-2016), which was acquired by CST in 2016. He also developed the autoCircuits web service for automated circuit problem generation, widely used in electrical engineering education. He leads the EMC Group (Electromagnetic Compatibility) at DET and has been instrumental in establishing the Compact Dynamical Modeling research area. His work has practical applications in high-speed electronics design, with algorithms embedded in commercial tools like IBM PowerSPICE. Grivet-Talocia maintains strong industry connections through his research projects and serves as Associate Editor for IEEE Transactions on Components, Packaging and Manufacturing Technology.
Gareth Hall is a Senior Lecturer in Psychology at Aberystwyth University's Department of Psychology, where he has been an established member since the department's founding in 2007. He holds a PhD from Glamorgan University and is a Chartered Member of the British Psychological Society (BPS) and a Fellow of the Higher Education Academy (FHEA). His academic career includes significant administrative roles such as Examinations Officer (2007-2014, 2016), Senior Tutor (2014), and Acting Director of Admissions and Recruitment (2009, 2011). Dr. Hall's research focuses on social psychology with particular expertise in social identity theory applied to real-world contexts. His work spans sport psychology, examining sport for development programs, intergroup behavior in fandom, and well-being in physical culture communities like CrossFit. He has pioneered research testing laboratory theories in real-world settings, challenging traditional experimental paradigms through creative methodologies that incorporate digital technologies and interdisciplinary approaches. His publication record shows consistent output since 2006, with significant contributions in 2019-2023 focusing on sport psychology applications in Brazil, forensic psychology, and educational technology. His work demonstrates a clear trajectory toward interdisciplinary collaboration, particularly in sport for development contexts and the application of social identity theory to complex social issues. Scientific Awards and Recognition: Teaching and Learning Improvement Award from Aberystwyth University (2011) Active editorial roles including for Frontiers in Sports and Active Living (2021) and Bulletin of Latin American Research (2019) Dr. Hall has secured research funding from prestigious organizations including the Economic and Social Research Council (2018) and British Council (2015). His external engagements include committee membership with the British Psychological Society's Undergraduate Education Committee (2015-present), AQU Catalunya (2022-2023), and visiting researcher positions at the University of Padua (2017-2018). His work contributes to multiple UN Sustainable Development Goals, particularly those related to social development and inclusion.
Audrey Bowden is an Associate Professor at Vanderbilt University in both the Department of Biomedical Engineering and Department of Electrical and Computer Engineering . She is also the Dorothy J Wingfield Phillips Chancellor Faculty Fellow . Education: PhD in Biomedical Engineering (2007) from Duke University BSE in Electrical Engineering (2001) from Princeton University Research Interests: Bowden's work focuses on biomedical optics and point-of-care diagnostics , with a strong emphasis on addressing healthcare disparities through low-cost technologies. Key areas include: Biomedical Imaging Biophotonics Image Processing Machine Learning in Medical Imaging Optical Coherence Tomography (OCT) Functional Near-Infrared Spectroscopy (fNIRS) Publication Trends: Recent work combines machine learning with endoscopic imaging to differentiate cancer from inflammation, develops low-cost OCT systems for smartphones, and improves fNIRS accessibility for diverse patient populations. Her lab also focuses on 3D reconstruction algorithms for urological applications and specular reflection removal in endoscopic videos. Lab & Clinical Collaborations: The Bowden Biomedical Optics Laboratory (BBOL) collaborates with clinical departments including urology , dermatology , otolaryngology , and women's health . The lab integrates optics , microfluidics , and computer science to create hardware/software tools for resource-constrained environments.
Prof. Michael Krivelevich holds the Baumritter Chair in Combinatorics at the School of Mathematical Sciences, Tel Aviv University. His research focuses on probabilistic methods in combinatorics, random graphs, and positional games. He has authored influential books such as Positional Games and contributed to foundational work in random graph theory. Currently teaching Introduction to Combinatorics and Graph Theory (Spring 2025), he has extensive experience in courses like Graph Theory and Hypergraph Coloring. His work bridges theoretical computer science, coding theory, and combinatorics, with over 150 publications. Recent research explores game-theoretic thresholds, random graph evolution, and equitable coloring algorithms. Education: Ph.D. in Mathematics, Tel Aviv University (not explicitly stated, inferred from career trajectory). Research Interests Krivelevich's work emphasizes random structures , extremal graph theory , and probabilistic combinatorics . He investigates phase transitions in random graphs, positional game strategies, and algorithmic challenges in graph coloring. His contributions include proving sharp thresholds for Hamilton cycle games and analyzing WalkSAT performance on smoothed k-CNF formulas. Collaborations span theoretical computer science and discrete mathematics. Publications Recent articles address Hamiltonicity in Maker-Breaker games, equitable coloring of random graphs, and smoothed analysis of satisfiability processes. His work often combines rigorous proofs with algorithmic insights. Teaching & Mentorship Guides students through advanced combinatorial topics and has taught foundational courses since 2002. No explicit student listings available in provided texts.
Murat Kantarcioglu is a Professor of Computer Science at Virginia Tech, affiliated with the College of Engineering. He is also a Faculty Fellow at the Commonwealth Cyber Initiative (CCI) and directs the Data Security and Privacy Lab. Previously, he held the Ashbel Smith Professorship at the University of Texas at Dallas. His research focuses on data and AI security, privacy, blockchain, and cybersecurity. He has received notable awards, including the NSF CAREER Award and IEEE Technical Achievement Award, and is a Fellow of AAAS and IEEE. Education: Ph.D. in Computer Science (Purdue University), B.S. in Computer Engineering (Middle East Technical University). Research Interests: Privacy-preserving machine learning and data analytics Adversarial machine learning and cybersecurity Blockchain technology and applications Healthcare data security and genomics privacy Risk and incentive models for assured data sharing Awards and Recognition: NSF CAREER Award AMIA Homer R. Warner Award IEEE ISI Technical Achievement Award Fellow of AAAS and IEEE Distinguished Member of ACM Advising and Labs: Directed over 20 PhD/Master’s students, many in cybersecurity and privacy domains. Founder and director of Virginia Tech’s Data Security and Privacy Lab. Associate at Harvard’s University Data Privacy Lab. Service and Leadership: Extensive program committee roles in top conferences (KDD, AAAI, IEEE ICDE). Former CCI co-chair for IEEE TrustCom. Co-authored influential textbooks on adversarial machine learning.
Professor Soo-Yeun Lee is a leading Sensory Scientist and academic leader at Washington State University (WSU), serving as Director of the School of Food Science since 2023. She holds a Ph.D. in Food Science from the University of California, Davis, and a B.S. in Food Engineering from Yonsei University, Seoul. Previously, she served as a Professor at the University of Illinois, Urbana-Champaign (UIUC) from 2001-2022, with administrative roles including Assistant Dean and Associate Head. Her research focuses on sensory science and healthful eating, addressing challenges in sodium and sugar reduction, functional food development, and understanding consumer behavior. Notable projects include strategies to enhance taste retention in low-sodium foods and analyzing picky eating behaviors in children. She has published over 100 papers, with recent works exploring remote consumer testing methodologies and sodium reduction perceptions in the food industry. Lee has received numerous awards, including the Fred W. Tanner Lectureship (2021), Paul A. Funk Award (2018), and Samuel Cate Prescott Award (2011). She actively contributes to professional service roles, such as chairing USDA review panels and serving on the IFT Board of Directors. As a mentor, she has shaped food science education through teaching awards and leadership in curriculum development.
Professor Antonio Griffo holds the position of Professor of Power Electronics and Electric Drives at the University of Sheffield's School of Electrical and Electronic Engineering. He leads the Electrical Machines and Drives Research Group and is involved in the High Reliability Drives Group. His academic journey includes a MSc (2003) and PhD (2007) in Electrical Engineering from the University of Naples, followed by research roles at Bristol and Sheffield Universities before becoming a Lecturer in 2013 and later a Professor. His research focuses on advanced control of electric drives, SiC-based power electronics for aerospace/renewables, fault detection in machines, and thermal management. Key projects include modeling hybrid AC/DC power systems for 'More Electric Aircraft', sensorless control techniques, and real-time simulation methodologies. He has pioneered work on SiC converter reliability, insulation monitoring, and condition-based maintenance systems. Publications (15+ in top journals like IEEE Transactions) emphasize innovative solutions for power electronics challenges, including voltage stress mitigation, thermal modeling, and fault tolerance. His work bridges theory and application, addressing critical issues in aerospace, renewable energy, and electric vehicle systems. Griffo also contributes to educational advancements through modular training platforms for power electronics education. Labs/Teams: Active in the Electrical Machines and Drives Research Group, focusing on high-reliability drive systems and sustainable energy technologies. Collaborates with industry on projects like the EPSRC Offshore Wind Prosperity Partnership.
Jessica Glazier is an Assistant Professor in the Frances L. Hiatt School of Psychology at Clark University, Worcester, MA. She completed her Ph.D. and M.S. in Psychological Science at the University of Washington (2022 and 2019, respectively) and a B.A. in Psychology & Music from Albion College (2015). Her research focuses on challenging societal norms about social categories like gender, race, and sexual orientation, emphasizing inclusivity for marginalized groups such as transgender, multiracial, and asexual individuals. She employs methods from social, developmental, cognitive psychology, and interdisciplinary approaches like feminist and LGBT studies. Research Interests Exploring how social categorization affects perceptions and experiences of individuals who defy traditional norms Examining consequences of gender/racial essentialism on prejudice and discrimination Investigating gender development in youth, including transgender and cisgender children Addressing statistical methodology limitations in psychological science Recent Research Trends Her 2024 work highlights challenges in LGBTIQ+ research inclusivity and examines gender attitudes across diverse children. Recent projects (2023–2024) emphasize statistical frameworks for meaningful inference, intersectionality in harassment perceptions, and the role of adult beliefs in shaping children’s identity autonomy. Earlier studies (2019–2022) established foundational insights into gender categorization mechanisms and transgender children’s developmental similarities to cisgender peers. Teaching & Mentoring Teaches Advanced Social Psychology (PHD) and Statistics (undergraduate), prioritizing student learning through dedicated skill-building sessions. Mentored research assistants (e.g., Liza Moore, Martina Khurana) and supervised Elizabeth Abel’s honors project on race and gender essentialism. Actively supports early-career researchers via peer mentoring programs. Labs & Collaborations Conducts research within Clark University’s Frances L. Hiatt School of Psychology lab environments, collaborating with institutions like Northeastern University and international teams on child development and social categorization projects.
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