Jiantao Jiao is an Assistant Professor at the University of California, Berkeley, affiliated with the Department of Electrical Engineering and Computer Sciences and the Department of Statistics. His research spans generative AI, foundation models, and systems for robust machine learning, integrating economics, statistics, and computation. Ph.D., Electrical Engineering, Stanford University (2018) His research interests include: Generative AI and foundation models Statistical machine learning and reinforcement learning Privacy and security in machine learning Optimization and economic perspectives of ML Applications in NLP, code generation, computer vision, and robotics Recent publications focus on reinforcement learning, generative AI alignment, and robust statistical methods. He co-directs the CLIMB research center and is affiliated with BAIR, RDI, and BLISS labs. His advisees include prominent graduate students working on foundational and applied machine learning. Teaching includes courses on statistical signal processing, probability, and convex optimization.
Dr. Francesco Burroni is a Researcher at the Institute of Phonetics and Speech Processing at Ludwig Maximilian University of Munich, specializing in the Spoken Language Processing Group. His work focuses on articulatory phonetics, speech production, and computational linguistics with a particular interest in tone languages, geminate consonants, and endangered languages. He employs machine learning techniques to analyze phonetic patterns and has contributed to studies on Thai, Japanese, Khmer, and Moklen, among others. Research interests include the timing of lexical tones relative to articulatory gestures, the role of cognitive constraints in speech rhythm, and the phonetic realization of geminate consonants. His studies integrate acoustic and articulatory data to explore phonological typology and language universals, often bridging experimental and computational methodologies. Recent work highlights adaptive planning of fundamental frequency trajectories under speaking rate changes, dissimilatory effects in tonal languages, and the application of deep learning to endangered language documentation. Burroni’s research also addresses issues like prominence clash in Italian and the functional load of vowel length in Thai. He serves as a reviewer for the Journal of the International Phonetic Association and has published extensively on topics such as syllabic prominence, coda consonant effects, and the dynamics of F0 planning. His work often involves cross-linguistic comparisons and collaborations with researchers in computational modeling and phonological theory.
Anwar Shiekh is an Instructor of Physics at Colorado Mesa University (CMU), located in Grand Junction, CO. He holds dual citizenship (American and British) and has a strong academic background with two BSc degrees (Physics and Mechanical Engineering) from Imperial College London (1980, 1983), followed by a PhD in Theoretical Physics from the same institution in 1987 under advisor Chris Isham. His research focuses on theoretical physics, including quantum gravity, black hole dynamics, quantum field theory, and the intersection of quantum mechanics with general relativity. He has contributed to textbooks such as College Physics (Serway & Vuille) and Principles of Physical Optics , providing critical feedback for improvements. Research Interests: His work addresses foundational challenges in theoretical physics, such as quantizing gravity, resolving paradoxes in black hole physics (e.g., event horizon evaporation), and exploring quantum computing error avoidance via the Zeno effect. He has also investigated impossibility proofs in physics, proposing solutions to issues like macroscopic wormhole limitations and gravitational radiation from accelerating charges. Publications Trends: Shiekh’s articles span decades, emphasizing quantum gravity corrections, operator regularization techniques, and black hole thermodynamics. Recent works include studies on magnetic monopoles and accelerating charges in gravitational fields, while earlier contributions focused on path integrals, canonical transformations, and zeta-function regularization. His 1990s research included pioneering efforts to quantize orthodox gravity and derive quantum field theory formalisms. Book Contributions: He actively collaborated on textbook revisions, notably College Physics (11th ed.) and Principles of Physical Optics (2nd ed.), where his insights addressed typographical errors and conceptual clarity. His expertise also extends to reviewing quantum gravitational corrections to Newtonian gravity and proposing experimental setups for quantum interference-based computing.
Dr. Jaemin Wang is a Research Fellow at the Max Planck Institute for Sustainable Materials in Düsseldorf, Germany. His research focuses on applying machine learning and computational modeling to advance materials science, particularly in the design and characterization of medium- and high-entropy alloys. Prior to this, he completed his M.S.-Ph.D. integrated program at Pohang University of Science and Technology (POSTECH), Republic of Korea, followed by postdoctoral research at the Center for Advanced Aerospace Materials at POSTECH. His educational background includes a B.Sc. (2015–2019) and M.Sc.-Ph.D. (2019–2024) in Materials Science and Engineering from POSTECH. His work integrates computational methods with experimental techniques to study microstructural evolution, mechanical properties, and phase transformations in advanced alloys, with applications in additive manufacturing and cryogenics. Key research areas include: Machine learning-driven alloy design and solidification modeling Computational modeling of TWIP/TRIP mechanisms in medium-entropy alloys Microstructure-control strategies for enhanced mechanical performance Cryogenic behavior of carbon-added ferrous alloys Phase stability and metastability engineering His recent publications explore the interplay between precipitation, microstructural hierarchy, and mechanical properties in novel alloy systems. Collaborative efforts focus on bridging AI-driven predictions with experimental validation for real-world material applications. Dr. Wang is affiliated with the Artificial Intelligence for Material Science research group and contributes to advancing predictive materials science through interdisciplinary approaches.
Russell Barlow is a Postdoctoral Researcher at the Department of Linguistic and Cultural Evolution within the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany. His work focuses on endangered languages of Papua New Guinea, particularly within the Keram language family. His educational background includes: PhD in Linguistics (2018), University of Hawai‘i at Mānoa MA in Linguistics (2016), University of Hawai‘i at Mānoa BA in Indo-European Studies (2013), CUNY Baccalaureate BA in Film Studies (2006), Wesleyan University Barlow's research centers on language documentation, historical linguistics, and linguistic typology with a geographical focus on the Pacific region. His fieldwork-intensive approach emphasizes preserving endangered Keram languages like Ulwa, Pondi, and Tomoip. He investigates numeral systems, language contact phenomena between Papuan and Austronesian languages, and morphosyntactic structures including antipassive constructions. His methodology combines traditional fieldwork with computational approaches to language evolution. His publication record shows consistent output in top linguistics journals with recent work examining numeral colexification patterns, areal loanwords in New Britain, and detailed grammatical descriptions of endangered languages. The publications demonstrate interdisciplinary connections between linguistic typology, cultural evolution, and cognitive science. As an active member of the Comparative Oceanic Linguistics (CoOL) research group, Barlow has secured significant research funding through Fulbright and DAAD programs. His fieldwork spans Indonesia (Gorontalo State University), Papua New Guinea, and Germany (MPI-SHH in Jena prior to Leipzig). His research infrastructure includes extensive language archives at SOAS, PARADISEC, and Kaipuleohone, ensuring long-term preservation of endangered language materials. Current projects involve analyzing esoteric numeral systems and cross-linguistic patterns in infix preservation.
Nello Blaser is a Professor at the Department of Informatics at the University of Bergen. His research focuses on topological data analysis (TDA), particularly in developing methods for encoding data into topological structures, validating unordered persistent homology, and applying these techniques in biomedicine and geophysics. He has contributed to theoretical advancements in TDA, including works on relative persistent homology and divisive cover algorithms. His interdisciplinary work bridges computer science, mathematics, and environmental science, addressing challenges in CO2 leak detection, marine pollution, and medical diagnostics. Blaser's research portfolio includes collaborations on machine learning models for flow reconstruction, receptor occupancy studies in neurology, and topological methods for analyzing gene interactions. He has been funded by the Research Council of Norway and other institutions. Notable publications include contributions to Discrete & Computational Geometry , Physics of Fluids , and Neurology: Neuroimmunology and Neuroinflammation . His work emphasizes practical applications of topological methods, such as improving environmental monitoring systems and advancing diagnostic tools for diseases like rheumatoid arthritis and multiple sclerosis.
Fabian Ruehle is an Assistant Professor of Physics and Mathematics at Northeastern University and a Senior Investigator at the NSF Institute for Artificial Intelligence and Fundamental Interactions (IAIFI). His research focuses on theoretical physics, particularly string theory, and its intersections with mathematics and artificial intelligence. He holds a PhD in Physics from the University of Bonn (2013) and a Diplom in Physics and a B.Sc. in Computer Science from the University of Heidelberg. Ruehle’s work applies machine learning techniques—such as transformers, neural networks, and genetic algorithms—to problems in knot theory, algebraic geometry, and Calabi-Yau manifolds. He has also explored applications of AI in studying multi-omic blood data for COVID-19. Education PhD in Physics (summa cum laude), University of Bonn (2010–2013) Diplom in Physics (highest distinction), University of Heidelberg (2003–2009) B.Sc. in Computer Science (highest distinction), University of Heidelberg (2006–2009) Research Interests Ruehle’s research bridges theoretical physics and computational methods. Key areas include: String Theory : Exploring dualities, compactifications, and connections to particle physics and cosmology. Machine Learning : Applying neural networks, reinforcement learning, and symbolic regression to problems in topology, algebraic geometry, and physics-informed models. Mathematics : Investigating algebraic geometry, knot theory, and Calabi-Yau metrics through computational tools. Publications Ruehle’s recent work emphasizes AI-driven approaches to theoretical physics, including studies on neural tangent kernels, ribbon knots, and Calabi-Yau manifold metrics. His articles often highlight interdisciplinary methods, such as combining genetic algorithms with string theory landscapes. Awards & Grants NSF IAIFI Grant (2021–2025) NSF Investigator-Initiated Research Project (2022–2026) Otto-Haxel Prize for Best Theoretical Physics Degree (2009) Teaching & Outreach Ruehle teaches graduate and undergraduate courses on quantum field theory, general relativity, and machine learning applications in physics. He has also organized seminars and workshops on topics like machine learning for mathematicians and string phenomenology. Labs & Collaborations He leads projects at the IAIFI and collaborates on initiatives like the String Pheno seminar series. His work often involves computational tools, such as the ribbon Python package for studying ribbon knots.
Dr. Manuela Campanelli is a Distinguished Professor of Astrophysics and John Vouros Endowed Professor at RIT, directing the Center for Computational Relativity and Gravitation (CCRG). Her research focuses on numerical relativity, black hole mergers, and gravitational wave astronomy, with landmark contributions including the first successful binary black hole simulations (2005) and discoveries of supermassive black hole recoils (2007). She leads projects modeling binary neutron stars and supermassive black hole binaries' electromagnetic emissions, contributing to LIGO collaborations. Education: Ph.D. in Physics, University of Bern (Switzerland) Research Interests: Her work combines computational astrophysics with relativistic phenomena, emphasizing gravitational waves and multi-messenger signals. Recent projects explore accretion disk dynamics around merging black holes and magnetohydrodynamics simulations of relativistic jets. Professional Highlights: Recipient of Marie Curie Fellowship (1998) Fellow of the APS (2009) and ISGR (2019) Recipient of the Richard Isaacson Award (2024) Mentioned in Kip Thorne's 2017 Nobel Lecture Grants & Funding: Leads NSF-funded projects totaling over $2M, including studies on supermassive black hole mergers and neutron star dynamics. Collaborates on computing infrastructure for multi-messenger astrophysics. Labs & Teams: Directs CCRG, a hub for computational relativity and gravitation research, and participates in the Astrophysics and Space Sciences Institute for Research Excellence (ASPIRE).
Prof. Claudia Scheimbauer is a tenure-track Professor at TU München’s Department of Mathematics, affiliated with the TUM School of Computation, Information, and Technology (CIT). Her research focuses on the intersection of mathematical physics and algebraic topology, particularly topological field theories (TFTs), higher category theory, and derived symplectic geometry. She has pioneered work on extended TFTs using factorization algebras and has contributed to foundational questions in categorical structures like 2-Segal spaces and dagger categories. She is a Principal Investigator in the SFB/CRC 1624 on Higher Structures and the prolonged SFB/CRC 1085 on Higher Invariants. Her group includes 1 PhD student (Anja Švraka) and 5 postdocs (Pelle Steffens, Walker Stern, Will Stewart, Jackson van Dyke, Yang Yang). She organizes workshops like Spaces of Tensor Categories (2025) and co-organized conferences on categorical symmetries and geometric topology. Her teaching spans algebraic topology, bordism theories, and category theory. Notable collaborations include work with Damien Calaque on cobordism categories and with Theo Johnson-Freyd on twisted TFTs. She is also involved in initiatives like the FACETS of mathematicians series addressing academic culture.
Filipa Prudêncio is an Assistant Professor in the Department of Information Science and Technology at ISCTE-IUL, University of Lisbon. She is also an Integrated Researcher at the Institute of Telecommunications (IT), where she served as a Senior Researcher from 2020 to 2024. Her research focuses on electromagnetics, wave propagation, metamaterials, and topological photonics. Education: PhD in Electrical and Computer Engineering, Instituto Superior Técnico (IST), University of Lisbon, 2014 Integrated Master’s in Electrical and Computer Engineering, IST, 2009 Bachelor’s in Electrical and Computer Engineering, IST, 2007 Research Interests: Her work spans electromagnetics, microwave engineering, antenna systems, nonreciprocal wave propagation, spacetime crystals, topological photonics, and plasmonics. She investigates novel photonic materials with non-Hermitian and nonlocal responses, aiming to control light in unprecedented ways. A central theme is the use of symmetry-breaking and time-modulation to achieve robust one-way wave transport and optical isolation. Publication Trends: Her recent publications focus on topological chiral gain, synthetic axion responses, homogenization of spacetime crystals, and nonlocal effects in photonic materials. These works contribute to the fundamental understanding of wave-matter interactions in complex media and have implications for next-generation photonic devices. Scientific Awards: ANACOM-URSI Award, 2023 IST Best Doctoral Thesis Award Best Student Paper Award, URSI General Assembly, 2015 Professor Abreu Faro Award for Best PhD Thesis (2013/2014) 3rd place, Student Paper Competition, 7th International Congress on Advanced Electromagnetic Materials, 2013 Advising and Grants: She has supervised 10 master’s and 1 doctoral student. She is a research member in 9 international projects and served as Co-Principal Investigator in one. Her work is supported by international collaborations, including the Simons Collaboration on Extreme Wave Phenomena Based on Symmetries. Labs and Teams: She is affiliated with the Antenna and Propagation Group at the Institute of Telecommunications and conducts research in the RadioFrequency Lab at IT. Her work involves close collaboration with Prof. Mario G. Silveirinha and international partners in topological photonics and metamaterials.
Mark F. Horstemeyer is the Giles Distinguished Professor and CAVS Chair in Computational Solid Mechanics at Mississippi State University (MSU), where he holds a faculty position in the Department of Mechanical Engineering within the College of Engineering. He also serves as Chief Technical Officer at the Center for Advanced Vehicular Systems (CAVS) and has held adjunct professorships in Physics and Materials Science at MSU and Tuskegee University, respectively, as well as an honorary professorship at Xihua University in China. Ph.D., Mechanical Engineering, Georgia Institute of Technology, 1995 M.S., Engineering Mechanics, Ohio State University, 1987 B.S., Mechanical Engineering, West Virginia University, 1985 His research spans solid mechanics, microstructure-property modeling, multiscale simulation, finite element analysis, atomistic modeling, damage and fracture, fatigue, and bioinspired materials . He integrates computational and experimental approaches to understand material behavior across length and time scales, with applications in lightweight design, manufacturing, and biomechanics. His work emphasizes Integrated Computational Materials Engineering (ICME), linking microstructural features to macroscopic performance. His recent publications highlight a strong focus on multiscale modeling of polymers, biological materials, and metallic systems , using molecular dynamics and finite element methods. Key themes include interatomic potential development (e.g., MEAM-BO), nanocomposite mechanics, bioinspired impact protection (e.g., woodpecker hyoid, football helmets), and constitutive modeling of complex materials. The articles demonstrate a consistent integration of computational physics with engineering design. Dr. Horstemeyer has received numerous honors, including: Fellow of AAAS, ASME, SAE, and ASM Giles Professor (MSU’s highest honor) Ralph Powe Award (highest MSU research award) West Virginia University Distinguished Alumni Award Thomas French Alumni Achievement Award (Ohio State) Multiple Sandia Awards and R&D100 recognition He has led major research initiatives, including founding the DOE Southern Regional Center for Lightweight Designs and Predictive Design Technologies, Inc. He advises graduate students and leads a research group focused on computational materials and mechanics, with funding from DoD, DOE, and industry. His work bridges fundamental science with engineering applications in automotive, aerospace, and biomedical fields. His laboratory, associated with CAVS and the Department of Mechanical Engineering, conducts advanced simulations and experimental validations in material behavior under extreme conditions. The team specializes in multiscale modeling frameworks that connect atomistic simulations to continuum mechanics, enabling predictive design of next-generation materials.
Albino Perego is an Associate Professor at the University of Trento's Department of Physics. His research focuses on gravitational physics, astrophysics, and multimessenger astronomy, particularly neutron star mergers, gravitational waves, and relativistic phenomena. He collaborates extensively with LIGO-Virgo and KAGRA collaborations. His teaching includes courses on quantum field theory, relativistic astrophysics, and general physics. Recent work includes modeling kilonovae, analyzing gravitational lensing signatures, and studying compact binary systems. He contributes to the theoretical understanding of black holes and neutron star mergers. Teaching: Quantum Field Theory I, Relativistic and Multimessenger Astrophysics, General Physics III Key Research Areas: Gravitational Wave Astronomy, Neutron Star Mergers, Multimessenger Observations Publications span high-impact journals like Physical Review D and Monthly Notices of the Royal Astronomical Society , reflecting his leadership in theoretical and observational astrophysics.
Dr. David K. Geller is a Researcher at Utah State University's College of Engineering, affiliated with the Space Dynamics Laboratory. His research program spans spacecraft dynamics, orbital mechanics, and UAV applications, with particular expertise in trajectory optimization and satellite operations. Dr. Geller's research focuses on solving complex problems in space operations through advanced mathematical techniques. His work bridges theoretical developments in orbital mechanics with practical applications for satellite inspection, debris removal, and autonomous spacecraft operations. He has pioneered the application of convex optimization for real-time trajectory planning and developed innovative approaches to spacecraft attitude determination using ground-based photometry. His research demonstrates consistent evolution from fundamental orbital dynamics to increasingly applied mission concepts. Analysis of Dr. Geller's publication record reveals a strategic progression from theoretical foundations to mission-critical applications. His recent work emphasizes autonomy in spacecraft operations, with multiple 2017-2021 papers addressing real-time trajectory planning and multi-spacecraft coordination. The recurring themes across his publications include optimization under constraints, safety in proximity operations, and efficient computational methods for space applications. Primary research areas: Satellite inspection, Spacecraft dynamics, Orbital rendezvous Methodological expertise: Convex optimization, Relative orbital mechanics, UAV navigation Application domains: Space debris removal, On-orbit servicing, Environmental monitoring Dr. Geller maintains active collaborations with researchers including Nicholas Ortolano, Aaron Avery, and previously mentored Austin M. Jensen on UAV-based fish tracking research. His work through the Space Dynamics Laboratory contributes to both fundamental aerospace engineering knowledge and practical space mission capabilities.
Zuleima T. Karpyn is a Professor of Petroleum and Natural Gas Engineering and Associate Dean for Graduate Education and Research at the College of Earth and Mineral Sciences, The Pennsylvania State University . She holds the Donohue Family Professorship and has received prestigious awards including the NSF CAREER Award and multiple Fulbright U.S. Scholar Awards . Education: Ph.D., Petroleum and Natural Gas Engineering, Penn State (2005) M.S., Petroleum and Natural Gas Engineering, Penn State (2001) B.S., Chemical Engineering, Universidad Central de Venezuela (1997) Dr. Karpyn's research focuses on multi-phase flow in porous media , digital rock physics , and fluid-rock interactions . Her work addresses critical challenges in carbon sequestration , unconventional reservoir characterization , and enhanced oil recovery through advanced imaging and computational modeling techniques. Recent publications highlight her expertise in X-ray computed tomography and wettability alteration in carbonate rocks. Her research team has pioneered studies on underground hydrogen storage and nanoporous shale transport mechanisms . Scientific Awards: 2024 Fulbright U.S. Scholar Award 2023 SPE Regional Reservoir Description and Dynamics Award 2018-2019 Big Ten Academic Leadership Fellow 2008 NSF CAREER Award Dr. Karpyn has served as Associate Editor for several journals including the Society of Petroleum Engineers Journal and Transport in Porous Media . She leads research projects on CO₂ storage pathways , deep-learning image analysis , and chemically tuned waterflooding .
George Androulakis is a Professor of Mathematics at the University of South Carolina's College of Arts and Sciences. He is actively involved in organizing and participating in the Quantum Information/Analysis seminars at USC, collaborating with faculty and students from Computer Science, Engineering, Mathematics, and Physics departments. Research Interests: His research lies at the intersection of Quantum Information , Functional Analysis , and Mathematical Physics . Recent work includes quantum divergences, Gaussian states, and quantum probability. He has co-authored significant papers on quantum data compression, f-divergences, and operator theory applications to quantum mechanics. Recent Publications: His 2024 papers on quantum block encoding and relative entropy via Nussbaum-Szkola distributions have advanced understanding of quantum divergences and Gaussian state entropies. Earlier works (2023–2015) span quantum algorithms, entanglement, dynamical entropy, and semigroup generators. Grants & Awards: Recipient of NSF Grant DMS-9970547 and multiple University of South Carolina Dean's Initiative Travel Grants (2019–2024). He has also served as Editor for the Annals of Functional Analysis (2010–2023) and Associate Editor for Quanta (2021–present).
