Arvind Parkhe is a Laura H. Carnell Professor of Strategy and International Business at Temple University’s Fox School of Business. He previously taught at Indiana University’s Kelley School of Business (1989–2003) and holds degrees from IIT Bombay (B.Tech.), Georgia State University (MBA), and Temple University (Ph.D.). His research focuses on strategic alliances, global supply chains, international joint ventures, and trust in cross-border partnerships. He has published in top journals like the Academy of Management Journal and Strategic Management Journal, earning awards such as the AIB Best Dissertation Award (1990) and JIBS Decade Award (2001). Teaching excellence spans all academic levels: recognized as outstanding faculty for Ph.D., MBA, and undergraduate programs. Service leadership includes Vice President of the Consortium for Undergraduate International Business Education (2014), Chair of Fox’s Strategic Management Department (2010–2020), and Managing Director of Fox MBA Programs (2005–2010). He received Temple’s Musser Outstanding Service Award (2012) and Faculty Service Excellence Award (2012). Key research contributions emphasize interorganizational networks, global competitive strategies, and trust mechanisms in alliances. His work bridges theory and practice, addressing challenges in global business operations and strategic collaboration.
Prof. Dr. Thomas Hofmann is a Full Professor and Head of the Department of Computer Science at ETH Zurich since 2014. He also leads the Institute for Machine Learning. His research focuses on machine learning, deep learning, natural language understanding, and text understanding. Hofmann holds a Ph.D. from the University of Bonn (1997) and has held academic positions at Brown University (1999–2004) and TU Darmstadt. He transitioned to industry as Director of Engineering at Google (2006–2014), leading the Zurich R&D center, before returning to academia. He co-founded Recommind (2000) and 1plusX (Swiss marketing tech company), currently serving as Chief Scientist and board member at 1plusX. Education: Ph.D. in Computer Science, University of Bonn (1997) Postdoctoral Work: MIT (CBCL/AI Lab), UC Berkeley (EECS/ICSI) His research explores advanced machine learning techniques, including diffusion models, generative adversarial networks, and optimization dynamics. Hofmann’s entrepreneurial ventures reflect his focus on applying AI to real-world challenges, such as e-discovery and marketing technology. His work spans theoretical contributions (e.g., neural network training dynamics, continual learning) and applied innovations (e.g., image editing, portrait generation). Hofmann actively bridges academia and industry, influencing both research and commercial AI applications.
Dr. Peichen Zhong is an Assistant Professor in the Department of Materials Science and Engineering at the National University of Singapore (NUS). He leads the Applied Machine Learning and Materials Modeling (AM³) Group, focused on advancing computational methods for clean energy technologies. His research integrates machine learning with atomistic simulations to tackle challenges in battery materials, disordered materials, and sustainable energy systems. Education: B.S. in Physics from University of Science and Technology of China (2018); Ph.D. in Materials Science from UC Berkeley (2023, advised by Prof. Gerbrand Ceder); Postdoctoral training at Lawrence Berkeley National Lab and BIDMaP, co-advised by Persson, Cheng, and Krishnapriyan. Research Interests: Computational modeling of battery cathodes/electrolytes, AI-driven interatomic potentials, statistical mechanics in disordered materials, and generative models for scientific discovery. Key areas include Li/Na-ion batteries, solid-state reactions, and sustainable energy materials. Awards: BIDMaP Emerging Scholar Fellowship (UC Berkeley CDSS, 202?), 2023 Rising Stars in Materials Science (CMU/MIT/Stanford). Labs/Teams: The AM³ Group at NUS MSE focuses on interdisciplinary research combining theory, computation, and AI4Science. Current openings include PhD students and postdoctoral researchers.
Sheng Shen is a Professor in the Mechanical Engineering Department at Carnegie Mellon University (CMU) , with courtesy appointments in the Departments of Electrical and Computer Engineering and Materials Science and Engineering . He earned his Ph.D. in Mechanical Engineering (Minor in Electrical Engineering) from Massachusetts Institute of Technology (MIT) , and his B.S. and M.S. from Huazhong University of Science and Technology in China. Prior to joining CMU in 2011, he conducted postdoctoral research at UC-Berkeley . Education: Ph.D., Mechanical Engineering, MIT (2010) B.S. & M.S., Power Engineering & Engineering Thermophysics, Huazhong University of Science and Technology (2000 & 2003) Research interests include nanophotonics , nanoscale energy transport and conversion , nanofabrication , and advanced manufacturing , with applications in thermal management , light sources and devices , thermal emission control , solar energy conversion , infrared sensing , and multifunctional materials . His work leverages interdisciplinary expertise in thermal and optical measurements , material synthesis , device fabrication , and theoretical modeling . Recent publications highlight advancements in infrared radiation control , thermal interface materials , metasurface engineering , and graphene-based nanosystems . His scientific awards include: NSF CAREER Award DARPA Director's Fellowship DARPA Young Faculty Award Elsevier/JQSRT Raymond Viskanta Award CMU Dean's Early Career Fellowship Philomathia Foundation Research Fellowship Hewlett-Packard Best Paper Award Best Paper Award, Julius Springer Forum Advising spans Ph.D. and postdoctoral researchers in nanoscale energy systems, with alumni contributing to solar energy conversion , infrared sensing , and flexible electronics . His lab receives funding from ARL, DARPA, DOE, DTRA, NASA, NSF, and ONR , and recently secured a DURIP award for instrumentation.
Professor Omar A. Saleh is a distinguished physicist and materials scientist at the University of California, Santa Barbara, holding appointments in both the Materials and Physics Departments. Since summer 2023, he has served as Chair of the Materials Department and maintains a minority appointment in the Biomolecular Science and Engineering (BMSE) Program, where he previously served as Director from 2013-2017. His educational background includes a B.S. in Physics from MIT (1997) and a Ph.D. in Physics from Princeton (2003), supported by a Hertz Fellowship. Following postdoctoral work at École Normale Supérieure in Paris developing single-molecule techniques for motor protein/DNA studies, he joined UCSB in 2005. Saleh's research centers on fundamental principles of biomolecular behavior through experimental investigation of biopolymer elasticity and biomimetic organelles. His lab pioneers precision single-molecule stretching experiments to study entropic/energetic contributions in soft systems and creates life-like behaviors using reconstituted nucleic acid/protein assemblies. Key focus areas include DNA nanostar phase separation, liquid-liquid phase behavior, intrinsically disordered proteins, and non-equilibrium biomolecular systems. His publication trends reveal a strong emphasis on biomolecular condensates (2023-2025), with recurring themes in DNA nanotechnology, polyelectrolyte physics, and single-molecule mechanics. Recent work explores tension-mediated control of phase separation, transcriptional regulation of biomolecular liquids, and active matter principles in DNA systems. NSF CAREER Award (2008) Bessel Research Award from Alexander von Humboldt Society (2017) Fellow of the American Physical Society (2019) Saleh actively mentors graduate students and postdocs including Sam Wilken, Gabrielle Abraham, Anna Nguyen, and Aria Chaderjian, whose research spans DNA nanostar liquids, active droplets, and complex coacervation. His lab develops innovative instrumentation including high-speed magnetic tweezers and GPU-based tracking systems, supported by grants such as NSF/MCB-BSF: Direct force measurements of intrinsically disordered proteins. The Saleh Group operates at BioE 3006, focusing on creating quantitative models of biological function through physical reconstitution.
Aarti Singh is a Professor in the Machine Learning Department at Carnegie Mellon University and Director of the NSF AI Institute for Societal Decision Making. She leads research at the intersection of machine learning, statistics, and decision making, with applications to scientific and societal domains. Her work focuses on designing principled interactive algorithms for learning and decision making under uncertainty. Education: Ph.D. in Electrical Engineering, University of Wisconsin-Madison (2008) M.S. in Electrical Engineering, University of Wisconsin-Madison (2003) B.E. in Electronics and Communication Engineering, University of Delhi (2001) Research Interests: Professor Singh's research centers on developing interactive machine learning algorithms that go beyond finding input-output associations to make higher-level decisions about the most informative data and actions. Her work spans autonomous decision making, including active sampling, stochastic optimization, bandits, and reinforcement learning that are statistically optimal, computationally tractable, and robust. She also investigates human factors in decision making, designing algorithms that model and leverage human feedback while accounting for bias, memory effects, and calibration. Her research has applications in material science, cosmology, and peer review systems. Research Trends: Professor Singh's recent publications demonstrate a strong focus on reinforcement learning, particularly in developing more efficient and robust algorithms for decision making under uncertainty. Her work bridges theoretical foundations with practical applications, spanning from fundamental algorithm development to real-world implementation in scientific domains. There's a clear trajectory toward integrating human factors into decision-making algorithms, with significant contributions to peer review systems and preference learning. Scientific Awards: NSF Career Award United States Air Force Young Investigator Award A. Nico Habermann Faculty Chair Award Harold A. Peterson Best Dissertation Award Multiple paper awards Advising and Grants: Professor Singh has advised numerous PhD and master's students, many of whom have gone on to faculty positions or research roles at leading institutions. Her research is supported by prestigious grants from ONR, Simons Foundation, AFRL, ARL, and NSF. She serves as General Chair (2025) and Program Chair (2020) for the International Conference on Machine Learning (ICML) and has held leadership roles in multiple professional organizations. Research Team: Professor Singh leads a vibrant research group within the Machine Learning Department at CMU, with current PhD students working on topics including reinforcement learning, human-AI collaboration, and decision making under uncertainty. She also directs the NSF AI Institute for Societal Decision Making, which brings together researchers from multiple disciplines to develop AI systems that support human decision making in societal contexts.
Stanislav Smirnov is a Professor of Mathematics at the University of Geneva, where he has been a faculty member since 2003. He also holds a part-time position at the Chebyshev Laboratory of St. Petersburg State University. As Director of the National Centre of Competence in Research SwissMAP since 2014, he leads a major research initiative funded by the Swiss National Science Foundation. His education includes a mathematics degree from St. Petersburg State University (1992) and a PhD from the California Institute of Technology (1996). Prior to joining Geneva, he held positions at Yale University, the Institute for Advanced Study in Princeton, the Max Planck Institute in Bonn, and the Royal Institute of Technology in Stockholm. Professor Smirnov's research focuses on the mathematical foundations of statistical physics, with particular emphasis on conformal invariance in two-dimensional lattice models. His work has revolutionized our understanding of critical phenomena through rigorous mathematical approaches, establishing deep connections between probability theory, complex analysis, and statistical mechanics. He develops novel discrete complex analysis techniques to prove continuum limits of lattice models at criticality. His publication record shows consistent advancement in understanding random planar geometry, percolation theory, and the Ising model, with increasing attention to Liouville quantum gravity in recent years. His work bridges deep mathematical analysis with physical insights, often providing rigorous proofs for phenomena previously understood only through physical intuition. Fields Medal (2010) for the proof of conformal invariance of percolation and the planar Ising model in statistical physics As an advisor, Professor Smirnov has mentored doctoral students including Ekin Arikök and Nikolai Bobenko. He leads the ANALYSE, PHYSIQUE MATHÉMATIQUE ET PROBABILITÉS research group at the University of Geneva. His research is supported by major grants including the NCCR SwissMAP, European Research Council's AG COMPASP, and Swiss National Science Foundation grants 200020_143434 and 200020_141329. Professor Smirnov has organized numerous influential conferences, including the "Conformal maps from probability to physics" workshop at Monte Verità (2010) and multiple "Random Planar Geometry" meetings in Les Diablerets, fostering collaboration between mathematicians and physicists working on critical phenomena and random geometry.
Stanislav Smirnov is a Professor at the University of Geneva's Department of Mathematics since 2003 and Head of the Chebyshev Laboratory at St. Petersburg State University since 2010. He holds a Ph.D. from the California Institute of Technology (1996) and a B.Sc./M.Sc. from St. Petersburg State University (1992). His research focuses on mathematical physics, probability, complex analysis, and dynamical systems, with groundbreaking contributions to the understanding of critical phenomena in statistical physics. Key achievements include receiving the Fields Medal (2010), the highest honor in mathematics, for his work on percolation and the Ising model. He has organized major international conferences, such as the 'St. Petersburg School in Probability & Statistical Physics' (2012) and the '2D Statistical Physics Workshop' (2013). His academic career includes positions at Yale University, the Max-Planck Institute, and KTH Royal Institute of Technology. Education: Ph.D., Mathematics, California Institute of Technology (1996) B.Sc./M.Sc., Mathematics (with honors), St. Petersburg State University (1992) Awards: Fields Medal (2010) European Research Council Advanced Grants (2008, 2013) Rollo Davidson Prize (2002) Salem Prize (2001) Smirnov’s research bridges probability theory and complex analysis, with notable results on conformal invariance in two-dimensional models. His work has advanced understanding of critical exponents, percolation thresholds, and the universality of phase transitions. He advises doctoral students and collaborates internationally on projects funded by Swiss and European grants. He co-organized over 20 conferences worldwide, including plenary talks at the International Congress of Mathematicians (2006, 2010) and the World Congress in Probability and Statistics (2012). His lab fosters interdisciplinary research, linking mathematics to physics and computer science.
Michael A Osborne is Professor of Machine Learning at the University of Oxford and leads the Bayesian Exploration Lab . He serves as Director of the EPSRC Centre for Doctoral Training in Autonomous Intelligent Machines and Systems and co-directs the Oxford Martin AI Governance Initiative. His research focuses on Bayesian optimization, Gaussian processes, and probabilistic numerics with applications in quantum devices, battery modeling, and AI governance. Key Positions: Professor of Machine Learning, University of Oxford Official Fellow, Exeter College Co-founder of Mind Foundry Lead Researcher, Oxford Martin Programme on Technology and Employment Research Themes: Probabilistic modeling for quantum systems Uncertainty quantification in energy storage AI safety and societal impact analysis Automated experimental design Quantum device calibration Probabilistic numerical methods Technical Contributions: Bridging reality gap in quantum devices Efficient Bayesian quadrature techniques Personalized neurostimulation algorithms Automated measurement protocols Quantum-classical hybrid ML
Dr. Krishnan Mahesh is a Professor at the University of Michigan with joint appointments in Mechanical Engineering and Naval Architecture and Marine Engineering. He serves as Director of the Center for Naval Research and Education and leads the Computational Fluids Laboratory, where he develops advanced numerical methods for simulating multi-physics turbulent flows. Education: Ph.D. (1996), M.S. (1990) from Stanford University, B.Tech (1989) from IIT Bombay Leadership: Director, Center for Naval Research and Education (2022-present) His research focuses on high-fidelity simulations of turbulent flows with applications in marine propulsors, multiphase systems, cavitation, hydroacoustics, superhydrophobic surfaces, biofouling, fluid-structure interaction, and flow stability. His group develops the MPCUGLES software for unstructured grid simulations on parallel computing platforms. Recent work examines cavitation dynamics , tip vortex flows , and roughness-induced transition in complex marine and aerospace systems. His 15 most recent articles demonstrate expertise in LES/DNS of multi-physics flows, with emphasis on marine propulsion, bubble collapse, and turbulent noise prediction. Scientific Honors: 2021 AIAA Best Paper Award 2018 Fulbright Scholar 2017 Marine Propulsors Symposium Best Paper 2011 APS Fellow 2010 Taylor Award for Distinguished Research He mentors numerous graduate students and postdoctoral fellows, with collaborative projects spanning jet in crossflow analysis, gas turbine simulations, and shock-turbulence interactions. His research receives funding from ONR, NSF, and international naval programs.
Karl Gustafsson is a Professor at Stockholm University within the Department of Economic History and International Relations. His work bridges security studies , collective memory , and digital research methods in international relations. Current Role: Professor of International Relations, Stockholm University Previous Positions: Post-Doc at Lund University, Researcher at Swedish Institute of International Affairs Visiting Appointments: University of Tokyo, Osaka University, Keio University, Academia Sinica, Nordic Institute of Asian Studies Research Focus: Karl specializes in memory politics , ontological security , and anxiety-driven international dynamics , particularly in Sino-Japanese relations and digital platforms . His studies explore how historical narratives and online memory construction influence state identity and policy. Awards & Grants: Recipient of the Wang Gungwu Prize (2014) and Stockholm University Association’s award (2011). Holds Swedish Research Council and Marianne & Marcus Wallenberg Foundation grants for projects on apologies in international politics and digital memory in East Asia . Publications: His work appears in journals such as International Studies Quarterly , European Journal of International Relations , and Memory Studies , addressing topics like narrative power in East Asia, anxiety’s role in policy change , and digital humanities applications in IR.
Professor Maarten Prak is a distinguished scholar of Economic and Social History at Utrecht University, where he has been a faculty member since 1992. He is affiliated with the Faculty of Humanities and the Department of History and Art History. Prak serves on the governing board of the Royal Netherlands Academy of Arts and Sciences (KNAW) and All European Academies (ALLEA), having previously chaired the Humanities Board of the Netherlands Organisation for Scientific Research (NWO) from 2014-2016. Prak's research spans social history, urban history, guild systems, citizenship, global history, and early modern European history, with particular focus on the Dutch Golden Age. His scholarly trajectory evolved from local Dutch social history to national history, then to comparative European history, and finally to global historical perspectives. His work demonstrates how urban citizenship, guild structures, and social organization shaped political development across Europe. His publication record reveals consistent engagement with long-term historical processes, particularly examining how citizenship evolved from urban contexts to national frameworks. His research connects economic structures with political institutions, showing how guilds, urban governance, and social hierarchies influenced the development of modern political systems across Europe. Member Royal Netherlands Academy of Arts and Sciences (2008) Teacher of the Year, Universiteit Utrecht (2014) Winner of the 2015 book award of the American Ceramic Circle Winner of the 2019 Prix Dix-Septième Siècle Prak has maintained an active teaching career alongside his research, earning recognition as Teacher of the Year in 2014. His academic governance responsibilities have included serving as research director for his department and faculty, chairing the Humanities Board of NWO (2014-2016), and participating in the governing boards of KNAW and ALLEA. He has organized numerous international workshops and conferences and has been a visiting scholar at prestigious institutions including the University of Cambridge, London School of Economics, and École des Hautes Études in Paris.
Professor Todd Squires is a distinguished faculty member in the Department of Chemical Engineering at the University of California, Santa Barbara, within the Robert Mehrabian College of Engineering. His research focuses on the fundamental principles of transport phenomena as applied to interfaces, membranes, and complex fluids, employing theoretical, computational, and experimental approaches to address significant challenges in micro-scale fluid mechanics. Dr. Squires' educational background includes: BS in Physics, UCLA (1995) BA in Russian Language and Literature, UCLA (1995) PhD in Physics, Harvard University (2002) His research interests span microfluidics and electrokinetics, active and nonlinear microrheology of complex materials, polymer dynamics and sensors, with particular emphasis on non-linear electrokinetic flows, interfacial rheology, and the self-assembly of nanostructured materials. His work bridges fundamental fluid mechanics with practical applications in microfluidic devices, energy storage, and biomedical systems, demonstrating the versatility of this fascinating field. Analysis of Professor Squires' recent publications reveals a consistent focus on interfacial phenomena, with particular attention to the rheological properties of fluid interfaces, particle dynamics in complex fluids, and novel microfluidic techniques for measuring and manipulating these systems. His research demonstrates strong interdisciplinary connections between chemical engineering, physics, and materials science, with applications spanning energy storage, biomedical engineering, and environmental systems. Professor Squires has received numerous prestigious awards and honors: 2018 Robert W. Vaughan Lecture in Chemical Engineering, Caltech 2015 Elected Fellow of the American Physical Society 2013 Mid-Career Award, American Electrophoresis Society 2012 The Dudley Saville Memorial Lecture at Princeton 2010 Pierre Gilles de Gennes Prize 2010 Allan P. Colburn Memorial Lectureship, University of Delaware 2009 Francois Frenkiel Award for Fluid Mechanics 2009 Camille Dreyfus Teacher-Scholar Award 2008 Beckman Young Investigator 2007 NSF CAREER Award 2005 'Rising Star' - Chronicle of Higher Education As principal investigator of the Squires Group, Professor Squires leads a dynamic research team that combines experimental, theoretical, and computational approaches to investigate transport phenomena at interfaces. His work has been supported by major funding agencies including the National Science Foundation, with his CAREER award indicating early recognition of his potential as both researcher and educator. While specific grant details aren't provided in the source material, his extensive publication record and prestigious awards suggest robust and sustained research funding. The Squires Group maintains state-of-the-art laboratory facilities for studying micro-scale fluid mechanics, including specialized equipment for microrheology measurements, microfluidic device fabrication, and interfacial characterization. Their research environment fosters collaboration across disciplines, with connections to materials science, physics, and biomedical engineering researchers at UCSB and beyond.
Prof. Gabriela Hug is a Full Professor at ETH Zurich's Department of Information Technology and Electrical Engineering, serving as Deputy Head of the Department and Deputy Head of the Power Systems and High Voltage Lab. She leads the Energy Science Center (ESC) and holds adjunct roles at Carnegie Mellon University. Her research focuses on modeling, control, and optimization of electric power systems for sustainable energy transitions. Education: PhD in Information Technology and Electrical Engineering, ETH Zurich (2004–2008) MSc in Information Technology and Electrical Engineering, ETH Zurich (1999–2004) Research Interests: Her work addresses challenges in smart grid integration, renewable energy systems, and advanced control strategies. Key areas include vehicle-to-grid technologies, distribution network optimization, and energy storage system planning. She emphasizes data-driven approaches and collaborative frameworks for grid resilience and flexibility. Key Achievements: Recipient of the 2019 ALEA Award (ETH Zurich) NSF Career Award (2013) IEEE Outstanding Young Engineer Award (2013) Leadership & Roles: Co-Director, NCCR Automation (Swiss National Centre of Competence in Research) Board Chair, Energy Science Center (ESC) Adjunct Faculty, Carnegie Mellon University Labs & Teams: Power Systems Laboratory (ETH Zurich) Energy Science Center (multi-disciplinary research hub)
Prof. Dr. Björn Corzilius is a University Professor (W2) of Physical Chemistry at the University of Rostock, Germany, leading the Corzilius group. His research focuses on solid-state NMR spectroscopy, dynamic nuclear polarization (DNP), and applications in biomolecules and materials. He holds affiliations with the Leibniz Institute for Catalysis (LIKAT) and serves on multiple academic boards, including the transregional Collaborative Research Center TRR 386 and the journal Magnetic Resonance . Education: 1999: Studies of Chemistry, TU Darmstadt 2005: Diploma in Physical Chemistry (TU Darmstadt) 2008: Ph.D. in Physical Chemistry (TU Darmstadt) Research Interests: Solid-state NMR, DNP for sensitivity enhancement, paramagnetic metal ions, biomolecular dynamics, and method development. His work bridges theoretical and experimental approaches to advance structural and functional studies of complex systems like proteins, nucleic acids, and catalytic materials. Recent Article Trends: Focus on DNP applications in biomolecular interfaces, novel polarizing agents (e.g., Gd(III) complexes), and methodological advancements like serial polarization transfer and electron-decoupled DNP. Contributions span inorganic chemistry, materials science, and biophysical systems. Awards: Emmy Noether Fellowship (2012) Felix Bloch Lecture (2016) Regitze M. Vold Memorial Prize (2017) Best Ph.D. Supervision (2018) Grants & Labs: Principal Investigator of the Emmy Noether Group (2013–2019), now leading the DNP research team at the University of Rostock. Collaborates closely with LIKAT on catalytic and materials projects. His group actively develops open-access publishing platforms like Magnetic Resonance and hosts international conferences. Labs/Teams: The Corzilius group at the Institute of Chemistry (Rostock) specializes in NMR method development and applications. Associated with LIKAT for interdisciplinary catalysis research.
