Jiaxin Lin is an Assistant Professor in the Department of Electrical and Computer Engineering at Cornell University , affiliated with the Computer Systems Laboratory . She earned her Ph.D. in Computer Science from UT Austin (2025) , preceded by an M.S. from University of Wisconsin-Madison and a B.S. from ShenYuan Honors College at Beihang University. Her research focuses on co-designing software and hardware systems to enable high-performance data center communication, particularly through: Programmable network interface controllers (SmartNICs) Terabit network system stacks Cache/memory interconnects Compilers for in-network computing Chip-to-chip interconnects Her work addresses challenges in portability across heterogeneous SmartNICs, demonstrated through the development of the Alkali compiler framework (NSDI '25). Key themes include hardware abstraction, data center scalability, and network-compute co-design. Scientific Awards: Google Junior Faculty Award (2025) MIT EECS Rising Star (2024) Google Ph.D. Fellowship (2021) Meta Ph.D. Fellowship (2021)
Zsolt Kira serves as an Assistant Professor in the School of Interactive Computing at Georgia Institute of Technology's College of Computing, with additional affiliations at the Georgia Tech Research Institute and as Associate Director of ML@GT. He leads the Robotics Perception and Learning (RIPL) Lab, driving research at the intersection of machine learning and robotics. Dr. Kira earned his Ph.D. in 2010 under Professor Ron Arkin, establishing foundational expertise in robotics and AI before transitioning to his current academic role after industry experience at SRI International Sarnoff. His research pioneers beyond supervised learning through unsupervised, semi-supervised, self-supervised, and continual/lifelong learning frameworks, while advancing distributed perception via multi-modal fusion and cross-robot information integration. This dual focus addresses core challenges in robotic autonomy and sensor processing. Analysis of his 15 most recent publications reveals dominant trends in embodied AI systems, robust foundation model adaptation, and multimodal learning architectures. Key themes include neural radiance field applications, reinforcement learning for locomotion, and novel benchmarks for memory evaluation in agents. While specific advisees and grants aren't documented in the source material, his RIPL Lab leadership implies active graduate mentorship and research funding acquisition. The lab's work directly enables next-generation robotic systems through algorithmic innovation in perception and learning. The RIPL Lab operates as a hub for developing machine learning techniques that solve difficult perception problems in robotics, with particular emphasis on unsupervised learning paradigms and distributed multi-robot systems that push the boundaries of autonomous operation.
Professor Sir Nigel Shadbolt is Principal of Jesus College Oxford and Professor of Computing Science at the University of Oxford. He is Chairman and Co-founder of the Open Data Institute which he established with Sir Tim Berners-Lee. His career spans multiple prestigious institutions including the University of Southampton and University of Nottingham, where he held leadership roles in AI research. He has served in significant government advisory positions including as Information Advisor to the UK Prime Minister and member of the Public Sector Transparency Board. Nigel Shadbolt earned his undergraduate degree in Philosophy and Psychology from the University of Newcastle (1st Class Honours, 1978) followed by a PhD in Artificial Intelligence from the University of Edinburgh. His academic journey includes positions as the Allan Standen Professor of Intelligent Systems at Nottingham and leadership of the Web and Internet Science Group at Southampton before joining Oxford. Shadbolt's research spans the interdisciplinary field of Web Science, which he helped originate, focusing on human-centered AI, social machines, open data, and ethical considerations in technology. His work examines how humans and computers integrate at web scale to create novel applications, with recent emphasis on children's digital autonomy and privacy. He has published over 500 articles exploring topics from cognitive psychology to computational neuroscience, Artificial Intelligence to the Semantic Web. His notable contributions include the development of data.gov.uk and leadership in establishing Oxford's Institute of Ethics in AI. His 2018 book 'The Digital Ape: how to live (in peace) with smart machines' has been described as a 'landmark book' in the field. Knighted in 2013 for services to science and engineering Fellow of The Royal Society (FRS) Fellow of the Royal Academy of Engineering (FREng) Fellow of the British Computer Society (FBCS) Technology Pioneer status by the Davos World Economic Forum UK national BT Flagship IT Award As an advisor, Shadbolt has supervised numerous PhD students who have gone on to positions at Google DeepMind, the World Bank, and other prestigious institutions. His research has been supported by multiple grants including SOCIAM, KOALA, and ReTiPS projects. He co-founded Garlik Ltd, which was acquired by Experian, demonstrating his commitment to translating research into practical applications that benefit society. Shadbolt leads the Web and Internet Science research group at Oxford, focusing on social machines - applications that succeed at web scale by integrating humans and computers in novel ways. His work on the KOALA Hero Toolkit and CHAITok system addresses critical challenges in children's data autonomy on social media platforms, reflecting his commitment to ethical technology design.
Kathrin Lang is a Full Professor at the Department of Chemistry and Applied Biosciences, ETH Zurich, and Head of the Organic Chemistry Laboratory. Her research focuses on chemical biology, particularly the development of tools for genetic code expansion to incorporate non-canonical amino acids into proteins and advance bioorthogonal chemistries for studying biological processes. Keywords: Genetic Code Expansion, Bioorthogonal Chemistry, Protein Engineering, Ubiquitylation Networks, Post-Translational Modifications. Lang’s work emphasizes proximity-triggered crosslinking reactions, bioorthogonal labeling, and in vivo chemistries to address challenges in protein interaction mapping and structural elucidation. Her group’s recent publications highlight methodologies for dual protein labeling, deciphering ubiquitin code, and enhancing cycloaddition reactivity. Current projects include exploring cyclopropene-fused dibenzocyclooctynes for improved labeling and investigating methylated lysine as a conformational regulator in Hsp90. Funding sources include the ERC (Ubl-tool), DFG (SFB1035, SPP1926), and ETH Zurich. She contributes to education through courses like Genetic Code Expansion for Studying Posttranslational Modifications and Chemical Biology and Synthetic Biochemistry . Collaborative efforts span structural biology, microbiology, and synthetic biochemistry, with applications in ubiquitin research and cellular imaging.
John C. Doyle is the Jean-Lou Chameau Professor of Control and Dynamical Systems, Electrical Engineering, and BioEngineering at the California Institute of Technology (Caltech), where he holds appointments in the Division of Engineering and Applied Science with primary affiliation in the Control and Dynamical Systems Department. His research bridges theoretical foundations with applications across biological, technological, medical, and ecological networks. He earned a BS and MS in Electrical Engineering from MIT (1977) and a PhD in Mathematics from UC Berkeley (1984), followed by consultancy at Honeywell Systems and Research Center (1976-1990). MIT: BS & MS in Electrical Engineering (1977) UC Berkeley: PhD in Mathematics (1984) Doyle's research centers on universal laws and architectures in complex systems, emphasizing robustness-efficiency tradeoffs, speed-accuracy tradeoffs (SATs), diversity-enabled sweet spots (DeSS), bowtie/hourglass structures, and evolvability. His work pioneers System Level Synthesis (SLS) for control systems with sparse, local, saturating, delayed, noisy, quantized, and distributed (SLSDNQD) components, integrating control theory, computation, communication, and machine learning to address challenges from neural networks to infrastructure resilience. Key concepts include virtualization, horizontal transfer, and virality in multiscale systems. Analysis of his publication trends reveals consistent interdisciplinary impact across neuroscience (brain connectivity modeling), systems biology (metabolic oscillations), network science (internet topology), and physics (turbulence, earthquakes), with recurring themes of robust-efficiency limits and architectural principles governing complex networks. His work demonstrates exceptional translation from abstract theory to practical tools like the Matlab Robust Control Toolbox and Systems Biology Markup Language (SBML). His scientific recognition includes: 1990 IEEE Baker Prize (ranked among top 10 most important mathematics papers 1981-1993) Three IEEE Automatic Control Transactions Awards (1998, 1999, 2021) ACM Sigcomm Paper Prize (2004) and Test of Time Award (2016) IEEE Control Systems Field Award (2004) Multiple early-career honors including IEEE Centennial Outstanding Young Engineer (1984) Doyle has mentored generations of students whose contributions include foundational software tools adopted globally. His research has secured sustained funding from NSF, NIH, and other agencies supporting theoretical advances in control frameworks and their applications to biomedical systems, network infrastructure, and environmental modeling. The SBML initiative exemplifies his group's impact in standardizing computational biology research. He leads a highly collaborative research ecosystem at Caltech that integrates engineers, biologists, neuroscientists, and computer scientists to develop universal principles for complex networks. Current efforts focus on translating theoretical insights into health technologies, resilient infrastructure, and climate-responsive systems through the application of robust-efficiency frameworks to emerging challenges in cyber-physical and biological domains.
Steven A. Corcelli is a Professor and Interim Dean of the College of Science at the University of Notre Dame, with a research focus on Theoretical Chemistry and Molecular Dynamics Simulations . His work bridges Physical Chemistry and Biochemistry , targeting Energy Applications and Biomolecular Binding Mechanisms . He leads the Computational Molecular Science & Engineering Laboratory (CoMSEL). Ph.D., Chemistry, Yale University (2001) Sc.B., Chemistry, Brown University (1997) Research interests span ionic liquids for Carbon Capture , aqueous electrolytes in battery technologies , and molecular binding processes in immunology and DNA interactions . His group employs GPU-accelerated simulations and weighted ensemble methods to uncover structural and dynamic motifs. Recent publications highlight trends in vibrational spectroscopy , TCR-MHC binding , and CO2 solvation mechanisms . Awards include the Thomas P. Madden Award (2020) , ACS Fellowship (2016) , and NSF CAREER Award (2009) . Staff: Erin Brossard (Ph.D.), Nell Karpinski, Shuang Wu, Noah Vasconez, Kaitlyn Handy, Isabel Thompson
John Hale, Ph.D., is a Professor and Chair of Computer Science at The University of Tulsa's Tandy School of Computer Science, where he holds the Tandy Endowed Chair in Bioinformatics and Computational Biology. He is a founding member of the TU Institute of Bioinformatics and Computational Biology (IBCB) and a faculty research scholar in the Institute for Information Security (iSec). Education: Ph.D., Computer Science, The University of Tulsa (1997) M.S., Computer Science, The University of Tulsa (1992) B.S., Computer Science, The University of Tulsa (1990) Dr. Hale's research spans cybersecurity , bioinformatics , cyber-physical systems , and applied formal methods . His work focuses on neuroinformatics, cyber trust, attack modeling, secure software development, and information privacy. Recent publications highlight trends in large-scale graph analysis for cybersecurity, attack graph generation on high-performance computing clusters, and security frameworks for nuclear reactor control systems. His research also explores hybrid attack graph modeling, reflective deception strategies, and compliance methods for cyber-physical infrastructures. Scientific Awards: 2000 National Science Foundation CAREER Award Dr. Hale has advised numerous research projects and received funding from the U.S. Air Force, Army, NSF, NIH, DARPA, NSA, and NIJ. He has testified before Congress on cybersecurity and holds a patent for anti-piracy technology. His lab work includes developing cyber-physical testbeds and science DMZ security solutions.
Dr. Kaibo Liu is the Grainger STAR Professor in the Department of Industrial and Systems Engineering at the University of Wisconsin-Madison and serves as Associate Director of the UW-Madison IoT Systems Research Center. He earned his B.S. from the Hong Kong University of Science and Technology (2009), and M.S. and Ph.D. from Georgia Tech (2011/2013). His research focuses on system informatics, big data analytics, and data fusion for process modeling, monitoring, and decision-making. He has been funded by NSF, ONR, DOE, and industry partners. Notable awards include the 2024 Hromi Medal (ASQ), 2021 IISE Technical Innovation Award, and multiple early-career recognitions. Recent work emphasizes real-time cyber-physical security, reinforcement learning for data streams, and Bayesian methods for prognosis. He edits IEEE Transactions on Automation Science and Engineering and IISE Transactions on Data Science.
Prof. Maciej Lewenstein is a Group Leader and ICREA Professor at the Institute of Photonic Sciences (ICFO), Spain. He leads the Quantum Optics Theory group, focusing on theoretical and computational studies of quantum many-body systems, topological phases, and nonlinear optics. He holds a Dr.rer.nat. in Physics from the University of Essen, Germany. His research interests include quantum simulations, high-harmonic generation, Bose-Einstein condensation, and quantum information processing. He has pioneered work on topological quantum thermometry and ultrafast phase transitions in materials like vanadium dioxide. His group actively explores the intersection of quantum optics with condensed matter physics and quantum computing. Recent articles highlight advancements in tensor network approaches for topological phases, quantum algorithms for many-body systems, and the application of sonification to quantum entanglement dynamics. He has received a prestigious ERC Advanced Grant and the ICREA Professorship, recognizing his contributions to quantum science. Prof. Lewenstein advises over a dozen PhD students and postdoctoral researchers, fostering a dynamic research environment at ICFO. His grants include ERC and ICREA funding, supporting projects on quantum simulations and nonlinear optical phenomena. The Quantum Optics Theory group collaborates internationally, with expertise in light-matter interactions, quantum resource theory, and quantum many-body localization. Their lab develops novel methods for probing quantum systems using high-harmonic spectroscopy and quantum trajectory simulations.
Professor Dawn A. Lott holds the position of Professor of Applied Mathematics at Delaware State University. She obtained her Ph.D. in Engineering Sciences & Applied Mathematics from Northwestern University (1994), M.Sc. from Michigan State University (1989), and B.Sc. from Bucknell University (1987). Her postdoctoral training was at the University of Maryland (1997). Her research focuses on numerical and analytical studies of nonlinear partial differential equations modeling solid/fluid mechanics, biomechanics, and physiology. She also investigates decision-making processes using operations research and machine learning techniques. Key areas of expertise include computational methods, artificial intelligence, and algorithm design. Recent work emphasizes decision-making under uncertainty in IoT-enabled battlefield scenarios. Her publications explore MATLAB/Java comparisons for decision algorithms, graph-based reasoning systems, and SAGE-inspired optimization frameworks. Collaborations with researchers like Raglin and Metu highlight interdisciplinary approaches to military and operational challenges. No specific grants, awards, or student advisories are noted in the provided materials. Her contributions bridge applied mathematics with real-world applications in defense, healthcare, and computational systems.
Soroosh Shafiee is an Assistant Professor in the School of Operations Research and Information Engineering at Cornell University since July 2023. Before joining Cornell, he held postdoctoral positions at the Tepper School of Business (Carnegie Mellon University) and the Automatic Control Laboratory (ETH Zurich). He earned a B.Sc. and M.Sc. in Electrical Engineering from the University of Tehran and a Ph.D. in Operations Research from École Polytechnique Fédérale de Lausanne (EPFL). His research focuses on optimization under uncertainty, robust optimization, optimal transport, and their applications in machine learning and finance. Specific interests include designing algorithms for data-driven optimization, analyzing statistical and computational complexity, and exploring nonconvex optimization structures. Swiss National Science Foundation Early PostDoc Mobility Fellowship (2020) PhD Thesis Distinction Award, EPFL (2020) His work bridges theoretical foundations with practical applications, contributing to areas such as distributionally robust optimization, Wasserstein-based methods, and scalable algorithm development. His research has been published in top venues like Journal of Machine Learning Research and Operations Research .
Xuemin (Sherman) Shen is a University Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. He is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE), the Royal Society of Canada, the Canadian Academy of Engineering, and the Engineering Institute of Canada. Professor Shen serves as Editor-in-Chief of multiple prestigious journals including the IEEE Internet of Things Journal and Springer Peer-to-Peer Networking and Applications. Dr. Shen received his Doctorate in Electrical Engineering from Rutgers University in 1990, following a Master of Applied Science from the same institution in 1987. His undergraduate degree is a Bachelor of Applied Science in Electrical Engineering from Dalian Marine University, China (1982). Professor Shen's research spans wireless communications and networking, with particular expertise in resource allocation, mobility management, wireless network security, and privacy preservation. His work extends to IoT applications, connected and automated vehicles, network digital twins, and satellite-terrestrial networks. His research has been applied to vehicular networks, wireless body area networks, remote e-healthcare systems, and smart grid technologies, demonstrating both theoretical depth and practical impact across multiple domains. His recent publications reveal strong trends in AI-assisted networking, security and privacy preservation for IoT applications, and energy management in vehicular and smart grid systems. The research shows an increasing focus on integrating AI techniques with traditional networking approaches, addressing critical challenges in security, privacy, and resource management for next-generation wireless systems. R.A. Fessenden Award (2019) from IEEE Canada James Evans Avant Garde Award (2018) from the IEEE Vehicular Technology Society Joseph LoCicero Award (2015) from the IEEE Communications Society Education Award (2017) from the IEEE Communications Society West Lake Friendship Award from Zhejiang Province (2023) President's Excellence in Research from University of Waterloo (2022) Canadian Award for Telecommunications Research (2021) Professor Shen has mentored over 100 graduate students and postdoctoral fellows throughout his career, with many now holding prominent academic positions at top universities worldwide. His supervision has been recognized with multiple awards including the Award of Excellence in Graduate Supervision (2006) from the University of Waterloo. He has served in numerous leadership roles including Past President of the IEEE Communications Society and has chaired major international conferences including IEEE Globecom 2024.
Marc Hodes is Professor in Mechanical Engineering and Mathematics at Tufts University. With a PhD from MIT, his research focuses on heat transfer phenomena with applications in electronics cooling, supercritical fluids, and thermoelectric systems. He directs the graduate program in Mechanical Engineering. Education: BS, University of Pittsburgh (1990) MS, University of Minnesota (1994) PhD, Massachusetts Institute of Technology (1998) Research Areas: Thermal management of electronics through microchannel cooling and liquid metal technologies; Apparent slip phenomena in microstructured surfaces; Mass transfer in supercritical CO 2 systems for aerogel processing; Thermoelectric module optimization for precision temperature control. Awards & Honors: NSF REU Fellowship (1989) E.T.S. Walton Visitorship Award Best Associate Editor, ASME Journal of Heat Transfer (2023) Research Leadership: Principal investigator on multiple NSF grants including projects on aerogel manufacturing, dropwise condensation, and analysis of convection in slip flows. Industry collaborations include Google, DARPA, and Bell Labs.
Dr. Andrew Cornwell is an Adjunct Assistant Professor in the Department of Biomedical Engineering at Case Western Reserve University’s Case School of Engineering. He serves as the Associate Director of the Case-Coulter Translational Research Partnership (CCTRP) and Director of the Case-Cleveland Incubator in the Office of Strategic Partnerships. Additionally, he holds the role of Director for Industrial and Strategic Collaborations at the Cleveland FES Center, bridging academic research with industry and clinical applications across the School of Medicine and School of Engineering. Dr. Cornwell earned his PhD in Biomedical Engineering from Case Western Reserve University. His early research focused on brain recording and neurotechnology, later transitioning to advancing technology transfer and translational research strategies. His research interests center on neurotechnology, particularly functional electrical stimulation (FES) systems for rehabilitation and clinical applications. He specializes in accelerating the translation of academic innovations into practical healthcare solutions, focusing on aligning clinical needs, market demands, and research priorities. Key areas include neuroprosthetics, assistive technologies for paralysis, and strategic partnerships to enhance technology commercialization. Dr. Cornwell’s publications highlight advancements in neurotechnology, including studies on FES systems, brain-computer interfaces, and clinical assessment tools. His work from 2010–2013 emphasizes improving arm mobility for individuals with paralysis, while earlier research (e.g., 2004) explores neural network approaches to predict movements using electrocorticography (ECoG). While no scientific awards were listed in the provided information, his roles involve managing grants and strategic collaborations through the CCTRP and Cleveland FES Center to fund translational research projects. He is affiliated with the Cleveland FES Center and the Case-Coulter Translational Research Partnership, leading initiatives to commercialize neurotechnology and biomedical innovations.
Louis A. Pérez, Jr. is the J. Carlyle Sitterson Professor of History at the University of North Carolina. His research focuses on 19th- and 20th-century Caribbean history, particularly Spanish-speaking Cuba, with emphasis on society, gender, and political economy. He holds offices in Hamilton Hall and teaches courses on Latin American and Caribbean history. Education: MA, University of Arizona, 1966 PhD, University of New Mexico, 1970 Research Interests: Pérez examines Cuban socio-cultural evolution through lenses of political economy, gender dynamics, and imperial discourse. His work analyzes colonial structures, national identity formation, and transnational relations. Publications: His seven major works span topics like Cuban food politics, civil-culture modernity, and revolutionary historiography. Recent publications emphasize economic structures and cultural narratives. Advising: Current advisees include Daniella McIvor and Anthony Rossodovito. He is not accepting new applicants for 2024-2025. Labs/Teams: No specific labs mentioned, but collaborates widely in Caribbean Studies networks.
