Viswanath Nagarajan is an Associate Professor of Industrial & Operations Engineering and Computer Science Engineering (courtesy) at the University of Michigan. His research focuses on combinatorial optimization, approximation algorithms, and stochastic models for routing, scheduling, and location problems. He previously served as an Assistant Professor at the University of Michigan (2014–2020) and a Research Staff Member at IBM T.J. Watson Research Center (2009–2014). He holds a Ph.D. in Algorithms, Combinatorics, and Optimization from Carnegie Mellon University (2004–2009) and a B.Tech. in Computer Science from IIT Bombay (1999–2003). His research explores uncertainty management in optimization, including stochastic models and approximation algorithms for decision-making under uncertainty. He has contributed to adaptive algorithms, submodular optimization, and applications in logistics, network design, and scheduling. Education: Ph.D., Algorithms, Combinatorics, and Optimization (Carnegie Mellon University, 2009) B.Tech., Computer Science and Engineering (IIT Bombay, 2003) Prof. Nagarajan has organized major conferences like IPCO 2019 and served on editorial boards for journals including Operations Research , ACM Computing Surveys , and ACM Transactions on Algorithms . His service includes program committees for SODA, APPROX, and IPCO. He advises Ph.D. students focusing on optimization theory and applications, with advisees securing positions at Yahoo! Research, the University of Chicago, Ford Motor Company, and Georgia Tech.
جستوجوی استاد و پژوهشگر
استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشیتان را پیدا کنید و با او ارتباط بگیرید.
نمایش ۷۶-۹۰ از ۵٬۵۶۹ استاد راهنما
اطلاعات این پروفایلها از صفحات عمومی دانشگاهها جمعآوری شده و ممکن است بهروز نباشد.
- Moral Psychology
- Forensic Psychology
- Neurolaw
- +۷ مورد دیگر
Eyal Aharoni is a Professor in the Department of Philosophy at Georgia State University's College of Arts & Sciences. He holds a Ph.D. in Psychology from the University of California, Santa Barbara (2009) and bachelor's degrees in psychology and religious studies from the same institution. Dr. Aharoni's research program bridges psychology, neuroscience, and legal studies with particular focus on: Risk models for antisocial behavior Application of neuroscience to legal contexts (neurolaw) Impact of emotion and cognitive bias on criminal, moral, legal, and political decision making Psychopathy and criminal justice outcomes His scholarly work demonstrates a consistent interdisciplinary approach to understanding the psychological and neurobiological underpinnings of criminal behavior and legal decision-making. Through experimental, longitudinal, and neuroimaging methodologies, Aharoni investigates how cognitive, behavioral, evolutionary, and neurobiological factors influence criminal justice outcomes and potential reforms. Dr. Aharoni maintains an active research laboratory and welcomes PhD students in psychology, with potential funding opportunities in neuroethics. His current research interests include ethical implications of neuroscience technologies and associated issues in cognitive neuroscience, moral psychology, legal psychology, and forensic psychology. His professional experience includes: Research Associate at the RAND Corporation Postdoctoral fellowship at The MIND Research Network for Neurodiagnostic Discovery and the University of New Mexico Psychology Research positions at the Research Center for Virtual Environments and Behavior Research positions at the Institute for Social, Behavioral, and Economic Research
Dr. Jia Zhang is the Inaugural Robert H. Dedman Jr. Endowed Department Chair and Professor of Computer Science at Southern Methodist University (SMU Lyle School of Engineering). She holds the Cruse C. and Marjorie F. Calahan Centennial Chair in Engineering and has a courtesy appointment in the Department of Operations Research and Engineering Management. Her research focuses on applying machine learning, natural language processing, and information retrieval to data science infrastructure, particularly scientific workflows, provenance mining, software discovery, knowledge graphs, cloud computing, immune AI, and applications in earth science and healthcare. Education: Ph.D. in Computer Science, University of Illinois at Chicago M.S. in Computer Science, Nanjing University B.S. in Computer Science, Nanjing University Dr. Zhang's work emphasizes data science infrastructure and machine learning for scientific workflows and knowledge graphs. Her recent publications highlight deep learning , graph neural networks , and optimization algorithms in cloud computing, cybersecurity, and environmental applications. Key trends include spatiotemporal modeling , hybrid neural architectures , and AI-driven service ecosystems . Scientific Awards: Best Paper Awards IEEE SCC (2011, 2017) Best Student Paper Awards IEEE ICWS (2014, 2018), IEEE ICCC (2018) Distinguished Paper Award ICSOC (2023) First Outstanding Service Award IEEE Technical Committee on Services Computing (2016) She has secured over $5 million in federal grants (as PI) and $11 million as PI/Co-PI from NSF, NASA, NIH, UTSW, Ericsson, SAP, and Google. Her lab (Caruth Hall 308) actively recruits research assistants. She previously served as a faculty member at Carnegie Mellon University, Northern Illinois University, and Nanjing University, and worked in industry as a software architect.
Susan Robertson holds the Chair in Sociology of Education at the Faculty of Education, University of Cambridge, where she serves as Director of the Doctoral Programme and Editor-in-Chief of Globalisation, Societies and Education . She joined Cambridge in 2016 after academic appointments at the University of Auckland and University of Bristol, bringing over three decades of international expertise in critical education studies. Her educational foundation includes doctoral research in Sociology/Policy at the University of Calgary (1990), preceded by professional experience in the Research Division of Western Australia's Ministry of Education. This trajectory established her cross-sectoral perspective on education systems and policy implementation. Robertson's research critically examines state-education relationships through governance frameworks that determine educational equity and outcomes. She investigates how global and regional actors mediate the social contract between states and citizens, with particular focus on geopolitical shifts, OECD influence, and neoliberal transformations in higher education. Her work bridges sociology, political economy, and decolonial perspectives to address social justice imperatives in education. Analysis of her 2024-2026 publications reveals sustained engagement with higher education geopolitics, digital transformation challenges, and global governance mechanisms. Key thematic clusters include critiques of OECD-driven policy frameworks, analyses of ordinal citizenship in education systems, and examinations of how digitalization reshapes university missions while exacerbating existing inequalities. As Director of the Doctoral Programme, Robertson oversees comprehensive PhD training while convening the Culture, Politics and Global Justice research cluster that fosters interdisciplinary collaboration on transnational education challenges. Her service on the ESRC funding council positions her at the nexus of research strategy and resource allocation in UK social sciences. The Culture, Politics and Global Justice cluster under her leadership functions as a dynamic hub for critical scholarship, hosting regular seminars and collaborative projects that connect Cambridge researchers with global partners to address emergent issues in education governance and social transformation.
Leslie Valiant is the T. Jefferson Coolidge Professor of Computer Science and Applied Mathematics in Harvard University's School of Engineering and Applied Sciences, where he has held a faculty position since 1982. A foundational figure in theoretical computer science, his work bridges artificial and natural computational phenomena across multiple disciplines. His academic background includes education at: King's College, Cambridge Imperial College, London Ph.D. in Computer Science from Warwick University (1974) Valiant's research spans computational complexity , machine learning theory , parallel systems , and computational neuroscience . He pioneered the PAC (Probably Approximately Correct) learning framework that established computational learning theory as a rigorous field. His holographic algorithms work revealed deep connections between computational complexity and statistical physics, while his neuroidal model and evolvability theory provide computational explanations for cognitive processes and biological evolution. Current investigations focus on cortical computation primitives and knowledge infusion architectures. His publication trends show increasing integration of neuroscience with computational theory since 2010, with dominant themes in holographic computation (2006-2018), cortical modeling (2012-2018), and evolvability (2009-2017). The work consistently applies computational complexity analysis to biological and cognitive systems. Major recognitions include: Nevanlinna Prize (1986) for mathematical aspects of computer science Knuth Award (1997) for foundational algorithms contributions EATCS Award (2008) for theoretical computer science impact Turing Award (2010) for computational learning theory and complexity Fellowship in the Royal Society and National Academy of Sciences Valiant's research has been supported by NSF and international grants enabling cross-disciplinary work in computational neuroscience and evolutionary algorithms. While specific advisees aren't documented in source materials, his theoretical frameworks have shaped generations of researchers in machine learning and complexity theory. His current research group explores neuroidal architectures for cognitive computation, investigating how cortical circuits achieve robust information processing through in-circuit testing methodologies. Ongoing projects aim to identify fundamental computational primitives in neural systems and develop biologically inspired AI frameworks.
Emmett Witchel is a Professor of Computer Science at the University of Texas at Austin , with research spanning computer architecture, systems, networking, security, and privacy . His work focuses on low-level systems optimization and secure concurrent execution. Research Interests: Concurrent systems, secure execution environments, GPU integration, distributed systems. Teaching: CS 380L (Advanced Operating Systems), CS 371M (Mobile Computing). Scientific Awards: Runner-up Best Paper, ASPLOS 2013 Runner-up Award for Outstanding Research, USENIX Symposium 2012 IEEE Micro Top Pick Award 2007 ACM Honorable Mention 2004 George M. Sprowls Award, MIT EECS 2004 Recent Publications demonstrate leadership in CXL pod databases ( Tigon ), stateful serverless computing ( Boki ), SmartNIC-accelerated file systems ( LineFS ), and GPU security ( Telekine ). His work bridges hardware-software co-design and practical systems implementation.
Saurabh Amin is a Professor in the Department of Civil and Environmental Engineering at the Massachusetts Institute of Technology (MIT), where he also serves as the Edmund K. Turner Professor and Undergraduate Officer. He is a Principal Investigator at the Laboratory of Information and Decision Systems and holds affiliations with the Operations Research Center and the Center for Computational Science and Engineering. His educational background includes: B.Tech. 2002, Indian Institute of Technology (IIT) Roorkee M.S. 2004, University of Texas (UT) Austin Ph.D. 2011, University of California (UC) Berkeley Saurabh Amin's research focuses on the design and control of infrastructure systems using game theory and optimization in networks. His work spans three main areas: resilient network control, information systems and incentive design, and optimal resource allocation in large-scale infrastructure systems. By concentrating on critical infrastructure domains including highway transportation, electric power distribution, and urban water networks, his research develops innovative theory and tools to enhance system performance against both stochastic and adversarial disruptions. His approach involves modeling cyber-physical interactions in infrastructures to assess vulnerabilities, developing detection and response tools for failures at various scales, and designing economic incentive schemes that improve aggregate public good while accounting for dependencies and private information among strategic entities. Amin's work bridges mathematical systems theory with practical civil engineering applications, creating a rigorous theoretical foundation for infrastructure resilience that addresses diverse failure mechanisms from natural disasters to deliberate malicious actions. His recent publications demonstrate a strong focus on decarbonization of energy systems, resilient infrastructure planning under climate uncertainty, optimization methods for complex networked systems, and game-theoretic approaches to sustainable infrastructure management. His work increasingly integrates artificial intelligence and machine learning techniques with traditional control theory to address contemporary challenges in infrastructure resilience and sustainability. The research shows a clear trajectory toward addressing climate change impacts on infrastructure systems while maintaining economic efficiency and operational reliability. Professor Amin has received numerous prestigious awards and honors: Common Ground Excellence in Teaching Award, 2025 HSCC Test-of-Time Award, 2024 MIT CEE, Distinguished Service and Leadership Award, 2023 Samuel M. Seegal Prize (SoE) – inspiring students in pursuing and achieving excellence, 2022 Earll M. Murman for Excellence in Undergraduate Advising, 2022 C3.ai Digital Transformation Institute Research Award, 2020 MIT, Ole Madsen Mentoring Award, 2020 MIT, Energy Initiative Research Award, 2020 National Academy of Engineering, China-America Frontiers of Engineering Symposium speaker, 2019 MIT, Robert N. Noyce Career Development Professor, 2015-2018 Google Faculty Research Award, 2015 National Science Foundation CAREER Award, 2015 Siebel Energy Institute Research Award, 2015 MIT, Solomon Buchsbaum AT&T Research Fund Award, 2012 Professor Amin has been actively involved in significant research projects including the C3.ai DTI project on Causal Reasoning for Real-Time Attack Identification in Cyber-Physical Systems and another on Learning in Routing Games for Sustainable Electromobility. He serves as the chief scientist on multi-institutional NSF grants, including the $9 million Foundations of Resilient Cyber-Physical Systems (CPS) project. His teaching portfolio includes courses such as 1.008 Engineering for a Sustainable World, 1.104 Sensing and Intelligent Systems, 1.020 Engineering Sustainability: Analysis and Design, and 1.208 Resilient Networks. As Undergraduate Officer, he plays a key role in shaping the educational experience for civil and environmental engineering students at MIT. Professor Amin leads the Resilient Infrastructure Networks Lab at MIT, where his team develops theoretical foundations and practical tools for infrastructure resilience. The lab focuses on the intersection of control theory, game theory, and optimization applied to cyber-physical infrastructure systems. Current research directions include pandemic-resilient urban mobility and hurricane-resilient smart grid operations, reflecting the lab's commitment to addressing pressing societal challenges through rigorous systems engineering approaches.
Christine Clarkمشاهده پروفایل
استادیار
- Otolaryngology
- Laryngology
- Voice Disorders
- +۵ مورد دیگر
Christine Clark, MD, MSc is an attending laryngologist at Weill Cornell Medicine’s Sean Parker Institute for the Voice and Assistant Professor in the Department of Otolaryngology-Head and Neck Surgery at Weill Cornell Medical College. She earned her B.A. from the University of Pittsburgh (2011) and her M.D. from Pennsylvania State University College of Medicine (2017), followed by residency at Georgetown University Medical Center and a fellowship in Laryngology at Weill Cornell, where she also obtained a master’s degree in Clinical and Translational Science. B.A. - University of Pittsburgh (2011) M.D. - Pennsylvania State University College of Medicine (2017) Residency - Georgetown University Medical Center Fellowship - Sean Parker Institute for the Voice (Laryngology) Master’s - Clinical and Translational Science at Weill Cornell Dr. Clark specializes in evaluating and treating swallowing, voice, and airway disorders. Her research focuses on chronic cough, laryngeal hypersensitivity, and benign phonotraumatic vocal fold lesions. She has developed clinical tools like the 3D-printed injection laryngoplasty simulator and quality improvement initiatives for surgical airway management. Her clinical work and research span topics such as vocal fold hemorrhage management, pharyngeal residue quantification in dysphagia, and granuloma as markers of malignancy. Recent publications emphasize global otolaryngology capacity building and performer-specific voice injury care. Scientific awards include: Teaching awards for excellence in medical student education during residency Dr. Clark is affiliated with the Sean Parker Institute for the Voice at Weill Cornell Medicine and serves as an Assistant Professor of Otolaryngology.
Jiaxin Linمشاهده پروفایل
استادیار
- Computer Systems
- Networking
- Computer Architecture
- +۵ مورد دیگر
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)
- System Informatics
- Big Data Analytics
- Data Fusion
- +۹ مورد دیگر
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.
Megan Bergkesselمشاهده پروفایل
استاد پژوهشی
Dr. Megan Bergkessel is a Research Professor in Molecular Microbiology at the University of Dundee's School of Life Sciences. Her research focuses on understanding how bacteria like Pseudomonas aeruginosa regulate activities during growth arrest, particularly in resource-limited environments. This work addresses antibiotic tolerance mechanisms critical to chronic infections. Principal Investigator leading studies on non-growing bacterial physiology Recipient of a £900k UKRI Future Leaders Fellowship (2020) Expertise in antimicrobial resistance and microbial stress responses Current research explores regulatory pathways enabling protein synthesis in non-growing states, with implications for developing novel infection treatments. Supervises PhD projects investigating two-component signaling systems and environmental sensing in P. aeruginosa. Recognized for teaching excellence in Biological and Biomedical Sciences programs. PhD opportunities: Adaptive antimicrobial resistance mechanisms and environmental sensing roles Media commentary available via Corporate Communications
Alyssa Ney is a leading Professor of Philosophy at Ludwig-Maximilians University Munich (LMU), holding the Chair of Metaphysics within the Faculty of Philosophy, Philosophy of Science, and Religious Studies. Her work bridges metaphysics with the philosophy of physics and mind, focusing on the interpretation of quantum theories, fundamentality, and the unity of science. Education: PhD in Philosophy (Brown University), MS in Physics (UC Davis), BS in Physics and Philosophy (Tulane University) Previous appointments: UC Davis (2019-2024), University of Rochester (2005-2019) Ney’s research explores the metaphysical implications of quantum mechanics, particularly wave function realism and its challenges in grounding macro-objects. She investigates the relationship between quantum theory and classical conceptions of space, time, and causation, with a focus on locality and nonlocality. Her work also addresses physicalism, mental causation, and the methodology of metaphysical inquiry. Recent publications include analyses of density matrix realism (“ Is the Universe Fundamentally a Density Matrix? ”), many-worlds interpretations (“ Branching (Almost) Everywhere and All At Once ”), and the metaphysical status of spacetime in quantum gravity contexts. She was awarded the 2025 Patrick Suppes Prize for her book The World in the Wave Function and the 2024 Humboldt Foundation Bessel Award. Scientific Awards Patrick Suppes Prize (2025) Friedrich Wilhelm Bessel Research Award (2024) FQxI Essay Contest Second Prize (2018) Elsie Field Dupre Prize in Physics (1999) Ney actively mentors underrepresented scholars in philosophy of science and serves on editorial boards for Philosophy of Physics and British Journal for the Philosophy of Science . She has organized workshops connecting metaphysics with philosophy of physics and quantum interpretation.
James Zouمشاهده پروفایل
دانشیار
James Zou is an Associate Professor of Biomedical Data Science at Stanford University, with courtesy appointments in Computer Science and Electrical Engineering. His research focuses on advancing machine learning methodologies for healthcare applications, emphasizing reliability, fairness, and statistical rigor. He holds a Ph.D. from Harvard University and has held positions at Microsoft Research, Cambridge University (as a Gates Scholar), and UC Berkeley (Simons Fellow). Zou leads the Stanford Data4Health hub and is a Chan-Zuckerberg Investigator. His work spans AI-driven diagnostics, spatial transcriptomics, and ethical AI frameworks. Key achievements include the EchoNet AI system for echocardiography and foundational contributions to data valuation (e.g., Data Shapley). Awards include the Sloan Fellowship, NSF CAREER Award, and Google/Tencent AI awards. Education: Ph.D., Harvard University (2014); Postdoctoral roles at Microsoft Research, Cambridge, and Berkeley. Research Interests: Machine learning for healthcare, algorithmic fairness, interpretable AI, spatial omics, and translational bioinformatics. His lab develops tools like TextGrad (PyTorch for text agents) and frameworks for evaluating medical AI systems. Recent work addresses LLMs in peer review and clinical decision-making. Grants/Grants: Supported by NSF, Sloan Foundation, Chan-Zuckerberg Initiative, and industry partnerships (Google, Amazon, Adobe). Advises on over 20 doctoral students, many contributing to high-impact papers in Nature , Science , and top conferences (NeurIPS, ICML). Leads collaborations in cardiology, oncology, and veterinary medicine. Labs/Teams: Stanford AI Lab, Stanford Data4Health, and interdisciplinary groups in precision medicine. Active in open-source projects like FrugalML and MetaViz.
Mohammadtaghi Hajiaghayi is the Jack and Rita G. Minker Professor of Computer Science at the University of Maryland, College Park. He is affiliated with the Robert H. Smith School of Business and holds Research Affiliate positions at MIT CSAIL and the Center for Discrete Mathematics and Theoretical Computer Science (DIMACS). His research focuses on algorithms, game theory, and network design, supported by NSF, ONR, and industry grants. He has received prestigious awards including ACM Fellow (2018) and EATCS Nerode Prize (2015) for his work on bidimensionality theory. Education: PhD from MIT (2005), postdocs at CMU and MIT, MSc from University of Waterloo, and BSc from Sharif University. He teaches courses like Data Science and Algorithms at UMD. Industry experience includes roles at Amazon, Google, and AT&T Labs. Over 20 students have graduated under his advisement, many in academia and industry. His work spans approximation algorithms, game theory, and big data. Projects include BigDND with Erik Demaine. He serves on editorial boards of Algorithmica, SODA, and others. Awards also include IEEE Fellow (2020) and Blavatnik Honoree (2020).
- Geriatric Medicine
- Aging Research
- Clinical Trials
- +۳ مورد دیگر
Denise Acampora, MPH, is a Lecturer in Geriatric Medicine at Yale School of Medicine. She specializes in aging-related research focusing on delirium prevention, post-hospitalization outcomes, falls prevention, and clinical trials in elderly populations. Her work spans over three decades, with significant contributions to understanding geriatric syndromes and improving care transitions for older adults. Education: MPH from Columbia University (1980), BS from St. Mary's College (1970). Key Research: Lead author on landmark studies about delirium interventions (NEJM 1999), cranberry clinical trials for UTIs in nursing homes (JAMA 2016), and post-COVID-19 outcomes in older adults (JAMA Network Open 2024). Collaborations: Works with prominent researchers like Thomas Tinetti, Mary Tinetti, and Laura Ferrante on aging-related studies. Her research emphasizes translational strategies to reduce disability and improve quality of life for elderly patients through evidence-based interventions. Current projects focus on longitudinal assessment of post-acute sequelae in older adults (VALIANT cohort).
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