جستجوی استاد راهنمای دانشگاهی

• Environmental Engineering
• Hydrology
• Hydraulics
• +۱۲ مورد دیگر

Joel S. Hayworth is an Associate Professor in the Department of Civil Engineering at Auburn University's College of Engineering. His research focuses on environmental and ecosystem restoration, particularly in estuarine, terrestrial, and freshwater systems. He leads the Estuarine Environments Research Program (EERP), which investigates the fate of endocrine-disrupting chemicals (EDCs), PFAS, and oil spill residues in coastal environments. Dr. Hayworth's educational background includes a PhD in Civil Engineering (Hydrology/Hydraulics) from Auburn University, an MS in Hydrology from the University of Nevada, Las Vegas via the Desert Research Institute, and a BS in Geophysics from the University of California, Santa Barbara. He previously worked at the Tennessee Valley Authority Engineering Laboratory and the U.S. Air Force Research Laboratory, and founded Hayworth Engineering Science in 1999 before returning to academia in 2010. His research interests span environmental engineering, hydrology, hydraulics, estuarine science, pollutant fate and transport, and chemical fingerprinting. He has developed advanced analytical methods for detecting EDCs and PFAS in water, sediment, and biota. His work integrates field studies, laboratory experiments, and environmental modeling to understand complex hydrologic, geologic, chemical, and biological processes in human-impacted ecosystems. The 15 most recent articles highlight a strong trend in environmental contaminant analysis, particularly focusing on PFAS, oil spill residues, and endocrine disruptors. His research combines analytical chemistry with environmental modeling and field monitoring, often in collaboration with interdisciplinary teams. Key themes include the development of UHPLC-MS/MS and GC-MS/MS methods, fate and transport modeling of pollutants, and ecological risk assessment in estuarine systems. Dr. Hayworth's scientific contributions are supported by funding from agencies such as the Gulf Coast Ecosystem Restoration Council (RESTORE Council). His work has led to significant publications in journals like Science of the Total Environment , Marine Pollution Bulletin , and Water . He actively mentors students and collaborates with researchers like T.P. Clement, G.F. John, and V. Mulabagal. His projects, such as the restoration assessment of Cotton Bayou and Terry Cove, demonstrate applied science for environmental problem-solving. He has developed state-of-the-art analytical laboratories and partnered with coastal communities for long-term monitoring. His laboratory, the Estuarine Environments Research Program (EERP), conducts multi-year studies on endocrine disruptors in estuaries, develops innovative sampling and analysis methods, and trains the next generation of environmental engineers and scientists. The team works across disciplines to address complex environmental challenges in the Gulf Coast region.

Chaowei Xiaoمشاهده پروفایل

استادیار

• Trustworthy Machine Learning
• Security
• Computer Vision
• +۳ مورد دیگر

Chaowei Xiao is an Assistant Professor at the University of Wisconsin-Madison (starting 2023), affiliated with the School of Computer, Data & Information Sciences. His research focuses on securing AI systems, particularly exploring robustness in trustworthy machine learning, autonomous systems, and large language models (LLMs). He holds a Ph.D. from the University of Michigan, Ann Arbor, and a B.S. from Tsinghua University. Before joining UW-Madison, he worked as a research scientist at NVIDIA (2020–2022) and at Arizona State University (2022–2023). His work bridges model and system perspectives to ensure practical robustness and provable guarantees in AI applications like autonomous driving, healthcare, and IoT. Key research areas include adversarial robustness, AI security, and ethical AI. Recent contributions include frameworks for detecting LLM hallucinations, mitigating jailbreak attacks, and securing multi-modal systems. His work on diffusion models for adversarial purification and physical-world attacks on autonomous driving systems has been widely recognized. Notable awards include the 2024 USENIX Security Distinguished Paper Award, ACM Gordon Bell Finalist (2024), and Schmidt Sciences AI2050 Fellowship. He has advised students like Xiaogeng Liu (NVIDIA Fellow) and secured grants from Amazon, Apple, and UW-Madison. His lab actively publishes at top venues like NeurIPS, ICML, and CVPR.

Scott Hopkinsمشاهده پروفایل

استاد

• Physical Chemistry
• Machine Learning
• Mass Spectrometry
• +۲ مورد دیگر

Scott Hopkins is a Professor in the Department of Chemistry at the University of Waterloo, specializing in Physical Chemistry. His research integrates machine learning with experimental techniques to study ion mobility, mass spectrometry, and spectroscopic analysis. He directs the Hopkins Laboratory, focusing on computational predictions of chemical behaviors and molecular interactions. His work addresses fundamental questions in gas-phase chemistry, cluster formation, and analytical method development. Research interests span physical chemistry, computational modeling, and analytical instrumentation, with a strong emphasis on developing predictive tools for complex chemical systems. Recent investigations explore ion-solvent dynamics, fragmentation mechanisms, and machine-learning applications for spectral interpretation.

Marina Blantonمشاهده پروفایل

دانشیار

• Applied Cryptography
• Information Security
• Privacy-Preserving Computation
• +۳ مورد دیگر

Marina Blanton is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, and Faculty Director of Women in Science and Engineering within the School of Engineering and Applied Sciences. She holds a PhD in Computer Science from Purdue University (2007), along with multiple advanced degrees in Computer Science and Electrical Engineering from prestigious institutions in the US and Russia. Her research focuses on applied cryptography, information security, and privacy-preserving computation and outsourcing. She has pioneered work on secure multi-party computation protocols, privacy-preserving biometric authentication, and secure data analytics across distributed systems. Her contributions include foundational frameworks like PICCO, a compiler for private distributed computation, and advancements in protocols for genomic data analysis and floating-point secure computation. Blanton has been recognized with numerous awards, including IEEE and ACM Senior Membership (2016/2015), the ACM CCS Test of Time Award (2015), and the AFOSR Young Investigator Award (2013). Her research has been supported by grants such as NSF SaTC awards and AFOSR funding. Her work emphasizes practical implementations of secure computation, with applications in healthcare, biometrics, and distributed data systems. She has advised numerous students and contributed to educational initiatives promoting women in STEM through her leadership roles.

• Cybersecurity and Privacy
• Data Management and Data Science
• Distributed Computing and Systems Software

Professor Jun Zhang is a leading academic in cybersecurity at Swinburne University, Australia, where he directs the Cybersecurity Lab. He has been honored as Australia's top cybersecurity researcher and instrumental in establishing Swinburne as a globally recognized cybersecurity research institution. His work includes high-impact papers and multi-million-dollar R&D projects, culminating in awards like the 2021 'Top Cybersecurity Research Institution' accolade. As course director of the Bachelor of Cyber Security, he pioneered an industry-driven teaching model with Deloitte and CSIRO, significantly boosting course enrollment. His collaborations extend to Adobe's Curriculum Innovation Program and the Australian P-TECH initiative, promoting STEM education and cybersecurity awareness. He supervises doctoral candidates and leads grants focused on AI-driven cybersecurity, smart home security, and blockchain-based edge computing. His research spans vulnerability detection, GAN forensics, IoT security, and privacy preservation in OSNs. Research interests include cybersecurity fundamentals, data science applications, and distributed systems. Notable achievements include the PTFix framework for Java vulnerabilities, the IoTFuzz smart home testing system, and CTI mining methodologies. Awards reflect his mid-career research excellence and industry partnerships. His grants with CSIRO and defense organizations emphasize real-world impact, addressing challenges from malware detection to adversarial machine learning. The Cybersecurity Lab and collaborative projects like Artchain demonstrate his commitment to bridging academia and industry. Professional activities include supervising over 20 HDR students and securing grants totaling millions. His work on blockchain-based edge storage (CSEdge) and SDCCP congestion control highlights innovation in networking. Future directions include advancing AI for design collaboration with CSIRO and enhancing privacy in smart energy technologies. His contributions span technical, educational, and community outreach domains, positioning him as a pivotal figure in cybersecurity's evolution.

Ruonan Hanمشاهده پروفایل

استاد

• Terahertz Electronics
• Integrated Circuits
• RF Systems
• +۴ مورد دیگر

Ruonan Han is a Professor of Electrical Engineering and Computer Science at MIT and serves as Associate Director of the Microsystems Technology Laboratories (MTL) and Director of the MIT-MTL Center for Integrated Circuits and Systems . His research focuses on ultra-high-frequency microelectronic circuits , particularly addressing the 'terahertz gap' in sensing, metrology, security, and communication. He leads the Terahertz Integrated Electronics Group at MIT's MTL, established in 2014. Education: B.S. in Microelectronics, Fudan University (2007) M.S. in Electrical Engineering, University of Florida (2009) Ph.D. in Electrical and Computer Engineering, Cornell University (2014) Research Interests: Terahertz (THz) integrated circuits and systems High-frequency CMOS technologies Quantum sensing and magnetometry RF systems for imaging, radar, and molecular sensing Energy-efficient communication systems His work bridges electronic circuits , electromagnetics , and quantum physics , with applications in defense, healthcare, and environmental monitoring. Awards & Recognition: 2023 IEEE SSCS New Frontier Award 2020 NSF CAREER Award 2019 Intel Outstanding Researcher Award 3× IEEE RFIC Best Student Paper Awards (2012, 2017, 2021) Advising & Leadership: Ph.D. advisor to over 10 students (many recipients of MIT MTL Dissertation Awards) Co-advises with Prof. Anantha Chandrakasan and Prof. Tomás Palacios Editorial roles at IEEE Transactions on Quantum Engineering and VLSI Systems Technical committee member for ISSCC, RFIC, and IMS Labs & Teams: Terahertz Integrated Electronics Group at MIT MTL: Focuses on chip-scale THz systems, quantum devices, and next-generation RF circuits Collaborations with industry (e.g., Apple, MediaTek) and academic groups (e.g., D. Englund's lab at MIT)

Michael John Janikمشاهده پروفایل

استاد

• Density Functional Theory
• Electrocatalysis
• CO2 Reduction
• +۷ مورد دیگر

Michael John Janik is a Professor in the Department of Chemical Engineering at Pennsylvania State University, with significant affiliation to the Institute of Energy and the Environment (IEE). His academic profile demonstrates exceptional research productivity with 270 research outputs, 25 funded projects, and substantial scholarly impact reflected in 17,238 citations and an h-index of 61. His research expertise centers on computational chemistry with particular focus on Density Functional Theory applications to catalysis and electrocatalysis. The fingerprint analysis of his work reveals strong concentrations in Density Functional Theory (76%), Oxidation Reactions (36%), Carbon Dioxide research (29%), Adsorption phenomena (27%), and First Principles Chemistry (22%). His work significantly contributes to UN Sustainable Development Goals related to clean energy and climate action. Analysis of his recent publications (2020-2025) reveals a strong research trajectory in electrocatalysis, particularly examining cation effects on CO 2 reduction mechanisms, intermetallic catalyst design, and computational modeling of electrochemical systems. His work bridges fundamental computational chemistry with practical applications in sustainable energy conversion. h-index of 61 17,238 total citations Multiple high-impact publications in journals including Nature Catalysis, Journal of the American Chemical Society, and Science Advances Professor Janik actively leads and collaborates on numerous research projects, particularly with Dr. Rioux and other colleagues, focusing on advanced catalyst development and electrochemical energy conversion systems. His current research portfolio includes multiple active NSF-funded projects extending through 2027 that address critical challenges in electrocatalysis, CO 2 reduction, and intermetallic catalyst design. His research group maintains strong connections with the Institute of Energy and the Environment, positioning his work at the intersection of fundamental computational chemistry and applied energy solutions. Current projects include combining DFT with classical simulations to predict solvation effects, developing high-entropy alloys for catalysis, and studying oxide overlayers in CO 2 reaction systems.

• System Security
• Cloud Computing Security
• Network Security
• +۷ مورد دیگر

Ki-Woong Park is a tenure-track full Professor in the Department of Computer and Information Security at Sejong University. He leads the System Security and Computer Engineering Research (SysCore) Lab, which focuses on system security research with numerous ongoing projects funded by major Korean research institutions including IITP, NRF, and KRIT. Sejong University, Department of Computer and Information Security System Security and Computer Engineering Research (SysCore) Lab Leader Member of IEEE, IEEE Computer Society, and ACM Education: Ph.D. in Electrical Engineering & Computer Science, KAIST (Advisor: Prof. Kyu-Ho Park) M.S. in Electrical Engineering & Computer Science, KAIST (Advisor: Prof. Kyu-Ho Park) B.S. in Computer Science, Yonsei University (Summa Cum Laude) Exchange Student at University of California, Los Angeles (UCLA) Professor Park's research focuses on designing, building, and analyzing secure systems, particularly for cloud computing, networked systems, and embedded systems. His work often involves reevaluating existing security mechanisms and actual system implementations with subsequent evaluation in real computing environments. He has made significant contributions to areas including cloud security, IoT security, ransomware detection, moving target defense, and metaverse security. His research approach emphasizes both theoretical foundations and practical implementation, with numerous publications in top-tier security and systems venues. His recent publications (2023-2024) demonstrate a strong focus on emerging security challenges in modern computing environments, particularly in metaverse platforms, UAV systems, and edge computing. These works span both theoretical security frameworks and practical implementations, with an emphasis on visualization techniques, hardware-based security mechanisms, and AI-enhanced security analysis. His research shows a clear progression from traditional cloud and network security toward next-generation security challenges in immersive virtual environments and cyber-physical systems. Scientific Awards: Microsoft Research Fellowship (2009-2010) Best Poster Gold Award at WISA 2020 Best Paper Award at MobiSec'18 Professor Park actively mentors numerous graduate and undergraduate students through the SysCore Lab, with current members including Ph.D. students, MS students, and undergraduate researchers. His research is supported by multiple significant grants, including the NRF Outstanding Researcher-Mid-career Researcher project, IITP Information Security Core Source Technology Development, and Defense Technology Advancement Research Institute projects. These grants total tens of billions of Korean won and address critical national security challenges in cyber defense, cloud security, and metaverse technologies. The SysCore Lab, under Professor Park's leadership, maintains a strong industry and government collaboration network, with part-time researchers from organizations including Hyundai Duty Free, Astron Security, Korea University, and various military cyber commands. This unique structure enables the lab to address both theoretical security challenges and practical implementation issues in real-world systems.

Zhibo Pangمشاهده پروفایل

استاد مدعو

• Embodied Intelligence
• Artificial Intelligence/ML
• Robotics
• +۷ مورد دیگر

Zhibo Pang is an Adjunct Professor at KTH Royal Institute of Technology's Department of Intelligent Systems (EECS) and Senior Principal Scientist at ABB Corporate Research Sweden. His work focuses on digital transformation in industry and healthcare, spanning robotics, AI, control systems, and wireless communication. He leads projects in embodied intelligence, Industry 4.0, and Healthcare 4.0, with 23 granted patents and over 120 journal papers. Education: PhD in Electronic and Computer Systems (KTH, 2013), MBA in Innovation & Growth (University of Turku, 2012). Key Roles: IEEE Technical Committee Chair, Editor of 6 IEEE journals, ABB Inventor of the Year (2016, 2018, 2021). Research Interests: Robotics safety, wireless automation, federated learning, digital twins, and IoT security. Recent Projects: Cloud-fog automation frameworks, robot skin systems for healthcare, and latency-aware industrial control. His work bridges academia and industry through cross-functional collaborations.

Sally Gibsonمشاهده پروفایل

پژوهشگر

• Geochemistry
• Volatiles cycling in Earth's mantle
• Mantle and volcanic processes
• +۳ مورد دیگر

Sally Gibson is a researcher at the Department of Earth Sciences, University of Cambridge, specializing in mantle geodynamics and volatile cycling processes. Her work integrates field observations, geochemical analysis, and numerical modeling to investigate how deep Earth processes influence surface environments over 3.5 billion years of planetary evolution. Research focuses on volatile cycling (CO₂, H₂O, F, Cl, S) in mantle systems Key projects include mantle plume-ridge interactions with collaborators in the US and Ecuador Operates a LA-ICP-MS laboratory for high-resolution geochemical analyses Supervises PhD students in petrology, geochemistry, and numerical modeling Her research addresses fundamental questions about Earth's habitability through studies of mantle-derived volatiles critical for climate regulation and energy transition metal deposits. Fieldwork in remote regions like Antarctica, Lesotho, and the Galápagos Islands provides empirical data for her interdisciplinary approach. Recent publications highlight her expertise in mantle xenolith analysis, plume dynamics, and volatile quantification in large igneous provinces. Her group's work combines 3He/4He isotopic analysis with seismic tomography to constrain lithospheric evolution and mineral deposit formation. Students under her supervision develop expertise in petrology and geochemical modeling while engaging with environmental and societal impacts of geological research. She actively promotes scientific outreach and community engagement, fostering connections between academia and broader society.

Markus Grillitschمشاهده پروفایل

استاد

• Economic Geography
• Innovation Studies
• Regional Development
• +۶ مورد دیگر

Markus Grillitsch is Professor in the Department of Human Geography at Lund University and Director of CIRCLE (Centre for Innovation, Research and Competence in the Learning Economy). His work spans EU member states, transition economies, and developing countries with focus on spatial transformation processes. His research interests include: Economic Geography and Innovation Studies Regional Development and Knowledge Institutions Place-Based Leadership and Institutional Entrepreneurship Network Analysis and Policy Implementation Recent publications demonstrate strong focus on energy justice transitions, innovation policy limitations, and multi-scale inequality analysis. His work connects theoretical frameworks with empirical studies of regional diversification and agency-structure dynamics. Key recurring themes include sustainable development pathways, capabilities approaches, and institutional transformation processes across diverse geographical contexts. Current research projects include: Multi-level learning journeys for green and just regional transformations (Vinnova-funded) Economic resilience through Swedish hidden champions study Circular value chains and policy dynamics research Klimatneutrala städer 2030 urban climate initiative Grillitsch's work actively contributes to UN Sustainable Development Goals through research on economic growth, reduced inequalities, sustainable cities, and climate action. His fingerprint analysis shows strongest connections to Innovation (100%), Knowledge (93%), and Regional Development (66%) research domains.

• Machine Learning
• Artificial Intelligence
• Explainability of AI
• +۳ مورد دیگر

Carlos Guestrin is the Fortinet Founders Professor of Computer Science at Stanford University and serves as Director of the Stanford AI Lab (SAIL) and Senior Fellow at the Institute for Human-Centered AI (HAI). He holds dual roles as Chief Scientist at Visual Layer and Virtue AI. His research focuses on machine learning methods, explainability, fairness, and ethics of AI, alongside systems for scalable AI deployment. Education details are not explicitly provided, but his work spans foundational contributions to machine learning systems (e.g., XGBoost) and explainable AI frameworks like Anchors and LIME. He emphasizes ethical AI through projects like CheckList for model testing and Model Equality Testing for API transparency. His scientific contributions include advancing optimization techniques (AdaScale SGD, TVM compiler) and ethical benchmarks for generative AI. He has been recognized as a Member of the National Academy of Engineering for his transformative impact on AI systems and their societal applications. Guestrin leads interdisciplinary initiatives at SAIL and HAI, fostering collaboration between technical innovation and human-centered design. His work bridges theory and practice, addressing challenges in healthcare (diabetes management systems) and AI security.

Carlos Fernandez-Grandaمشاهده پروفایل

دانشیار

• Machine Learning
• Medical AI
• Climate Science
• +۷ مورد دیگر

Carlos Fernandez-Granda is an Associate Professor of Mathematics and Data Science at New York University, holding joint appointments at the Courant Institute of Mathematical Science and the Center for Data Science. He currently serves as the Interim Director of the Center for Data Science. His academic career spans over a decade at NYU, where he has taught probability and statistics to data-science students. Dr. Fernandez-Granda's research focuses on designing and analyzing data-science methodology, with current emphasis on machine learning applications in medicine, climate science, and scientific imaging. His work bridges theoretical foundations with practical applications across multiple domains. His notable contributions include: Development of the COBRA (COnfidence-Based chaRacterization of Anomalies) score for automatic assessment of impairment and disease severity Applications of machine learning to improve climate projections through the M2LInES project Research on magnetic resonance fingerprinting for quantitative tissue parameter estimation Development of AI systems for medical diagnostics including Alzheimer's detection and breast cancer diagnosis Dr. Fernandez-Granda is the author of the book "Probability and Statistics for Data Science," published by Cambridge University Press. The book serves as a comprehensive guide to the two pillars of data science, featuring real-world datasets and addressing fundamental challenges like overfitting, the curse of dimensionality, and causal inference. His research has been supported by grants from the National Science Foundation (Division of Mathematical Sciences, grants 1616340 and 2009752) and the Alzheimer's Association (grant AARG-NTF-21-848627). Dr. Fernandez-Granda is actively involved in several collaborative projects: M2LInES project: An international collaboration focused on improving climate projections using machine learning to capture unaccounted physical processes at the air-sea-ice interface Math and Data group: Exploring the intersection of mathematical theory and data science applications

Yves-Alexandre de Montjoyeمشاهده پروفایل

دانشیار

• Computational Privacy
• AI Safety
• Machine Learning
• +۳ مورد دیگر

Yves-Alexandre de Montjoye is an Associate Professor of Applied Mathematics and Computer Science at Imperial College London, where he leads the Computational Privacy Group. He holds a joint affiliation between the Department of Computing and the Data Science Institute. His roles include serving as a Special Adviser on AI and Data Protection to the EC Justice Commissioner Didier Reynders, a Parliament-appointed Commissioner for the Belgian Data Protection Agency, and a Special Adviser to EC Competition Commissioner Margrethe Vestager, co-authoring the 'Competition Policy for the Digital Era' report. He earned his PhD from MIT in 2015 under Alex 'Sandy' Pentland. His master's degrees include an M.Sc. in Applied Mathematics from UCLouvain, an M.Sc. (Centralien) from École Centrale Paris, and an M.Sc. in Mathematical Engineering from KU Leuven. He also holds a B.Sc. in Engineering from UCLouvain. His research interests focus on computational privacy, anonymization techniques, AI safety, and machine learning attacks. He develops methods to 'red team' AI systems and create privacy-preserving mechanisms. His work addresses vulnerabilities such as membership inference, attribute inference, and re-identification risks in datasets, with applications to location tracking, synthetic data, and LLMs. His articles analyze adversarial attacks against privacy systems, emphasizing robustness and practical guarantees. He advocates for privacy-by-design approaches in big data analytics and has explored ethical AI, competition policy in digital markets, and humanitarian uses of mobile data. While no scientific awards are explicitly listed, his contributions have been widely covered in media. He is currently recruiting motivated PhD students for his group at Imperial College. His advising and grants narrative includes work on privacy-preserving technologies and policy implications of AI, with collaborations across academia and public institutions. He is affiliated with the Computational Privacy Group and contributes to platforms like OPAL for privacy analytics. His office is in the ACE Extension building (ACEX 259), accessible via Exhibition Road.

Suining Heمشاهده پروفایل

استادیار

• Cyber-Physical Systems
• Smart & Connected Communities
• Human-Centered Computing
• +۱۰ مورد دیگر

Suining He is an Assistant Professor at the University of Connecticut (UConn)'s School of Computing, leading the Ubiquitous and Urban Computing Lab since 2019. Previously, he was a postdoctoral research fellow at the University of Michigan's Real-Time Computing Lab (2016–2019). He holds a Ph.D. in Computer Science from the Hong Kong University of Science and Technology (2016) and a B.Eng. in Mechanical Design from Huazhong University of Science and Technology (2012). His research focuses on Cyber-Physical Systems (CPS), Smart & Connected Communities, Human-Centered Computing, and Urban Computing Cyberinfrastructure, with emphasis on mobility, equity, and AI-driven solutions. He has received prestigious awards including the NSF CAREER Award (2023), Google Research Scholar Program Award (2021), and recognition as a Stanford Top 2% Scientist (2020–2024). His work spans interdisciplinary grants from NSF, USDA, Google, NVIDIA, and industry partners. Recent publications explore autonomous driving simulation, equity-aware mobility prediction, and urban crowd activity modeling. Teaching excellence is reflected in his 2020 UConn Provost Award. He advises on reinforcement learning, CPS, and mobile computing, with openings for 2025/2026 PhD students. His lab collaborates on socially-conscious AI, privacy-preserving learning, and location-based services with industrial impact.