جستجوی استاد راهنمای دانشگاهی

Shiqing Maمشاهده پروفایل

استادیار

• Security and Privacy
• Trustworthy Machine Learning
• Software Engineering
• +۳ مورد دیگر

Shiqing Ma is an Assistant Professor in the Manning College of Information and Computer Sciences at the University of Massachusetts Amherst. Previously, he held a faculty position at Rutgers University from 2019 to 2023. He earned his Ph.D. in Computer Science from Purdue University (2019) and B.E. from Shanghai Jiao Tong University (2013). His research focuses on secure, intelligent, and transparent computing systems, particularly at the intersection of security, AI, and software systems. Key areas include integrating machine learning into software systems, ensuring algorithmic security through program analysis, and developing novel system architectures. Professor Ma's work has been recognized with prestigious awards, including the NSF CAREER Award (2023), and distinguished paper awards at USENIX Security (2017) and NDSS (2016). He actively contributes to the academic community through editorial roles and program committees in security, privacy, and software engineering. His research explores topics like backdoor attacks, AI safety, and bias mitigation in large language models. Recent articles emphasize defense mechanisms against adversarial attacks, watermarking techniques, and automated debugging systems for machine learning pipelines.

• Robotics
• Transfer Learning
• Neuro-fuzzy Systems
• +۲ مورد دیگر

C. S. George Lee is a Professor of Electrical and Computer Engineering at Purdue University's Elmore Family School of Electrical and Computer Engineering, located in West Lafayette. His research focuses on Robotics, Transfer Learning, Neuro-fuzzy Systems, Automatic Controls, and Computer Engineering. He holds a BSEE (1973), MSEE (1974) from Washington State University, and a PhD (1978) from Purdue University. His work integrates computational intelligence with AI, robotics, and education technology, emphasizing human-machine co-learning models and bilingual systems. His contributions span domains like quantum computing, generative AI, and knowledge graph applications. He leads the Art Lab at Purdue and has published extensively on topics ranging from humanoid robotics to cross-cultural educational platforms. His research areas include developing intelligent agents for edutainment, robotic assistants for student learning, and advanced machine learning techniques. Notable trends in his publications involve computational intelligence applied to bilingual language models (e.g., Taiwanese/English co-learning), quantum-based AI systems, and human-centric robotics. He has explored applications in healthcare (e.g., blood donor analysis), autonomous navigation, and game AI (e.g., Go). His work often bridges theoretical advancements with real-world implementations, such as Java software tools for motor activity assessment (JKinect) and AI-driven platforms for skill evaluation. Lee's research emphasizes interdisciplinary collaboration, with contributions to IEEE conferences and cross-institutional projects. His lab develops tools for adaptive e-learning, robotic task performance evaluation, and human pose estimation using neural networks. Despite prolific publishing, no specific grants or awards are explicitly mentioned in the provided text. His work continues to explore the intersection of human intelligence and smart machines through platforms like Metaverse integration and BCI (Brain-Computer Interface) applications.

LU Wen Fengمشاهده پروفایل

دانشیار مدعو

• Additive Manufacturing
• Robotics
• Smart Manufacturing
• +۴ مورد دیگر

LU Wen Feng is an Adjunct Associate Professor in the Department of Mechanical Engineering at the National University of Singapore (NUS), affiliated with the College of Design and Engineering. His research focuses on advanced manufacturing technologies, including additive manufacturing, robotics, and AI-driven systems. He explores sustainable design methodologies, smart manufacturing innovations, and bioprinting applications. Key areas include optimizing material processes, enhancing mechanical properties of printed materials, and developing autonomous robotic solutions for industrial tasks. Contact: mpelwf@nus.edu.sg , located at E3-02-07. Research Interests : His work bridges AI and manufacturing, emphasizing Knowledge graph integration for additive manufacturing, Autonomous robotic systems in industrial settings, Bioprinting for tissue repair with smart bioinks, Topology optimization for lightweight and sustainable structures, Material characterization and process engineering for 3D-printed composites. Recent Article Trends : LU Wen Feng's 2025 articles highlight advancements in AI-augmented manufacturing systems (e.g., MaViLa, AutoMEX) and sustainable design workflows. His 2024 studies address material anisotropy, corrosion behavior, and topology optimization strategies for lattice structures. These trends reflect his interdisciplinary approach to solving challenges in additive manufacturing, robotics, and biomedical applications. Awards : No scientific awards explicitly mentioned. Advising & Grants : No current graduate students or grants listed. His research likely integrates industry-academia collaborations given the focus on applied manufacturing technologies. Labs/Teams : Not explicitly detailed, but his work suggests involvement in advanced manufacturing labs and AI-robotics teams at NUS.

• Digital Agriculture
• Machine Systems Engineering
• Data Science
• +۴ مورد دیگر

Dr. Dennis Buckmaster is a Professor in Agricultural & Biological Engineering at Purdue University, serving as Dean's Fellow for Digital Agriculture. He holds a B.S. from Purdue University and M.S./Ph.D. from Michigan State University. His research focuses on digital agriculture, machine systems engineering, and data science applications in farming. He co-coordinates the Agricultural Systems Management program and teaches courses like Computing Technology with Applications and Ag Tech and Innovation. He leads the Open Ag Technology and Systems Center (OATS Center), advancing open-source solutions for agriculture through platforms like ISOBlue and OADA. His work integrates IoT, robotics, and machine learning to optimize crop production, livestock management, and farm decision-making. He has authored over 150 publications on precision agriculture technologies. Professional memberships include American Society of Agricultural and Biological Engineers and Fluid Power Society. He emphasizes data interoperability, edge computing, and bridging engineering with agricultural practices through collaborative frameworks like LATTICE and Meta Ag.

• Statistics
• Optimization
• Machine Learning
• +۳ مورد دیگر

Andrew Li is an Associate Professor of Operations Research at Carnegie Mellon University's Tepper School of Business since 2024, previously serving as Assistant Professor since 2018. His research bridges statistics, optimization, and machine learning with applications to healthcare operations and retail management. Current teaching: Optimization, Business Analytics Capstone, and Topics in Optimization and Statistics PhD from MIT's Operations Research Center (2018), BS in Operations Research/Applied Mathematics from Columbia University (2012) Research Focus: Dr. Li develops data-driven decision frameworks for complex systems. Key areas include: Experience-based learning models with fairness constraints (organ allocation) Anomaly detection in low-rank matrices (retail inventory accuracy) Nanoparticle-based diagnostic systems for CAD and Alzheimer's Nonstationary demand forecasting in supply chains Publication Trends: Recent work combines bandit algorithms with healthcare applications (split liver transplants, CAD detection) and retail operations (inventory accuracy). Theoretical contributions include regret-optimal policies and entrywise anomaly detection guarantees. Scientific Honors: INFORMS Nicholson Award (2018) INFORMS Pierskalla Award (2021) NSF CAREER Award (2023) Professional Leadership: Active in INFORMS and CMU committees including MBA Analytics Curriculum, Thompson Award, and ENAiBLE AI-driven retail collaborative co-founder since 2021.

Pascale Bironمشاهده پروفایل

استاد

• Hydro-geomorphology
• River Restoration
• Floodplain Management
• +۳ مورد دیگر

Pascale Biron is a Professor in the Department of Geography, Urban Planning and Environment at Concordia University, Montreal. She holds a Ph.D. in Geography from Université de Montréal (1995) and has been with Concordia since 1998. Her research focuses on river dynamics, stream restoration for fish habitat, flood modeling, and climate change impacts. She specializes in hydrogeomorphology, river management in agricultural watersheds, and numerical modeling of fluvial processes. Research Interests: Her work includes river restoration strategies, flood risk assessment using LiDAR technology, and the 'river freedom' concept promoting ecosystem resilience. She collaborates closely with government agencies to translate research into practical river management policies. Professional Affiliations: Canadian Geomorphology Research Group, Canadian Association of Geographers, American Geophysical Union, GRIL (Limnology Research Group), and RIISQ (Quebec Flood Risk Network). Publications & Research: Recent studies address global salmonid biomass patterns, fluvial hazard detection via machine learning, and large-scale flood modeling. She supervises 19 graduate students in Ph.D./M.Sc. programs in Geography and Environmental Studies, focusing on topics like river confluence hydraulics and agricultural stream restoration. Grants & Funding: Active projects include river dynamics in fish habitats, flood modeling for road infrastructure vulnerability, and computational fluid dynamics simulations of river flows. She also leads research on societal dimensions of river restoration and policy frameworks for flood resilience.

Simon Dobsonمشاهده پروفایل

استاد

• Complex Systems
• Sensor Systems
• Data Analytics
• +۳ مورد دیگر

Simon Dobson is a Professor of Computer Science and Deputy Head of the School of Computer Science at the University of St Andrews. His research focuses on complex systems, sensor analytics, computational tools for simulation, and data analytics. He leads grants exceeding EUR30M, including a £5M EPSRC-funded programme in Sensor Systems Software. He is a Fellow of the Royal Society of Edinburgh (2020) and advises the Scottish government. Education: BSc (University of Newcastle), DPhil (University of York), both in Computer Science. Professional: Chartered Engineer, Fellow of the British Computer Society. Research Interests: Complex systems, network science, higher-order networks, epidemiological modeling, and sensor data integration. Teaching: CS4203 (Computer Security), CS5728 (Complex Systems Modelling). Supervises PhD/MSc projects. Awards: Includes RSE Fellowship, BCS Fellowship, and multiple leadership roles in conferences and committees.

• Software Engineering
• Graph Transformation Systems
• Model-Based Development
• +۵ مورد دیگر

Reiko Heckel is a Professor of Software Engineering at the University of Leicester, serving as Director of Postgraduate Teaching for Computing degrees and Data Analytics Lead at the Leicester Innovation Hub. She previously held academic roles at the Technical Universities of Dresden and Berlin before joining Leicester in 2004. Her research focuses on graph transformation systems, model-based development, stochastic modeling, and formal methods in software engineering. She earned her PhD (Dr.-Ing.) in Computer Science from TU Berlin in 1998. Her research interests span software engineering pedagogy, formal specification techniques, and applications of graph grammars in system modeling. Recent work explores stochastic graph transformations for social networks, transparency engineering in AI systems, and blockchain-based smart contract frameworks. Her contributions bridge theoretical foundations with practical applications in cybersecurity, data integration, and human-centric systems design. Key contributions include advancements in automated test case generation via graph transformations, visual contracts for software reverse engineering, and formal methods for complex system analysis. Her work frequently intersects with industry through collaborations via the Leicester Innovation Hub, emphasizing data analytics and technology transfer. Education: MSc Computer Science, Technical University of Dresden PhD (Dr.-Ing.), Computer Science, TU Berlin (1998) Leadership Roles: Head of Department (2014-2018) Director of Postgraduate Teaching (Ongoing) Research Themes: Model-Based Development Stochastic Systems Analysis Graph Neural Networks Trustworthy AI Her publications reflect a focus on formal methods, with recent trends in applying graph transformation techniques to social network modeling, blockchain smart contracts, and educational pedagogy.

Iqbal Husainمشاهده پروفایل

دانشگاهی

• Power Electronics
• Electric Vehicles
• Control Systems
• +۳ مورد دیگر

Dr. Iqbal Husain is the Director of the FREEDM Center and an ABB Distinguished Professor in the Department of Electrical and Computer Engineering at North Carolina State University. Previously, he served at the University of Akron for 17 years before joining NC State. He holds a Ph.D. (1993), M.S. (1989), and B.S. (1987) in Electrical Engineering from Texas A&M University and Bangladesh University of Engineering and Technology, respectively. His research focuses on power electronics, electric drives, and renewable energy systems, with applications in transportation, automotive, and aerospace. Notable contributions include advancements in electric machine design, inverter controls, and grid synchronization. He authored the textbook *Electric and Hybrid Vehicles: Design Fundamentals*, now in its third edition. Dr. Husain’s awards include the NSF CAREER Award (1997), SAE Vincent Bendix Award (2006), and IEEE Fellow (2009). His recent work includes developing AI-enabled tools for power grid cybersecurity and medium-voltage solid-state transformers for EV fast charging. He leads interdisciplinary projects at the FREEDM Systems Center, addressing challenges in clean energy and smart grid technologies.

Steven Sicilianoمشاهده پروفایل

استاد

• Soil Toxicology
• Environmental Science
• Polar Ecosystems
• +۵ مورد دیگر

Steven Siciliano is a Professor and NSERC/FCL Industrial Research Chair in In Situ Remediation and Risk Assessment at the University of Saskatchewan's College of Agriculture and Bioresources. He leads the CREATE Human and Ecological Risk Assessment Program. His expertise spans soil toxicology, greenhouse gas dynamics in polar ecosystems, and nitrogen cycle interactions in contaminated environments. Education: Ph.D. in Toxicology, University of Saskatchewan B.Sc. in Biochemistry, Concordia University Research Interests: His work focuses on human-soil interaction dynamics, including soil pollution impacts on human health (e.g., PAH toxicity via soil ingestion) and ecosystem resilience (e.g., nitrogen cycle disruptions). He investigates Arctic/Antarctic soil microbiology, greenhouse gas production in polar deserts, and the ecological effects of pollutants like mercury and petroleum hydrocarbons. His lab is divided into toxicology (e.g., metal cardiovascular effects, soil ingestion models) and ecology (e.g., sub-zero water effects on gene expression, Arctic nitrogen cycles). Teaching: Teaches courses on environmental fate analysis, contaminated site management, and advanced risk assessment methodologies at both undergraduate and graduate levels. Courses include EVSC 420, TOX 820, and EVSC 821. Grants & Labs: Directs the CREATE Program and leads projects funded by NSERC and industry partnerships. His lab integrates fieldwork, molecular techniques, and modeling to address environmental remediation challenges. Collaborates on projects like cryoturbation-driven carbon dynamics and microbial community analysis in agricultural systems. Labs/Teams: Active in soil science research teams, including Arctic soil microbiology and bioremediation innovation groups. Engages in interdisciplinary collaborations with environmental engineers and ecologists to advance in situ remediation technologies.

Brooke Erin Duffyمشاهده پروفایل

دانشیار

• Digital Media Industries
• Gender and Identity
• Cultural Production
• +۴ مورد دیگر

Brooke Erin Duffy is an Associate Professor in the Department of Communication at Cornell University, with affiliations in the College of Agriculture and Life Sciences (CALS), the Graduate Field of Feminist, Gender, and Sexuality Studies, and Media Studies. Her research investigates digital and social media industries, gender and identity dynamics, the gig economy’s impact on creative labor, and algorithmic governance in cultural production. She is a prominent voice in feminist media studies, blending academic rigor with public engagement through outlets like The Atlantic , Vox , and The New York Times . Education : Ph.D. in Communication (University of Pennsylvania, 2011), M.A. (University of Pennsylvania, 2008), B.A. in Communications (Penn State University, 2002) Her work highlights the gendered politics of digital labor , focusing on social media influencers, platform precarity, and the tension between authenticity and visibility. Recent research examines algorithmic systems, platform paternalism, and the visibility bind in creator economies. Duffy’s academic contributions include leadership in organizations like the American Influencer Council and Content Creator Scholar Network. She received multiple honors, including the 2021 Top Student-Led Paper award and the 2014 Lillian Lodge Kopenhaver Outstanding Woman Junior Scholar Award. Teaching : Courses on New Media & Society , Gender and Media , and Platform Labor and Precarity Public Impact : Regular commentary in global media and a 2024 contributor role at Forbes

Ivan Coleمشاهده پروفایل

استاد مدعو

• Corrosion Science
• Multiscale Modelling
• Additive Manufacturing
• +۷ مورد دیگر

Prof. Ivan Cole is an Adjunct Professor at RMIT University's School of Engineering, specializing in rapid materials discovery for corrosion protection, nanostructures, and additive manufacturing. His work integrates computational modeling with high-throughput experimentation, focusing on corrosion inhibitors, biocompatible surfaces, and additive manufacturing process optimization. With over 30 years of experience across academia and industry (including leadership roles at CSIRO and Centro-Svilluppo Materiali), he leads the Rapid Discovery & Fabrication Team (RDF) to advance these research areas. Research Interests: Corrosion science, microbially induced corrosion (MIC), additive manufacturing surfaces, nanostructure sensing, multiscale modeling, and green materials discovery. His team addresses challenges in corrosion protection, biomedical implants, and environmental remediation through innovative methodologies. Awards: 2019 Australian Corrosion Medal 2016 CSIRO Lifetime Achievement Award 2013 Best Paper in NACE Corrosion Supervision & Projects: Active in mentoring PhD/Master’s students across corrosion inhibition, additive manufacturing, and nanostructure design. Notable projects include developing quorum sensing inhibitors for biofilm control, in-situ monitoring for metal AM, and eco-friendly corrosion inhibitors. Labs & Collaborations: Leads the Rapid Discovery & Fabrication Team and collaborates with industry partners to translate research into practical solutions for materials durability and sustainability.

Vijay Vaziraniمشاهده پروفایل

استاد

• Algorithmic Game Theory
• Matching Markets
• Computational Complexity
• +۶ مورد دیگر

Vijay Vazirani is a Distinguished Professor in the Department of Computer Science at the University of California, Irvine , where he directs the ACO Center @ UCI . He earned his Ph.D. in Computer Science from UC Berkeley and a S.B. from MIT. Vazirani is a Guggenheim Fellow , ACM Fellow , and 2022 INFORMS John von Neumann Theory Prize recipient. Research Areas: Algorithmic Game Theory, Matching Markets, Computational Complexity, Approximation Algorithms His groundbreaking work includes co-founding algorithmic game theory and solving a 30-year-old problem with an NC algorithm for perfect matching in planar graphs . Recent research focuses on matching-based market design, with a $500K NSF grant for advancing algorithms in matching and market equilibria. His 15 most recent papers explore topics like core imputations, stable matching lattices, and Nash bargaining solutions. Scientific Awards: Guggenheim Fellowship ACM Fellow 2022 INFORMS John von Neumann Theory Prize Vazirani advises numerous Ph.D. students and postdocs, including Tung Mai , Thorben Trobst , and Rohith Reddy Gangam . He contributes to major workshops and co-edited foundational texts like Algorithmic Game Theory and Online and Matching-Based Market Design .

Jens O. Brunnerمشاهده پروفایل

استاد

• Healthcare Operations Management
• Operations Research
• Analytics
• +۳ مورد دیگر

Jens O. Brunner is a Professor of Decision Science in Healthcare at the Technical University of Denmark (DTU), affiliated with the Department of Technology, Management and Economics. Previously, he held a professorship at the University of Augsburg until March 2023 and served as co-director of the University Center for Health Care (UNIKA-T) from 2013 to 2020. He earned his PhD from the TUM School of Management (2009) and a diploma in Business Administration from the University of Mannheim (2006). Roles: Professor, Department Editor for Health Care Management Science , and Associate Editor for multiple journals. Education: PhD in Management, TUM School of Management (2009) Diploma in Business Administration, University of Mannheim (2006) His research focuses on healthcare operations management and the application of quantitative methods to optimize service systems. Key areas include triage policies, staff scheduling, and AI-driven healthcare solutions. His work has contributed to improving resource allocation in hospitals and pandemic response strategies. Notable awards include the Harold W. Kuhn Award (2015) and the IISE/SSE Outstanding Innovation Award (2022). His research has been published in journals like IIE Transactions and European Journal of Operational Research . He supervises PhD students in projects such as AI-integrated pooling strategies and resource optimization in healthcare. His involvement in interdisciplinary collaborations and editorial roles highlights his leadership in advancing healthcare operations research.

Dhiraj Murthyمشاهده پروفایل

استاد

• Social Media
• Digital Research Methods
• Race/Ethnicity Studies
• +۷ مورد دیگر

Professor Dhiraj Murthy holds appointments in the Moody College of Communication , Sociology , and School of Information at the University of Texas at Austin. He earned a Ph.D. in Sociology from the University of Cambridge. His research focuses on social media, digital methods, health communication, and disaster response. He directs the Computational Media Lab , a leading research group with over 20 students, and co-edits the journal Big Data & Society . Notably, he authored the seminal book Twitter: Social Communication in the Twitter Age (2013/2018), which won the ALA CHOICE Prize. Dr. Murthy's work has been funded by NIH, NSF, and other major grants, including studies on e-cigarette marketing, disaster informatics, and AI-driven disinformation detection. He also serves on advisory boards for MediaWell and chairs international social media conferences. Education : Ph.D. in Sociology, University of Cambridge. Grants : Over $5M from NIH, NSF, and UT Austin’s Good Systems initiative for projects like 'AI Technologies to Curb Disinformation' and 'E-cigarette Use Among Mexican American Students.' Labs/Teams : Computational Media Lab (UT Austin), focusing on AI, social media analytics, and health research. Awards : Stanford University’s 2023 Top 2% Global Scientists in Communication & Media Studies and Sociology, ALA CHOICE Prize (2018), and multiple NIH/NSF grants. His work bridges sociology, media studies, and computational methods to address societal challenges like health disparities and misinformation.