جست‌وجوی استاد و پژوهشگر

Brenna D. Argallمشاهده پروفایل

دانشیار

• Robotics
• Rehabilitation Engineering
• Human-Robot Interaction
• +۳ مورد دیگر

Brenna D. Argall is an Associate Professor of Computer Science, Mechanical Engineering, and Physical Medicine & Rehabilitation at Northwestern University, and a Faculty Research Scientist at the Shirley Ryan AbilityLab. Her research focuses on assistive and rehabilitation robotics, with an emphasis on human-robot interaction, shared autonomy, and intelligent control systems. She holds a PhD in Robotics from Carnegie Mellon University and has held postdoctoral fellowships at EPFL (Switzerland) and the NIH. Education: PhD in Robotics, Carnegie Mellon University (2009) Postdoctoral Fellow, EPFL (2009–2011) B.S. in Mathematics, Carnegie Mellon University (2002) Affiliations: Director, Argallab (Assistive & Rehabilitation Robotics Laboratory) Member, Northwestern Center for Robotics and Biosystems Advisor, Northwestern MS in Robotics Program Her research explores dynamic autonomy allocation , shared control systems , and interface-aware robotics , with applications in rehabilitation and assistive devices. Key projects include wheelchair automation, robotic arm control, and body-machine interfaces for users with motor impairments. Research Highlights: NSF CAREER Award (2016) AIMBE Fellow (2020) "40 under 40" Innovator (Crain’s Chicago Business) Publications emphasize human-centered robotics, including over 50 peer-reviewed articles on topics like intent inference, assistive autonomy, and teleoperation assistance. Current lab efforts prioritize interface-aware systems and customizable shared control to enhance accessibility for users with disabilities.

John Taylorمشاهده پروفایل

استاد

• Gauge Field Theory
• Thermal Field Theory
• Theoretical Physics
• +۳ مورد دیگر

John Taylor is a Professor of Mathematical Physics at the Department of Applied Mathematics and Theoretical Physics (DAMTP), University of Cambridge. His career includes roles as Reader in Theoretical Physics at Oxford University and earlier positions as Lecturer at Cambridge and Imperial College. His research focuses on Gauge Field Theory, Thermal Field Theory, and fluid dynamics with applications to oceanography and climate science. He leads the High Energy Physics research group at DAMTP and contributes to interdisciplinary projects on carbon sequestration and ocean biogeochemical modeling. Key research interests include turbulence in stratified flows, submesoscale ocean dynamics, and climate-related processes such as ice shelf-ocean interactions. His work integrates theoretical physics, computational modeling, and machine learning to address challenges in environmental science. Taylor has authored influential publications, including Hidden Unity in Nature's Laws (2001) and edited volumes on gauge theories. Recent studies explore carbon dioxide removal via macroalgae cultivation and the impact of fluid dynamics on kelp forests. His collaborative projects include developing the OceanBioME framework for coupled biogeochemical and physical ocean modeling.

Lingming Zhangمشاهده پروفایل

دانشیار

• Software Engineering
• Programming Languages
• Machine Learning
• +۶ مورد دیگر

Lingming Zhang is an Associate Professor at the Department of Computer Science, University of Illinois Urbana-Champaign, affiliated with the Grainger College of Engineering. His research focuses on the intersection of Software Engineering, Programming Languages, and Machine Learning, with a particular emphasis on automated program repair, compiler testing, and large language model (LLM) applications in software engineering. He has published over 100 papers, achieving an h-index of 50+, and holds an ACM Distinguished Member status. Research Interests: LLM-based software testing, repair, and synthesis Fuzzing of deep-learning libraries and compilers Open-source code LLMs (e.g., StarCoder2, Magicoder) with over 1M downloads Automated program repair systems (e.g., AlphaRepair, ChatRepair, Agentless) Recent Contributions: Developed TitanFuzz for coverage-guided compiler fuzzing Released Agentless , an LLM-based coding tool adopted by OpenAI and DeepSeek Proposed SWE-RL to enhance LLM reasoning via reinforcement learning Service Roles: Program Co-Chair for ASE 2025 and LLM4Code 2025 Associate Chair for OOPSLA 2024 and Area Chair for ICSE 2025/2026 Recipient of NSF CAREER Award and ACM SIGSOFT Early Career Award Lab/Teams: Develops open-source tools like UniAPR for efficient patch validation Active in releasing industry-adopted LLM-based software engineering tools

Wing Wah Thamمشاهده پروفایل

دانشیار

• Econometrics
• Market Microstructure
• Asset Pricing
• +۳ مورد دیگر

Associate Professor Wing Wah Tham holds a position at the School of Banking and Finance within the University of New South Wales (UNSW) Business School . He also maintains affiliations as a Marie Skłodowska-Curie Fellow and a Tinbergen Institute Fellow . Previously, he served as an Associate Professor of Financial Econometrics at the Econometric Institute, Erasmus School of Economics (2014–2016) and as an Assistant Professor there (2009–2014). Education : PhD, University of Warwick MSc, Imperial College, UK BEng, Nanyang Technological University of Singapore Research Interests : Professor Tham specializes in econometrics , market microstructure , asset pricing , and financial innovation . His work bridges quantitative finance with applications in artificial intelligence and sustainable development goals (SDG) , focusing on reproducibility, liquidity dynamics, and policy impacts. Recent Publications span high-impact journals like Journal of Finance , Management Science , and Review of Financial Studies , addressing topics such as nonstandard errors , AI for SDG mapping , and toxic arbitrage . These works are frequently presented at American Finance Association and Econometric Society meetings. Scientific Honors : PanAngora Crowell Second Prize Midwest Finance Association Best Paper Award Literati Network Awards for Excellence ARC Discovery Projects Grant Additional Activities : He has served as a visiting scholar at the Haas Business School, UC Berkeley and National University of Singapore , with interests in triathlons and ocean swimming.

Lokukaluge Prasad Pereraمشاهده پروفایل

استاد

• Maritime Technology
• Offshore Systems
• Advanced Data Analytics
• +۶ مورد دیگر

Lokukaluge Prasad Perera is a Professor in Maritime Technology at UiT The Arctic University of Norway and a Senior Research Scientist in Smart Data at SINTEF Digital . He holds a BSc in Mechanical Engineering from Oklahoma State University (1999), MSc in Systems & Controls from the same institution (2001), and a PhD in Naval Architecture and Marine Engineering from Technical University of Lisbon (2012). His research focuses on Maritime and Offshore Systems , Advanced Data Analytics , Autonomous Navigation , Energy Efficiency , and Digital Twin Applications . He has published over 100 peer-reviewed papers and was recognized in the World's Top 2% Scientists (2021-2022) by Stanford University. Key professional experiences include roles at SINTEF Ocean (2014–2017), Center for Marine Technology and Engineering in Portugal (2008–2012), and Wärtsilä Finland (2012–2014). He has also held academic positions at Naval & Maritime Academy and Ocean University of Sri Lanka . His work addresses challenges in emission reduction , renewable energy integration , and safety-critical systems for maritime operations. Current projects emphasize trustworthiness of autonomous ships and data-driven decision frameworks for energy efficiency.

• Process Metallurgy
• Advanced Materials Processing
• Steelmaking Technology
• +۷ مورد دیگر

Bryan Webler is a Professor in the Department of Materials Science and Engineering at Carnegie Mellon University (CMU) since 2013, with a courtesy appointment in the Department of Mechanical Engineering. He serves as Co-Director of the Center for Iron and Steelmaking Research (CISR), an industry-supported consortium, and is affiliated with the NextManufacturing Center and Mill 19 digital backbone initiative. His expertise spans process metallurgy, additive manufacturing, and steelmaking technologies. Education: B.S. in Engineering Physics (2005) from the University of Pittsburgh; M.S. (2007) and Ph.D. (2008) in Materials Science and Engineering from CMU. Prior to academia, he worked as a Senior Engineer at the Bettis Atomic Laboratory's Materials Technology department. Research focuses on four core areas: chemical reactions during liquid steel refining, non-metallic inclusion control, continuous casting of steel, and additive manufacturing (laser powder bed fusion, directed energy deposition). His group integrates high-temperature experiments, computational thermodynamics, and kinetic modeling. Notable contributions include developing oxide dispersion strengthening methods and advancing digital twin applications in manufacturing. Key awards include the Kent D. Peaslee Junior Faculty Award (AIST Foundation) and the AIST Foundation Steel Professor title. He serves on editorial boards for Metallurgical and Materials Transactions B and Metallurgical Research and Technology , and actively contributes to industry partnerships. Beyond technical work, Webler explores the history of metallurgy, particularly Pittsburgh's steel industry legacy. His lab's innovations address carbon management, energy production, and advanced materials processing for extreme environments.

• Public Law
• Algorithmic Decision-Making
• Constitutional Law
• +۵ مورد دیگر

Adam Harkens is a Lecturer in Public Law at the University of Strathclyde. He holds a PhD in Law from Queen's University Belfast, funded by the Leverhulme Interdisciplinary Network on Cybersecurity and Society (LINCS). His research focuses on the intersection of public power, digital decision-making tools, and constitutionalism, addressing issues like algorithmic policing, surveillance, and AI governance. He is a founding member of the Strathclyde Centre for Doctoral Training (SCDT) in Human Rights-Based Decision-Making and the LEADS Lab at the University of Birmingham. Teaching includes modules on constitutional law, administrative law, and digital regulation at both undergraduate and postgraduate levels. Professional activities include advising bodies like the Office for AI and the Dutch Raad van State. He co-leads the SCDT project (2023–2027) and contributed to the FATAL4JUSTICE? Programme (2019–2022). His upcoming monograph, The Algorithmic State: Power, Constitutionalism and the Future of Administrative Law , explores these themes further. Research interests emphasize preventing power abuse via algorithmic systems, engaging legal theory, human rights, and interdisciplinary collaboration. Recent projects include workshops on predictive policing regulation and EU AI accountability frameworks.

Zoe Liمشاهده پروفایل

دانشیار

• Uncertainty Analysis
• Risk Management
• Stochastic Modelling
• +۷ مورد دیگر

Dr. Zoe Li is an Associate Professor in the Department of Civil Engineering at McMaster University, with an additional role as an Associate Member in the Department of Computing and Software. She specializes in developing modeling and decision-support tools to address challenges in water resources management, environmental systems analysis, and climate change impacts. Her research focuses on hydrological modeling, probabilistic forecasting, risk analysis, and environmental systems optimization. She holds a B.Eng. from China and M.A.Sc./Ph.D. degrees from the University of Regina. Her work spans interdisciplinary collaborations, including studies on dam safety under climate change, wastewater treatment plant optimization, and AI-driven environmental monitoring. She has been actively involved in projects such as CityDNA, a digital tool to model urban environments for decision-making during crises like the pandemic. Dr. Li teaches courses in environmental systems engineering and principles of environmental engineering, emphasizing uncertainty quantification and sustainable practices. Her research publications (15+ recent articles) address topics like machine learning applications in environmental systems, climate change impacts on water resources, and infrastructure resilience. She advises graduate students in environmental engineering and systems optimization. Notable grants include funding from Roche Canada for pandemic-related urban modeling. Her work is frequently published in high-impact journals like Journal of Environmental Management and Water Resources Research .

Jiangwen Sunمشاهده پروفایل

استادیار

• Machine Learning
• Data Mining
• Medicine
• +۶ مورد دیگر

Jiangwen Sun is an Assistant Professor in the Department of Computer Science at Old Dominion University (ODU), within the College of Science. He directs the ODU Computational Systems Medicine Lab and focuses on machine learning approaches for analyzing multi-dimensional biological data (phenome, genome, transcriptome, etc.) to advance precision medicine and its automation. His research is supported by ODU and federal agencies like NIH and NSF. Education: Ph.D., University of Connecticut M.E., Nanjing University, China B.M., Secondary Military Medical University, China Research Interests: Machine learning/data mining for medicine, health, drug discovery, and bioinformatics Multi-view bi-clustering and integrative analysis of genomic/phenotypic data Phenotype refinement and genetic association studies for complex diseases Applications in addiction medicine, cardiovascular biology, and bovine development Publications: Over 40 peer-reviewed articles in top venues like NIPS, ICML, Bioinformatics, and BMC Genomics. Recent work focuses on cryo-EM protein structure analysis, single-cell multiomics, and epigenetic modeling. Awards/Grants: NIH/NSF funding pending; previously supported by UConn's Health Informatics Lab and collaborations with University of Pennsylvania. Teaching: Courses include Machine Learning (CS722/822), Data Structures (CS361), and Deep Learning in Medicine (CS795/895). Labs/Teams: Leads the ODU Computational Systems Medicine Lab and collaborates with UConn Health Informatics Lab, Penn Medicine, and others.

• Energy Harvesting
• Piezoelectric Materials
• Biomedical Engineering
• +۳ مورد دیگر

Lin Dong is an Assistant Professor in the Department of Mechanical and Industrial Engineering at New Jersey Institute of Technology (NJIT). His research focuses on advanced energy harvesting technologies, particularly in piezoelectric materials, flexible electronics, and their biomedical applications. He leads a federally funded project (NSF grant) titled Membranous Energy Harvester with Tuning Capability for Flexible Electronics , which explores energy harvesting systems for wearable and implantable devices. His research interests include the design of self-powered sensors, piezoelectric hydrogels, and nature-inspired nanofibers for health monitoring. Notable contributions include amphibious energy generators, helical piezoelectric hydrogels for human-machine interfaces, and flexible sensors for cardiac monitoring. His work bridges materials science, biomedical engineering, and mechanical systems, with applications in smart health and wearable technology. Dr. Dong’s publications (29+ articles) emphasize energy harvesting innovations, with 16+ citations. His articles highlight trends in flexible, bio-integrated energy systems and multimodal sensing. He collaborates on projects involving body sensor networks and tunable energy harvesters for flexible electronics. He has secured a 2021 NSF grant (PI) and generated media attention for advancements in flexible energy harvesting and nanofiber research. His lab develops cutting-edge materials and devices for sustainable energy solutions and healthcare applications.

• Nonlinear Dynamics
• Structural Dynamics
• Vibration Control
• +۳ مورد دیگر

Professor David Wagg is a Professor of Nonlinear Dynamics and Departmental Director of Research and Innovation at the School of Mechanical, Aerospace and Civil Engineering, University of Sheffield. His research focuses on nonlinear structural dynamics, digital twins, vibration suppression, and real-time hybrid testing. He holds a BEng and PhD from University College London and previously served as a Professor at the University of Bristol (2008–2013). Notable awards include the EPSRC Advanced Research Fellowship (2004–2009). Education: BEng and PhD in Nonlinear Dynamics from University College London. Research Interests: Digital twins for dynamics applications, nonlinear structural dynamics, vibration control, real-time hybrid testing, and identification methods for nonlinear dynamics. His work emphasizes applying nonlinear models and control strategies to engineering challenges like wind turbines and large civil infrastructure. Grants & Leadership: Co-Investigator for EPSRC grants on CITCoM and Digitwin, coordinator of the Marie Curie ETN DyVirt, and PI for the EPSRC programme on Engineering Nonlinearity (2012–2017). He co-authored Nonlinear Vibration with Control (2015) and edited books on structural dynamics. Lab/Teams: Involved in the Laboratory for Verification and Validation (LVV) and leads research groups focused on digital twin applications, inerter-based systems, and structural health monitoring.

Ferreira Joao Carlosمشاهده پروفایل

استاد

• Artificial Intelligence
• AI in Health and Medicine
• AI in Energy and Transportation
• +۶ مورد دیگر

Joao Carlos Amaro Ferreira is a Professor at the Faculty of Logistics, Molde University College (HiMolde), Norway. He holds PhDs in Computer Engineering and Industrial Engineering from the Technical University of Lisbon and the University of Minho, respectively. His research focuses on Artificial Intelligence (AI) applications in healthcare, energy, transportation, IoT, blockchain, and smart cities. He has led over 40 projects, including 6 as Principal Investigator, and contributed to international conferences like OAIR and INTSYS. He served as IEEE CIS President (2016-2018) and is an IEEE Senior Member since 2015. His academic contributions span AI-driven solutions for public sector informatics, healthcare data quality, and cybersecurity. He actively participates in European projects such as e-Hospital4Future and explores blockchain applications in supply chains and medical records. Ferreira leads the ABC-AI research group, emphasizing ethical and applied AI. His work bridges academia and industry through projects like gamification systems for eco-driving and AI in fisheries traceability. Recent publications highlight AI's role in cardiovascular disease detection, emergency department optimization, and blockchain-enhanced healthcare interoperability. He collaborates internationally, co-editing journals like Applied Sciences , and has authored patents in edge computing for maritime monitoring.

Ana Lucicمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Interpretable Machine Learning
• +۶ مورد دیگر

Dr. Ana Lucic is an Assistant Professor at the University of Amsterdam , holding a joint appointment between the Institute for Logic, Language, and Computation (ILLC) and the Informatics Institute . Her research focuses on interpretable machine learning for applications in science and society, with emphasis on Earth system modeling and AI for environmental forecasting . PhD in Explainable Machine Learning (University of Amsterdam, 2022) MSc/BSc in Mathematics (McMaster University, Canada) Former researcher at Microsoft Research AI for Science and Partnership on AI Her recent work includes Aurora , a foundation model for Earth system forecasting published in Nature , and Clifford-Steerable CNNs at ICML 2024. Ana actively mentors PhD students and leads projects in mechanistic interpretability and geospatial machine learning . Scientific awards include top placements in ML competitions. She contributes to open science through reproducibility initiatives and collaborates with AI for climate consortia.

• Computational Photography
• 3D Vision
• AI Security
• +۱۲ مورد دیگر

Dr. Wan Renjie is an Assistant Professor in the Department of Computer Science at the Faculty of Science, Hong Kong Baptist University (HKBU). He holds a BEng in Network Engineering from the University of Electronic Science and Technology of China and a PhD from Nanyang Technological University (NTU), Singapore. Prior to joining HKBU, he was a Wallenberg-NTU Presidential Postdoctoral Fellow (2020–2022) and a guest researcher at Peking University (2019–2020). His research focuses on computational photography, 3D vision, AI security, digital watermarking, and neural representations . He explores robustness and security in vision models, especially concerning NeRFs and 3D Gaussian Splatting, and develops methods for low-light enhancement, reflection removal, and domain adaptation. Dr. Wan has published in top-tier venues including TPAMI, IJCV, CVPR, ICCV, NeurIPS, AAAI, and ECCV . His recent work emphasizes copyright protection for neural 3D models , adversarial attacks in multimodal and event-based systems, and medical image reconstruction. He is actively mentoring PhD students and research assistants. VCIP 2020 Best Paper Award Outstanding Reviewer, ICCV 2019 He teaches courses such as Introduction to AI and ML (COMP3057) , AI Application Development (COMP3065) , and Python for Data Analysis and Machine Intelligence (COMP7035) . Dr. Wan leads a dynamic research group with ongoing projects on watermarking, 3D reconstruction, and AI security, and he is currently recruiting new PhD students and research assistants.

Humphrey Southallمشاهده پروفایل

استاد

• Historical Geography
• Geographical Information Systems (GIS)
• Historical GIS
• +۱۲ مورد دیگر

Humphrey Southall is Professor of Historical Geography at the University of Portsmouth, affiliated with the Faculty of Science & Health and the School of the Environment and Life Sciences. He has been a key figure in advancing digital historical geography through large-scale projects such as A Vision of Britain through Time and the Great Britain Historical GIS . University: University of Portsmouth Faculty: Faculty of Science & Health Department: School of the Environment and Life Sciences Academic Rank: Professor Education: Bachelor's Degree, University of Cambridge (1976) Special Student, Harvard University (1976–1977) PhD, University of Cambridge (awarded 1984) Humphrey Southall's research centers on historical geography, with a focus on geospatial data modeling, gazetteers, and historical GIS. His work explores the long-term impacts of locality on health inequalities, the North-South divide in Britain, and the political roles of travellers. He has pioneered methods for disambiguating historical place names and constructing digital gazetteers from old maps and census data. His interdisciplinary approach bridges geography, history, and data science, contributing to digital humanities and sustainable development goals related to health and inequality. His recent publications reveal a strong trend toward integrating historical data with modern GIS and ontologies. Themes include electoral analysis (e.g., Reform UK), climate-land use interactions, and the digitization of historical statistics. His work emphasizes data accessibility, public engagement, and the application of historical insights to contemporary policy challenges. Scientific Awards and Recognition: No specific awards listed in the provided text. Humphrey Southall has secured major research grants from the ESRC, AHRC, JISC, and the European Commission. He leads the DDME: Data Discovery Made Easy project, applying machine learning to social science databases. He has supervised PhD students and actively collaborates with researchers across disciplines. His public engagement includes media commentary on homelessness, air pollution, and elections via The Conversation and national press. Labs and Research Teams: Lead Principal Investigator, A Vision of Britain through Time (VoB) Lead, Great Britain Historical GIS (GBHGIS) Team Member, PastPlace and AOU Resources as a Pelagios GIF Resource Collaborator with Patrick Aucott, Chris Thomas, and others on biodiversity and health projects