جست‌وجوی استاد و پژوهشگر

Heitor Murilo Gomesمشاهده پروفایل

مدرس ارشد

• Machine Learning
• Data Streams
• Online Continual Learning
• +۳ مورد دیگر

Heitor Murilo Gomes is a Senior Lecturer (Assistant Professor) in Artificial Intelligence at Victoria University of Wellington (New Zealand) since 2022. Previously, he served as Senior Researcher and Co-Director of the AI Institute at the University of Waikato. His research focuses on adaptive machine learning for data streams, including cybersecurity applications, ensemble methods, and online continual learning. He leads the development of the open-source library CapyMOA and has organized numerous international tutorials and workshops on streaming data techniques. Education : Ph.D. in Computer Science (2013-2017), Pontifícia Universidade Católica do Paraná, Brazil M.Sc. in Computer Science (2011-2012), same institution B.Sc. in Computer Science (2007-2010), UTP, Brazil Research Interests : Adaptive learning systems, concept drift detection, semi-supervised learning for delayed labels, and cybersecurity applications of ML. His work emphasizes practical implementations via libraries like CapyMOA and StreamDM. Key Contributions : Authored foundational papers on Adaptive Random Forests, Streaming Gradient Boosted Trees, and semi-supervised learning for data streams. His grants include a $360,000 Marsden Fund grant (2023-2026) for disagreement-based learning research. Awards : ACM SAC 2014 Best Paper Award (SAE2), PAKDD 2020 Outstanding Reviewer Honor Roll. Grants & Funding : Key researcher in the $13M TAIAO environmental AI program (MBIE SSIF), and sole PI for multiple grants totaling over $400,000 NZD. Active in editorial roles for Machine Learning (Springer) and conference reviewing (KDD, IJCAI, AAAI). Teaching : Leads COMPX523 (Data Stream Mining) and teaches fundamentals of AI. Delivers guest lectures globally on streaming data topics.

Ricardo Baeza-Yatesمشاهده پروفایل

استاد

• Algorithms
• Responsible AI
• Web Search and Mining
• +۷ مورد دیگر

Ricardo Baeza-Yates serves as Director of Research at the Institute for Experiential AI at Northeastern University's Silicon Valley campus. He also maintains part-time professor positions at Universitat Pompeu Fabra in Barcelona and Universidad de Chile in Santiago. Previously, he was VP of Research at Yahoo Labs (2006-2016) and CTO of NTENT, a semantic search technology company. His academic career spans over three decades with significant contributions to both industry research and academia. Dr. Baeza-Yates earned his Ph.D. in Computer Science from the University of Waterloo, Canada, in 1989. His academic journey includes professorships at Universidad de Chile (1989-2004), ICREA Professor at Universitat Pompeu Fabra (2004-2005), and ongoing part-time appointments at both institutions since 2004 and 2006 respectively. His research spans algorithms, information retrieval, web search and mining, data science, with increasing emphasis on responsible AI and ethical considerations in technology. He is particularly renowned for his work on bias in search systems, algorithmic fairness, and the societal impacts of AI. His expertise uniquely bridges technical aspects of search and data mining with ethical and societal implications, making him a leading voice in the responsible AI movement globally. His recent scholarly output demonstrates a strong focus on bias detection, fairness metrics, responsible technology development, and the societal impacts of algorithms. The work spans technical machine learning and information retrieval while increasingly addressing ethical and social dimensions across diverse application areas from finance to healthcare to social media. Dr. Baeza-Yates has received numerous prestigious awards throughout his distinguished career: 2019 Corresponding Member of the Brazilian Academy of Sciences 2019 Award Salvà i Campillo to the Person of the Year 2018 National Research Award for applied research and technology transfer 2012 ASIS&T Best Information Science Book Award for Modern Information Retrieval 2011 IEEE Fellow for contributions to computer science development 2009 ACM Fellow for contributions to information retrieval algorithms 2002 Corresponding member Chilean Academy of Sciences As an educator and mentor, Dr. Baeza-Yates has advised numerous students throughout his academic career at multiple institutions. His textbook 'Modern Information Retrieval' has become a standard reference in the field, influencing generations of computer scientists. He has secured significant research funding through his leadership roles at Yahoo Labs and academic grants, demonstrating his ability to bridge theoretical research with practical applications. Dr. Baeza-Yates is actively involved with the DATA Lab at Northeastern University's Khoury College of Computer Sciences and previously founded the Web Science and Social Computing Research Group at Universitat Pompeu Fabra. He serves on multiple high-impact advisory boards including the Global AI Ethics Consortium, Global Partnership on AI, and IADB's fAIr LAC Initiative for Latin America and the Caribbean, reflecting his global influence in shaping responsible AI practices.

Cem Ersoyمشاهده پروفایل

استاد

• Computer networks
• Pervasive computing
• Edge computing
• +۱ مورد دیگر

Cem Ersoy is a Professor at Bogazici University 's Department of Computer Engineering, with a career spanning over 30 years. He has held visiting positions at the University of Trento, Italy, and previously served as Department Head at Bogazici University multiple times. Education : Ph.D. in Electrical Engineering (Polytechnic University, 1992), M.S. in Electrical Engineering (Bogazici University, 1986), B.S. in Electrical Engineering (Bogazici University, 1984) His research focuses on computer networks , pervasive computing , edge computing , and wireless networks . Recent work highlights AI integration in air computing, stress monitoring with wearables, and edge network optimization. Articles span applications of multi-agent DRL, probabilistic tracking, and network slicing. Scientific awards : Elected to the Academy of Sciences of Turkey (2022) Bogazici University Research Excellence Awards (Junior 2007, Senior 2014) He has supervised 24 PhD and 58 MS theses. As principal investigator, he led 35 funded research projects by agencies such as the EU, TUBITAK, and Bogazici University Research Fund. His Google Scholar profile shows 11,856 citations, h-index 43, and i10-index 130.

• Virtual Reality
• Augmented Reality
• Human-Computer Interaction
• +۷ مورد دیگر

Professor Yi-Ping Hung is a distinguished faculty member in the Department of Computer Science and Information Engineering at National Taiwan University's College of Electrical Engineering and Computer Science. With a prolific publication record spanning over three decades from 1988 to 2025, Professor Hung leads research at the intersection of virtual reality, human-computer interaction, and computer vision. Their work bridges theoretical innovation with practical applications in health monitoring, biomechanics, and immersive technologies. Professor Hung's research interests focus on creating novel interaction paradigms for virtual and augmented reality environments, with particular emphasis on multisensory feedback systems. Their lab has pioneered approaches for haptic feedback, gaze-based interaction, and physiological response integration in immersive environments. Recent work explores breathing-integrated relaxation techniques, wind simulation for VR, and personalized biofeedback systems that demonstrate the translational impact of their research. Analysis of publication trends reveals a consistent focus on making virtual experiences more natural and embodied, with increasing integration of machine learning techniques in recent years. Professor Hung's team has developed innovative systems for Tai Chi training, archaeological simulation, and mental wellness applications that showcase practical implementations of their research. Professor Hung has mentored numerous graduate students who have become first authors on significant publications, including Ping-Hsuan Han, Yang-Sheng Chen, and Kuan-Wei Tseng. The research group maintains strong collaborations across disciplines and has secured funding for projects spanning VR hardware development, health monitoring systems, and cultural heritage applications. Current research directions include blockchain applications for environmental stewardship, advanced avatar creation techniques using generative models, and sophisticated sensor fusion approaches for precise indoor localization. The lab continues to push boundaries in creating more immersive, natural, and beneficial human-computer interaction experiences.

Xiao Guمشاهده پروفایل

پژوهشگر

• AI for Healthcare
• Biomedical Signal Processing
• Pervasive Healthcare
• +۳ مورد دیگر

Xiao Gu is a Researcher at the Computational Health Informatics Lab, Department of Engineering Science, University of Oxford. He holds a PhD in Computing from Imperial College London (2023), an MRes in Medical Robotics and Image Guided Intervention (2019), and a BEng in Electronic Engineering from Fudan University (2018). His research focuses on integrating pervasive sensing and deep learning for healthcare applications, addressing challenges in generalization and data scarcity. He has been recognized with awards including the BMVC Outstanding Reviewer (2024) and IEEE ICRA Student Travel Grant (2023). Key research interests include AI-driven healthcare solutions, biomedical signal processing, and the development of robust models for real-world medical applications. His work spans datasets like CFP for biomedical sensing and contributions to workshops on wearable intelligence. Xiao Gu has authored over 30 peer-reviewed publications, with recent work focusing on medical imaging, domain adaptation, and vision-language models. He actively contributes to academic activities, including editorial roles and conference reviewing.

Jorma Laaksonenمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۴ مورد دیگر

Jorma Laaksonen is a Senior Lecturer at the Department of Computer Science, Aalto University (School of Science). His research focuses on artificial intelligence, machine learning, computer vision, and multimedia systems, with notable contributions to cross-lingual evaluation, hyperspectral imaging, and audio-visual attention mechanisms. He holds a Doctoral degree in Engineering and Technology from Helsinki University of Technology (1997). Education: Doctoral degree, Engineering and Technology, Helsinki University of Technology (1997) Licentiate degree, Engineering and Technology, Helsinki University of Technology (1991) Master's degree, Engineering and Technology, Helsinki University of Technology (1990) His research interests span AI-driven visual computing, human-computer interaction, and multimedia systems. Key projects include USSEE (audio-visual scene understanding) and ARTISDIG (AI for forest spectral analysis). He has published over 280 papers and supervised multiple theses. Awards include the IEEE Best Paper Award (2017) and Microsoft's Best Practice Award (2016). Recent work includes cross-cultural language modeling, efficient text-to-video retrieval, and open-world video instance segmentation. He leads the Lecturer Laaksonen Jorma group and actively participates in editorial roles and doctoral thesis evaluations.

Mehdi Khakiمشاهده پروفایل

مدرس ارشد

• Data Assimilation
• Geodesy
• Satellite Remote Sensing
• +۴ مورد دیگر

Dr. Mehdi Khaki is a Senior Lecturer in the School of Engineering at the University of Newcastle, Australia. He specializes in geodetic and remote sensing techniques applied to hydrology and environmental science. His research focuses on integrating satellite data products with hydrological models to improve water resource management and climate change studies. Educations: Bachelor of Civil Engineering, University of Tehran, Iran Master of Civil Engineering, University of Tehran, Iran PhD in Civil Engineering, Curtin University, Australia (2018) Research Interests: Dr. Khaki's work emphasizes the application of advanced statistical and machine learning methods to analyze satellite remote sensing data, particularly in areas such as data assimilation, GRACE satellite products, and environmental monitoring. His research spans global scales (e.g., water storage changes in the Middle East, Africa, Australia) and focuses on topics like dam impacts, soil moisture, and climate-driven hydrological changes. Publications: His contributions include over 48 journal articles, 6 conference papers, and a book on Satellite Remote Sensing in Hydrological Data Assimilation . Recent work highlights include studies on dam impacts in Saudi Arabia, tidal analysis in China Seas, and vegetation dynamics downstream of dams. Awards & Grants: 2023 Alexander-von-Humboldt Fellowship 2020 ASIA-PACIFIC Spatial Excellence Awards Total grants: $1,084,320 (e.g., ARC Discovery Projects, Alexander-von-Humboldt Foundation) Teaching & Supervision: Dr. Khaki supervises PhD and postdoctoral researchers in areas like remote sensing applications, hydrological modeling, and geodetic techniques. He actively contributes to teaching and curriculum development in environmental and geospatial engineering.

Muhammad Akbar Rhamdhaniمشاهده پروفایل

استاد

• Extractive Metallurgy
• Metals Recycling
• Low-Carbon Metallurgical Processes
• +۶ مورد دیگر

Professor Muhammad Akbar Rhamdhani is a Professor in Extractive Metallurgy and Metals Recycling at Swinburne University of Technology's School of Engineering. He leads the Fluid and Process Dynamics (FPD) Group, the Net Zero Carbon Materials and Processes Research Platform, and the Energy Transition Metals Research Flagship. His research spans advanced metal refining, low-carbon metallurgy, and extraterrestrial processing, with a focus on hydrogen-based technologies and solar energy applications. He serves as Editor-in-Chief of the Journal of Sustainable Metallurgy and holds a PhD in Materials Science from McMaster University. Education: PhD, Materials Science and Engineering, McMaster University (2005) BEng (Hons), Materials Engineering, Institute Technology Bandung (2000) Graduate Certificate in Learning and Teaching, Swinburne (2010) Research Interests: Akbar's work addresses critical challenges in metallurgical decarbonization, e-waste recycling, and space resource utilization. His projects include hydrogen plasma for low-carbon steelmaking , solar thermal processing of lunar materials , and REE extraction from NdFeB magnets . These align with SDGs 7 (Clean Energy), 9 (Industry Innovation), and 12 (Responsible Consumption). Publication Trends: His recent articles emphasize hydrogen metallurgy for CO2 reduction, ISRU technologies for Mars regolith processing, and slag-based silicon refining . Studies often combine thermodynamic modeling with experimental validation, focusing on resource efficiency and environmental sustainability. Scientific Awards: 2024 LMD/EPD Best Energy Paper (TMS, USA) 2023 JSM Best Paper Award (TMS, USA) 2023 Adrian Normanton Award (IOM3, UK) 2020 Williams Award (IOM3, UK) 2019 Kent D. Peaslee Award (AIST, USA) 2015 MetSoc Award (Metallurgical Society of Canada) Supervision & Grants: He actively supervises PhD students in topics like lunar steel production and hydrogen-based e-waste processing . Current grants include Australian Renewable Energy Agency (8/2024–6/2029) and HILT CRC projects (2023–2028) for hydrogen DRI and solar metallurgy innovations.

Mark Philip Philipsenمشاهده پروفایل

استادیار

• Computer Vision
• Robotics
• Machine Learning
• +۳ مورد دیگر

Mark Philip Philipsen is an Assistant Professor at the Department of Architecture, Design and Media Technology, Aalborg University. He holds a PhD (ErhvervsPhD) from 2017 to 2019. His research focuses on computer vision, robotics, and machine learning applications in environmental science, infrastructure, and industrial automation. He leads projects such as ReDoCO2 (2020–2025) addressing peatland CO2 emissions and Applications of Vision and Robotics in Meat Production (2017–2020), exploring automation in food processing. His work spans diverse areas, including semantic segmentation of underground utilities using 3D point clouds, peat mapping with graph neural networks, and anomaly detection in agricultural vehicles. Philipsen has contributed datasets like OpenTrench3D and LISA Traffic Light Dataset, advancing research in infrastructure analysis and vision systems. His publications emphasize practical applications of AI in environmental monitoring, robotics, and data-driven solutions for industry challenges. Key achievements include developing synthetic thermal human scenarios (ThermalSynth) and semi-supervised learning models for sewer systems. His research often bridges theory and real-world problems, with a focus on sustainability and automation.

Sylvester B. Aboagyeمشاهده پروفایل

استادیار

• Wireless Communications
• Optical Communications
• Optimization Theory
• +۳ مورد دیگر

Sylvester B. Aboagye is an Assistant Professor in the School of Engineering at the University of Guelph, Canada. He holds a Ph.D. in Electrical Engineering from Memorial University (supervised by Profs. Telex M. N. Ngatched and Octavia Dobre) and completed a postdoctoral fellowship at York University’s Next Generation Wireless Networks lab under Prof. Hina Tabassum. His research focuses on wireless and optical communications, optimization theory, machine learning, and emerging technologies like RIS and NOMA. He currently serves as an Associate Editor for the IEEE Open Journal of Communications Society and Editor for IEEE Communications Letters. Research interests include: Terrestrial/non-terrestrial integrated sensing-communication systems Physical layer security mechanisms Convex/non-convex optimization for resource allocation Applications of machine learning in wireless networks Recent publications emphasize energy-efficient spectrum partitioning, multi-band wireless networks, and optical STAR-RIS-aided VLC systems. His work bridges theoretical advancements with practical implementations in next-generation communication systems. Awards include the prestigious Governor General’s Gold Medal (2023), David Dunsiger Award, and Provost’s Postdoctoral Fellowship for Black and Indigenous Scholars. He advises undergraduate researchers like Zohaib Saghir and Riley Brownsdon through NSERC programs, and maintains active collaborations across academia and industry.

Michael Kartmannمشاهده پروفایل

پژوهشگر

• Adaptive Reduced Order Modeling
• PDE-Constrained Optimization
• Optimal Control
• +۳ مورد دیگر

Michael Kartmann is a doctoral student and Research Assistant at the Department of Mathematics and Statistics, University of Konstanz, Germany, since October 2022. His work is funded by the BMBF ElAN project, focusing on efficient local waste heat utilization in low-temperature networks, and he collaborates with the YMMOR group (Young Mathematicians in Model Order Reduction). Research Interests: His work centers on adaptive reduced-order modeling, PDE-constrained optimization, optimal control, and domain decomposition methods for nonlinear preconditioning, with applications in switched low-temperature heat networks and large-scale dynamical systems. He also explores reinforcement learning for optimization problems. Publications: Recent submissions include methods for model predictive control of switched systems and L1-regularized optimal control. His 2024 published work details adaptive trust region reduced basis approaches for parameter identification, with a 2022 master thesis on hierarchical multiobjective optimization. Scientific Contributions: He presented talks at conferences including MORE24, IFIP24, and EUCCO23. His software contributions are available on GitHub. Teaching Roles: He supervises courses such as 'Numerical Mathematics,' 'Proper Orthogonal Decomposition for Linear-Quadratic Optimal Control,' and 'PDE-constrained Optimization' at the University of Konstanz, collaborating with Professors Stefan Volkwein, Behzad Azmi, and others since 2022.

• Offshore Renewable Energy
• Hydrogen Safety
• Risk Assessment
• +۷ مورد دیگر

Ehsan Arzaghi is a researcher at the University of Tasmania, affiliated with the College of Sciences and Engineering, School of Engineering. His work focuses on offshore renewable energy systems, hydrogen safety, corrosion modeling, and risk assessment in marine environments. His research interests include offshore renewable energy, hydrogen safety, risk assessment, marine infrastructure reliability, corrosion modeling, process safety, offshore wind energy, green hydrogen production, computational fluid dynamics, and machine learning applications in safety engineering. These areas are reflected in his extensive publication record in high-impact journals such as Renewable Energy , Ocean Engineering , and International Journal of Hydrogen Energy . The recent articles highlight a strong trend toward integrating risk assessment with renewable energy systems, particularly in offshore and hydrogen-related applications. His work combines computational modeling, machine learning, and multi-criteria decision-making frameworks to address safety and reliability challenges in marine and energy infrastructure. There are no scientific awards mentioned in the provided text. Dr. Arzaghi has collaborated extensively with researchers such as Rouzbeh Abbassi, Vikram Garaniya, and Mohammad Mahdi Abaei on numerous projects related to offshore safety and renewable energy systems. No specific grants are mentioned, but the collaborative nature and scope of the research suggest involvement in funded projects. There is no mention of labs or research teams in the provided text.

• Health Management
• Public Administration
• Healthcare Innovation
• +۴ مورد دیگر

Prof. Kim Putters is a Visiting Professor at the Erasmus School of Health Policy & Management (Health Care Governance department), Erasmus University Rotterdam. He holds a PhD in Public Administration and has extensive experience across academic, governmental, and advisory roles. Previously, he worked at Tilburg University (until 2008) and advised the Dutch Ministry of Health (1997–2003). His research focuses on healthcare governance, hybrid organizational models, and the interplay between market, government, and civil society in healthcare. Key themes include healthcare innovation barriers, policy-practice integration, and intersectoral collaboration between health, housing, mobility, and welfare sectors. Recent publications explore normativity in hospital prevention, digital welfare state transformations, and population health management strategies. His work contributes to UN Sustainable Development Goals related to health and well-being (SDG 3) and sustainable cities (SDG 11). Prof. Putters has received the 2015 Academy of Management Best Article Award. He has supervised 10 academic works and actively engages in policy-oriented research with practical implications for healthcare systems globally.

Chao Lanمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Data Science
• +۴ مورد دیگر

Chao Lan is an Assistant Professor at the School of Computer Science , University of Oklahoma. His research focuses on Machine Learning, particularly in fairness, multi-view learning, kernel methods, and privacy-preserving techniques. He holds a Ph.D. in Computer Science from the University of Kansas, and M.S. and B.S. degrees from Nanjing University of Posts and Telecommunication, China. Key professional roles include Area Chair for ICML'25 and NeurIPS'24, and Senior Program Committee member for PAKDD'25. He serves as an Associate Editor for ACM Transactions on Probabilistic Machine Learning (2024–present) and has received recognition as a Top Reviewer for multiple conferences. Education: Ph.D., Computer Science, University of Kansas M.S., Computer Science, Nanjing University of Posts and Telecommunication, China B.S., Computer Science, Nanjing University of Posts and Telecommunication, China His research emphasizes theoretical and applied machine learning, including fairness-aware algorithms, efficient kernel methods, and distributed systems with privacy guarantees. Recent work explores randomized learning frameworks and debiasing techniques in semi-supervised and multi-view contexts. Lauded for contributions, he has earned awards such as the NSF CRII Award (2019), Distinguished Paper Award at ACSAC 2021, and multiple scholarship recognitions. His publications span top venues like ICML, NeurIPS, KDD, and IJCAI.

Stef De Sabbataمشاهده پروفایل

دانشیار

• Geographical Artificial Intelligence (GeoAI)
• Urban Analytics
• Generative Artificial Intelligence
• +۳ مورد دیگر

Stef De Sabbata is an Associate Professor of Geographical Information Science at the University of Leicester, holding dual affiliations with the School of Geography, Geology and the Environment and the Institute for Digital Culture. She serves as Chair of the Geographic Information Science Research Group at the Royal Geographical Society and previously chaired GISRUK 2018. Her research focuses on GeoAI, urban analytics, and cultural informatics, with notable contributions to graph neural networks in geodemographic classification and urban form analysis. Education includes a PhD in Geography from the University of Zurich (2013), and BSc/MSc in Computer Science from the University of Udine. Prior to Leicester, she held roles at the Oxford Internet Institute (OII) including Researcher (2013-2015), Junior Research Fellow at Wolfson College (2014-2015), and Research Associate (2015-2021). Her work explores spatially-explicit approaches to urban systems and the application of large language models in geographic contexts. Professional roles include membership in the International Cartographic Association's Commission on Location-Based Services and leadership in interdisciplinary initiatives like the GeoNet project examining Sub-Saharan Africa's knowledge economies. No specific awards are explicitly listed in the provided materials.