جست‌وجوی استاد و پژوهشگر

Tao Hongمشاهده پروفایل

استاد

• Energy Forecasting
• Power Systems Operations
• Renewable Integration
• +۷ مورد دیگر

Dr. Tao Hong is the Duke Energy Distinguished Professor and NCEMC Faculty Fellow at the Department of Systems Engineering and Engineering Management, University of North Carolina at Charlotte. He directs the Big Data Energy Analytics Laboratory (BigDEAL) and has been a Founding Chair of the IEEE Working Group on Energy Forecasting (2011-2019). Ph.D., Electrical Engineering & Operations Research (2010), NC State University M.S., Operations Research & Industrial Engineering (2008), NC State University B.Eng., Automation (2005), Tsinghua University His research focuses on Energy Forecasting with applications in power systems operations, renewable integration, risk management, and cross-sector forecasting for healthcare, transportation, and sports. He has led major Delivery point level load analysis (2017-present) Short-term probabilistic forecasting (2016) Demand response modeling using smart meter data (2014-2015) Dr. Hong's scientific contributions include 9+ journal articles on energy forecasting methodologies and 3 major forecasting competitions (GEFCom2012-2017, BigDEAL Challenge 2022). His work has been cited in leading journals like International Journal of Forecasting and IEEE Transactions on Smart Grid . Charlotte Business Journal Energy Education Leader of the Year (2017) IEEE PES PSPI Technical Committee Prize Paper Award (2016) As a dedicated educator , Dr. Hong has advised multiple PhD and Master's students including Shreyashi Shukla (2023), Yike Li (2022), and Jordan McCorey (2021). He teaches specialized courses in energy systems planning and computational intelligence.

• Transportation Systems
• Smart Cities
• Traffic Simulation
• +۳ مورد دیگر

Maria Paz Linares Herreros is a Lecturer at the Universitat Politècnica de Catalunya (UPC), affiliated with the School of Mathematics and Statistics (FME) and the Department of Statistics and Operations Research. She is a member of the IMP (Information Modeling and Processing) research group and collaborates with inLab FIB on intelligent transportation systems. Research interests: Transportation systems, smart cities, traffic simulation, data-driven modeling, environmental impact assessment Specializes in applying machine learning and simulation to urban mobility challenges Her recent publications focus on: Parking availability prediction using deep learning Traffic emission modeling linked to urban policies Dynamic ride-sharing system optimization Integration of IoT data in transportation planning Scientific recognition: Recipient of the IV International Award on Transport Infrastructure Management Research (2018) Active contributor to projects like CitScale and Virtual Mobility Lab Collaborator in European initiatives like KIC Urban Mobility

• Electrical Engineering
• Smart Grids
• Electric Power Systems Regulation
• +۷ مورد دیگر

Dr. Miguel Ángel Sánchez Fornié is a Collaborating Researcher at the Instituto de Investigación Tecnológica (IIT), affiliated with the School of Engineering at Universidad Pontificia Comillas (ICAI). He has been actively involved with IIT since 1980, contributing to European research projects and teaching Smart Grids in Master's programs since 2002. His work bridges industry leadership and academic research, particularly in the digitalization and modernization of electricity systems. Electromechanical Engineering, ICAI (1974) Diploma in Nuclear Safety, MIT, Boston (1977) Postgraduate coursework in Electricity Sector Regulation, 2008 His research focuses on smart grids, electricity system regulation, power system planning and operation, asset management, telecommunications for power systems, cybersecurity, and the application of big data and artificial intelligence in energy systems . He has led and contributed to major European projects such as H2020 and Horizon Europe, focusing on grid resilience, digitalization, and workforce skills development. The recent publications reflect a strong trend toward the digital transformation of electricity distribution networks , with emphasis on metrics, investment analysis, and the integration of distributed energy resources. His work spans from foundational reliability modeling in the 1980s to contemporary policy and technical frameworks for smart grids, showing a lifelong commitment to evolving energy infrastructure. Dr. Sánchez Fornié has been involved in several funded research projects and educational initiatives, including EDDIE, CoordiNet, and Digital Twin for Europe. He has also contributed to workforce development through sectoral skills alliances in the energy domain. He holds leadership roles in external organizations such as FUTURED and the European Technology and Innovation Platform on Smart Energy Networks (ETIP SNET), where he serves as Honorary Co-Chair of WG4. He has organized and participated in numerous scientific conferences and seminars, particularly on digitalization and education in the energy sector. Member, Education for the Digitalisation of the Energy System (EDDIE ASBL), Brussels (2024–Present) Board Member, FUTURED, Zaragoza (2017–Present) Co-Chair (Honorary), WG4, ETIP SNET, Brussels (2017–Present)

• Sustainable Transport
• Urban Mobility
• Logistics and Supply Chains
• +۸ مورد دیگر

Mengqiu Cao is a Lecturer in Urban Systems Predictive Analytics and Machine Learning at the University College London (UCL) within the Bartlett School of Environment, Energy and Resources . He integrates academia and industry expertise to advance interdisciplinary research at the intersection of transport analysis and urban studies. Research Focus : Sustainable transport, urban mobility, logistics, social equity, and low carbon transitions. Teaching : Coordinates modules on climate sciences, data-driven consumer behavior analysis, and transport policy. Awards : Holds fellowships with the Royal Geographical Society, Royal Statistical Society, and Royal Society of Arts. Publications : Recent works examine green space impacts on mobility, equitable EV charging access, dockless bike-sharing patterns, and 15-minute city frameworks.

• Database Systems
• Query Optimization
• Index Tuning
• +۷ مورد دیگر

Surajit Chaudhuri is a Researcher at Microsoft , with a career spanning decades in database systems and data management . He has received the prestigious SIGMOD Edgar F. Codd Innovations Award (2011) for his contributions to query optimization , index tuning , and data lakes . Research Interests : His work focuses on database tuning , approximate query processing , fuzzy similarity joins , automated data transformations , and machine learning integration for scalable data systems. Recent Publications : In 2025, his research includes Auto-Test for unsupervised error detection in tables, Esc for budget-aware index tuning, and MMTU for multi-task table understanding benchmarks. Earlier works in 2024–2023 address spreadsheet formula recommendation , low-overhead index filtering , and time-series pattern recognition . Scientific Impact : He has co-authored influential papers in SIGMOD , VLDB , and IEEE Transactions , shaping practices in cloud databases , query optimization , and self-service BI . His collaborations span institutions like Microsoft, MIT, and ETH Zurich.

• Database Systems
• Big Data Analytics
• Cloud Database Systems
• +۵ مورد دیگر

Michael J. Franklin is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley's College of Engineering. He has a prolific publication record spanning over three decades with more than 300 publications in top-tier database and systems conferences and journals, demonstrating his continued active research and leadership in the field. Franklin's research spans multiple areas within data management, with a recent focus on time-series analysis, AI-integrated database systems, cloud-native databases, and data quality. His work has evolved from traditional database systems to address modern challenges in big data, machine learning integration, and distributed systems. He has made significant contributions to data cleaning, crowdsourced data management, and stream processing systems. Analysis of his recent publications (2022-2025) reveals a strong trend toward integrating AI/ML capabilities with database systems, particularly in time-series anomaly detection, LLM applications for data management, and resource-adaptive query processing for cloud environments. His work increasingly focuses on practical systems that address real-world data challenges, often involving collaborations with industry partners and other leading academic researchers. Throughout his career, Franklin has mentored numerous PhD students who have become prominent researchers in their own right, including Sanjay Krishnan, Aaron Elmore, and Jiannan Wang. His collaborative research has frequently involved significant funding from NSF and industry partnerships, enabling large-scale systems research with real-world impact. Franklin leads research efforts that bridge theoretical database principles with practical system implementations. His work on projects like Data Station demonstrates his commitment to building trustworthy infrastructure for data sharing and analysis, addressing critical challenges in data privacy, security, and usability in collaborative environments.

Mark Williamsمشاهده پروفایل

مدرس ارشد

• Risk Management
• Fintech
• Blockchain Technology
• +۵ مورد دیگر

Mark Williams is a Senior Lecturer in Finance at Boston University's Questrom School of Business, with over three decades of experience in risk management. Since 2002, he has taught graduate and undergraduate courses while maintaining an active role in financial analysis, media commentary, and policy advisory. Education: MBA (Boston University School of Business, 1993), BS (University of Delaware, 1985) Williams specializes in Risk Management across banks, hedge funds, and Fintech sectors, with particular focus on Cryptocurrency and Blockchain Technology . His recent research explores Immigration and Outmigration patterns in Massachusetts and economic implications of technological disruption in sports. His publications span 15 recent works including analyses of crypto regulations, student debt impacts, and sports economics. These works demonstrate his interdisciplinary approach blending finance, public policy, and social sciences. Scientific Awards Beckwith Teaching Award (2008, 2021) James E. Freeman Lecturer Chair (2018) Williams frequently advises policymakers, having served on President Biden’s Economic Subcommittee (2020), provided congressional testimony (2014), and consulted with The World Bank. He currently presides over the Boston Economic Club (since 2022) and serves on Lesley University’s Board of Trustees (since 2018).

Tassilo Pellegriniمشاهده پروفایل

استاد

• Semantic Web
• Linked Data
• Digital Business
• +۴ مورد دیگر

FH-Prof. Mag. Dr. Tassilo Pellegrini is a Professor at the University of Applied Sciences St. Pölten , leading the Institute for Innovation Systems within the Department of Digital Business and Innovation . His work bridges semantic technologies with digital business strategies. Education : Business Economics, Communication Studies, Political Science Research Focus : Semantic Web, Linked Data, Digital Media Economics, Network Neutrality, Data Licensing His publications highlight trends in Semantic Metadata for news production, Linked Data Integration , and Cloud-based Business Models under network neutrality constraints. Recent work explores thesaurus-driven knowledge organization and the economic implications of Big Data. Scientific Awards : Best Paper Award at I-Semantics 2012 Key Projects : ECO-TCO (Digital Data for Sustainability), Corporate Semantic Web initiatives Contact: tassilo.pellegrini@fhstp.ac.at

• Business Analytics
• Information Technology
• Artificial Intelligence
• +۵ مورد دیگر

Dr Saif Dewan is a Senior Lecturer at the School of Law & Business , University of Notre Dame Australia. He holds a PhD in Business IT from the Australian National University and has taught Quantitative Methods for Business and Business Information Technology courses. Dr Dewan maintains honorary research affiliations with the University of New South Wales and the University of Twente, Netherlands. PhD in Business IT from Australian National University His research spans IT artefact design , business analytics , digital innovation , cybersecurity management , and AI . His work focuses on integrating technology with organizational effectiveness and consumer behavior. While the recent publications highlight his expertise in analytics knowledge management , neuro-IS studies , and mobile banking research , his broader contributions include conceptual frameworks for digital entrepreneurship, context-aware business processes, and information transparency in e-commerce. Dr Dewan actively collaborates with international institutions and has consulted for the United Nations, Samsung, and governments on IT and business analytics. He has supervised numerous PhD and Honours students and served on boards of technology startups, NGOs, and private schools globally.

• Analysis and transformation of programs
• Software Security
• Parallel and distributed computing technologies

Harutyun Ishkhanovich Avetisyan is a Professor and Head of the Basic Department "System Programming" at the Faculty of Computer Science of the National Research University Higher School of Economics (HSE). He began his tenure at HSE in 2017 and brings 30 years of scientific and teaching experience to his role. Additionally, he serves as the Director of the Institute for System Programming of the Russian Academy of Sciences (ISP RAS), a position he has held since 2015. Avetisyan holds numerous prestigious academic distinctions, including being elected as an Academician of the Russian Academy of Sciences in 2019 and as a Corresponding Member in 2016. He earned his Doctor of Physical and Mathematical Sciences degree in 2012 and was awarded the academic title of Associate Professor in 2009. His educational background includes a specialty in "Applied Mathematics" from Yerevan State University (1993). His research focuses on three main areas: analysis and transformation of programs, software security, and parallel and distributed computing technologies. These interests are reflected in his extensive publication record and leadership in major research initiatives. His work bridges theoretical computer science with practical applications in cloud computing, secure data storage, and high-performance computing systems. Avetisyan's scholarly contributions demonstrate a consistent focus on system programming challenges, particularly in the areas of code analysis, optimization, and security. His recent publications indicate a growing interest in cloud computing paradigms, smart city infrastructure, and energy-efficient computing solutions. His research has significant implications for both academic theory and industrial applications in software development. Among his notable recognitions, Avetisyan was awarded the medal of the Order "For Merit to the Fatherland" 2nd degree in 2021 for his significant contributions to science and dedicated service. He also serves on the editorial boards of several prestigious journals including "Programming" (since 2015) and "Proceedings of the Institute for System Programming of the RAS" (since 2010). Throughout his career, Avetisyan has led and participated in numerous research grants funded by the Ministry of Education and the Russian Foundation for Basic Research. His professional trajectory shows steady progression from postgraduate studies (1997-2000) to research fellow (2000-2002), deputy director of ISP RAS (2002-2015), and ultimately director of the institute (2015-present). At HSE, Avetisyan teaches courses in parallel programming and mentor seminars for master's students in Software Engineering. His teaching philosophy emphasizes the integration of cutting-edge research with practical software development skills, preparing students for careers at the forefront of computer science.

• Sustainable Manufacturing
• Industry 4.0
• Industry 5.0
• +۵ مورد دیگر

Morteza Ghobakhloo is a Senior Lecturer and Researcher at Uppsala University , affiliated with the Department of Civil Engineering and Industrial Engineering (Industrial Engineering) and the Institute for Research on Conflicts of Goals in Sustainable Social Transition . His email is morteza.ghobakhloo@angstrom.uu.se . He focuses on digital transformation, sustainability, and human-centric technologies. Research Interests: Morteza’s work bridges Industry 4.0/5.0 , Sustainable Manufacturing , and Generative AI applications. His studies explore blockchain, big data analytics, and smart technologies in supply chain resilience, energy efficiency, and organizational innovation. Article Trends: Recent publications highlight Industry 5.0’s role in sustainable supply chains, AI-driven healthcare optimization, and blockchain for socioenvironmental solutions. He employs hybrid methodologies like PLS-fsQCA, ANN, and simulation modeling across sectors including energy, healthcare, and tourism.

Anna Monrealeمشاهده پروفایل

دانشیار

• Privacy-Preserving Data Mining
• Big Data Analytics
• Social Network Analysis
• +۷ مورد دیگر

Anna Monreale is an Associate Professor in the Department of Computer Science at the University of Pisa and a key member of the Knowledge Discovery and Data Mining Laboratory (KDD-Lab), a joint research group with the Information Science and Technology Institute of the National Research Council (ISTI-CNR) in Pisa. Her academic career is rooted in the University of Pisa, where she completed her Bachelor's, Master's, and Ph.D. in Computer Science. Her research focuses on privacy-preserving data analytics, with core interests in big data analytics, social network analysis, spatio-temporal mining, and explainable AI. She is particularly known for her work on privacy-by-design in data mining and evaluating privacy risks in analytical processes. Her research bridges technical innovation with ethical and legal considerations in data science. Her recent publications reveal a strong trend toward explainable AI, privacy in federated learning, and risk assessment in mobility and health data. She actively contributes to developing methods for explaining black-box models, assessing privacy exposure, and balancing privacy, utility, and fairness in AI systems. Privacy by Design Ambassador (2014) ISTI-CNR Young++ Researcher Award (2014) Monreale has advised and co-chaired several international workshops, including PriSMO, PinSoDa, and MoKMaSD, and serves on editorial boards such as Transactions on Data Privacy. She teaches advanced data mining, big data ethics, and database systems across multiple graduate and undergraduate programs. She is involved in major EU projects like SoBigData, XAI, TAILOR, and HumMingBird, reflecting her leadership in data science and AI ethics. She is affiliated with the KDD-Lab, a prominent research group focused on knowledge discovery, social mining, and big data analytics, contributing to both theoretical advances and real-world applications in privacy-aware data science.

Qiang Zhuمشاهده پروفایل

استاد

• Data Science
• Data Management
• Machine Learning
• +۳ مورد دیگر

Qiang Zhu is a Professor in the Department of Computer and Information Science at the University of Michigan-Dearborn, holding the William E. Stirton Professorship (2017–2024). He founded the Data Science/Management Research Laboratory and is affiliated with the Michigan Institute for Data Science (MIDAS). His research spans data science, data management, and machine learning. Ph.D., University of Waterloo M.S., McMaster University M.Eng., Southeast University B.S., Southeast University Research focuses on advanced data indexing, query optimization, and AI-driven data management, with applications in genomics, network systems, and education. His work integrates machine learning with database systems for scalable solutions. Recent publications include topics in federated learning fairness, digital twin middleware, project-based CS education, and genome data indexing. Scientific contributions recognized through awards like the Wilkes Award (2008), ACM Distinguished Scientist (2013), and Springer Nature Editor of Distinction (2025). 2013–2018: Department Chair NSF, IBM, and Ford grants Over 250 conference committee roles He directs the Data Science/Management Research Lab, focusing on collaborative projects in genome analytics and smart computing infrastructures.

Jia Xueمشاهده پروفایل

دانشیار

• Intimate Partner Violence
• Sexual Assault
• AI Ethics
• +۶ مورد دیگر

Jia Xue is an Associate Professor at the Factor-Inwentash Faculty of Social Work, University of Toronto, with a joint appointment in the Faculty of Information. She joined U of T in 2018 as an Assistant Professor and was promoted in 2025. Her research focuses on computational approaches to social justice issues, including intimate partner violence, rape myth culture, and AI ethics. She holds a Ph.D. from the University of Pennsylvania, a law degree from Tsinghua University, and postdoctoral training at Harvard University. Her research lab, the Artificial Intelligence for Justice (AIJ) Lab, develops AI tools to study social ills like image-based sexual abuse and school bullying. Key projects include AI-powered chatbots for sexual violence victims and analyzing biases in algorithmic systems. Funded by grants from Connaught, SSHRC, and CIHR, her work bridges social work, computer science, and policy analysis. Jia has authored over 50 peer-reviewed articles in journals like Journal of Interpersonal Violence and Child Abuse & Neglect . Awards include the Ontario Early Researcher Award (2025) and Deborah K. Padgett Early Career Achievement Award (2025). She leads initiatives at the Schwartz Reisman Institute for Technology and Society, focusing on tech’s societal impacts. Teaching emphasizes ethical big data use in social justice contexts. Recent work includes pandemic-related social media analysis and developing interventions for marginalized populations. Her interdisciplinary approach combines machine learning, policy analysis, and qualitative research to address systemic inequities.

• Data Integration
• Data Quality
• Recommender Systems
• +۵ مورد دیگر

Assoc Prof Henry Nguyen is an Associate Professor at Griffith University's School of Information and Communication Technology, with expertise in data integration, data quality, recommender systems, and big data visualization. He directs the Responsible Big Data Lab and has secured over $3.5M in funding since 2015 from ARC, DFAT, and industry partners. PhD & Master's from EPFL, Switzerland ARC DECRA Award (2020) His research focuses on privacy-preserving AI for social data , IoT , and satellite analytics , with over 200 publications in top venues like SIGMOD, KDD, and IEEE TKDE. Recent work spans federated learning , graph neural networks , and secure AI systems . Article trends highlight 2024-2025 publications on: Federated recommendation security On-device AI optimization Privacy-preserving explainable AI Graph condensation techniques LLM-powered risk analysis Cloud-edge collaboration Scientific contributions include ARC DECRA Award 2020 Multiple senior PC roles in A* conferences Citations in International AI Safety Report 2025 Henry Nguyen supervises 12 active PhD/MSc students and has directed 8 completed doctoral theses . His funded projects include collaborations with Ubitech , KARI , and CSIRO , focusing on Australia-Korea partnerships and responsible AI development.