جست‌وجوی استاد و پژوهشگر

• Computational Fluid Dynamics (CFD)
• Hydraulic Turbines
• Cavitation Modeling
• +۴ مورد دیگر

Jean Decaix is a Researcher at the University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis - Haute Ecole d'Ingénierie ) within the Department of Energy and Environmental Techniques . His work focuses on hydropower systems , computational fluid dynamics (CFD) , and cavitation modeling for hydraulic turbines. Decaix contributes to projects like SCCER-SoE (Supply of Electricity center) and XFlex Hydro , aiming to enhance grid stability through advanced turbine operation. Decaix's research spans Francis and Pelton turbines , with a focus on flow topology , unsteady cavitating flows , and hydraulic short-circuit modes . He develops freely distributable CFD tools for building airflow and turbine efficiency, validated through experimental measurements and numerical simulations . Notable projects : SCCER-SoE (2017-2020): Innovation roadmaps for geothermal and hydropower Solution de transfert d'énergie par pompage-turbinage à petite échelle (2015-2017): Economic model development for small-scale hydropower Decaix's 15 most recent publications (2015-2024) cover topics like cavitation suppression , vortex rope dynamics , Pelton turbine efficiency , and CFD validation for building energy systems. His work emphasizes renewable energy integration and mechanical stress reduction in hydropower plants.

Samiran Banerjeeمشاهده پروفایل

استاد آموزشی

• Applied Microeconomic Theory
• Industrial Organization
• Experimental Economics
• +۱ مورد دیگر

Samiran (Shomu) Banerjee is a Teaching Professor in the Department of Economics at Emory University. He holds a PhD in Economics from the University of Minnesota, an MA from Delhi School of Economics, and a BA in Commerce from Shri Ram College of Commerce, University of Delhi. His research interests focus on Applied Microeconomic Theory , Industrial Organization , Experimental Economics , and Environmental Economics . He has authored the textbook Intermediate Microeconomics: A Tool-Building Approach (2nd ed., Routledge, 2021), which emphasizes constrained optimization and learning-by-doing methodologies. His work bridges theoretical rigor with practical applications in economics education. Notable contributions include studies on net neutrality regulation, healthcare resilience strategies, and optimization in power distribution systems. His interdisciplinary approach spans economics, policy analysis, and computational methods. His book has garnered acclaim for its pedagogical clarity, with praise from MIT’s David Autor and Cornell’s Kaushik Basu. Banerjee’s research also extends to medical imaging technology and oncology case studies, reflecting his diverse academic engagement.

Daniel Cohanمشاهده پروفایل

استاد

• Photochemical modeling
• Atmospheric sensitivity analysis
• Air quality management
• +۴ مورد دیگر

Dr. Daniel Cohan is a Professor of Civil and Environmental Engineering at Rice University. He leads the Cohan Research Group, focusing on air quality modeling, energy systems, and climate policy. His work integrates atmospheric chemistry with policy analysis to address challenges like ozone pollution, renewable energy transitions, and agricultural emissions. Dr. Cohan earned a B.A. in Applied Mathematics from Harvard University and a Ph.D. in Atmospheric Sciences from Georgia Tech. Research interests include photochemical modeling, climate change mitigation, and the health impacts of pollutants. He has authored over 50 peer-reviewed publications and the book Confronting Climate Gridlock , which explores policy solutions for clean energy. Dr. Cohan serves on the U.S. EPA’s Board of Scientific Counselors and has received the NSF CAREER Award. Recent publications highlight wind-solar energy potential in Texas, health impacts of gas flaring, and soil nitrogen emissions modeling. His work emphasizes interdisciplinary approaches to environmental challenges, combining engineering, economics, and policy.

Leonardo Duenas-Osorioمشاهده پروفایل

استاد

• Infrastructure Resilience
• Quantum Computing Applications
• Network Reliability
• +۷ مورد دیگر

Leonardo Duenas-Osorio is a Professor of Civil and Environmental Engineering at Rice University, affiliated with the George R. Brown School of Engineering. He holds a Ph.D. from Georgia Institute of Technology (2005) and advanced degrees from MIT and Colombian universities. His research focuses on computational methods for infrastructure resilience, quantum computing applications in engineering, and risk assessment of interdependent systems. Key areas include network reliability, disaster management, and smart grid resilience. He leads the SISRRA research group, collaborating with statisticians, computer scientists, and engineers to address societal challenges. Recognitions include the NSF CAREER Award (2008), IASSAR Early Achievement Award (2017), and the 2020 Society for Risk Analysis Best Paper Award. His work is funded by NSF, DoD, NIST, and city initiatives. Current projects explore quantum algorithms for infrastructure reliability, socio-technical community resilience, and decentralized network restoration strategies. Education: B.S., Universidad de La Salle, 1996 M.S., Universidad de Los Andes, 1998 Professional Masters, Pontificia Universidad Javeriana, 2000 M.Eng., MIT, 2001 Ph.D., Georgia Tech, 2005 Research interests span infrastructure resilience quantification, quantum-classical optimization, and risk analysis of lifeline systems. He serves as Associate Editor for Natural Hazards Review and Structural Safety , and actively participates in ASCE committees. His group emphasizes interdisciplinary collaboration, addressing urban water security, hurricane risk economics, and topology optimization of critical networks.

Peter Alstoneمشاهده پروفایل

دانشیار

• Energy Systems
• Renewable Energy
• Off-Grid Power Solutions
• +۳ مورد دیگر

Peter Alstone is an Associate Professor at California Polytechnic State University, Humboldt's School of Engineering. His research focuses on distributed electricity technology, demand response systems, off-grid energy solutions in developing regions, and the nexus of information technology with energy systems. He holds a PhD in Energy and Resources from UC Berkeley, an MS in Environmental Systems and Technology from Humboldt State University, and a BS in Chemical Engineering from North Carolina State University. PhD: Energy and Resources (UC Berkeley) MS: Environmental Systems and Technology (Humboldt State University) BS: Chemical Engineering (North Carolina State University) Dr. Alstone's work emphasizes sustainable energy access, grid resilience, and decarbonization strategies. His research bridges technical innovation with policy implications, particularly in underserved regions. He leads studies on demand response mechanisms to support renewable energy integration, wildfire resilience in rural infrastructure, and the environmental impacts of off-grid fossil fuel generators. His recent articles analyze California's demand response potential through 2050, global off-grid energy challenges, and wildfire mitigation technologies for Indigenous communities. He collaborates on grid-interactive microgrids and energy-efficient technologies for developing countries. Alstone's research has contributed to understanding the 'dirty footprint' of fossil-fuel reliant off-grid systems and advancing LED lighting market dynamics in sub-Saharan Africa. His work frequently intersects with environmental justice and climate adaptation. He is affiliated with the Sustainable Energy Research Center (SERC) at Humboldt State University and actively engages in community-oriented energy projects.

Jun Zhuangمشاهده پروفایل

استاد

• Operations Research
• Game Theory
• Hazard Response
• +۵ مورد دیگر

Jun Zhuang is the Associate Dean for Research and Morton C. Frank Professor at the University of Buffalo's School of Engineering and Applied Sciences, Department of Industrial and Systems Engineering. With a PhD in Industrial Engineering from the University of Wisconsin-Madison, his work bridges operations research, game theory, and hazard response, focusing on cybersecurity, disaster management, and social media analysis during crises. Education: PhD, Industrial Engineering, University of Wisconsin-Madison MS, Industrial Engineering, University of Wisconsin-Madison MS, Agricultural Economics, University of Kentucky BE, Industrial Engineering, Southeast University, China His research employs game theory to model attacker-defender dynamics in homeland security, fire risk management, and misinformation control during disasters. Recent work explores machine learning applications for social media monitoring and resource allocation optimization. Jun Zhuang has supervised over 40 graduate/undergraduate researchers, with 8 PhD graduates now as faculty at institutions like Cal Poly, University of Houston, and Stevens Institute. His students' work spans terrorism interdiction, fire safety models, and pandemic-related risk management. Scientific Awards: Fellow, Society for Risk Analysis (2022) SUNY Chancellor's Excellence in Scholarship (2020-21) UB Exceptional Scholar Sustained Achievement (2019) SEAS Senior Researcher of the Year (2018) Koopman Prize, INFORMS Military Applications (2017) As advisor and researcher, he has secured multiple NSF REU awards, collaborated with international scholars from China, India, and Saudi Arabia, and contributed to policy development for disaster response and fire protection strategies.

Bogdan Ghitaمشاهده پروفایل

دانشیار

• Cybersecurity
• Network Security
• IoT Security
• +۸ مورد دیگر

Dr. Bogdan Ghita is an Associate Professor and Associate Dean International in the Faculty of Science and Engineering at the University of Plymouth. His primary affiliation is with the School of Engineering, Computing and Mathematics. He leads network research within the Centre for Security, Communications, and Network Research. His research focuses on cybersecurity, IoT security, machine learning applications in networking, blockchain technology, network function virtualization, and disaster communication systems. He has supervised over 20 PhD students on topics ranging from smart grid optimization to network intrusion detection. Teaching responsibilities include undergraduate courses like Cyber Security and Networks, Ethical Hacking, and Network Monitoring, as well as postgraduate modules in Ethical Hacking. He actively contributes to curriculum development in online education and cybersecurity pedagogy. Key research themes include: Network slicing and NFV in disaster recovery systems Cybersecurity for IoT and industrial systems Machine learning for network anomaly detection Blockchain-based trust management for M2M services Forensic analysis of digital evidence His recent work explores AI-driven personalized education frameworks and quantum-resistant cryptographic schemes. He has published extensively in top-tier conferences/journals with a focus on applying computational methods to solve real-world cybersecurity challenges.

Gianvito Pioمشاهده پروفایل

دانشیار

• Data Mining
• Bioinformatics
• Social Network Analysis
• +۳ مورد دیگر

Gianvito Pio is an Associate Professor at the Department of Computer Science, University of Bari Aldo Moro, Italy. His research spans data mining, bioinformatics, social network analysis, multi-relational data mining, and big data analytics. He holds a PhD in Computer Science from the University of Bari (2015) and has taught courses such as Big Data Management and Analysis and Security in Blockchain Technology . As an expert in heterogeneous network analysis, he develops methods for anomaly detection in cryptocurrency trends, microbiome data interpretation, and legal judgment clustering. He leads the local research unit of the PRIN 2022 project COCOWEARS and contributes to journals like the Machine Learning Journal and Expert Systems with Applications as an associate editor. His recent work includes multi-view learning for risk identification in dynamic networks, spatially-aware models for energy forecasting, and biclustering algorithms for biological data. Collaborations with researchers such as Michelangelo Ceci and Antonio Pellicani highlight his interdisciplinary approach. Gianvito Pio also organizes academic events like the Discovery Science conference and contributes to open-source software tools including HOCCLUS2 and GENERE .

Djoko Sigit Sayogoمشاهده پروفایل

مدرس ارشد

• Public Policy
• Information Technology
• Economic Development
• +۶ مورد دیگر

Djoko Sigit Sayogo is a Senior Lecturer in the Department of Economics and Business at the University of Muhammadiyah at Malang (UMM), Indonesia. He also served as Director at the Center for Economics, Business & Entrepreneurship Development at UMM. His academic career includes a Postdoctoral Associate role at the Center for Technology in Government (CTG) from 2015, where he contributed to the I-Choose project leveraging Semantic Web technologies. Educations: Ph.D., Public Administration, 2013, Rockefeller College, University at Albany M.Acc, Accounting, 2003, The University of Melbourne, Australia B.S., Accounting, 1997, University of Muhammadiyah at Malang Research Interests: Focus on the intersection of information technology, public policy, and economic development. Key areas include open data initiatives, smart disclosure policies, e-financial reporting, and interagency information sharing. His work emphasizes understanding motivations for private sector data sharing and consumer trust in digital platforms like I-Choose. Awards & Recognition: Recipient of Best Management/ Policy Paper (2013) for 'Understanding Smart Data Disclosure Policy Success: The Case of Green Button' Nominated for Best Paper Award (2013) for 'Open Budgets and Open Government: Beyond Disclosure' Leadership & Contributions: Managed undergraduate accounting and computer laboratories at UMM (2006–2008), organized Internet training programs, and actively contributes to digital government conferences. His research explores socio-political determinants of open budgets and cross-boundary information integration challenges. Labs/Teams: Core contributor to the CTG team developing the I-Choose platform, which uses OWL ontology for global information systems. Collaborations include work on semantic web architectures to support ethical consumer choices.

Maitreyee Deyمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Artificial Intelligence
• Low Carbon Technologies
• +۹ مورد دیگر

Dr. Maitreyee Dey serves as a Visiting Fellow in Mechanical Engineering and Design and works as a Post-doctoral research fellow at London South Bank University's Department of Electrical and Electronics Engineering. She concurrently holds the position of Data Mining Lead at Neuville Grid Data Management Limited, where she contributes to significant energy research projects. Her research expertise spans machine learning/artificial intelligence and low carbon technologies, with additional interests in pattern recognition, big data analysis, deep learning, image processing, energy optimization in smart buildings, renewable energy technology, and Computer-aided Diagnosis for smart health applications. Her work directly contributes to UN Sustainable Development Goals related to clean energy and sustainable communities. Analysis of her recent publications reveals a strong research trajectory focusing on two primary domains: power grid analysis using machine learning techniques and microwave-based medical imaging for breast cancer detection. Her work demonstrates sophisticated applications of neural networks and data mining methods to solve complex problems in both energy systems and medical diagnostics. Best Paper Award at the CUE conference, Elsevier (2020) Endorsement by the Royal Academy of Engineering Dr. Dey serves as an Editorial board member for MDPI journals and as an Adhoc reviewer for high-impact publications including IEEE transactions and Nature Scientific Data. She is actively involved in the Access to Innovation (A2i) and Low Carbon London (LCLDN) projects funded by the EU commission through its regional development Fund, working in collaboration between London South Bank University and Neuville Grid Data Management Limited. Her professional affiliations include active membership in IEEE, CIGRE NGN, and the Energy Institute, demonstrating her engagement with key professional organizations in her fields of expertise.

Zhu Hanمشاهده پروفایل

استاد

• Game Theory
• Wireless Networking
• Security
• +۴ مورد دیگر

Dr. Zhu Han is the John and Rebecca Moores Professor at the University of Houston's Cullen College of Engineering, Department of Electrical and Computer Engineering. His research focuses on game theory, wireless networking, security, data analysis, and smart grid applications. He holds doctoral and master's degrees from the University of Maryland and a bachelor's from Tsinghua University. Research interests span: Next-generation wireless systems (6G/7G) AI/ML integration in communications Reconfigurable intelligent surfaces Quantum machine learning applications Secure and efficient network architectures His recent publications demonstrate strong focus on generative AI integration in wireless systems, quantum networking, semantic communications, and security frameworks for future networks. Awards and honors include: IEEE/ACM/AAAS Fellow status IEEE Kiyo Tomiyasu Award (2021) Highly Cited Researcher since 2017 IEEE Distinguished Lecturer (2015-2018) Dr. Han leads research in wireless communications and networking, with extensive industry collaboration. His lab focuses on developing theoretical foundations and practical implementations for next-generation communication systems.

Paulo Cesar Tabares-Velascoمشاهده پروفایل

دانشیار

• Building Energy Simulation
• Thermal Storage
• Green Roofs
• +۳ مورد دیگر

Dr. Paulo Cesar Tabares-Velasco is an Associate Professor in the Mechanical Engineering Department at the Colorado School of Mines. His research focuses on building energy simulation, thermal storage, green roofs, and smart grid integration. Previously, he worked at the National Renewable Energy Laboratory (NREL), developing tools like BEopt and advancing phase change material (PCM) modeling in EnergyPlus. He holds a PhD from Penn State University, an MSc from Colorado State University, and a BSc from the Monterrey Institute of Technology. His work has earned multiple awards, including the 2009 Crosby Field Award and the 2011 Green Roof Research Award. He leads the Advanced Multiscale Building Energy Research (AMBER) Group and contributes to the Sustainable Energy Undergraduate Program. Key research areas include cross-laminated timber (CLT) thermal performance, district energy systems, and energy storage optimization. Publications highlight innovations in PCM validation, CLT moisture monitoring, and building-grid interaction. He collaborates with national labs and industry partners to advance energy-efficient construction and grid resilience.

Chadi Assiمشاهده پروفایل

استاد

• Wireless Networks
• Information Security
• Cybersecurity
• +۶ مورد دیگر

Chadi Assi is a Professor and Tier II Concordia Research Chair at the Concordia Institute for Information Systems Engineering, Concordia University. His research focuses on wireless networks, information security, and smart grid systems, with particular emphasis on reconfigurable intelligent surfaces (RIS), integrated sensing and communication (ISAC), cybersecurity for electric vehicles (EVs), and machine learning-driven network optimization. He has pioneered work on mitigating cyber-physical attacks in power grids and IoT ecosystems, while advancing cooperative communication protocols like RSMA and NOMA. His technical contributions span theoretical frameworks for energy efficiency maximization in hybrid SDMA/NOMA schemes, low-complexity RIS element selection algorithms, and adversarial PINN models for grid dynamics. He also investigates vulnerabilities in EV charging infrastructure and O-RAN synchronization protocols, proposing robust detection mechanisms like PEACE and Grid Mirror. His interdisciplinary work bridges communications, power systems, and AI, addressing challenges in 5G/6G security and resilient IoT provisioning. Key Research Areas: RIS-enabled ISAC networks, EV cybersecurity, meta-learning in communications, IoT malware analysis Current Projects: Grid resilience against load-altering attacks, Movable antenna optimization, federated learning for AGC systems Recent publications (2024-2025) emphasize deep reinforcement learning frameworks for RIS-aided networks, cooperative RSMA performance enhancement, and defense mechanisms against dynamic trigger-based attacks. He has also developed novel datasets for advanced persistent threats and frameworks like ChargePrint for EV charging security analysis. His work is published in top venues including IEEE Transactions on Smart Grid, IEEE JSAC, and IEEE ICC, reflecting contributions to both theoretical advancements and practical system implementations.

Marta Ariasمشاهده پروفایل

دانشیار

• Machine Learning
• Data Mining
• Design and Analysis of Algorithms
• +۳ مورد دیگر

Marta Arias is an Associate Professor in the Computer Science Department at Universitat Politècnica de Catalunya (UPC), Barcelona, and a member of the LARCA research group. She has held academic positions since 2007, including roles at Columbia University and the University of Edinburgh. Her research focuses on Machine Learning, Data Mining, Algorithm Design, and Logic in Computer Science. She teaches advanced courses in Machine Learning, Information Retrieval, and Complex Networks at undergraduate and master's levels, including the Erasmus Mundus program in Data Mining and Knowledge Management. Educations: PhD in Computer Science from Tufts University (2000-2004), Postgraduate Studies at University of Edinburgh (1999-2000), B.Sc. in Computer Science from UPC (1992-1997). Professional experience includes software engineering and research roles in New York and Barcelona. Research highlights include developing algorithms for real-time ranking systems, Twitter-based financial forecasting, and causal network analysis. Notable contributions include the 'Best Paper Award' at AIPESW@ECAI 2020 and a 3rd place award in football performance research. Her work spans theoretical foundations (e.g., Horn clause learning) and applied domains like cybersecurity, healthcare analytics, and energy systems. Teaching responsibilities include labs and lectures on Machine Learning, Information Retrieval, and Programming, with active involvement in curriculum design and pedagogical innovation. Ongoing projects include enterprise risk analysis, synthetic data generation, and network modeling.

Pia Manzمشاهده پروفایل

پژوهشگر

• Energy Systems Modelling
• District Heating
• Renewable Energy
• +۴ مورد دیگر

Pia Manz is a Researcher at the Department of Energy Technologies and Energy Systems at Fraunhofer ISI since 2017, focusing on energy system transformation pathways with an emphasis on district heating, excess heat utilization, and GIS-based modeling. She holds a PhD from Utrecht University (2024) on 'Towards climate-neutral district heating in the EU,' awarded for her dissertation exploring decarbonization strategies for heating systems. Her educational background includes a Bachelor's in Renewable Energy Technology and Systems Engineering from Nordhausen University of Applied Sciences, complemented by international experience at the University of Dundee, Scotland. During her studies, she gained hands-on research experience as a research assistant at Nordhausen's Institute for Renewable Energy Technology. Manz's research bridges technical analysis and policy design, addressing challenges such as cost-effective integration of renewable and excess heat into district heating systems, hydrogen infrastructure needs in decarbonized energy systems, and spatial analysis of heat potentials. Her work frequently employs geographic information systems (GIS) to model demand sectors and assess policy instruments. Her publication trends show a consistent focus on EU-wide decarbonization pathways, with contributions to studies like 'Achieving climate neutrality in district heating' (2025) and 'Hydrogen Infrastructure in the Future CO2-Neutral European Energy System' (2025). She collaborates extensively with institutions like Utrecht University and the German state of Baden-Württemberg on energy transition scenarios and congestion management strategies. Key contributions include developing the FORECAST model for bottom-up industry sector analysis and pioneering georeferenced databases for industrial excess heat potentials. Her interdisciplinary approach integrates technical, economic, and policy dimensions to advance climate-neutral energy systems.