Find Academic Supervisors

Gustavo de AlmeidaView profile

Researcher

• Industrial AI
• Process Monitoring
• Data-Centric AI
• +3 more

Gustavo de Almeida is a Researcher at the Department of Energy Technology , School of Energy Systems , Lappeenranta-Lahti University of Technology (LUT). He holds a verified email at LUT and has over 15 years of experience as a professor in Brazil before joining LUT in 2022. Education: M.Sc. in Chemical Engineering, Federal University of Minas Gerais (2003) Ph.D. in Chemical Engineering, University of São Paulo (2006) His research focuses on data analysis applications in the process industry and AI in digital learning , with specific interests in Industrial AI, Process Monitoring, Model Interpretability, and Data-Centric AI. Recent work includes online course development and applications of machine learning in chemical engineering processes. Key publication trends: Spanning 2025 to 2010, his 15 most recent articles emphasize Industrial AI, fault detection, process optimization, and bioenergy technologies. Topics include explainable AI for energy systems, stochastic boiler optimization, and SO2 emission monitoring in industrial processes.

• Distributed computing
• Parallel computing
• Cloud computing
• +6 more

Dana Petcu is a Professor at the Computer Science Department of the Faculty of Mathematics and Computer Science at West University of Timisoara. She serves as Director of both the Institute for Advanced Environmental Research and Institute e-Austria Timisoara. With expertise in distributed and parallel computing, she has published over two hundred papers on Cloud, Grid, Cluster, and HPC computing. She is also the chief editor of the open-access journal Scalable Computing: Practice and Experience (SCPE) and has coordinated multiple European Commission-funded projects. Education: Ms. Degree in Computer Science Ph.D. in Numerical Analysis Dana Petcu's research focuses on distributed and parallel computing systems. Her current interests include Cloud & Grid computing, and HPC & Cluster computing. Previously, she worked on Mathematical software, Numerical methods, and Computer graphics. Her work bridges theoretical foundations with practical implementations, particularly in resource management, scheduling algorithms, and scalable computing architectures. She has developed significant expertise in applying these technologies to scientific computing, data-intensive applications, and multi-cloud environments. Her scholarly output demonstrates consistent focus on cloud and distributed computing evolution. Over the past decade, her research has shifted from foundational grid computing to modern cloud technologies, edge computing, and exascale systems. Key themes include resource management across heterogeneous environments, autonomic systems, security SLAs, and multi-cloud portability. Her work shows increasing interdisciplinary connections, particularly with AI/ML techniques applied to resource optimization and anomaly detection in large-scale systems. Scientific Awards: Maria Sibylla Merian-Award (2005) IBM Faculty Award (2009) MLNR Award "Spiru Haret" (2015) Romanian Academy Award "Gheorghe Cartianu" (2015) Dana Petcu has advised numerous graduate students through various master's programs in Distributed and Parallel Computing. She has secured substantial research funding as coordinator of FP7 projects HOST and SPRERS, and as scientific coordinator of mOSAIC. Her grant portfolio includes multiple European Commission-funded initiatives focused on cloud computing infrastructure, resource management, and multi-cloud environments. She has also contributed to EU Research Activities in Cloud Computing as an editor, demonstrating her leadership in shaping European research agendas in this field. She leads the Computer Science Research Center (CCI) and High Performance Computing Service Center (HPC-UVT) at West University of Timisoara. Her teams develop and maintain significant infrastructure for distributed computing research, including simulation environments like CloudSim and iFogSim. She has established strong connections between academic research and practical applications through Institute e-Austria Timisoara, fostering technology transfer and innovation in cloud computing solutions.

Dimitrije RozgićView profile

Assistant Professor

• Electrical Power Engineering
• Signal Processing
• Power System Analysis
• +3 more

Dimitrije Rozgić is an Assistant Professor at the Department of Electrical Power Engineering within the Faculty of Technical Sciences in Čačak , University of Kragujevac . He has been affiliated with the university since 2008, holding roles from teaching assistant to his current position. His educational background includes a B.Sc. and Ph.D. in Electrical Engineering (Electrical Power Engineering) from the University of Kragujevac. His research focuses on signal processing applications in power engineering, specifically in harmonics and phasor parameter estimation removal of decaying DC components from fault currents electromagnetic transient analysis optimization of power line emissions His publications highlight expertise in Newton-Raphson algorithms , DFT-Prony methods , and symmetrical component analysis . He has contributed to international journals like IET Signal Processing and Electrical Engineering , and conferences such as IEEE EUROCON . He participated in the national project III 42009: Intelligent Energy Networks (2018-2019, 2021-present). His teaching portfolio includes High Voltage Techniques Power System Analysis Electric Power Transmission Power System Substations He is actively involved in Laboratory for Electrical Machines, Electromotor Drives and Automation , and collaborates with institutions like the University of Belgrade’s School of Electrical Engineering.

Samiran BanerjeeView profile

Teaching Professor

• Applied Microeconomic Theory
• Industrial Organization
• Experimental Economics
• +1 more

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 CohanView profile

Professor

• Photochemical modeling
• Atmospheric sensitivity analysis
• Air quality management
• +4 more

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-OsorioView profile

Professor

• Infrastructure Resilience
• Quantum Computing Applications
• Network Reliability
• +7 more

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 AlstoneView profile

Associate Professor

• Energy Systems
• Renewable Energy
• Off-Grid Power Solutions
• +3 more

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 ZhuangView profile

Professor

• Operations Research
• Game Theory
• Hazard Response
• +5 more

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 GhitaView profile

Associate Professor

• Cybersecurity
• Network Security
• IoT Security
• +8 more

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 PioView profile

Associate Professor

• Data Mining
• Bioinformatics
• Social Network Analysis
• +3 more

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 SayogoView profile

Senior Lecturer

• Public Policy
• Information Technology
• Economic Development
• +6 more

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 DeyView profile

Research Fellow

• Machine Learning
• Artificial Intelligence
• Low Carbon Technologies
• +9 more

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 HanView profile

Professor

• Game Theory
• Wireless Networking
• Security
• +4 more

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-VelascoView profile

Associate Professor

• Building Energy Simulation
• Thermal Storage
• Green Roofs
• +3 more

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 AssiView profile

Professor

• Wireless Networks
• Information Security
• Cybersecurity
• +6 more

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.