جست‌وجوی استاد و پژوهشگر

Prasad Enjetiمشاهده پروفایل

استاد

• Power Electronics
• Renewable Energy Systems
• Smart Grid Technologies
• +۳ مورد دیگر

Prasad Enjeti is a Professor and Texas Instruments Jack Kilby Chair in Electrical & Computer Engineering at Texas A&M University, College of Engineering. With expertise in power electronics and renewable energy systems, he has significantly advanced grid-connected technologies, energy storage, and power quality solutions. Ph.D., Electrical Engineering, Concordia University (1988) M.S., Electrical Engineering, I.I.T. Kanpur (1982) B.S., Electrical Engineering, Osmania University (1980) His research focuses on power electronic converters for renewable energy integration, solid-state transformers, high-temperature power systems, grid-edge intelligence, and cybersecurity in distributed energy systems. He has pioneered innovations in AC/DC microgrids, droop control, and advanced filtering technologies. Recent publications emphasize cybersecurity for renewable systems, wide-bandgap semiconductor applications, and AI-driven power electronics optimization. He holds 20+ patents and has supervised 29 Ph.D. and over 50 Master's students, many now in leading academic and industrial positions. IEEE Fellow (2000) R. David Middlebrook Technical Achievement Award (2012) Best Paper Awards at PCIM (2014), IEEE IAS IPCC (2003, 2002, 1998, 1996) NSF Research Initiation Award (1990) Texas A&M Faculty Fellow (1996-97, 2001) He leads the Power Electronics Intelligence at the Network Edge (PINE) research group, with significant contributions to eVTOL energy systems, cryptocurrency mining load analysis, and secure peer-to-peer energy transactions.

Wei-keng Liaoمشاهده پروفایل

استاد پژوهشی

• Parallel and distributed file I/O
• Storage system design
• Data mining algorithms
• +۵ مورد دیگر

Wei-keng Liao is a Research Professor in the Department of Electrical Engineering and Computer Science at Northwestern University's McCormick School of Engineering. His research spans high-performance computing with a focus on parallel and distributed systems. Dr. Liao's research interests include parallel and distributed file I/O and storage system design, data mining algorithm design and their parallelization, data management for large-scale scientific applications, and computational model design for large-scale applications on parallel and distributed environments. He is a key contributor to the Parallel netCDF project, which provides parallel I/O capabilities for scientific applications. His recent work shows strong trends in high-performance computing infrastructure, particularly in optimizing I/O systems for scientific applications, parallel data clustering algorithms, and machine learning acceleration in distributed environments. His publications span computational science, parallel computing, and data-intensive applications across various scientific domains including materials science, astrophysics, and healthcare. Best Paper Award at IEEE International Conference on Cluster Computing (2016) for Parallel DTFE Surface Density Field Reconstruction Dr. Liao has supervised numerous research projects funded by DOE, NSF, NASA, and Argonne National Laboratory, with recent work focusing on data libraries for exascale science, machine learning-driven resilience for extreme-scale systems, and scalable data clustering for scientific computing. He leads research on the Parallel K-means Data Clustering software package and is a principal developer of Parallel netCDF. His work connects multiple research groups through the Center for Ultra-scale Computing and Information Security (CUCIS) at Northwestern University, where he collaborates with scientists across disciplines to develop scalable computing solutions for complex scientific problems.

Farzaneh Bagheriمشاهده پروفایل

استادیار

• Power Electronics
• Control Systems
• Power Systems
• +۳ مورد دیگر

Farzaneh Bagheri is an active Assistant Professor in the Department of Electrical and Electronics Engineering at Antalya Bilim University, Turkey, since 2021, following her Research Assistant role at the same institution in 2019. She holds a Ph.D. from Eastern Mediterranean University (2019), M.Sc. from Azarbaijan Shahid Madani University (2010), and B.Sc. from Shahid Beheshti University (2005), all in Electrical and Electronics Engineering. As an IEEE and Industrial Electronics Society (IES) member, she serves as a regular reviewer for IEEE, Elsevier, and MDPI journals. Her educational background demonstrates a consistent focus on power engineering: Ph.D. in Electrical and Electronics Engineering, Eastern Mediterranean University, Cyprus (2019) M.Sc. in Electrical and Electronics Engineering, Azarbaijan Shahid Madani University, Iran (2010) Bachelor's in Electrical and Electronics Engineering, Shahid Beheshti University, Iran (2005) Research interests center on power electronics control systems with emphasis on power inverter control , microgrid stability , renewable energy management , and laboratory validation . Her work bridges theoretical control design with industrial applications, particularly in grid-tied systems for solar and wind energy conversion under unstable conditions. Publication trends (2021–2025) reveal deep specialization in sliding mode control variants applied to photovoltaic inverters, dynamic voltage restorers, and battery chargers. Key themes include chattering reduction, grid distortion resilience, and multi-level converter topologies for renewable integration, with increasing focus on AI-driven fault diagnosis and digital twin modeling in her 2025 output. Scientific awards are not explicitly listed in the source material. She contributes to European and national research/industrial projects in power systems and power electronics, though specific grant details are omitted. No student advising roles are documented, but her faculty position suggests graduate mentorship responsibilities. Laboratory validation work implies hands-on experimental leadership. Her IEEE/IES membership and journal reviewing activities indicate active participation in professional communities. Experimental research is conducted within power electronics laboratories, with recent projects emphasizing solar plant integration and AI maintenance tools.

• Multifunctional Materials
• Multifunctional Composites
• Graphene-based Composites
• +۱۲ مورد دیگر

Dr. Nisa Salim is a Senior Lecturer at the School of Engineering, Swinburne University of Technology , where she conducts pioneering research in multifunctional composite materials, smart coatings, and sustainable energy technologies. Her work is aligned with national and global priorities in space technology, clean energy, and circular economy. Institution: Swinburne University of Technology School: School of Engineering Academic Rank: Senior Lecturer Email: nsalim@swin.edu.au ORCID: 0000-0001-8069-8039 Dr. Salim’s research focuses on developing smart, engineered materials that can sense, actuate, and store energy. Her key areas include graphene-based composites, structural health monitoring, hydrogen storage, and digitalization of composite manufacturing. She leverages advanced nanomaterials to create next-generation composites for aerospace, marine, robotics, and energy applications. The recent publications highlight a strong trend in multifunctional materials, particularly in energy storage (supercapacitors, hydrogen), smart sensing (graphene sensors, digital twins), and sustainable composites (biomass-derived carbon, recycled polymers). Her work integrates machine learning, IoT, and Industry 4.0 principles into material design and manufacturing processes. Scientific Awards and Recognition Alexander von Humboldt Fellowship Philip Law Award, Royal Society of Victoria Theo Murphy Award, Australian Academy of Science Alfred Deakin Post-Doctoral Fellowship Victoria Fellowship Endeavour Research Fellowship AINSE Gold Medal for PhD Excellence University Ambassador, Royal Australian Chemical Institute Dr. Salim actively supervises PhD and master’s students in cutting-edge projects related to hydrogen storage, lunar dust mitigation, structural batteries, and smart coatings. She has secured multiple competitive grants from ARC, CSIRO, and industry partners, including projects on Scalable Graphene Enabled Smart Composites and Passive Lunar Dust Mitigation . Her editorial roles include serving on the boards of Chemical Engineering Journal , Polymers , and Journal of Composites Science . She leads research in advanced labs focused on composite manufacturing, nanomaterial synthesis, and smart sensor integration, often in collaboration with CSIRO, University of Melbourne, and international institutions. Her vision is to develop living materials that enable digitalization and IoT integration in engineering systems.

Dilum Bandaraمشاهده پروفایل

عضو هیئت علمی

• Distributed Systems
• Blockchain
• Cloud Computing
• +۱۳ مورد دیگر

Dilum Bandara is a Principal Research Scientist at CSIRO's Data61 in Australia and an Adjunct Senior Lecturer at the School of Computer Science and Engineering, Faculty of Engineering, University of New South Wales (UNSW). He has previously served as a Senior Lecturer at the University of Moratuwa, Sri Lanka, and has over two decades of experience in research, teaching, and consultancy in distributed systems, security, and software engineering. His academic qualifications include: PhD in Computer Science, Colorado State University, USA (2012) MS in Computer Science, Colorado State University, USA (2008) BSc Eng. (Hons) in Computer Science and Engineering, University of Moratuwa, Sri Lanka (2004) Dilum's research interests are centered on Distributed Systems (Blockchain, Cloud, P2P), Computer Security , Software Architecture , Data Engineering , Performance Engineering , and the Internet of Things (IoT) . He applies these technologies in multidisciplinary domains such as Supply Chains , Digital Finance , Environmental, Social, and Governance (ESG) , Fleet Management , and Weather Monitoring . His work emphasizes real-world impact through trusted data management in multi-party ecosystems. The analysis of his recent publications reveals a strong focus on blockchain for transparency and security, cloud-native performance engineering, IoT integration with edge and cloud, and data-driven solutions for smart cities and sustainability. His work consistently bridges theoretical innovation with practical deployment, particularly in national and international infrastructure projects. His scientific awards include: Best Paper Award at BPM 2024 Multiple CSIRO internal awards (Customer First, Engineering and Technology, Collaboration) from 2021–2023 Student Paper Award (Merit) at IEEE SOLI 2018 Award of Excellence for Outstanding Research at University of Moratuwa (2015–2018) Dilum has led and contributed to several research grants, particularly during his time at the University of Moratuwa, including projects on smart city integration, real-time data forecasting, and cloud platforms for scientific computing. He has also held leadership roles such as Director of the Engineering Research Unit and co-founder of VaticHub. He is actively involved in professional communities as a Senior Member of IEEE and a Chartered Engineer with IESL. At CSIRO, he serves as a Health and Safety Representative, reflecting his commitment to corporate citizenship. He has advised students and early-career researchers, though specific names are not listed in the provided text. His labs and research teams include the Architecture and Analytics Platforms (AAP) team at CSIRO Data61 and collaborations with academic institutions like UNSW and University of Moratuwa.

Osama A. Mohammedمشاهده پروفایل

استاد

• Power Systems
• Smart Grid
• Energy Cyber Physical Systems
• +۹ مورد دیگر

Dr. Osama A. Mohammed is a Distinguished Professor and Associate Dean of Research at the College of Engineering and Computing, Florida International University (FIU), where he also serves as Director of the Energy Systems Research Laboratory (ESRL) in the Department of Electrical and Computer Engineering. He has been a faculty member since 1983 and is internationally recognized for his pioneering work in power systems, smart grids, and energy cyber-physical systems. His educational background includes: B.S. in Electrical Engineering, Zagazig University, Egypt (1977) M.S. in Electrical Engineering, Virginia Tech (1981) Ph.D. in Electrical Engineering, Virginia Tech (1983) Dr. Mohammed's research is centered on advancing energy systems through innovation in power electronics, electric drives, computational electromagnetics, and smart grid technologies. He emphasizes real-world applications, student involvement, and interdisciplinary collaboration. His work bridges academia and industry, focusing on resilient, secure, and efficient energy infrastructure. His extensive publication record—over 750 papers—demonstrates a strong trend toward intelligent control, cybersecurity in energy systems, real-time simulation, and optimization of hybrid AC/DC microgrids. Many of his recent works integrate AI and machine learning for predictive maintenance, demand response, and digital twin applications in power systems. His scientific awards and recognitions include: Fellow of the National Academy of Inventors (2022) IEEE Fellow (1996) ACES Fellow (2006) IEEE PES Cyril Veinott Award (2010) Multiple Best Paper Awards in IEEE Transactions Top 2% Scientist Worldwide (Stanford, 2020) Dr. Mohammed is a dedicated mentor, having supervised 34 PhD graduates and over 60 master’s students, many of whom now hold prestigious positions in academia and industry. He has secured over $30 million in research funding from DoE, ONR, NSF, and industry. His leadership extends to major multi-university consortia, including the $12.2M DoE SEEDS Center. He has developed key research labs at FIU, such as the Smart Grid Test-Bed and Power Electronics Laboratory, providing unparalleled hands-on experience for students.

Oscar Romero Moralمشاهده پروفایل

استاد

• Data Management
• Data Science
• Data Governance
• +۷ مورد دیگر

Oscar Romero Moral is a Professor at the Polytechnic University of Catalonia (UPC), affiliated with the Department of Services and Information Systems Engineering at the Barcelona School of Informatics (FIB). He leads research in the inSSIDE, inLab FIB, and DTIM groups, focusing on data management, data science, and big data technologies. His work emphasizes knowledge graphs, data governance, and machine learning integration with data systems. Affiliations: UPC, inSSIDE, inLab FIB, DTIM Group Research Interests: Data Management, Data Engineering, Big Data, Knowledge Graphs, Data Governance, Machine Learning Integration He has authored over 276 academic contributions, including peer-reviewed articles on federated healthcare data systems, GPU-accelerated workflows, and graph-driven data integration. His recent work addresses challenges in heterogeneous computing, automated data governance, and scalable data architectures. Romero has served on the program committees of major conferences like VLDB, ICDE, and EDBT, and led competitive research projects in data systems and analytics. He collaborates extensively with industry partners and academic institutions, driving innovations in distributed data management and edge computing.

• Computer Security
• Program Analysis
• Machine Learning
• +۴ مورد دیگر

Mu Zhang is an Assistant Professor at the Kahlert School of Computing, University of Utah. His research focuses on computer security, particularly developing tools using program analysis, machine learning, and data mining to address security issues in Web3, cyber-physical systems, and mobile systems. Previously, he was a Postdoc at Cornell University and a Research Staff Member at NEC Labs America. Education and Background: Postdoc, Cornell University Research Staff Member, NEC Labs America Research Interests: His work emphasizes automated detection and mitigation of security vulnerabilities, including smart contract flaws, industrial control system threats, and malware analysis. He explores innovative solutions like ICSTracker for intrusion backtracking and DEEPVMUNPROTECT for VM-protected Android malware recovery. Recent efforts span blockchain formal verification, Wasm runtime testing, and cross-domain threat inference. Recent Contributions: Notable publications include papers on provenance analysis for industrial control systems (DSN'25), storage collision mitigation in smart contracts (USENIX Sec'25), and automated generation of security-centric smart contract descriptions (ISSTA'23, distinguished paper). Funded projects include NSF grants for AI security education and Cisco Research for smart contract semantics recovery. Awards: His team received the ACM SIGSOFT Distinguished Paper Award (2023) and CCS 2022 Best Paper Honorable Mention. Advising and Grants: Supervises PhD/MSc students like Yu, Wanjing, and Taiji. Active in proposal funding (e.g., Idaho National Lab for industrial control systems, Stellar Foundation for smart contract analysis). Served on TPCs for NDSS, CCS, and ISSTA. Labs/Teams: Leads a research group at University of Utah focusing on secure software systems and automated security tool development.

• Decision support models in the electricity sector
• Optimization techniques
• Electric power system modeling
• +۷ مورد دیگر

Javier García González is a Full Professor in the Department of Electrical Engineering at the School of Engineering, Comillas Pontifical University, Madrid. He has been a key researcher at the Technological Research Institute (IIT) since 1996 and served as Deputy Director of IIT from 2016 to 2022. He holds a Ph.D. in Industrial Engineering from Comillas, awarded the best thesis in its category by the Royal Academy of Doctors. He has held visiting positions at MIT and Lawrence Berkeley National Laboratory. Education: Ph.D. in Industrial Engineering, Comillas Pontifical University (2001) Industrial Engineering (Electricity), ETSEIB, UPC Barcelona (1996) His research focuses on decision support systems for the electricity sector , applying optimization techniques to power system modeling, energy market design, and renewable integration. He has led over 80 research projects for utilities and institutions, with expertise in hydro scheduling, energy storage, and market modeling. His recent work emphasizes microgrid optimization , deep reinforcement learning , and pumped storage hydropower . The trends in his publications reveal a strong focus on optimization under uncertainty , market participation of storage and renewables , and advanced modeling of hybrid AC/DC systems . His work bridges engineering and economics, often involving stochastic programming and real-world applications. Scientific Awards: Best doctoral thesis, Royal Academy of Doctors (2001) Outstanding reviewer, Electric Power Systems Research (2017) He has supervised six doctoral theses and currently mentors a Ph.D. student. He has been principal investigator in numerous national and EU-funded projects, including TWENTIES and OptiREC. He has also delivered training courses at MIT and for industry partners like Endesa. He is actively involved in professional service, having organized the IEEE PowerTech 2021 conference and served on thesis committees at UPC, TU Delft, and Universidad Politécnica de Madrid. He is a long-standing reviewer for top journals such as IEEE Transactions on Power Systems , Applied Energy , and Energy Policy .

• Electrical Power Systems
• Analysis, Planning, Operation and Economics of Electrical Systems
• Renewable Energy Integration
• +۱۲ مورد دیگر

Enrique Lobato Miguélez is a Full Professor at the Higher Technical School of Engineering (ICAI) of Comillas Pontifical University in Madrid, Spain, where he has been a faculty member since June 1, 1998. His research is conducted at the Technological Research Institute (IIT), focusing on electrical power systems, with a strong emphasis on renewable integration, energy storage, and island grid stability. His research interests include the analysis, planning, operation, and economics of electrical systems, with specific expertise in frequency-power control, voltage control, electricity markets, and the sustainability of insular systems. He has made significant contributions to the integration of renewable energy sources and the application of storage elements in power systems. The recent publications highlight a consistent focus on optimization, control, and integration challenges in modern power systems, particularly in islanded and renewable-rich environments. Key themes include unit commitment with frequency constraints, robust design of under-frequency load shedding, battery energy storage in wind farms, and data-driven modeling for stability enhancement. His work often combines theoretical modeling with practical applications for industry partners like Red Eléctrica de España, Naturgy, and Endesa. Scientific Awards: Eolo annual Innovation Award in May 2016 awarded by the Wind Energy Business Association AEE Distinción Honorífica a la mejor Tesis Doctoral en Ingeniería «Voltage control design of wind energy harvesting networks» por Elena Sáiz Professor Lobato has supervised several PhD students, including M. Rajabdorri, I. Saboya, and E. Saiz. He has led numerous research and consulting projects funded by the European Commission, Spanish government agencies, and private companies such as Iberdrola, Endesa, and Viesgo, covering topics like grid integration of renewables, energy storage, and market design. He has also organized major scientific events such as the ICREPQ conferences and conducted training courses for industry professionals. He has conducted research stays at Sophia University in Tokyo and University College Dublin, and his work has resulted in a book on island power systems and over 60 journal publications.

Steven R. Spurgeonمشاهده پروفایل

دانشیار

• AI-driven materials discovery and design
• Interface science
• Electron microscopy
• +۳ مورد دیگر

Steven R. Spurgeon is a Senior Materials Data Scientist at the National Renewable Energy Laboratory (NREL) and holds an Affiliate Associate Professor position in Physics at the University of Washington (2021–2024). His pioneering work focuses on AI-driven materials discovery, electron microscopy, and interface science, with recognition through awards from the Materials Research Society and Microscopy Society of America. Education: PhD in Materials Science and Engineering, Drexel University Bachelor's in Materials Science and Engineering, Carnegie Mellon University Research Focus: Leads teams developing autonomous systems for materials discovery in extreme environments, computer vision for microelectronics analysis, and multimodal AI approaches for accelerated materials design. His work bridges fundamental interface science with applications in energy storage and radiation-hardened technologies. Honors & Activities: Editor for Microscopy and Microanalysis journal Member: American Physical Society, Materials Research Society, Microscopy Society of America Founding member of The Community for Autonomous Scientific Experimentation Leadership: Spearheads NREL's electron microscopy capabilities and industry partnerships transforming AI-guided materials research for sustainable technology solutions.

• Database Systems
• Data Management
• Cloud Computing
• +۵ مورد دیگر

Abdelkader Hameurlain is an active academic researcher specializing in database systems, data management, and cloud computing with a prolific publication record spanning over three decades (1990-2025). He has authored or co-authored more than 170 publications and serves as an editor for the prestigious 'Transactions on Large-Scale Data- and Knowledge-Centered Systems' series published by Springer as part of the Lecture Notes in Computer Science. His research interests focus on database systems, data management, cloud computing, query optimization, data replication, and big data analytics. Hameurlain has made significant contributions to multi-tenant database management systems, SLA-aware query optimization, data replication strategies in cloud environments, and knowledge-based systems. His work bridges theoretical foundations with practical applications in large-scale data processing environments. Analysis of his recent publications (2021-2025) reveals a continued focus on cloud database performance optimization, with particular emphasis on multi-tenant systems, SLA compliance, and cost-effective resource allocation. His research demonstrates a consistent trajectory from traditional database systems toward cloud-native and distributed data management solutions, reflecting the evolving landscape of data-intensive computing. Hameurlain has established long-term collaborations with prominent researchers including Franck Morvan (63 joint publications), Roland R. Wagner (50 joint publications), Josef Küng (40 joint publications), and A Min Tjoa (26 joint publications), indicating his central position in the database research community. As an editor of the Transactions on Large-Scale Data- and Knowledge-Centered Systems series, he has played a significant role in shaping research directions in data management through numerous special issues covering database technologies, big data analytics, cloud computing, and knowledge systems. His editorial work spans multiple volumes from TLS-DCS XIII (2014) through TLS-DCS LVI (2024), demonstrating sustained leadership in the field.

Adrian Spătaruمشاهده پروفایل

مدرس

• Cloud Computing
• Distributed Systems
• Edge Computing
• +۴ مورد دیگر

Adrian Spătaru serves as a Lecturer at the Faculty of Mathematics and Computer Science, West University of Timisoara, Romania, with his office located in room 058. He maintains active academic engagement through direct contact channels including email (adrian.spataru@e-uvt.ro) and phone ((0256) 592 157), reflecting ongoing institutional affiliation and research activities within computer science. His research centers on the integration of edge, cloud, and high-performance computing resources within the cloud continuum framework. Key focus areas include service orchestration, resource management, blockchain applications for decentralized systems, and AI-driven optimization of cloud infrastructures. His work addresses critical challenges in heterogeneous platform integration, fault tolerance, and predictive maintenance across large-scale distributed environments, with notable contributions to container deployment and accelerator-aware application specification. Analysis of his publication trends reveals sustained emphasis on the edge-cloud-HPC continuum since 2018, evolving toward intent-based AI orchestration and heterogeneous hardware integration in recent works. His research bridges theoretical distributed systems concepts with practical applications in environmental monitoring (solar forecasting, freshwater quality assessment) and industrial cloud reliability, demonstrating both academic rigor and real-world impact. No scientific awards are documented in the provided institutional information. Details regarding student supervision, research grants, or laboratory affiliations are not specified in the available materials. Current research directions appear focused on advancing the edge-cloud-HPC continuum through heterogeneous platform integration, with 2025 publications indicating active development in this domain.

• Nuclear Reactor Design
• Advanced Reactors
• Integrated Energy Systems
• +۴ مورد دیگر

Ben Lindley is an Assistant Professor of Nuclear Engineering and Engineering Physics at the University of Wisconsin-Madison since 2020. He leads research in advanced reactor design, reactor physics, and integrated energy systems with a focus on cost reduction, nuclear-solar co-generation, and multiphysics modeling. His work spans computational methods development, safety analysis, and fuel cycle optimization, supported by DOE grants and collaborations with Argonne National Laboratory. Education: PhD in Nuclear Engineering (Cambridge, 2014), MEng & BA in Mechanical Engineering (Cambridge, 2011) Affiliations: Joint faculty appointment at Argonne National Laboratory His research explores nuclear reactor design , flexible operation (load-following, thermal storage), and economic viability of advanced reactors. Recent publications highlight innovations in microreactors, molten salt systems, and fusion-fission hybrids, with methodological advances in reinforcement learning for reactor control and open architecture design . Key article trends include: Advanced reactor cost reduction Nuclear-solar synergy Accident-tolerant fuel analysis Fusion energy commercialization Uncertainty quantification High-fidelity computational modeling Scientific Awards : 2021 ICONE21 Best Paper Award 2011 Babcock Award Runner-Up IET Bill Kerss Scholarship ANS 40 Under 40 Cambridge Rex Moir Prize Ben leads the RETI Lab (reti.ep.wisc.edu), mentoring graduate students through courses like Nuclear Reactor Theory (NE405) and advising on advanced reactor projects with national laboratories.

• Power Systems
• Renewable Energy Integration
• Fault Detection and Analysis
• +۵ مورد دیگر

Mehdi Etezadi-Amoli is a Professor in the Department of Electrical and Biomedical Engineering at the University of Nevada, Reno's College of Engineering. His research focuses on power systems, renewable energy integration, fault detection, and energy storage optimization. His research interests include: Power Systems Stability and Fault Analysis Renewable Energy and Smart Grid Integration Machine Learning Applications in Microgrid Protection Energy Recovery from Pressure Reducing Valves His recent scientific contributions highlight: Hardware-in-the-loop (HIL) platforms for relay performance evaluation Deep belief networks for microgrid fault detection Time-time transform methodologies in protection systems Hydropower recovery systems in water distribution networks Student Advising : He has mentored graduate students including M. Afshar, M. Majidi, and O. A. Gashteroodkhani in research areas like power system fault analysis and energy recovery systems. Key Publications Overview : His work spans three decades, covering topics from harmonic distortion analysis (1980s) to modern AI-driven protection systems for microgrids (2019-2024). Recent articles focus on: Transient stability analysis in multi-contingency scenarios (2024) Resonance effects in interagency transmission lines (2023) AI-enhanced fault detection methodologies (2019-2022) Energy recovery through in-conduit hydropower systems (2018-2020)