Find Academic Supervisors

• Coal Chemistry
• Carbon Nanomaterials
• Graphene
• +5 more

Dr. Binoy Kumar Saikia is a Scientist and Assistant Professor at the Coal Chemistry Division of CSIR-North East Institute of Science & Technology (CSIR-NEIST) in Jorhat, Assam, India. A Fellow of the Institution of Chemists (India), he has been with CSIR-NEIST since 2011 and is also affiliated with the Academy of Scientific and Innovative Research (AcSIR). With a Ph.D. in Coal Chemistry from Dibrugarh University (2008), his research bridges traditional coal science with cutting-edge nanomaterials development. Dr. Saikia's research program focuses on transforming coal and coal waste materials into high-value carbon nanomaterials including graphene, carbon quantum dots, and nanodiamonds. His work spans multiple applications in energy storage (particularly supercapacitors and hybrid capacitors), environmental remediation, and sensing technologies. Recent publications demonstrate his innovative approach to upcycling coal waste, atmospheric particulate matter, and other byproducts into functional materials with commercial potential. His publication record is substantial with approximately 107 works, showing increasing productivity in recent years with numerous high-impact publications in journals like ACS Omega, Energy & Fuels, and Environmental Science: Nano. His research demonstrates a clear trajectory from fundamental coal chemistry toward applied materials science with practical environmental and energy applications. Young Scientist Award from International Union for Crystallography (2009) Rajiv Gandhi Excellence Award (2012) As an active member of the scientific community, Dr. Saikia serves on the editorial board of the International Journal of Geology, Earth and Environmental Sciences and has completed over 40 peer reviews for major scientific journals, particularly in the energy and environmental fields. His research program represents an innovative approach to sustainable resource utilization, transforming traditionally problematic coal waste streams into valuable advanced materials.

Gang MeiView profile

Associate Professor

• Numerical Simulation and Computational Modeling
• GPU Computing
• Machine Learning
• +5 more

Dr. Gang Mei is an Associate Professor in Scientific Computing within the School of Engineering and Technology at China University of Geosciences (Beijing), where he has held academic positions since 2014. His career progression includes Postdoctoral Researcher (2014-2016), Lecturer (Oct-Dec 2016), and current Associate Professor (since Jan 2017). His research bridges computational science and engineering applications with significant editorial contributions to computer science literature. Education: Ph.D. in Computer Science, University of Freiburg, Germany (2014) Research Interests: Dr. Mei specializes in Numerical Simulation and Computational Modeling, GPU Computing, Machine Learning, and Data Mining, with strong applications in Network Science and Spatial Information Systems. His work integrates Distributed and Parallel Computing techniques for large-scale scientific simulations, particularly in geospatial modeling and network analysis. The research demonstrates consistent focus on computational efficiency through hardware acceleration and algorithmic optimization across diverse domains including satellite imagery processing, financial event detection, and medical image classification. Publication Trends: His editorial portfolio reveals strong interdisciplinary patterns connecting computer science fundamentals with domain-specific applications. Recent works emphasize GPU-accelerated methods for data-intensive problems (2020-2022), spatial-temporal modeling (2019-2020), and network science applications (2021). The publications consistently address computational scalability challenges while maintaining practical relevance across geospatial, financial, medical, and engineering contexts. Professional Recognition: As an IEEE Member, Dr. Mei serves on editorial boards for IEEE Access and PeerJ Computer Science, reflecting peer recognition in computational fields. His editorial contributions span 15+ publications demonstrating expertise in evaluating cutting-edge computer science research. Academic Service: Beyond editorial work, Dr. Mei's service includes advising on computational methodology across multiple disciplines. His role as Academic Editor demonstrates commitment to scholarly communication, particularly in bridging theoretical computer science with practical engineering applications. No grant funding details were specified in available materials.

Mansour KarkoubView profile

Professor

• Robust Control
• Vibration Control
• Robotics
• +2 more

Mansour Karkoub serves as Associate Dean of Accreditation & Assessment at Lamar University's College of Engineering, holding the Michael E. and Patricia P. Aldredge Endowed Chair while serving as Professor of Mechanical Engineering. His academic career spans leadership roles at Texas A&M University, the Petroleum Institute (Abu Dhabi), and INRIA (France), with expertise rooted in robotics and control systems. Education: Ph.D. Mechanical Engineering, University of Minnesota M.S. Mechanical Engineering, University of Minnesota B.S. Mechanical Engineering, University of Minnesota Habilitation to Direct Research (HDR), University of Versailles, France Research Focus: Dr. Karkoub pioneers Robust Control methodologies (H-infinity, adaptive, AI-based), Vibration Control for flexible structures, and Robotics applications spanning medical, inspection, and manufacturing systems. His work on Ground/Underwater Autonomous Vehicles addresses self-driving technologies and mobile robotics, while his Engineering Education research integrates ABET accreditation standards with technology-enhanced learning. Publication Trends: Recent articles (2021-2024) reveal concentrated advancements in neural network-integrated motion cueing algorithms, adaptive fuzzy control for underwater manipulators, and sustainable energy harvesting from vehicle suspensions. His work consistently bridges theoretical control frameworks with real-world applications in autonomous systems, emphasizing uncertainty handling and disturbance rejection. Scientific Recognition: Outstanding Researcher Award (2019, Texas A&M Qatar) Distinguished Achievement Award (2012, Dwight Look College) Best Teacher Award (2012, Texas A&M Qatar) Fellow of ASME, IET, and IMechE IEEE Senior Member Research Leadership: Secured over $12M in funding including a $1.2M 2022 grant for smart vehicle research. Founded and directs the Smart Systems Laboratory at Texas A&M Qatar, mentoring teams focused on autonomous vehicle innovation while leading ABET accreditation initiatives as a commissioner. Laboratory Impact: The Smart Systems Laboratory drives advancements in underwater vehicle manipulators, medical robotics, and energy-efficient transportation through cross-disciplinary collaboration, directly translating control theory into deployable autonomous systems for industrial and medical applications.

• Machine Learning
• Operations Research
• Supply Chain Management
• +7 more

Hany Osman is an Associate Professor in the Master of Data Analytics program at the University of Niagara Falls Canada, holding a PhD in Industrial Engineering from Concordia University and a Professional Engineer (PEng) license in Ontario. His academic-industrial career bridges theoretical research with practical applications across multiple sectors. Dr. Osman's research spans three interconnected domains: Machine Learning & Data Analytics : Specializing in logical analysis of data, cost-sensitive learning, and ensemble techniques for industrial applications Operations Research : Developing nature-inspired metaheuristics (cuckoo search, ant colony optimization) for NP-hard problems in manufacturing and logistics Supply Chain Management : Focusing on sustainable optimization of lot sizing, production planning, and inventory control under stochastic conditions His recent publications (2023-2024) reveal a strategic pivot toward AI-integrated manufacturing systems, notably the CAPP-GPT framework for generative AI in process planning and emission-aware lot sizing models. This work demonstrates consistent translation of theoretical advances into industrial solutions for rail, oil, and smart manufacturing sectors. Professional credentials include: IBM Mastery Certificate in Predictive Data Analytics Professional Engineer (PEng) license from Ontario Dr. Osman leverages extensive industrial experience in supply chain logistics, oil industry optimization, and education technology to inform both research and teaching. His supervision in the Master of Data Analytics program emphasizes hands-on application of machine learning to real-world operational challenges, with students contributing to publications in Manufacturing Letters and related journals. While no formal lab is specified, his research group operates at the intersection of data science and industrial engineering, maintaining strong industry partnerships that drive applied projects.

Lea Hildebrandt RuizView profile

Associate Professor

• Air Quality
• Atmospheric Chemistry
• Nanoparticles
• +4 more

Lea Hildebrandt Ruiz serves as an Associate Professor in the McKetta Department of Chemical Engineering at the University of Texas at Austin, holding the Chevron Centennial Teaching Fellowship and affiliated with the Center for Energy and Environmental Resources. Her work addresses the global air pollution crisis, which causes over 7 million annual deaths worldwide. Her educational background includes: NSF Postdoctoral Fellowship at the National Center for Atmospheric Research (2011-2012) Ph.D. in Chemical Engineering and Engineering & Public Policy from Carnegie Mellon University (2011) B.S. in Chemical Engineering from California Institute of Technology (2006) Dr. Hildebrandt Ruiz's research centers on atmospheric chemistry and air quality, employing laboratory experiments, field measurements, and mathematical modeling to study pollutant formation and transformation. Her group investigates nanoparticles, mass spectrometry applications, and environmental sustainability with direct policy implications for improving human health. Key methodologies include state-of-the-science instrumentation for indoor/outdoor environments and chemical transport modeling. Analysis of her 2020-2023 publications reveals dominant research trends in chlorine chemistry's role in urban air quality, particularly in unconventional oil/gas regions and Delhi, India. Her work integrates machine learning for pollution source apportionment while examining disinfectant emissions, cooking aerosols, and VOC transformations. The publications span atmospheric chemistry, aerosol science, and environmental health with strong emphasis on real-world policy applications. Her scientific recognition includes: James J. Morgan Early Career Award (American Chemical Society, 2021) Early Career Award (AIChE Environmental Division, 2020) Election to American Association for Aerosol Research Board (2018) NSF CAREER Award (2017-2022) NSF Postdoctoral Fellowship (2011-2012) EPA Graduate Fellowship (2010-2011) NSF Graduate Fellowship (2006-2009) Dr. Hildebrandt Ruiz actively mentors students through her research group, evidenced by continuous group photos from 2014-2024. She has secured significant funding including the NSF CAREER award and maintains collaborations with National Center for Atmospheric Research and Carnegie Mellon University. Her teaching portfolio includes CHE 317 (Chemical Engineering Analysis), CHE 348 (Numerical Methods), and specialized courses in atmospheric chemistry and professional development. Her research group operates from the Chemical and Petroleum Engineering Building (CPE 5.458) and Engineering and Materials Engineering Building (EME 1.320E), conducting advanced laboratory and field studies. The group's work directly informs environmental policies through mechanistic understanding of pollutant formation, transformation, and atmospheric fate, with particular focus on reducing health impacts in vulnerable populations.

Boyun GuoView profile

Professor

• Development and utilization of geo-energy resources
• Unconventional oil and gas reservoirs
• Gas hydrate reservoirs
• +2 more

Dr. Boyun Guo is a Professor and Graduate Coordinator in Petroleum Engineering at the University of Louisiana at Lafayette's College of Engineering. He serves as the Director of the Center for Optimization of Petroleum Systems (COPS) at the Energy Institute of Louisiana (EIL). His educational background includes: Ph.D. in Petroleum Engineering, 1992 from New Mexico Institute of Mining and Technology M.S. in Petroleum Engineering, 1989 from Montana College of Mineral Science and Technology B.S. in Engineering, 1982 from Daqing Petroleum Institute Dr. Guo's research focuses on the development and utilization of geo-energy resources , with particular expertise in unconventional oil and gas reservoirs, gas hydrate reservoirs, and geothermal resources. His work integrates petroleum engineering principles with environmental sustainability considerations, emphasizing innovative approaches to energy resource extraction. His recent publications demonstrate a strong focus on CO 2 -CH 4 swapping processes in gas hydrates, optimization of geothermal energy extraction, and machine learning applications in reservoir characterization. His extensive publication record of over 140 peer-reviewed journal papers and 70+ conference presentations reflects his significant contributions to petroleum engineering. The research trends show increasing emphasis on sustainable energy practices, carbon management, and advanced computational techniques applied to complex reservoir systems. Dr. Guo's scientific recognition includes: Distinguished Achievement Award for Petroleum Engineering Faculty from SPE (2012) Distinguished Professor at UL Lafayette (2017) Multiple Outstanding Doctoral Student Mentor Awards (2018-2021) Teacher of the Year Award from UL Lafayette College of Engineering (2008) Researcher of the Year Award from UL Lafayette College of Engineering (2016) With 9 years of industry experience, 5 years at a U.S. research center, and over 20 years in academia, Dr. Guo has supervised 15 Ph.D. students and over 40 master's students. His research has been supported by high-level projects including those sponsored by NASA and the Department of Energy. He has authored 11 books and numerous invention patents in petroleum engineering. Dr. Guo leads the Center for Optimization of Petroleum Systems (COPS) at the Energy Institute of Louisiana, where his team conducts laboratory testing and computer simulation of CO 2 -CH 4 swapping processes in gas hydrate reservoirs for natural gas production and CO 2 storage.