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Liangping LiView profile

Associate Professor

• Hydrogeology
• Groundwater Modeling
• Data Assimilation
• +5 more

Dr. Liangping Li is an Associate Professor in the Department of Geology and Geological Engineering at South Dakota School of Mines & Technology. He holds a Ph.D. from Technical University of Valencia and an M.S. from China University of Geoscience, with expertise in hydrogeology, groundwater modeling, and geothermal energy systems. Education: M.S., China University of Geoscience; Ph.D., Technical University of Valencia His research focuses on integrating machine learning with groundwater modeling, data assimilation, geostatistics, and optimization of geothermal energy systems. He has pioneered methods combining generative adversarial networks (GANs) and ensemble smoother techniques for inverse modeling in complex aquifers. Recent publications highlight his work on extremal optimization for well placement, progressive growing GANs for facies modeling, and stochastic inversion of fracture networks. His research trends emphasize computational innovation in subsurface flow simulation and sustainable groundwater management. Scientific Awards: NSF RII Track-4 Grant, NSF REU Site Grant, BLM Environmental Monitoring Grant, and appointments as Associate Editor for Advances in Water Resources and Mathematical Geosciences . Dr. Li teaches courses in groundwater engineering, statistical methods, and environmental field camp, while mentoring graduate and undergraduate researchers in subsurface energy and water resource projects.

Gillian Ruth GowardView profile

Professor

• Advanced Energy Materials
• Magnetic Resonance Spectroscopy
• Electrochemistry
• +5 more

Gillian Ruth Goward is a Professor and Chair of the Department of Chemistry and Chemical Biology at McMaster University, where she also serves as Associate Dean of the Faculty of Science. She holds a prestigious McMaster Faculty of Science Research Chair in Magnetic Resonance of Materials for Energy Storage. Her research focuses on advanced energy materials, particularly lithium-ion batteries, fuel cells, and alternative energy systems, utilizing magnetic resonance spectroscopy and imaging. She is a Senior Editor for the Journal of Physical Chemistry and contributes to the Canadian and international Magnetic Resonance and Materials Chemistry communities. Her team employs state-of-the-art magnetic resonance tools to study electrolyte-electrode interfaces and ion dynamics in solid/solution phases. Education: Ph.D. in Chemistry, University of Waterloo (1995-1999) Certificate in University Teaching, University of Waterloo (1997-1998) Honours Bachelor of Science in Chemistry, McMaster University (1991-1995) Her research interests span atomic/molecular spectroscopy, electrochemistry, and chemical characterization of materials, with a focus on improving energy storage technologies. Recent work emphasizes sodium-ion batteries, solid-state electrolytes, and operando NMR techniques to track ion dynamics during battery operation. Her studies often integrate experimental methods like solid-state NMR with computational approaches (e.g., DFT) and advanced imaging (MRI). She has secured significant grants, including a $4.2M award to advance critical minerals research in collaboration with industry leaders. Her contributions include developing polymer-rich composite solid-state electrolytes and plastic inorganic electrolytes for safer batteries. Scientific Awards: McMaster Faculty of Science Research Chair in Magnetic Resonance of Materials for Energy Storage Her teaching activities include Spectroscopy (CHEM 776) and Sustainable Chemistry: Natural Resources and Energy (CHEM 3SC3) . She leads a research group engaged in collaborative projects, as evidenced by her 111 scholarly activities in the last decade. Her lab specializes in air-sensitive studies and has developed innovative RF probes for battery analysis.

Archie ChapmanView profile

Associate Professor

• Artificial Intelligence
• Game Theory
• Optimization
• +8 more

Associate Professor Archie Chapman is an Associate Professor in Computer Science and Deputy Director (Teaching and Learning) at the School of Electrical Engineering and Computer Science, The University of Queensland. His research focuses on applying artificial intelligence, game theory, optimization, and machine learning to address challenges in future power systems, including renewable energy integration and battery storage optimization. Prior to UQ, he held roles as a Research Fellow in Smart Grids at the University of Sydney (2011-2019) and a postdoc at the University of Southampton (2009-2010), where he completed his PhD in 2004. Research interests include: - Large-scale optimization for energy systems - Demand response and peer-to-peer energy trading - Renewable energy integration and grid stability - Battery storage strategies for smart grids - Algorithmic game theory for energy market design Notable projects: - Bruny Island battery trial for network congestion management - Analysis of tariff impacts on solar households - Development of decentralized energy management frameworks Publications span over 100 articles, with recent work focusing on: - Prosumer battery systems and capacity firming (2025) - Unbalanced optimal power flow benchmarks (2024) - P2P energy trading mechanisms (2021-2023) Expertise includes: - Techno-economic analysis of energy systems - Distributed optimization algorithms - Policy and market design for renewable integration

Constantin Catalin DraganView profile

Senior Lecturer

• Applied Cryptography
• Provable Security
• Electronic Voting
• +3 more

Dr. Constantin Catalin Dragan is a Senior Lecturer in Secure Systems at the University of Surrey, UK. He holds a PhD in Computer Science from Alexandru Ioan Cuza University of Romania (2014), focusing on cryptographic primitives. His research expertise includes applied cryptography, provable security, electronic voting systems, and formal verification. Dr. Dragan has held postdoctoral positions at LORIA, CNRS, INRIA (France) and the University of Surrey. He leads modules such as Privacy Enhancing Technologies (COM3030), Information Security Management (COM3017/COMM037), and supervises final year projects. Currently advising PhD student Navid Abapour, his teaching emphasizes cybersecurity, operating systems, and privacy-preserving technologies. His research focuses on formal verification of security protocols, end-to-end verifiable voting systems, and cryptographic primitives. Notable contributions include work on machine-checked proofs for accountability in systems, privacy-preserving e-voting protocols, and blockchain-based trust services like TAPESTRY and KYChain. Publications span venues like IEEE S&P, EuroS&P, and ESORICS, with a focus on cryptographic protocol design and formal security models. He actively contributes to international workshops on cryptology and cyber security, advancing theoretical foundations and practical implementations of secure systems.

Frank E. TalkeView profile

Professor

• Medical Device Technology
• Information Storage
• Tribology
• +3 more

Frank E. Talke is the CMRR Endowed Chair Professor in the Department of Mechanical and Aerospace Engineering at UC San Diego. His research focuses on medical device technology and information storage systems. He has contributed to advancements in hard disk drive tribology, thermal flying height control, and biomedical innovations like intraocular pressure sensors and 3D-printed endoscopes. Talke holds over 350 publications and 11 patents, with honors including the ASME Medal, Tribology Gold Medal, and membership in the National Academy of Engineering. Education: Diplom-Ingenieur (1965, University of Stuttgart), M.S. and Ph.D. in Mechanical Engineering (1966, 1968, UC Berkeley), honorary doctorate from Technical University of Munich (2005). Research interests span interdisciplinary fields combining mechanical engineering, materials science, and precision instrumentation. Current projects include medical device development (e.g., biofilm-resistant catheters, detachable bronchoscopes) and information storage tribology. His work emphasizes translational applications in both engineering and healthcare sectors. Key Awards: ASME Medal (2008), Tribology Gold Medal (2010), Honorary ASME Membership (2018). Grants and Funding: Extensive industry and academic collaborations in disk drive technology and biomedical engineering. Labs/Teams: Leads the Center for Memory and Recording Research (CMRR), fostering interdisciplinary research in data storage and medical devices.

Ryan HenryView profile

Assistant Professor

• Applied Cryptography
• Secure Systems
• Privacy-Preserving Technologies
• +3 more

Ryan Henry is an Assistant Professor in the Department of Computer Science at the University of Calgary. His research focuses on applied cryptography, emphasizing the development of secure systems that prioritize user privacy. His work spans designing privacy-enhancing technologies, implementing cryptographic protocols, and analyzing number-theoretic attacks on cryptographic assumptions. He also explores theoretical aspects of cryptographic efficiency and practical deployment challenges. While specific educational background details are not provided in the text, his research contributions highlight expertise in cryptography, secure systems, and privacy-preserving technologies. His work has addressed topics such as Private Information Retrieval (PIR), secure messaging, and blockchain privacy. Key research interests include: Secure Multiparty Computation Privacy-Preserving Data Access Efficient Cryptographic Protocols Zero-Knowledge Proofs IoT Security Cryptocurrency and CBDC Design His recent publications emphasize advancements in distributed systems security, privacy in recommendation systems, and cryptographic efficiency. Notable contributions include the Grotto and Duoram frameworks for secure computation, and proposals for Canadian CBDC frameworks. Despite extensive research output, no scientific awards or grants are explicitly mentioned in the provided text. Collaborations and lab affiliations are not detailed, though his work suggests involvement in interdisciplinary projects on privacy and security technologies.

Stephen LeeView profile

Assistant Professor

• Computer Systems
• Cyber-Physical Systems
• Data Mining and Data Science
• +3 more

Stephen Lee is an Assistant Professor in the Department of Computer Science at the University of Pittsburgh, affiliated with Pitt Cyber. His research focuses on distributed systems, cyber-physical systems, and sustainability, emphasizing energy efficiency and cost optimization. Dr. Lee holds a PhD from the University of Massachusetts Amherst, a Master’s from Chennai Mathematical Institute, and a Bachelor’s from St. Stephen’s College, Delhi. He actively seeks students for his research group. Education: PhD, Computer Science, University of Massachusetts Amherst Master’s, Chennai Mathematical Institute Bachelor’s, St. Stephen’s College, Delhi Research Interests: Dr. Lee’s work integrates distributed systems, machine learning, and optimization to enhance sustainability. Key areas include IoT-enabled energy systems, emission-aware computing, and privacy-preserving frameworks. He leads projects like GreenWhisk (serverless emission reduction) and Sat2map (3D building modeling from satellite imagery). Recent Achievements: Best Paper Award in IEEE TPS 2024 DOE-funded Cyber Energy Center (2024) MCSI Seed Grant for Pitt building sustainability (2024) NSF Grant on sustainable distributed infrastructures (2023) Grants & Advising: Secured over $2M in grants, including NSF and DOE funding. Advises on energy-efficient systems and IoT security. Teaches CS 2510 (Operating Systems) and CS 1699 (Systems & Sustainability). Labs & Teams: Directs the Sustainable Systems Research Group, focusing on decarbonizing IT and optimizing renewable energy systems. Collaborates with industry partners on smart grid solutions and edge-cloud systems.

Eduardo GildinView profile

Professor

• Reservoir Modeling and Simulation
• Control and Optimization of Dynamical Systems
• Model Reduction Techniques
• +5 more

Eduardo Gildin is a Professor of Petroleum Engineering and Associate Department Head for Graduate Studies at Texas A&M University's College of Engineering. He holds the L.F. Peterson '36 Professorship and directs the university's graduate studies in petroleum engineering. His research focuses on reservoir modeling, control optimization, model reduction techniques, and CO2 sequestration. Gildin has pioneered data-driven approaches for reservoir simulation, integrating machine learning and physics-based models to enhance efficiency and accuracy. Education: Ph.D. in Aerospace Engineering, University of Texas at Austin (2006) M.S. in Mechanical Engineering, University of São Paulo, Brazil (1998) B.S. in Mechanical Engineering, Faculdade de Engenharia Industrial, Brazil (1995) Research Interests: Model reduction of large-scale dynamical systems Control and optimization of reservoir operations CO2 storage and geological carbon sequestration Machine learning applications in reservoir engineering and drilling automation Geomechanics and compaction damage evaluation Key Awards: 2020: William O. and Montine P. Head Memorial Research Award 2017-2018: Dean of Engineering Excellence Award 2013-2019: Energi Simulation Chair in Robust Reduced Complexity Modeling 2021: Distinguished Membership in Society of Petroleum Engineers Grants and Advising: Gildin has secured major funding for projects on reservoir simulation, drilling automation, and CO2 storage. He advises graduate students on topics such as surrogate modeling and reinforcement learning applications in petroleum systems. His lab collaborates with industry partners to translate research into practical tools for reservoir management and subsurface operations. Labs and Teams: He leads the Reservoir Simulation and Control Lab, focusing on advanced computational methods for reservoir optimization. His team develops open-source drilling models and collaborates globally on projects like the DREAMS (Drilling and Extraction Automated System) initiative.

Chao TianView profile

Associate Professor

• Information Theory
• Distributed Data Storage
• Coding Theory
• +6 more

Dr. Chao Tian is an Associate Professor in the Department of Electrical and Computer Engineering at Texas A&M University, part of the College of Engineering. He holds a Ph.D. from Cornell University (2005) and a B.E. from Tsinghua University (2000). His research focuses on information theory, distributed storage systems, coding theory, and machine learning applications, including large language models (LLMs) and privacy-preserving techniques like steganography and private information retrieval (PIR). He has received notable awards, including the 2017 IEEE Jack Wolf ISIT Best Student Paper Award and the 2014 IEEE ComSoc DSTC Best Paper Award. Dr. Tian’s work bridges theoretical foundations and practical applications, such as optimizing storage codes for distributed systems, developing secure PIR protocols, and exploring LLMs in energy and steganographic contexts. His group has pioneered methods for variable-order Markov chain modeling with transformers and designed quantization techniques for perceptual quality. Recent activities include a faculty development leave at MIT/Harvard and delivering distinguished lectures globally on AI and information theory. He advises students on cutting-edge topics like LLM-based steganography and diffusion models. His publications span journals like IEEE Transactions on Information Theory and conferences such as NeurIPS and ISIT, with a focus on coding theory, privacy, and machine learning. He has also contributed to open-source tools like the CAI toolbox for investigating information-theoretic limits. Current projects include optimizing cryptocurrency mining in energy markets and advancing federated learning with adversarial robustness.

Chuan KhooView profile

Lecturer

• Interaction Design
• Physical Computing
• Tangible Embodied Interaction
• +3 more

Dr. Chuan Khoo is a Lecturer in the Department of Design at Monash University, specializing in interaction design, digital media, and physical computing. He holds a PhD from RMIT University and an MFA from the Rhode Island School of Design. His work explores the dual edges of technology through projects like Touchstone (interactive public art) and Lumogram , which interrogate the relationship between humans and digital systems. Khoo’s research focuses on 'slow data'—design perspectives that critically engage with digital augmentation. He has exhibited internationally and developed tools like the mote mini , an IoT microcontroller for design students. His academic roles include teaching at RMIT and heading the Interaction Design program at Nanyang Polytechnic, Singapore. Key projects include When Echoes Find Light (2019), an interactive public bench installation, and Slow Data in the Age of Digital Things , his PhD work critiquing tech velocity. He co-designed the Alfred Health Universal Design Principles project (2024) and received a 2024 DIA Award shortlist for Lumogram . Khoo maintains Technologies for Interactivity , an open-source resource for physical computing, and collaborates globally on projects blending art, tech, and critical design.

Fan HongjinView profile

Professor

• Nanomaterials
• Nanotechnology
• Semiconductor Nanocrystals
• +5 more

Professor Fan Hongjin serves as Director Professor in the Division of Physics & Applied Physics at Nanyang Technological University's School of Physical & Mathematical Sciences, with a courtesy appointment in the School of Chemistry, Chemical Engineering and Biotechnology. He leads the SMILE research group focusing on sustainable energy materials and has established himself as a leading researcher in aqueous battery systems and electrocatalysis. His research interests span nanomaterials and nanotechnology, semiconductor nanocrystals, surfaces and coatings, with particular focus on aqueous batteries (especially zinc-based systems), electrocatalysis for hydrogen generation and CO2 reduction, and energy storage materials . Fan's group pioneered research on aqueous zinc-ion batteries since 2018 and has developed innovative approaches to hydrogel electrolytes, iodine conversion chemistry, and dual-plating strategies for large-scale energy storage. His publication record demonstrates consistent high-impact research, with 15 recent articles (2024-2025) appearing in journals including Nature Communications , Journal of the American Chemical Society , Energy & Environmental Science , and Joule . These works collectively advance understanding of zinc-halogen battery chemistry, strain engineering in catalysts, and novel electrolyte design principles. Highly Cited Researcher by Clarivate Analytics (2016-present) Fellow of Royal Society of Chemistry (FRSC, 2018) Young Scientist Award by Singapore Institute of Physics Editor-in-Chief of Materials Today Energy (since 2021) Member of editorial boards for Energy & Environmental Sciences, Advanced Science, Small, and other top journals Professor Fan actively mentors PhD students including Rao Ruijun, Annisaa Hayya Arundati, Liu Qingyi, and Wu Jiawen, with recent successes including Yang Jin-Lin winning the MRSS Metal in Physics (July 2025). His research group continues to expand with new members joining regularly, reflecting ongoing research momentum and funding support in the sustainable energy field. The group maintains strong industry and academic collaborations across Asia, Europe, and North America.

• Algebra
• Number Theory
• Coding Theory
• +3 more

Assoc Prof Frederique Elise Oggier is an Associate Professor in the School of Physical and Mathematical Sciences, Division of Mathematical Sciences at Nanyang Technological University (NTU). She holds a PhD from the Swiss Federal Institute of Technology (EPFL) and has held visiting positions at Caltech and the Research Center for Information Security (Tokyo). Her research focuses on algebraic coding theory, lattice-based cryptography, and applications of number theory to secure and reliable communication systems. Education: Bachelor’s and Master’s in Mathematics from the University of Geneva PhD in Mathematics from EPFL Research Interests: Her work bridges abstract algebra with practical coding challenges, emphasizing lattice codes for wiretap channels, distributed storage systems, and security protocols. Specialized in algebraic structures like cyclic division algebras and modular lattices, her contributions advance both theoretical foundations and real-world implementations of secure communication systems. Publications: Her recent work addresses cutting-edge topics such as MDS codes, non-GRS code constructions, and lattice-based security in noisy channels. These contributions highlight her expertise in coding theory and its interdisciplinary applications. Grants/Advising: While specific grants are not detailed, her prolific publication record reflects sustained research activity. She advises on projects related to distributed storage and secure coding, though student names are not listed in the provided texts. Labs/Teams: Affiliated with NTU’s mathematical sciences division, she collaborates with global researchers on projects such as lattice coding for 5G/6G systems and cryptographic protocols leveraging algebraic number theory.

Charles Raymond SarimuthuView profile

Senior Lecturer

• Power Systems
• Renewable Energy
• Smart Grids
• +3 more

Dr. Charles Raymond Sarimuthu is a Senior Lecturer in the Department of Electrical and Computer Systems Engineering at Monash University Malaysia. He holds a Ph.D. in Electrical Power Engineering from National Energy University, Malaysia. His research focuses on voltage control, power transformers, distribution systems, renewable energy, and smart grids. He actively supervises undergraduate and postgraduate students and has published extensively in high-impact journals such as Electric Power Systems Research and Renewable Energy . Dr. Sarimuthu has collaborated on projects including the Electric Field Imaging (EFI) Sensor for Comprehensive Static Charge Analysis (2024-2025) and the Fundamental study on memristor switching performances (2023-2026). He has also led the Investigation of on-load tap changer transformer operation (2019-2022), demonstrating expertise in grid stability and renewable integration. Teaching commitments include ECE3051 - Electrical Energy Systems , ECE4053 - Electrical Energy-Generation and Supply , and ECE5886/6886 - Smart Grids . He is a member of professional bodies such as the Board of Engineers Malaysia (BEM) and IEEE. His work aligns with UN Sustainable Development Goals related to affordable and clean energy (SDG7) and industry innovation (SDG9). Recent research highlights include game theory approaches for voltage control and adaptive synchronverter technologies for solar power systems.

Gonzalo Barluenga BadiolaView profile

Professor

• 3D Printing Materials
• Cement-Based Composites
• Self-Healing Concrete
• +5 more

Gonzalo Barluenga Badiola is a Professor at the Department of Architecture within the School of Architecture at the University of Alcalá. His research focuses on advanced construction materials, including 3D-printable mortars, self-healing concrete, phase change materials (PCM), and nanomaterials for sustainable architecture. He leads the 'Promarq' research group, specializing in architectural projects and building materials. He holds a Ph.D. from the Universidad Politécnica de Madrid (2002), with a thesis on joint systems in facade construction. His research interests emphasize material innovation for energy efficiency, structural health monitoring, and environmental adaptation. Key areas include bio-based composites, thermal/acoustic mortar properties, and the integration of nanotechnology into construction materials. Recent work explores post-fire self-healing mechanisms, PCM-enhanced mortars, and additive manufacturing applications. His publications (2023–2025) highlight advancements in 3D-printed cement-lime mortars, nano-modified self-compacting concretes, and fiber-reinforced composites. He investigates rheological properties of materials at early stages and their structural performance. No scientific awards are explicitly mentioned, but his work is widely cited in sustainable construction and materials science. Grants and collaborations are inferred from his research output, though specific funding details are not provided here. His lab, 'Promarq,' likely focuses on experimental and numerical analysis of building materials. No student advising records are listed in the provided data.

• Optimization Algorithms
• Smart Grids
• Renewable Energy Systems
• +3 more

Silvia Jiménez Fernández is an Associate Professor in the Department of Signal Theory and Communications at Universidad Autónoma de Madrid. Her research focuses on optimization algorithms, smart grids, renewable energy systems, telemedicine, and machine learning applications. She holds a Ph.D. from Universidad Politécnica de Madrid (2009), supervised by Dr. Francisco del Pozo Guerrero and Dr. Paula de Toledo Heras. Her work integrates interdisciplinary approaches, such as combining evolutionary algorithms with engineering challenges in energy systems and healthcare. Key contributions include advancements in coral reefs optimization algorithms for energy management, machine learning for battery health estimation, and telemedicine systems for chronic disease monitoring. Recent research trends emphasize hybrid learning models in education, multi-objective optimization in renewable energy systems, and risk analysis in smart grids with electric vehicles. She is affiliated with the GHEODE Research Group (Modern Heuristics and Network Design).