جست‌وجوی استاد و پژوهشگر

Derek Wrightمشاهده پروفایل

دانشیار

• Digital ICs
• Neuromorphic hardware
• VLSI
• +۴ مورد دیگر

Derek Wright is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, serving as Director of Mechatronics Engineering and faculty advisor for the Waterloo Aerial Robotics Group. His research focuses on Digital ICs (especially neuromorphic hardware and spiking neural networks), Medical Imaging Physics, and Multidomain Modeling & Simulation, with an emphasis on commercialization. He holds a Doctorate in Electrical and Biomedical Engineering from the University of Toronto (2010) and degrees from the University of Waterloo (MASc 2005, BASc 2003). Education: PhD, Electrical & Biomedical Engineering, University of Toronto (2010) MASc, Electrical Engineering, University of Waterloo (2005) BASc, Electrical Engineering, University of Waterloo (2003) Research interests include neuromorphic hardware design, VLSI innovation, and multidisciplinary simulation techniques. His work bridges theoretical advancements with practical applications in electronics and biomedical systems. Notable contributions include low-power flip-flop designs, SRAM dosimeters for radiation characterization, and mechatronics modeling. His teaching portfolio includes courses like ECE 140 (Linear Circuits), MTE 481/482 (Mechatronics Projects), and PD19 (Workplace Success Tactics). He has received the 2017 Faculty of Engineering Teaching Award for his pedagogical innovations in engineering education. Dr. Wright advises the Waterloo Aerial Robotics Group and oversees the Mechatronics Engineering program. He actively engages in curriculum development and student-driven projects, emphasizing hands-on learning through hackathons and design competitions.

Themistoklis Prodromakisمشاهده پروفایل

استاد

• Electrical and Electronic Engineering
• Materials Engineering
• Analytical Chemistry
• +۳ مورد دیگر

Themistoklis Prodromakis holds the Regius Chair of Engineering at the University of Edinburgh and serves as Director of the Centre for Electronics Frontiers. His research focuses on metal-oxide Resistive Random-Access Memory (RRAM) technologies and their applications, leading an interdisciplinary team of 30 researchers. He is an Adjunct Professor at UTS Australia, Visiting Professor at Tsinghua University's Department of Microelectronics and Nanoelectronics, and Honorary Fellow at Imperial College London. Affiliations: Centre for Electronics Frontiers, UKRI CDT MINDS, Lloyds Register Foundation ICoN, Royal Society, Royal Academy of Engineering, IEEE, IET. Companies Founded: ArC Instruments Ltd (2015) and SoneT.ai (2019). His research spans nanotechnology, neuromorphic AI hardware, and energy-efficient computing. He has pioneered RRAM applications in embedded systems and developed novel nanodevice characterization tools. His work integrates materials science, semiconductor devices, and systems engineering. Prodromakis has received the Royal Society Industry Fellowship and Royal Academy of Engineering Chair in Emerging Technologies. He leads initiatives such as the UKRI CDT MINDS and co-directed the Lloyds Register Foundation ICoN consortium.

Xiaogan Liangمشاهده پروفایل

استاد

• Advanced Nanofabrication
• Nanomanufacturing
• Microsystem Technologies
• +۷ مورد دیگر

Professor Xiaogan Liang is a faculty member in the Department of Mechanical Engineering at the University of Michigan, Ann Arbor, and serves as Associate Chair for Undergraduate Education. His research focuses on advanced nanofabrication, nanomanufacturing, and microsystem technologies, with applications in nanoelectronics, nanophotonics, and biosensing systems. He leads the Nanoengineering and Nanodevice Laboratory and holds a tenured position. Liang has been recognized with awards such as the Monroe-Brown Education Excellence Award (2018-19) and the NSF CAREER Award (2015). His work bridges nanotechnology and biomedical engineering, emphasizing scalable fabrication techniques and neuromorphic computing hardware. Education and Career: Liang joined the University of Michigan in 2012 as an Assistant Professor, advancing to his current rank. His academic background includes expertise in mechanical engineering and nanotechnology. Key research contributions include novel 2D material-based biosensors, memristive devices, and plasmonic systems for real-world applications. Research Interests: His lab develops nanoscale fabrication methods (e.g., nanoimprint lithography) for creating high-performance devices like MoS₂ photodetectors and Bi₂Se₃ memristors. Applications span environmental monitoring, medical diagnostics, and energy-efficient robotics. Recent innovations include brain-inspired computing hardware for robotics and bioinspired sensors for viral detection. Publications: Over 150 peer-reviewed articles highlight his work on neuromorphic systems, plasmonic colorimetric sensing, and scalable nanoassembly. Notable 2020-2025 publications address reservoir computing hardware, site-selective 2D material growth, and airborne particle monitoring systems. Awards: Monroe-Brown Award (2018), NSF CAREER (2015), CoE Awards (2016) Grants: Supported by NSF, U-M, and industry partnerships Advising: Mentors graduate students (e.g., Hongsuk Nam, Sungjin Wi) in nanofabrication and biosensor development. Collaborates with Professors Katsuo Kurabayashi and Allen Liu on interdisciplinary projects. Labs/Teams: Directs the Nanoengineering and Nanodevice Laboratory, fostering cross-disciplinary research in nanotechnology and biomedical engineering. Engages in collaborative efforts with materials science and electrical engineering groups.

• Machine Learning
• Ensemble Learning
• Feature Selection
• +۴ مورد دیگر

Gavin Brown is a Professor of Computer Science at the University of Manchester, affiliated with the Data Science Institute and the Machine Learning and Optimisation group. His research focuses on machine learning theory, ensemble methods, feature selection, and hardware-accelerated learning. He holds roles in interdisciplinary initiatives like the Centre for Digital Trust and Society, EnnCore project (privacy-preserving neural architectures), and the Robotics and Artificial Intelligence Centre. Education: PhD in Computer Science from the University of Birmingham (2003), with a thesis on 'Diversity in Neural Network Ensembles'. Research interests span theoretical foundations of machine learning, including bias-variance decomposition, ensemble diversity, and algorithmic stability. Applications include healthcare (e.g., outlier detection in vital signs), robotics (low-cost prediction hardware), and ethical AI (conceptual guarding of neural networks). He has pioneered work on feature selection for resource-constrained systems and neuromorphic computing. Recent articles emphasize unifying ensemble theory, hardware-efficient learning (FPGA-based feature selection), and clinical applications of machine learning. Projects include EnnCore (privacy-preserving AI), RAI Centre (robot-AI ethics), and Data Visualisation for clinical trials. He leads or co-leads 8 major projects, including £multi-million initiatives in digital trust, robotics, and AI. Supervised 24 doctoral students, with a focus on interdisciplinary work combining theory and applied machine learning.

Lianzhou Wangمشاهده پروفایل

استاد

• Semiconductor Nanomaterials
• Renewable Energy Conversion
• Photocatalysts
• +۳ مورد دیگر

Professor Lianzhou Wang is a Professor at the School of Chemical Engineering, University of Queensland (UQ), and an ARC Australian Laureate Fellow. He leads the Nanomaterials Centre (Nanomac) and serves as a Senior Group Leader at the Australian Institute for Bioengineering and Nanotechnology (AIBN). His research focuses on semiconductor nanomaterials for renewable energy applications, including photocatalysts, batteries, and solar cells. He has attracted significant funding from ARC, industry, and CRC programs, resulting in over 600 journal publications with a H-index of 131. Awards include STA Fellowship, ARC Laureate Fellowships, and prestigious fellowships from Australian and international academies. Education: PhD in Materials Science (1999, Shanghai Institute of Ceramics, CAS), postdoctoral roles at NIMS and AIST (Japan). Academic roles at UQ include ARC QEII Fellow (2006), Senior Lecturer (2007), Associate Professor (2010), and Professor (2012–present). Current roles also include Director of Nanomac and leadership in professional societies. Research interests emphasize functional nanomaterials for solar energy conversion and storage. Key achievements include record-breaking perovskite solar cells, ultrastable photoelectrochemical systems, and advanced battery technologies. His work has been featured in media for innovations like eco-friendly tin-based perovskites and printed batteries. Grants and funding span solar-to-chemical systems, battery materials, and nanotechnology. Supervision includes over 45 completed PhDs and ongoing guidance of ~20 PhD students and 15 postdocs. He edits journals like Advanced Materials and is a Clarivate Highly Cited Researcher. Labs and teams include Nanomac, AIBN collaborations, and the HBIS-UQ Innovation Centre for Sustainable Steel. His research addresses global challenges in clean energy and sustainable materials.

Peter McMahonمشاهده پروفایل

دانشیار

• Quantum Information Science
• Optical Physics
• Artificial Intelligence
• +۱۰ مورد دیگر

Peter McMahon is an Associate Professor in the School of Applied and Engineering Physics at Cornell University. He holds a Ph.D. in Electrical Engineering from Stanford University (2014) and a B.S. in Electrical and Computer Engineering from the University of Cape Town. His research focuses on unconventional computing paradigms, including quantum computing, photonic computing, and neuromorphic systems. He explores quantum information processing in platforms like semiconductor spins, superconducting circuits, and optical systems, with applications in optimization, machine learning, and quantum simulation. Education B.S., Electrical and Computer Engineering, University of Cape Town (2003–2008) M.S., Electrical Engineering, University of Cape Town (2003–2008) M.S., Computer Science, University of Cape Town (2003–2008) M.S., Electrical Engineering, Stanford University (2008–2010) Ph.D., Electrical Engineering, Stanford University (2010–2014) Postdoctoral Fellow, Applied Physics, Stanford University (2014–2019) Research Interests His lab investigates the physics of computation, emphasizing quantum and classical alternatives to conventional von Neumann architectures. Key areas include quantum annealing, photonic neural networks, and neuromorphic systems. McMahon’s work bridges theoretical foundations and experimental implementations, with a focus on leveraging physical systems for computational advantage in optimization and machine learning. Awards Optica Adolph Lomb Medal (2025) IUPAP Early Career Scientist Prize (2022) Office of Naval Research Young Investigator Award (2022) Sloan Research Fellowship (2022) Packard Fellowship in Science and Engineering (2021–2026) CIFAR Azrieli Global Scholar (2020–2022) Advising & Grants McMahon oversees a research group focused on experimental and theoretical exploration of quantum technologies. His funding includes awards from the Packard Foundation, Office of Naval Research, and Google Quantum Research. He collaborates with industry and academic partners to advance quantum and photonic computing hardware. Labs & Teams He leads the McMahon Lab, which develops novel optical and quantum computing platforms. The lab collaborates on projects such as optical neural networks and quantum annealing systems, with applications in imaging, optimization, and quantum simulation.

Jesús A. del Alamoمشاهده پروفایل

استاد

• Semiconductor Devices
• Microelectronics
• Nanoelectronics
• +۷ مورد دیگر

Jesús A. del Alamo serves as the Donner Professor of Science and Professor of Electrical Engineering in the Department of Electrical Engineering and Computer Science (EECS) at Massachusetts Institute of Technology. He also directs the Microsystems Technology Laboratories (MTL) at MIT, a leading nanofabrication facility supporting cutting-edge research across multiple disciplines. His research interests focus on semiconductor device physics, particularly nanoscale electronic devices based on novel materials including III-V and III-N compound semiconductors. His work aims to expand microelectronics frontiers by developing transistors with higher frequencies, greater speed, smaller size, extremely low power consumption, and higher operating temperatures. A significant portion of his recent research explores novel devices for artificial intelligence applications, including analog deep learning hardware. His publication trends show consistent contributions to advanced transistor architectures, with recent work emphasizing nanoscale transistors, compound semiconductor devices, and hardware for artificial intelligence. His research spans fundamental device physics to practical applications, with strong industry collaboration through MIT.nano facilities. Intel's 2023 Outstanding Researcher Award (with Yanjie Shao) IEEE Electron Devices Society Education Award (2012) Amar Bose Award for Excellence in Teaching (2002) Louis D. Smullin Award for Excellence in Teaching (2001) H. E. Edgerton Junior Faculty Achievement Award (1993) Baker Memorial Award for Excellence in Undergraduate Teaching (1992) Professor del Alamo has advised numerous PhD, Master's, and undergraduate students throughout his career at MIT, with alumni now working at leading technology companies including Analog Devices, Texas Instruments, IBM, and academic institutions worldwide. His research group, the Xtreme Transistors Group, maintains close connections with industrial partners and leverages MIT.nano facilities for device fabrication and characterization. The group's research spans experimental device design, fabrication, characterization, reliability testing, and modeling, with a strong emphasis on practical applications and educational impact through his widely-used textbook.

Barry P. Randمشاهده پروفایل

استاد

• Thin-film Electronics
• Photovoltaics
• Light Emitting Diodes
• +۵ مورد دیگر

Barry P. Rand is Professor of Electrical and Computer Engineering and the Andlinger Center for Energy and the Environment at Princeton University, with additional affiliations at the Princeton Materials Institute (PMI) and High Meadows Environmental Institute (HMEI). His research program focuses on advancing thin-film electronic materials for energy conversion and optoelectronic applications, bridging electrical engineering, materials science, physics, and chemistry. His educational background includes a PhD in Electrical Engineering from Princeton University (2007) and a Bachelor of Engineering in Electrical Engineering from The Cooper Union (2001). This foundation supports his interdisciplinary approach to semiconductor research. Rand's work centers on emerging thin-film semiconductors—particularly organic, oxide, and metal-halide perovskites—for solar cells, LEDs, and transistors. He investigates fundamental optical/electrical properties, material processing techniques (both vacuum and solution-phase), and critical device stability challenges. His research emphasizes understanding degradation mechanisms while developing novel device architectures to improve efficiency and longevity in real-world conditions. Analysis of his recent publications reveals dominant themes in perovskite optoelectronics, with concentrated efforts on stability enhancement through interface engineering, halide chemistry control, and novel transport layers. Significant growth appears in machine learning applications for materials discovery (e.g., LLM-Prop) and expansion into neuromorphic photonics and terahertz modulation, indicating strategic diversification while maintaining core expertise in energy devices. His scientific recognition includes: Gordon and Betty Moore Foundation Experimental Physics Investigators Initiative award (2023) ONR Young Investigator Program Award (2016) DARPA Young Faculty Award (2015) DuPont Young Professor Award (2015) 3M Nontenured Faculty Award (2014) As Director of Graduate Studies and active mentor, Rand supervises a diverse cohort of graduate researchers across thin-film electronics topics. His lab operations are supported by substantial research funding from federal agencies (ONR, DARPA) and industry partnerships, enabling state-of-the-art thin-film fabrication and characterization facilities. The RandLab, established in 2013, serves as the operational hub for his research group, focusing on translating fundamental semiconductor discoveries into next-generation electronic and optoelectronic devices for computing, sensing, and renewable energy applications.

• Optoelectronics
• Organic Electronics
• Perovskite Solar Cells
• +۳ مورد دیگر

Thomas Anthopoulos is Professor of Emerging Optoelectronics at the University of Manchester's Department of Electrical and Electronic Engineering. His research focuses on next-generation optoelectronic technologies including organic and perovskite photovoltaics, printed electronics, and neuromorphic computing systems. Research interests span scalable nanomanufacturing of electronic devices, with emphasis on organic semiconductors, metal-oxide transistors, graphene diodes, and perovskite-based computing architectures. Key application areas include renewable energy, biosensors, flexible electronics, and neuromorphic systems. Recent publications demonstrate strong focus on advanced materials for optoelectronics, including record-efficiency organic photovoltaics (20.5%), neuromorphic computing elements, flexible oxide transistors, and novel biosensing platforms. Research consistently bridges fundamental materials science with device engineering. Supervises PhD projects on third-generation photovoltaics and scalable nanomanufacturing. Organizes international conferences including IEC TC 119 Printed Electronics events at the Henry Royce Institute. Research contributes to UN Sustainable Development Goals through renewable energy and advanced materials innovation.

Bilel HAFSIمشاهده پروفایل

دانشیار

• Organic Electronics
• Nanotechnology
• Materials Engineering
• +۵ مورد دیگر

Bilel HAFSI is an Associate Professor at the ICAM Institute (University of Lille) and a member of the NCM research group. His expertise spans organic electronics, nanotechnology, materials engineering, and computer modeling. He obtained his PhD from the Institute of Electronic, Microelectronics and Nanotechnology (IEMN) under Prof. Kamal Lmimouni and Prof. Adel Kalboussi, focusing on nanoparticle-based memory devices. He has held roles as a research and teaching assistant at École Centrale Lille, IMT Lille-Douai, and University of Lille. Previously, he worked at AIMAN-Films Group on phononic crystal sensors and as a robotics/IoT consultant at Techshop Les Ateliers Leroy Merlin. Research interests include developing novel soft-electronic devices through self-assembly processes, optimizing memory device performance (e.g., endurance, memory window), and exploring neuromorphic applications using organic materials. His work integrates electrical engineering and materials science, with a focus on nanoscale systems. Notable achievements include winning the 2018 regional award for best international PhD thesis in sciences and technologies. His scientific production includes publications in Organic Electronics and Journal of Electronic Materials, emphasizing polymeric memory devices, graphene-based simulations, and neuromorphic transistor behavior. He collaborates with multiple research groups (e.g., NCM, ACOUSTICS, ANODE) and contributes to projects in micro/nano-optoelectronics, THz photonics, and low-power sensors. Current affiliations include the ICAM Institute, where he teaches and conducts advanced materials research.

Regina Pohle-Fröhlichمشاهده پروفایل

استاد

• Image Processing
• Pattern Recognition
• Computer Vision
• +۵ مورد دیگر

Regina Pohle-Fröhlich is a Professor of Computer Science and Graphical Data Processing at the Department of Electrical Engineering and Computer Science, Niederrhein University of Applied Sciences. Her research focuses on image processing, pattern recognition, computer vision, and medical imaging applications. Education: Diplom-Ingenieurin in Materials Engineering (1989), PhD in Image Analysis of Welding Defects (1995), Habilitation in Medical Image Analysis (2004) Her work spans applications in neuromorphic event cameras for outdoor monitoring, 3D city modeling, and biomedical image analysis. She collaborates extensively with institutions like the University of Cologne, German Aerospace Center, and Charité Berlin. Recent research trends include deep learning for event stream segmentation, semantic scene filtering, and advanced 3D reconstruction techniques. She actively participates in the iPattern Institute for Pattern Recognition and the Promotionskolleg NRW graduate institute. Key Projects: MLPCO (Machine Learning for Crop Output), KIRaPol.5G (AI for Radar Surveillance), BeeVision (Bee Population Monitoring), and EU/DFG-funded agricultural sustainability initiatives.

• Nanomechanics
• Nanomaterials
• Low-Dimensional Materials
• +۵ مورد دیگر

Travis Hu is an Associate Professor of Mechanical Engineering at California State University, Los Angeles (Cal State LA), affiliated with the College of Engineering, Computer Science, and Technology. His research focuses on bio-inspired nanomaterials, multifunctional energy materials, and multiscale modeling. He leads the Bio-Nano Materials and Interfaces Lab, investigating bio-inspired smart materials for applications in energy, biomedical, and environmental fields. Dr. Hu's academic background includes postdoctoral research at Case Western Reserve University, University of Florida, and University of Delaware, followed by roles as a Teaching Assistant Professor at the University of Denver. His teaching spans mechanics, materials science, and nanotechnology. His research emphasizes bio-inspired design principles from organisms to create advanced materials with adaptive properties like self-cleaning surfaces, smart adhesives, and energy-efficient coatings. Recent work includes neuromorphic computing memristors, energy harvesting nanogenerators, and self-healing hydrogels. Key grants include NSF CREST and PREM Centers supporting interdisciplinary research initiatives. He collaborates widely, publishing extensively in journals like Science China Materials and Advanced Functional Materials. Dr. Hu is committed to diversity in STEM education, highlighted in a 2023 JOM article showcasing Cal State LA's DEI outcomes. His lab actively recruits students from diverse backgrounds for research in nanomaterials and bio-inspired engineering.

Antonio Guerreroمشاهده پروفایل

دانشیار

• Materials Science
• Electronic Devices
• Memristors
• +۵ مورد دیگر

Antonio Guerrero is an Associate Professor in Applied Physics at Jaume I University and Principal Investigator of the Active Materials and Systems Research (AMSY) group at the Institute of Advanced Materials (INAM). His work focuses on developing novel materials for electronic devices, with emphasis on memristors, photovoltaics, and energy applications. Education: Bachelor of Chemistry, University of Alcalá de Henares (2002) Ph.D. in Organometallic Chemistry, University of East Anglia, UK (2006) Guerrero's research centers on three interconnected domains: memory devices (memristors/transistors for neuromorphic computing), photovoltaics (perovskite/organic solar cells), and energy materials . His approach integrates materials synthesis, device fabrication, and fundamental characterization to understand ion transport mechanisms in halide perovskites. This interdisciplinary work bridges chemistry, physics, and engineering to address stability challenges in next-generation electronics. Analysis of his 2023-2025 publications reveals dominant trends in perovskite-based memristors for neuromorphic systems (60% of articles), photovoltaic innovations (25%), and sustainable energy materials (15%). Key advancements include engineering perovskite compositions for resistive switching control, developing organic-inorganic hybrid electrolytes for synaptic transistors, and creating scalable manufacturing techniques for solar cells. His work consistently explores the role of ion migration in device performance. Professional Recognition: Panel member of ERC Consolidator program Regular reviewer for Science, Nature Energy, and Energy & Environmental Science As Principal Investigator of the AMSY group, Guerrero mentors students across all levels and evaluates international research proposals. His leadership has yielded over 110 publications (h-index 53), three patents, and significant contributions to perovskite device physics. He actively collaborates with European research networks and industry partners through INAM's technology transfer initiatives. The AMSY group operates within INAM's advanced laboratories, utilizing specialized equipment for materials synthesis, thin-film deposition, and nanoscale device characterization. Current projects focus on ion migration dynamics in perovskites, flexible memristor arrays, and enzymatic PET recycling processes, with strong ties to Spain's neuromorphic computing roadmap.

Naresh Kumar Pendyalaمشاهده پروفایل

پژوهشگر

• Semiconductor Devices
• Photovoltaics
• Perovskite Materials
• +۴ مورد دیگر

Naresh Kumar Pendyala is a postdoctoral researcher at the Institute of Advanced Materials (INAM) of Universitat Jaume I , Spain, since February 2023. His academic journey includes a Ph.D. in Chemistry (2017) from the Indian Institute of Technology Hyderabad , followed by postdoctoral research at the State Key Laboratory , Fujian Institute of Research on the Structure of Matter (FJIRSM), Chinese Academy of Sciences (2018–2019), and the Institute of Chemistry , The Hebrew University of Jerusalem (February 2020–September 2023). Education : Ph.D. in Chemistry (IIT Hyderabad, 2017) His research focuses on semiconductor devices, particularly perovskite and quantum dot solar cells , memristors , and chemiresistive gas sensors . At INAM, he investigates perovskite material-based memristors under the guidance of Juan Bisquert and Antonio. His expertise includes additive manufacturing techniques like inkjet printing for advanced solar cells and gas sensors. Naresh has published 24 peer-reviewed articles in journals such as J. Mater. Chem. A , ACS Appl. Mater. Interfaces , and Solar RRL , and holds a patent on inkjet-printed semitransparent perovskite solar cells. His work has earned him competitive postdoctoral fellowships in China, Israel, and Spain, though specific award names are not listed in the text. He has contributed to advancements in scalable fabrication methods, stability optimization, and multifunctional device design. His collaborations span institutions in three countries, reflecting a globally connected research profile. Current projects emphasize perovskite memristors for neuromorphic computing and energy-efficient electronics.

Ignacio Sanjuán Moltóمشاهده پروفایل

پژوهشگر ارشد

• Electrochemistry
• Electrocatalysis
• CO2 Electroreduction
• +۵ مورد دیگر

Ignacio Sanjuán Moltó is a Postdoctoral Researcher at the Institute of Advanced Materials (INAM) under the Universitat Jaume I in Spain. He joined the Active Materials and Systems Research (AMSY) group in September 2024 as part of the NEUROVISIONM project, focusing on developing halide perovskite-based memristor devices for neuromorphic computing applications. Education: Bachelor's degree in Chemistry (B.Sc.), University of Alicante (2014) Master's degree in Electrochemistry (M.Sc.), University of Alicante (2015) Ph.D. in Electrochemistry, University of Alicante (2020) Research Interests: Electrocatalysis of energy conversion reactions (CO2 electroreduction, alcohol electrooxidation, water splitting) Advanced electrochemical techniques (e.g., Scanning Electrochemical Microscope - SECM) Electrochemical treatment processes (e.g., reject water treatment for EDR plants) Surface neuromorphic computing and intelligent vision systems Career Highlights: Collaborated with Aguas de Valencia S.A., conducted research at Sorbonne University/CNRS (Paris), and worked for four years at the University of Duisburg-Essen on electrocatalysis projects. His contributions include 21 publications (h-index: 10), a Spanish invention patent, and over 20 conference presentations.