جست‌وجوی استاد و پژوهشگر

• Photovoltaics
• Materials Science
• Energy Research
• +۳ مورد دیگر

Annalisa Bruno is an Associate Professor at Nanyang Technological University (NTU), holding joint positions in the School of Physical & Mathematical Sciences and the School of Materials Science & Engineering. She also serves as a Visiting Professor at Queen Mary University of London. Her research focuses on advanced materials for optoelectronic applications, particularly perovskite-based photovoltaics, solar cells, and quantum well systems. Bruno earned her B.Sc., M.Sc., and Ph.D. in Physics from the University of Naples Federico II, Italy, followed by post-doctoral work at Imperial College London. She has held roles as a Senior Scientist at ENEA (Italy) and Principal Scientist at NTU’s Energy Research Institute (ERI@N). Her academic expertise spans perovskite synthesis, device engineering, and scalable manufacturing processes. Key contributions include studies on thermal evaporation methods for perovskite thin films, quantum cutting mechanisms in doped perovskites, and the development of highly efficient solar cells. Bruno’s work bridges fundamental materials science with applied energy technologies, emphasizing sustainable and commercializable solutions. Her publications highlight innovations in perovskite optoelectronics, such as quantum well design, infrared photodetectors, and machine learning-optimized materials. Bruno collaborates widely in interdisciplinary projects, aiming to advance green energy systems through cutting-edge materials research.

• Semiconductor Device Modeling
• Field Effect Transistors (FETs)
• Radiation Effects on Integrated Circuits
• +۳ مورد دیگر

Jean-Michel Sallese is a Senior Researcher at École polytechnique fédérale de Lausanne (EPFL), affiliated with multiple units including the Group of Semiconductor Devices (GR-SCI-IEL) , SEL-ENS , and EDMI-GE . His work focuses on semiconductor device modeling, biosensors, radiation effects in electronics, and microfluidic systems. Research Areas: Field Effect Transistor (FET) physics and modeling Radiation-induced soft errors in integrated circuits High-energy particle solid-state sensors Nanowire and junctionless FET biosensors Microfluidic mixer modeling Recent publications highlight advancements in ISFET biosensors , radiation-hard CMOS , and negative capacitance FETs , with applications spanning medical diagnostics, high-energy physics, and industrial monitoring. He supervises PhD students and co-developed the EDLAB initiative for device modeling. Teaching includes core electronics courses and specialized topics like Modeling Micro-/Nano-Field Effect Devices . No scientific awards are explicitly mentioned in the provided texts.

Arijit Raychowdhuryمشاهده پروفایل

استاد

• Low Power Digital Circuits
• Compute-in-Memory (CIM)
• Adaptive Clocking and Power Management
• +۷ مورد دیگر

Arijit Raychowdhury is a Professor and the Steve W. Chaddick School Chair at Georgia Tech's School of Electrical and Computer Engineering (ECE). He leads the Center for the Co-Design of Cognitive Systems (CoCoSys) and directs the DoD-sponsored SCALE Workforce Development Program in SoC Design. Current affiliations: Georgia Tech (ECE), Integrated Circuits and Systems Research Lab Prior affiliations: Intel Corporation (6 years), Texas Instruments (1.5 years) Research interests focus on low-power circuits, compute-in-memory (CIM) systems, cryogenic electronics, and neuro-symbolic AI. His work bridges circuit design with emerging device technologies and machine learning applications. Scientific contributions include: Over 250 publications and 27 patents Leadership in top conferences (ISSCC, VLSI Symposium, DAC, CICC) Pioneering 3D Gaussian Splatting acceleration, adaptive echo-cancellation networks, and CIM architectures Advancing GaN-based power converters and cryogenic CMOS Awards : IEEE Fellow (2022) SRC Technical Excellence Award (2021) Qualcomm Faculty Award (2021, 2020) IEEE/ACM Innovator under 40 (2018) Intel Young Faculty Award (2015) Dimitris N. Chorafas Award (2007) Leadership : • Director of CoCoSys Center • Site Director for SCALE Program • Distinguished Lecturer, IEEE Solid-State Circuits Society

Dragan Bosnackiمشاهده پروفایل

استادیار

• Machine Learning
• Bioinformatics
• Computational Biology
• +۶ مورد دیگر

Dragan Bosnacki is an Assistant Professor at Eindhoven University of Technology (TU/e), holding joint appointments in the departments of Biomedical Engineering and Mathematics and Computer Science. He specializes in interdisciplinary research at the intersection of computer science and biomedicine, with a focus on machine learning, bioinformatics, and computational modeling of medical therapies. His work combines formal verification techniques, GPU-accelerated algorithms, and biomedical applications such as High Intensity Focused Ultrasound (HIFU) therapy modeling. Dr. Bosnacki earned his BSc in Electrical Engineering and MSc in Computer Science from Sts. Cyril and Methodius University (Macedonia), followed by a PhD in Mathematics and Computer Science at TU/e under Professors Jos Baeten and Dennis Dams. He has pioneered advancements in parallel model checking and contributed significantly to the SPIN model checking tool. His research also spans separation logic, biomedical data analytics, and the application of mathematical methods to biological systems. Education: BSc in Electrical Engineering, Sts. Cyril and Methodius University (Macedonia) MSc in Computer Science, Sts. Cyril and Methodius University (Macedonia) PhD in Mathematics and Computer Science, TU/e (2001) Research Interests: Mechanisms of machine learning for biomedical data Formal verification of hardware/software systems GPU-optimized algorithms for computational biology Mathematical modeling of HIFU cancer therapies Reconstruction of biological networks and drug response modeling Teaching: Advanced programming and biomedical data analysis Simulation of biochemical systems Programming for data analytics Capita selecta in bioinformatics Thermodynamics & chemical kinetics Key Contributions: Co-developed GPU-based model checking tools (e.g., GPUexplore) Improved partial-order and symmetry reduction techniques Contributions to the SPIN model checker and VeriFast tool Advising: Supervised 37 academic works, focusing on interdisciplinary projects in computational biology and formal methods.

Juan Núñezمشاهده پروفایل

استاد پژوهشی

• Tunnel Field-Effect Transistors (TFET)
• Low-power electronics
• Emerging semiconductor technologies
• +۶ مورد دیگر

Juan Núñez is a Research Professor at the Microelectronics Institute of Seville (IMSE-CNM), part of the Spanish National Research Council (CSIC). His primary research focus lies at the intersection of emerging semiconductor technologies and novel computing paradigms, with particular expertise in tunnel field-effect transistors (TFETs) and their applications in low-power circuit design. Institution: Spanish National Research Council (CSIC) Research Institute: Microelectronics Institute of Seville (IMSE-CNM) Specialization: TFET, Pipeline, Variability, Low-power, Emerging technologies, RTD, NDR, Emerging devices, Dynamic logic Professor Núñez's research portfolio demonstrates a strong evolution from traditional digital circuit design toward emerging computing paradigms. His early work focused on optimizing conventional CMOS circuits and exploring tunnel transistors as potential successors to traditional MOSFETs. More recently, his research has pivoted toward neuromorphic computing, particularly oscillatory neural networks and Ising machines implemented with emerging devices. His work bridges the gap between device physics, circuit design, and computational applications, with a consistent emphasis on energy efficiency. The trend in his recent publications (2020-2024) shows a significant shift toward neuromorphic computing applications, particularly using phase transition materials and oscillatory networks for solving complex optimization problems. His research on VO 2 (vanadium dioxide) based Ising machines represents cutting-edge work in non-von Neumann computing architectures that could potentially solve NP-hard problems more efficiently than conventional computers.

Michael Riveraمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Digital Fabrication
• Computational Design
• +۴ مورد دیگر

Michael Rivera is an Assistant Professor of Computer Science at the ATLAS Institute, University of Colorado Boulder. He directs the Utility Research Lab—a highly interdisciplinary group that invents and investigates digital manufacturing technology by combining materials science, computational fabrication, and sustainable design practices. His research has been published in premier human-computer interaction venues including ACM CHI, UIST, DIS, and IMWUT, and featured in national media outlets such as NPR's All Things Considered, Ars Technica, and CBS News. Dr. Rivera earned his Ph.D. and M.S. in Human-Computer Interaction from Carnegie Mellon University's Human-Computer Interaction Institute, where he was advised by Scott Hudson. Prior to CMU, he completed a M.S.E in Computer Graphics and Game Technology and a B.S.E in Digital Media Design at the University of Pennsylvania, and worked as a software engineer at Facebook. Michael Rivera's research focuses on sustainable digital fabrication techniques that democratize access to manufacturing tools while addressing environmental concerns. His work explores bio-based materials, computational recycling approaches, and low-cost fabrication methods. The Utility Research Lab has developed innovative projects including the Desktop Biofiber Spinning Machine for Smart Textiles Design and techniques for 3D Printing with Spent Coffee Grounds. His research bridges materials science, computational design, and human-centered approaches to create more accessible and environmentally responsible fabrication technologies. Rivera's publication record shows a clear trajectory toward increasingly sophisticated computational approaches to sustainable manufacturing. His recent work emphasizes material recycling processes, biofiber development, and computational design pipelines that enable disassembly and reuse of fabricated objects. This research direction reflects a commitment to addressing the environmental impact of digital fabrication while expanding its accessibility to diverse users and contexts. CRA/CCC Computing Innovation Fellowship Google CMD-IT Dissertation Fellowship Carnegie Mellon University Sansom Endowed Presidential Fellowship Adobe Research Fellowship Honorable Mention Xerox Technical Minority Scholarship Dr. Rivera is actively recruiting PhD students to join the Utility Research Lab, demonstrating his commitment to mentoring the next generation of researchers in human-computer interaction and digital fabrication. His research has been supported by prestigious fellowships including the NSF/CRA Computing Innovation Fellowship. He collaborates extensively with researchers across institutions, as evidenced by his co-authorship with scholars from various universities. The Utility Research Lab, directed by Dr. Rivera, serves as a hub for interdisciplinary innovation in digital fabrication. The lab has developed several notable projects that reflect its mission to advance science and engineering while positively impacting people, society, and the environment through sustainable design practices. Current work focuses on computational approaches to material recycling, biofiber design, and novel animation techniques that make fabrication more accessible and environmentally responsible.

Daniela Bortolettoمشاهده پروفایل

استاد

• Particle Physics
• Experimental High-Energy Physics
• Silicon Detectors
• +۵ مورد دیگر

Professor Daniela Bortoletto is Professor and Head of the Particle Physics subdepartment at the University of Oxford, holding a Nicholas Kurti Senior Research Fellowship at Brasenose College. She leads the UK ATLAS collaboration and serves as Deputy Scientific Coordinator of the EU Network AIDA. Her academic journey includes distinguished professorships at Purdue University prior to joining Oxford in 2013. Her research focuses on experimental particle physics within the ATLAS experiment at CERN's Large Hadron Collider. Bortoletto was a key member of the team that discovered the Higgs boson in 2012 and continues to investigate Higgs boson properties, dark matter couplings, and higher-mass Higgs-like particles. Her expertise spans silicon detector development, particularly for the ATLAS inner tracking system upgrade, and she has made significant contributions to Higgs physics through precision measurements of production mechanisms and decay channels. Bortoletto's recent publications demonstrate leadership in cutting-edge detector technology (MALTA2 sensors), novel statistical methods (neural simulation-based inference), and comprehensive Higgs boson characterization. Her work addresses fundamental questions in particle physics through both experimental innovation and sophisticated data analysis techniques. Fellow of the Institute of Physics (2015) Fellow of the American Association for the Advancement of Science (2013) Fellow of the American Physical Society (2004) Alfred P. Sloan Fellow (1994-1996) Ruth and Joel Spira Award for Excellence in Undergraduate Education (2004) Bortoletto maintains extensive leadership in international collaborations, serving on numerous advisory committees including the UK STFC LBNF DUNE PIP-II Oversight Committee and the Scientific Advisory Panel for Belgium's be.h Excellence of Science program. Her editorial work for Nuclear Instruments and Methods reflects her commitment to advancing detector physics methodology. She actively participates in major detector upgrade projects for the High-Luminosity LHC, focusing on silicon pixel technology that will handle the increased collision rates from 2022 onward.

Tommaso Polonelliمشاهده پروفایل

مدرس

• Embedded systems
• IoT
• Wireless Sensor Networks
• +۷ مورد دیگر

Dr. Tommaso Polonelli is a Lecturer and Postdoctoral Researcher at ETH Zürich's Department of Information Technology and Electrical Engineering, affiliated with the Center for Project-Based Learning (PBL). He leads teaching initiatives and research in IoT systems, energy-efficient electronics, and autonomous technologies. His research focuses on energy-efficient systems, smart sensing, and ultra-low power computing, with applications in UAVs, wind turbine monitoring, and wearable devices. He also serves as a Scientific Advisor at RTDT Laboratories AG, an ETH spin-off. Polonelli holds a PhD (2020) and Master’s degree (2017) in Electronic Engineering from the University of Bologna. He has co-authored over 60 publications and received awards such as the Spark Award (2021), KITE Award finalist (2024), and the Certificate of Achievement for National Scientific Qualification (2023). He is an active IEEE member and contributes to both academia and industry through innovations in sensor technology and predictive maintenance. His work emphasizes interdisciplinary collaboration, with projects ranging from structural health monitoring to AI-enhanced systems. Recent efforts include Aerosense—a MEMS-based monitoring system for wind turbines—and ElectraSight, a smart eyewear platform with non-invasive eye tracking.

• Quantum Computing
• Quantum Thermodynamics
• Nanotechnology
• +۳ مورد دیگر

Dr. Federico Fedele is a Senior Research Fellow in the Materials Department at the University of Oxford, holding the W. W. Spooner Junior Research Fellowship in Engineering since 2022. He earned his undergraduate and Master's degrees in Physics from the University of Modena and Reggio Emilia and completed his PhD at the Niels Bohr Institute in Copenhagen, focusing on semiconductor quantum devices for quantum computing. His research centers on quantum technologies, including nanoscale quantum devices for quantum information encoding and manipulation, and hybrid systems coupling quantum entities with nanomechanical resonators. He investigates thermodynamic aspects of quantum information processing, particularly the energetics of quantum-to-classical transitions. His work also integrates machine learning for optimizing quantum device performance and stability. Fedele’s contributions include advancing quantum dot array simulations (QArray) and developing autonomous tuning algorithms for spin qubits. He has published extensively on topics such as quantum thermodynamics, spin-mechanical couplings, and AI-driven quantum control systems. Awards: W. W. Spooner Junior Research Fellowship (2022) Labs/Teams: Machine Learning Research Group at the University of Oxford His research bridges fundamental physics and applied quantum engineering, with implications for scalable quantum computing and nanoscale thermodynamics.

Kerem Çamsarıمشاهده پروفایل

دانشیار

• Micro- and Nanoscale Engineering
• Photonics
• Electronics
• +۳ مورد دیگر

Kerem Çamsarı is an Associate Professor in the Department of Electrical and Computer Engineering at the University of California, Santa Barbara (UCSB). He leads the Orchestrating Physics for Unconventional Computing (OPUS) Lab, focusing on interdisciplinary research that bridges materials science, device engineering, and computational systems. His work emphasizes exploiting novel materials and phenomena to design energy-efficient electronic circuits and architectures, diverging from traditional Moore's Law-driven approaches. Çamsarı holds a PhD and BS from Purdue University and Middle East Technical University, respectively, and completed a postdoc at Purdue. Research Interests : Micro- and nanoscale engineering, photonics, spintronics, probabilistic computing, and unconventional computing systems. His lab develops innovative hardware solutions for combinatorial optimization, probabilistic inference, and quantum-inspired algorithms using stochastic magnets and spintronic devices. Publications : Recent work focuses on Ising machines, probabilistic computing architectures, and spintronics-based hardware. Key themes include scalable connectivity solutions, low-power electronics, and hybrid CMOS-stochastic systems. Awards : Misha Mahowald Prize NSF Early CAREER Award IEEE Magnetics Society Early Career Award Advising & Grants : Active in securing NSF grants for probabilistic computing and neuromorphic systems. Collaborates on hardware-aware machine learning frameworks. Labs & Teams : OPUS Lab explores physics-to-systems integration, emphasizing cross-disciplinary innovation in computing architectures.

• Quantum Computing
• Quantum Metrology
• Semiconductor Nanotechnology
• +۳ مورد دیگر

Alessandro Rossi is a University Reader in the Department of Physics at the University of Strathclyde and leads the Semiconductor Quantum Electronics Lab (SEQUEL). He holds a UKRI Future Leaders Fellowship and a Measurement Fellowship at the National Physical Laboratory. His research focuses on quantum computing, quantum metrology in semiconductors, and hybrid superconductor-semiconductor nanotechnology. Education: BSc and MSc (summa cum laude) in Electronic Engineering from the University of Naples Federico II (2003). PhD in Physics from the University of Cambridge (2011), with a dissertation on microwave-assisted charge transport in single-electron transistors. Postdoctoral work included positions at Hitachi Cambridge Lab (UK), University of New South Wales (Australia), and a Marie Curie Fellowship at Cambridge (2016–2018). Research Interests: Development of silicon-based quantum devices, single-electron pumps, cryogenic metrology systems, and superconductive-semiconductor hybrids. Key achievements include record-accurate electric current generation in silicon devices and £3M in competitive research funding. Scientific Awards: Australia’s National Measurement Institute Prize (2015), UKRI Future Leaders Fellowship (2019), Emerging Leader 2021, and multiple institutional awards. Grants & Projects: Principal/Co-Investigator on projects like 'Empowering Practical Interfacing of Quantum Computing' (£3M+ funding from UK/EU/Australian agencies). Active in quantum hardware development, cryogenic systems, and quantum metrology. Labs & Teams: Semiconductor Quantum Electronics Lab (SEQUEL) focuses on translating quantum technologies into practical applications. Collaborations span academia and industry, including National Physical Laboratory and Hitachi.

Sarah Burkeمشاهده پروفایل

دانشیار

• Nanoscale Electronic Materials
• Optoelectronic Materials
• Scanning Probe Microscopy
• +۵ مورد دیگر

Sarah Burke is an Associate Professor at the University of British Columbia with joint appointments in the Department of Physics & Astronomy and the Department of Chemistry under the Faculty of Science. Her research focuses on nanoscale electronic and optoelectronic materials, utilizing advanced scanning probe microscopy (SPM) techniques such as atomic force microscopy (AFM) and scanning tunneling microscopy (STM) in ultrahigh vacuum and low-temperature environments. Education: PhD, Physics (McGill University, 2009) MSc, Physics (McGill University, 2005) BSc(Hons), Physics with minor in Chemistry (Dalhousie University, 2002) Research Interests: Sarah’s work bridges nanoscale materials characterization and electronic/optoelectronic device development. Key themes include: Understanding organic semiconductor interfaces through molecular-scale imaging and spectroscopy Investigating graphene and other 2D materials for strain-induced electronic phenomena Developing novel SPM-optical hybrid techniques for clean energy applications Exploring surface science challenges in nanoscale photovoltaics and molecular electronics Scientific Awards: Canada Research Chair (Tier 2) in Nanoscience (2010, renewed 2015) Peter Wall Institute for Advanced Studies Early Career Scholar Award (2011) Associate Member of CIFAR Nanoelectronics Program (2010-2012) NSERC Postdoctoral Fellowship (2009-2010) Advising & Grants: Burke’s group supports interdisciplinary graduate training, with experience in collaborative research programs. Her grants include Canada Research Chair funding and NSERC fellowships. Labs & Teams: She leads the UBC Laboratory for Atomic Imaging Research (LAIR), pioneering SPM techniques for atomic-scale characterization of nanomaterials.

• Microfluidics
• Acoustofluidics
• Surface acoustic waves
• +۷ مورد دیگر

Professor Julien Reboud is a prominent researcher in Biomedical Engineering at the University of Glasgow, specializing in the integration of engineering and biology for healthcare applications. With extensive experience from his PhD in France and postdoctoral work in Singapore, he has established a strong track record in microfluidic systems development for cell-based assays, diagnostics, and drug discovery. His work bridges the gap between academic research and commercial applications, having co-founded companies like SAW Dx Ltd and NebuFlow Ltd. Reboud's research focuses on three main areas: acoustofluidics for sample manipulation with diagnostic applications, synthetic biology using microfluidics for artificial cell platforms, and low-cost/zero-cost diagnostics for resource-limited settings. His work emphasizes developing technologies suitable for low-resource environments, particularly in the developing world, where acoustic platforms offer low-cost, low-power solutions for complex bioassays without requiring large infrastructure. His expertise spans microfluidics, surface acoustic waves, phononics, microfabrication, cell-based assays, and synthetic biology. His recent publications demonstrate a strong emphasis on point-of-care diagnostic technologies, particularly for infectious diseases and veterinary applications. There's a clear trend toward developing integrated solutions that combine microfluidics with smartphone technology, blockchain, and AI for decision support in field settings. His work increasingly addresses global health challenges, with multiple publications focused on diagnostics for use in developing countries and resource-limited environments. The Royal Academy of Engineering ERA Foundation Entrepreneurs prize PhD prize in the French national start-up competition (2004) Highly Commended Technology and Innovation at the Times Higher Education Awards (2014) Professor Reboud has successfully translated his research into commercial applications through spin-out companies SAW Dx Ltd and NebuFlow Ltd. His work demonstrates strong industry collaboration, particularly in integrating microfluidic systems for diagnostics and drug discovery. His research group actively collaborates with healthcare professionals and researchers in Africa to develop and deploy diagnostic innovations in low-resource settings. With over 70 peer-reviewed publications and 15 patent applications (2 granted), his work has significant impact in both academic and commercial spheres. His research group develops advanced techniques for designing and fabricating acoustic systems, novel assay designs, and paper-based microfluidic solutions. The team works extensively on creating open innovations in diagnostics that can be deployed in resource-limited settings, covering both materials/processes for assays and digital technologies for field decision support.

• Nanoelectronics
• Quantum Computing
• Semiconductor Devices
• +۵ مورد دیگر

Jing Guo is a Professor in the Department of Electrical & Computer Engineering at the University of Florida. Her primary research area is electrophysics, focusing on modeling, simulation, and design in nanoelectronics and quantum computing. She has made significant contributions to the study of spin qubits, ferroelectric tunnel junctions, and 2D materials like MoS2 and WSe2. Guo holds a PhD in Electrical Engineering from Purdue University (2004), an MS from Shanghai Jiao Tong University (2000), and a BSEE from the same institution (1998). Her work bridges computational methods with experimental device fabrication, emphasizing multiscale simulations and machine learning integration. Her research interests span quantum device modeling, nanoelectronics performance optimization, and reconfigurable electronics. Notable achievements include developing hybrid machine learning-physical models for nanotransistors and advancing low-resistance contact engineering in 2D semiconductors. Honors: NSF CAREER Award (2009) Labs: Engages in quantum computing and nanoelectronics labs at UF, focusing on device simulation and materials innovation. Her publications span over two decades, with recent work emphasizing quantum noise analysis, ferroelectric junctions, and van der Waals heterostructures. Collaborations include industry partnerships for scalable nanoelectronics solutions.

Alex Cassonمشاهده پروفایل

استاد

• Biomedical Engineering
• Wearable Sensors
• Flexible Electronics
• +۵ مورد دیگر

Prof. Alex Casson is a Professor of Biomedical Engineering at the University of Manchester, School of Engineering. He specializes in non-invasive bioelectronic interfaces, wearable sensors, and flexible electronics for health monitoring. His work spans ultra-low power sensor design, signal processing, and closed-loop systems for conditions like chronic pain, sleep disorders, and kidney disease. He holds cross-disciplinary roles, including Visiting Reader at the University of Leeds and Honorary Reader at Northern Care Alliance NHS Trust. Prof. Casson leads the Manchester Bioelectronics Network and is Bioelectronics Technology Lead at the Henry Royce Institute. Education: MEng (Engineering Science, University of Oxford), PhD (Imperial College London). Awards include the IET JA Lodge Award (2013), Eryl Cadwaladr Davies Prize (2010), and Fellowships from the Alan Turing Institute (2021–2023) and Academy of Medical Sciences (2022–2024). Research focuses on multi-disciplinary projects funded by EPSRC, Wellcome Trust, and EU Horizon 2020. Key projects include the Long Covid multidisciplinary consortium, ROBOCOENOSIS (EU H2020), and bioelectronic circadian rhythm monitoring. His lab develops low-power wearable devices, AI-driven signal processing, and commercializable technologies (e.g., spin-out companies funded via Venture Further awards). Leadership roles include Chair of the IET Healthcare Technologies Network, IEEE Senior Member, and outreach coordinator for widening participation in engineering. He supervises PhD students and mentors postdoctoral researchers in bioelectronics, sensor design, and healthcare technologies. Impact includes over £20M in research funding, 177+ publications, and open-access datasets/software (e.g., EEG/PPG signal databases on PhysioNet). His work addresses SDGs such as Good Health (SDG3), Affordable Energy (SDG7), and Industry Innovation (SDG9).