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Professor Bharat Bhuva is a faculty member in the School of Engineering at Vanderbilt University, holding the position of Professor of Electrical Engineering and Computer Engineering . His research focuses on radiation effects on integrated circuits, semiconductor device modeling, and VLSI design, with an emphasis on advancing the resilience of nanoscale electronics against single-event effects and total-ionizing-dose damage. He also investigates emerging technologies like FinFET and FDSOI for improved radiation hardness and performance. Education: Ph.D. in Electrical Engineering, North Carolina State University M.S. in Electrical Engineering, North Carolina State University B.S. in Electrical Engineering, Maharaja Sayajirao University Research Interests: Professor Bhuva’s work spans computer-aided design tools, semiconductor process modeling, and the mitigation of radiation-induced failures in advanced integrated circuits. His studies address challenges posed by scaling to smaller technology nodes (e.g., 3-nm FinFET) and the impact of environmental factors like temperature, bias conditions, and neutron exposure on circuit reliability. Key areas include multicell upsets, single-event upset (SEU) cross-section analysis, and the efficacy of radiation-hardened-by-design (RHBD) techniques. Awards & Recognition: None explicitly listed in the provided text. However, his extensive publications in top-tier journals like IEEE Transactions on Nuclear Science highlight his contributions to the field. Grants & Advising: Advises on projects related to advanced semiconductor technologies and radiation effects. His research has been supported by grants from institutions focusing on space electronics and nanotechnology. No specific grant details or student advisees are listed. Labs & Teams: Likely affiliated with Vanderbilt’s Cyber-physical Systems and Nano Science and Technology research neighborhoods, though specific lab names are not mentioned in the text.

• Computer-Aided Design
• Radiation Effects on Electronics
• Semiconductor Device Modeling
• +3 more

Naglaa Elagamy is an Associate Teaching Professor in the Department of Mechanical and Manufacturing Engineering at Ontario Tech University. She holds a Ph.D. in Mechanical Engineering from Carleton University (2015), an M.A.Sc. in Engineering from Alexandria University (2002), and a B.Sc. in Engineering from the same institution (1994). As a licensed Professional Engineer (P.Eng.) in Ontario (2016–present) and a Certified SolidWorks Associate (CSWA), her expertise spans advanced composite materials, micro-CT imaging, stress simulation, and fatigue assessment of composite structures. Her research focuses on predicting progressive damage in materials and applying micro-CT for quantitative and qualitative damage analysis in carbon fiber reinforced polymers (CFRP). She has also explored aerodynamic performance optimization of small unmanned aerial vehicles (UAVs) through propeller design studies. Elagamy’s publications and presentations emphasize interdisciplinary approaches, combining experimental techniques like micro-CT with computational methods such as the Cohesive Zone Model and Finite Element Analysis. Her work addresses challenges in composite material durability, structural integrity, and multi-mode fatigue behavior. Beyond research, she contributes to teaching core mechanical engineering courses, including Kinematics and Dynamics of Machines, Statics, Solid Mechanics, and Computer-aided Design. Her professional recognitions include the Carleton University Development Grant (2014) and the AUD Recognition for Services (2018). Her advising and grants activities are not explicitly detailed here, but she has secured funding for her research at Carleton University. She is affiliated with the Faculty of Engineering and Applied Science and collaborates with industry and academic conferences such as SAMPE and CAMX. While specific lab affiliations are not mentioned, her research aligns with cutting-edge structural and materials analysis within the department.

• Advanced Composite Materials
• Micro Computed Tomography (micro-CT)
• Stress Simulation
• +6 more

Roland N. Horne is the Thomas Davies Barrow Professor of Earth Sciences at Stanford University and Senior Fellow at the Precourt Institute for Energy. He holds positions in the Department of Energy Science & Engineering and is an Affiliate at the Stanford Woods Institute for the Environment. With degrees from the University of Auckland (BE, PhD, DSc), Horne has established himself as a leading expert in geothermal reservoir engineering and energy production optimization. His research focuses on inverse problems in reservoir modeling, including tracer analysis of fractures, computer-aided well test analysis, production schedule optimization, and automated history matching. Horne has made significant contributions to understanding geothermal reservoir engineering and multiphase flow of boiling fluids through porous materials and fractures. The analysis of his recent publications (2023-2025) reveals a strong emphasis on enhanced geothermal systems (EGS), with particular focus on flexible operations, economic modeling, and advanced characterization techniques. His work increasingly incorporates machine learning approaches for reservoir analysis and has expanded into microbial tracing methods for interwell connectivity assessment. There's also significant attention to US geothermal resource potential and integration into the broader energy transition. Honorary Member of the Society of Petroleum Engineers Member of the US National Academy of Engineering Multiple SPE Distinguished Lecturer appointments (1998, 2009, 2020) John Franklin Carl Award recipient Five Best Paper awards from Geothermal Resources Council Patricius Medal from German Geothermal Society Core Values Award from Women in Geothermal (2023) Horne has supervised 60 PhD and 135 MS students throughout his career. His current teaching includes undergraduate and graduate courses in Fundamentals of Energy Processes, Geothermal Reservoir Engineering, Mass and Energy Transport in Porous Media, and Well Test Analysis. He previously served as President of the International Geothermal Association (2010-2013) and Technical Program Chair for multiple World Geothermal Congress events. Horne maintains active research collaborations worldwide, including with the University of Tokyo (where he was a Fellow of the School of Engineering in 2016) and China University of Petroleum. His current research group focuses on advancing EGS technologies and developing more accurate reservoir characterization methods for geothermal applications.

• Geothermal reservoir engineering
• Energy production optimization
• Well test interpretation
• +8 more

Federica Sandrone is a Lecturer at the School of Architecture, Civil and Environmental Engineering (ENAC) at École Polytechnique Fédérale de Lausanne (EPFL), where she also serves as a Scientist at the Laboratory of Experimental Rock Mechanics (LEMR) within the Institute of Civil Engineering. Her academic career spans over 15 years with continuous contributions to tunnel engineering and rock mechanics research. Her research focuses on the intersection of rock mechanics and tunnel engineering, with particular expertise in tunnel pathology analysis, TBM performance in challenging geological conditions, and long-term tunnel behavior. Sandrone's work bridges theoretical analysis with practical engineering applications, addressing real-world problems in tunnel infrastructure management and maintenance. Her research methodology combines field investigations, laboratory testing, and numerical modeling to understand complex geomechanical behaviors. Analysis of her recent publications reveals a consistent focus on tunnel inspection methodologies, TBM performance prediction in difficult ground conditions, and the long-term behavior of tunnel structures. Her work has evolved from fundamental tunnel pathology studies to more advanced applications involving GIS integration, probabilistic modeling, and modern inspection techniques including laser scanning and image analysis. Engineer at SBB-Infrastructure (2008-present) responsible for Tunnels Management and Maintenance Assistant for Tunnel Engineering courses (2007-present) PhD supervision including Erika Paltrinieri's 2015 thesis on TBM performance Development of tunnel inspection methodologies and condition assessment procedures Her teaching activities include courses in Rock Mechanics and Underground Construction, where students learn about the mechanical behavior of rock materials, tunnel excavation and support design, planning and management of underground works, and risk assessment in tunnel construction.

• Rock Mechanics
• Tunnel Engineering
• Underground Construction
• +4 more

Dr. Tathagata Bhaduri is a Lecturer in the Department of Civil and Environmental Engineering at Rensselaer Polytechnic Institute (RPI). He holds a Ph.D. in Civil Engineering from RPI (2021), an M.Tech. from the Indian Institute of Technology, Kanpur (2016), and a B.E. from the Indian Institute of Engineering, Science and Technology, Shibpur (2014). His research focuses on computational modeling of ultra-high-performance concrete (UHPC), particularly multi-scale techniques, fiber orientation effects, and failure modes in UHPC structures. He also explores smart systems for structural vibration control using bracing and fluid dampers. Dr. Bhaduri teaches core courses including Strength of Materials and Engineering Economics, and served as the course coordinator for Strength of Materials in Fall 2023. His professional involvement includes contributions to the American Concrete Institute (ACI) 239C committee, aiding in UHPC design guide development. His publications emphasize UHPC's mechanical properties, multi-scale modeling, and fiber-reinforced material behavior. Research trends highlight interdisciplinary approaches combining experimental and computational methods to address structural challenges in advanced materials.

• Concrete Materials Science
• Structural Engineering
• Computational Modeling
• +4 more

Dr. Sumanta Das is an Associate Professor and Graduate Director in the Department of Civil and Environmental Engineering at the University of Rhode Island. His research focuses on sustainable infrastructure materials, with particular expertise in cementitious materials, composite structures, and advanced computational modeling techniques. He directs a vibrant research group that bridges experimental mechanics with computational modeling and machine learning approaches to address challenges in infrastructure durability and performance. Dr. Das received his educational training from prestigious institutions: Ph.D. in Materials and Structures from Arizona State University (2015) M.Tech. in Structural Engineering from Indian Institute of Technology, Kanpur (2012) B.E. in Civil Engineering from Jadavpur University (2010) His research interests center around developing sustainable and durable infrastructure materials through innovative design approaches. Dr. Das investigates microstructure-property relationships in cementitious systems, with special focus on materials containing microencapsulated phase change materials for freeze-thaw durability, fiber-reinforced composites, and smart cementitious materials with self-sensing capabilities. His work integrates advanced experimental techniques like nanoindentation with computational modeling approaches including finite element analysis, molecular dynamics simulations, and machine learning algorithms to predict material behavior and optimize performance. Dr. Das's recent publications demonstrate a clear trajectory toward integrating machine learning with traditional materials science approaches. His research group has made significant contributions to understanding the behavior of cementitious composites under extreme conditions, developing multifunctional composites with embedded sensing capabilities, and creating computational frameworks that bridge multiple scales from molecular to structural levels. The work shows increasing sophistication in combining experimental validation with predictive modeling. Dr. Das has successfully secured numerous research grants as PI or Co-PI from diverse funding sources including the Office of Naval Research, Department of Defense, US Department of Transportation, and industry partners like Goetz Composites. His research portfolio spans infrastructure durability, composite materials for marine applications, and smart sensing technologies for structural health monitoring. As an educator and mentor, Dr. Das has supervised multiple doctoral and master's students who have completed theses on topics including: Multiscale simulation and machine learning-assisted performance prediction for cementitious composites Performance-based multiscale tuning of inclusion-modified and 3D printed composites Enhancing freeze-thaw durability of cementitious composites through innovative materials design Underwater explosion response of composite structures Implosion pulse mitigation using additively manufactured filler profiles

• Sustainable Cementitious Materials
• Microstructure and Material Modeling
• Materials Design for Sustainable and Durable Infrastructure
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Farouq Ali is a Distinguished Professor in the Department of Petroleum Engineering at the University of Houston's Cullen College of Engineering. With over 40 years of experience spanning academia and industry, he is globally recognized as a leading expert in reservoir engineering and enhanced oil recovery techniques. Previously holding the Encana/Petroleum Society Chair at the University of Calgary, he has also served as a professor at Pennsylvania State University, University of Alberta, and University of Regina. His educational background includes: Ph.D. in Petroleum and Natural Gas Engineering, Pennsylvania State University M.S. in Petroleum and Natural Gas Engineering, Pennsylvania State University B.Sc. (Hons.) in Petroleum Production Engineering, Birmingham University, England B.Eng. in Electrical and Mechanical Engineering, Karachi University, Pakistan Professor Ali's research focuses on breakthrough methods for oil recovery from challenging reservoirs, particularly heavy oil systems. His pioneering work established micellar-polymer flooding as an industry standard and developed foundational steam injection techniques. Current investigations center on solvent-assisted thermal processes, pore-scale modeling of bitumen mobilization, and advanced reservoir simulation for optimizing steam-assisted gravity drainage (SAGD) and in-situ combustion. His 2015-2018 publications reveal a concentrated research trajectory toward integrating solvents with thermal recovery methods, developing non-equilibrium pore-scale simulators, and optimizing SAGD performance through analytical modeling. Key thematic clusters include solvent-steam synergies, temperature-dependent reservoir behavior, and field-scale implementation of advanced recovery techniques for oil sands and heavy oil deposits. His exceptional contributions are evidenced by prestigious accolades including: Election to the US National Academy of Engineering (2009) Anthony F. Lucas Gold Medal (SPE's highest technical honor, 2007) Kapitsa Gold Medal from Russian Academy of Sciences (1998) SPE Lester C. Uren Award (1996) Multiple SPE Distinguished Lecturer appointments Professor Ali maintains active industry engagement through over 250 reservoir studies and 30 major oilfield designs, advising governments and corporations on production strategies. His academic mentorship includes current Ph.D. candidate Seyed Mahdi Razavi, continuing his legacy of training petroleum engineering leaders. Research funding stems from extensive consulting contracts and collaborative industry projects focused on thermal recovery optimization. His laboratory investigations emphasize thermal recovery mechanisms and reservoir simulation, with current projects developing integrated solvent-steam models and advanced analytical tools for SAGD performance prediction. The research team maintains close industry partnerships for field validation of novel recovery techniques.

• Enhanced Oil Recovery
• Reservoir Engineering
• Heavy Oil Recovery
• +5 more

Dr. Aydin K. Sunol is a Professor of Chemical, Biological and Materials Engineering at the University of South Florida's College of Engineering. With a distinguished career spanning several decades, he leads the Environmentally Friendly Engineered Systems (EFES) Lab and serves as principal investigator for numerous research projects funded by NASA, DOD, NSF, and industry partners. Education: PhD in Chemical Engineering, VPI & SU, Blacksburg, Virginia MEng in Industrial Engineering and Operational Research, VPI & SU, Blacksburg, Virginia Diploma in Chemical Engineering, University of Aston, Birmingham, England BS in Chemical Engineering, Bogazici University, Istanbul, Turkey Dr. Sunol's research focuses on green engineering and chemistry, sustainability in the chemical industry, systems engineering, and cleaner energy conversion processes. His work integrates global computational methods, machine learning, product prototyping, and experimentation across multiple temporal and spatial scales. Recent projects include developing nano-structured photo-catalysts, therapeutic particles, and energetic materials using environmentally friendly pathways, as well as creating efficient fuel conversion processes utilizing supercritical fluids. His research demonstrates a consistent trend toward sustainable solutions that address fundamental challenges in materials science, energy conversion, and environmental protection through innovative application of supercritical fluid technology and computational methods. Scientific Awards: USF Chemical and Biomedical Engineering Department Outstanding Teaching Award, 2018 University of South Florida Outstanding Undergraduate Teaching Award, 2002-2003 Engineering Professor of the Year, 1984 Outstanding Professor of Chemical Engineering, VPI & SU, 1981 Outstanding Technology Innovation Award, Aerospace Space System Conference, 2010 As an educator, Dr. Sunol has advised 18 PhD and 29 Master's students, developing innovative teaching methods and curricula including NSF-funded Web-based Teaching Modules and Design Course Series. His research has been supported by diverse funding sources including DOE, NSF, NATO, UNESCO, NAVY, NASA, and numerous industry partners. Dr. Sunol also serves as principal partner and CTO of Temptroll LLC and Accent Creations LLC, which develop self-heating and cooling products, demonstrating the practical application of his research. The EFES Lab, which Dr. Sunol directs, brings together interdisciplinary researchers including chemical engineers, mechanical engineers, and computer scientists to tackle complex challenges in sustainable engineering. Current team members include PhD candidates working on nano-structured materials, wastewater management systems, and temperature modulation products, continuing the lab's tradition of innovation in environmentally friendly engineered systems.

• Green Engineering
• Supercritical Fluid Technology
• Systems Engineering
• +7 more

Dr. Yaguang Zhang is a Clinical Assistant Professor at Purdue University, jointly appointed in the Department of Agricultural & Biological Engineering (ABE) and the Department of Agricultural Sciences Education & Communication (ASEC) . Holding a Ph.D. in Electrical and Computer Engineering from Purdue (2021), he specializes in data science , digital agriculture , and UAV-aided wireless communication systems , with applications in intelligent transportation, proactive road maintenance, and engineering education. Education: Ph.D. and M.Sc. in Electrical and Computer Engineering (Purdue), B.Eng. in Communication Engineering (Tianjin University) Research Interests span cutting-edge domains including: Digital Agriculture: GPS-based field shape generation, product traceability trees, and automated metadata collection for agricultural operations Wireless Communication: Millimeter-wave channel modeling, UAV relay systems, and rural network coverage optimization Smart Infrastructure: Pavement condition assessment tools, sun-shadow simulation for road treatment, and vehicle automation platforms Recent Publications emphasize scalable solutions for agricultural IoT, machine learning in crop monitoring, and interoperable data frameworks. His scientific awards include: 2024 Outstanding Engineering Teacher (Purdue) 2024 ASABE Superior Paper Award 2020 FFAR Student Poster First Prize Multiple NSF/IEEE travel supports Grants from USDA, NSF, INDOT, and industry partners (CableLabs, Nokia) fund projects like tractor autopilot development, rural 6G networks, and pavement monitoring systems. He mentors graduate students in agricultural robotics , data science , and connected vehicle research .

• Data Science
• Digital Agriculture
• UAV-Aided Wireless Communication Systems
• +4 more

Associate Professor Phil Clausen is a computational biomechanics and wind energy expert at the School of Engineering, University of Newcastle . His career spans two major research themes: small wind turbine dynamics and fatigue testing and computational biomechanics of biological structures using finite element analysis (FEA). He has led the development of accelerated fatigue test programs for turbine blades and reverse-engineered iconic fossils like Smilodon fatalis and the Tasmanian Tiger to understand biomechanical evolution. Education: PhD and BEng (Hons) from University of Newcastle Research Expertise focuses on: Small wind turbine blade design, fatigue life prediction, and performance optimization Computational biomechanics of crocodiles, komodo dragons, and extinct species Publications (65+ journal articles) cover wind energy systems (2000–2020) and biomechanics (2005–2021), with high-impact work featured in Nature , PLoS ONE , and Royal Society B . Notable findings include debunking assumptions about sabre-toothed cat bite force and quantifying dingo vs. thylacine predatory mechanics. Grants ($1.06M+ total) include ARC Discovery Projects, industry partnerships with Aerogenesis Australia and TUNRA , and commercialization of diffuser-augmented turbine technology. He has supervised numerous research students and collaborated with interdisciplinary teams across engineering, biology, and paleontology.

• Small Wind Turbine Dynamics
• Computational Biomechanics
• Finite Element Analysis
• +3 more

Dr. Xuliang Li is a Postdoctoral Research Fellow at the School of Mechanical and Mining Engineering, The University of Queensland, within the Faculty of Engineering, Architecture and Information Technology. His work focuses on advanced materials processing, particularly in precision machining of brittle solids and nanoscale surface engineering. Research Themes: Brittle material machining, graphene oxide applications, machine learning integration in manufacturing, and multiscale modeling of deformation mechanisms Recent Publications: 14 studies (2019-2024) covering nanoscratch mechanics, laser 3D-printed ceramics, and innovative polishing techniques Funding: Currently developing ductile grinding techniques for dental prostheses applications (2025-2026) Expertise: Available for supervision in advanced manufacturing and materials science domains Key areas include computational modeling of grinding processes, hybrid nanoparticle suspensions, and ductile-to-brittle transition analysis. His collaborations span multiple disciplines in mechanical engineering and materials science.

• Materials Science
• Mechanical Engineering
• Nanotechnology
• +3 more

Professor Daniel Kujawski is a faculty member in the Department of Mechanical and Aerospace Engineering at Western Michigan University. His research focuses on advanced materials testing, fatigue and fracture mechanics, and cyclic behavior analysis of metals and composites. He has contributed significantly to understanding fatigue crack growth, damage characterization under fatigue loading, and the interplay between static and fatigue thresholds in engineering alloys. His work often explores novel methodologies for fatigue analysis, including the development of stress intensity factor models (e.g., Kmax-ΔK approaches) and the application of damage models like GTN. He has also investigated unique phenomena such as the 'Marci Effect' in long cracks and the role of chemical notches in stress-corrosion cracking. His research extends to additive manufacturing, examining materials like Inconel 718 under low-cycle fatigue conditions. Kujawski's publications emphasize empirical and theoretical advancements in fatigue crack growth prediction under varying stress ratios (R-ratios), environmental effects, and geometrical constraints. His work challenges historical debates, such as the 50-year controversy over fatigue crack closure mechanisms. He has developed web-based tools for fatigue analysis, including interactive Neuber’s master curve applications and cloud-based platforms for notch fatigue analysis. While no formal awards are listed, his prolific publication record reflects sustained contributions to mechanical engineering and materials science. His research addresses both fundamental and applied aspects of material durability, with implications for aerospace, automotive, and structural engineering applications.

• Computer-aided testing (CAT)
• Fatigue and fracture mechanics
• Metals and composites testing
• +3 more

Erkan Günpınar is an Associate Professor at the Department of Mechanical Engineering, Istanbul Technical University (ITU), specializing in Additive Manufacturing and Computer-Aided Design. His research focuses on optimizing printing paths, material properties, and geometric precision in additive manufacturing processes. He has pioneered work on lattice structures, patient-specific medical systems, and structural optimization for marine applications. Key research interests include generative design methodologies, support structure optimization, and machine learning applications in manufacturing. His work bridges engineering disciplines, integrating mechanical principles with computational techniques to solve complex design challenges. Awards: Best Presentation Award (2016, 2018), Outstanding Contribution in Reviewing (2016), Session Best Paper (2017) Projects: Includes initiatives on yacht hull optimization, cross-derivative surface modeling, and liquid flow-inspired printing paths Advising: Supervises 8 ongoing theses in additive manufacturing and geometric modeling Dr. Günpınar’s recent projects emphasize interdisciplinary collaboration, particularly in biomedical and marine engineering contexts. He actively contributes to journals like Journal of Manufacturing Processes and Computer-Aided Design .

• Additive Manufacturing
• Design Space
• Printing Path Optimization
• +5 more

Andrzej Wicher serves as Associate Professor and Head of the Department of Acoustics within the Faculty of Physics and Astronomy at Adam Mickiewicz University (UAM) in Poznań, Poland. His academic leadership extends to membership on the Council of Disciplines of Physical Sciences and Astronomy since 2016, and previous service as Deputy Director of the Institute of Acoustics (2016-2019). Internationally, he holds an honorary Adjunct Professor position at La Trobe University in Melbourne, Australia. Wicher's research spans psychoacoustics, audiology, and auditory neuroscience, with particular focus on tinnitus mechanisms, otoacoustic emissions (especially DPOAE), binaural hearing phenomena, and speech intelligibility assessment. His work integrates clinical applications with fundamental auditory system modeling, recently expanding into environmental noise impacts—particularly wind turbine acoustics—on cognitive functions. This research portfolio reflects through 15+ recent publications showing consistent interdisciplinary connections between auditory diagnostics, neurological assessment, and real-world sound environments. His scientific contributions are recognized through multiple Rector's Awards for both organizational and scientific activities at UAM (2015-2024). As an active member of the Polish Academy of Sciences' Committee on Acoustics, European Acoustical Society, and Polish Acoustical Society, he contributes to the global acoustics community while co-organizing major conferences including the Open Seminar in Acoustics and Fechner Day. Wicher's teaching program includes specialized courses in psychoacoustics, hearing diagnostics, and auditory system analysis. His research infrastructure benefits from international collaborations with institutions including University of Cambridge, Tohoku University, University of Manchester, and University of Minnesota, supported through national (NCN) and international (EU FP6, NOR/POLNOR) grants.

• Psychoacoustics
• Audiology
• Tinnitus Research
• +5 more

Dr. Jiang Li is a Professor in the Batten College of Engineering & Technology at Old Dominion University (ODU). He holds a Ph.D. in Electrical Engineering from the University of Texas at Arlington (2004), an M.S. in Automation from Tsinghua University (2000), and a B.S. in Electrical Engineering from Shanghai Jiao Tong University (1992). Before joining ODU in 2007, he was a postdoctoral fellow at the NIH's Department of Radiology (2004–2006). Dr. Li's research focuses on machine learning, medical imaging, and signal processing. His work spans computer-aided diagnosis systems for medical applications, neural networks, and modeling/simulation. He has led or co-led numerous grants, including funded projects on biomarker identification, robotic dental implantation, and hazard detection. His research trends emphasize interdisciplinary applications of AI, such as medical imaging analysis, remote sensing, and cybersecurity in engineering systems. Recent publications highlight advancements in deep learning for radiation estimation, seagrass mapping, and adversarial attack detection. Awards : NIH Fellows Award for Research Excellence (2006) UTA TxTEC Award (2003) Image Processing Scholarship (2002) Herman Fellowship (2000) Dr. Li's advising and grants reflect collaborations across disciplines, with notable contributions to biomedical engineering and computational methods. He has contributed to labs and teams in medical imaging, robotics, and environmental remote sensing.

• Machine Learning
• Computer-Aided Medical Diagnosis Systems
• Medical Signal/Image Processing
• +5 more