جست‌وجوی استاد و پژوهشگر

Jennifer Bragginمشاهده پروفایل

مدرس ارشد

• Engineering Management
• Semiconductor Manufacturing Yields
• Knowledge Management
• +۳ مورد دیگر

Jennifer Braggin is a Part-time Senior Lecturer at the Gordon Institute, School of Engineering, Tufts University. Her roles combine academic teaching with industry leadership, focusing on engineering management and semiconductor manufacturing. She currently serves as Director of Technology at Entegris, Inc., and has held multiple technical and managerial positions in the semiconductor industry. Education: M.S. in Engineering Management, Tufts Gordon Institute (2014) M.S. in Engineering Science (Microelectronics Manufacturing), Rensselaer Polytechnic Institute (2004) B.S. in Materials Science and Engineering, Lehigh University (2001) Research Interests: Jennifer specializes in semiconductor manufacturing yields, engineering leadership, and knowledge management. Her work emphasizes defect reduction, process optimization, and cross-functional collaboration in high-tech industries. She has contributed to advancements in filtration systems, lithography techniques, and yield improvement strategies. Recent Work Trends: Her publications focus on semiconductor process optimization, defect mitigation, and advanced materials handling. Key themes include point-of-use filtration, lithography variability reduction, and industry-wide reliability challenges. She frequently collaborates on conference proceedings for the SEMI Advanced Semiconductor Manufacturing Conference. Awards: 2021 SEMI Foundation Excellence in Achievement Award Teaching & Professional Activities: Jennifer teaches Engineering Leadership courses at Tufts and actively participates in industry committees like the Critical Materials Council. She has led over a dozen teaching modules since 2015, blending academic theory with real-world industry practices.

Carmelo De Mariaمشاهده پروفایل

دانشیار

• Bioengineering
• Biomedical Engineering
• Tissue Engineering
• +۵ مورد دیگر

Carmelo De Maria is an Associate Professor in Bioengineering at the Department of Information Engineering, University of Pisa. His research focuses on biofabrication, 3D/4D printing of sustainable biomaterials, and development of advanced medical devices for regenerative medicine. He leads projects in the Enrico Piaggio Research Center, emphasizing applications in tissue engineering, biomedical instrumentation, and low-resource healthcare solutions. Key research areas include: Bioprinting of self-deployable scaffolds for endoluminal tissue regeneration Development of in vitro microphysiological systems for disease modeling Sustainable biomaterials from biomass-derived polymers Open-source medical technologies for global health equity Recent work includes innovations in robotic-based in situ bioprinting, mechanical stimulation of cell cultures, and defect detection in additive manufacturing. His interdisciplinary approach bridges robotics, materials science, and clinical applications to address challenges in musculoskeletal, cardiovascular, and neural tissue engineering. Collaborative projects focus on international cooperation to enhance access to safe, affordable medical technologies in low-resource settings. He actively publishes in high-impact journals and contributes to regulatory frameworks for open-source medical devices.

Yongjia Xuمشاهده پروفایل

پژوهشگر ارشد

• Optical Surface Metrology
• Structured Light Techniques
• Phase Measuring Deflectometry
• +۴ مورد دیگر

Dr. Yongjia Xu is a Research Fellow at the Department of Engineering, School of Computing and Engineering, University of Huddersfield. He actively contributes to precision metrology through structured light technologies and serves as a core researcher for two EPSRC projects: The EPSRC Future Advanced Metrology Hub (EP/P006930/1) and A Multiscale Digital Twin-Driven Smart Manufacturing System (EP/T024844/1). PhD in Mechanical Engineering (University of Huddersfield, 2019) MSc in Instrument Science and Technology (Hebei University of Technology, 2014) BEng in Control Technology and Instrument (Hebei University of Technology, 2011) His research spans optical surface metrology , fringe projection , phase measuring deflectometry , and 3D optical measurement systems . Key expertise includes calibration algorithms , error compensation , and portable metrology for industrial applications. Recent publications highlight advancements in deep-learning-enabled 3D measurement , refraction error modeling , and digital twin frameworks for smart manufacturing. His work has been cited over 409 times (Scopus h-index: 12) and 375 times (Google Scholar h-index: 11). Awarded the 2019 Chinese Government Award for Outstanding Self-financed Students Abroad, he also serves as a peer reviewer for journals like Optics Express and PhotoniX . He is a member of Optica and SPIE.

• Ballistic Testing
• Structural Health Monitoring
• Building
• +۳ مورد دیگر

Kerim Ikikardaslar is a Subs.Assist.Professor of Mechanical Engineering at The City College of New York (CCNY). His research focuses on advanced materials and structural systems, with expertise in Ballistic Testing, Structural Health Monitoring, and Building technologies. He holds a position in the Department of Mechanical Engineering and is affiliated with Steinman Hall, Office 224. His research interests emphasize the behavior of composite materials under extreme conditions, including ballistic impacts and cyclic loading. He explores smart materials and self-sensing technologies for damage detection in advanced composites. Recent work includes studies on 3D-printed cellular structures and sensor-integrated nanocomposites for structural integrity assessment. In publications from 2014-2023, Dr. Ikikardaslar has investigated topics such as adhesive joint performance, carbon nanotube (CNT)-reinforced composites, and auxetic materials. Trends show a focus on material characterization under dynamic loads and structural health monitoring via electrical conductivity changes. No scientific awards are listed in the provided materials. Details about advising students or grant involvement are not explicitly stated. His work contributes to advancing composite material applications in aerospace, defense, and civil engineering sectors.

• Additive Biomanufacturing
• Biofabrication
• Computer-Aided Tissue Engineering
• +۷ مورد دیگر

Robert Chang is an Associate Professor and Associate Chair for Graduate Studies in the Department of Mechanical Engineering at Stevens Institute of Technology. His research focuses on Additive Biomanufacturing, Biofabrication, and Computer-Aided Tissue Engineering, with a strong emphasis on developing advanced materials and technologies for biomedical applications. He holds affiliations at the Charles V. Schaefer, Jr. School of Engineering and Science. His work integrates engineering principles with biological systems, emphasizing the design of microscale physiological models and biomimetic tissue constructs. Notable contributions include advancements in melt electrowriting, low-cost bioprinting systems, and mechanobiology studies. Dr. Chang has secured significant funding, including an NSF CAREER Award in 2016, and has authored over 100 peer-reviewed publications and patents in biomanufacturing and materials science. Research Highlights Development of fibrous constructs via melt electrohydrodynamic processes Design of gradient biomaterials for functional engineered tissues Open-source modular bioprinting systems Microscale in vitro models for drug screening Dr. Chang’s awards include the Sigma Xi NIST Best Poster Award (2011) and Drexel’s Best Dissertation Award (2009). He serves on editorial boards for journals like Macromolecular Materials and Engineering and International Journal of Bioprinting , and actively participates in professional societies such as ASME and ASEE. His work bridges academia and industry, with patents pending in bioprinting and microfluidic technologies. Ongoing efforts focus on advancing biomanufacturing for personalized medicine and regenerative therapies.

• Computer Vision
• Machine Learning
• Medical Imaging
• +۳ مورد دیگر

Qing En is a Post Doctoral Fellow at the School of Computer Science, Carleton University, hosted by Yuhong Guo. Their research focuses on advanced machine learning techniques, particularly in medical imaging, computer vision, and agricultural technology. Key areas include unsupervised learning, few-shot classification, and domain adaptation for applications such as plant disease detection, lung infection segmentation, and steel defect analysis. Their work emphasizes developing robust models for scenarios with limited labeled data. Research interests span computer vision applications, medical image segmentation, and deep learning frameworks. Notable contributions include innovations in attention-based neural networks, prototype-guided learning, and contrastive variance methods. Recent projects highlight cross-domain adaptation and exemplar-based approaches for improving segmentation accuracy in healthcare and industrial contexts. Publications reflect a consistent focus on solving real-world challenges through AI, with applications in agriculture, healthcare, and cybersecurity. No awards or grants are explicitly listed, though their prolific publication record underscores active research engagement.

• Machine Learning
• Time Series Analysis
• Generative Models
• +۶ مورد دیگر

Srinjoy Das is an Assistant Professor in Data Science at the School of Mathematical and Data Sciences, part of the Eberly College of Arts and Sciences at West Virginia University (WVU). He holds a Ph.D. and M.S. in Electrical Engineering and Statistics from the University of California, San Diego (2018), followed by postdoctoral research at UCSD’s Department of Mathematics until 2021. His research focuses on algorithms for predictive inference on time series, generative models, and efficient implementation of deep learning on edge computing devices. Education: Ph.D. in Electrical Engineering, UCSD (2018) M.S. in Statistics, UCSD (2018) Postdoctoral Researcher, UCSD Mathematics (2018–2021) Research Interests: Algorithms for real-time inference on generative neural networks Efficient implementation of deep learning on FPGAs and edge devices Time series analysis and nonparametric prediction Data-efficient learning in additive manufacturing and healthcare Recent Research Trends: His recent work emphasizes machine learning applications in manufacturing defect detection (e.g., melt pool characterization in 3D printing), geospatial analysis, and healthcare prediction systems. He also explores hybrid optimization strategies and bandwidth-efficient video processing techniques. Mentoring & Collaboration: Advised students on projects including FPGA-based neural network design (Xinyu Zhang), generative model evaluation (Ojash Neopane), and statistical inference for random fields (Ivy Zhang). Collaborates with industry partners like Qualcomm and Microsoft Research, focusing on edge computing and hardware optimization. Labs/Teams: His research group focuses on interdisciplinary projects at the intersection of data science, signal processing, and applied mathematics, with active collaborations in both academia and industry.

David Larbalestierمشاهده پروفایل

استاد

• Superconductivity
• Materials Science
• Superconducting Magnets
• +۳ مورد دیگر

David Larbalestier is the Krafft Professor and Chief Materials Scientist at the National High Magnetic Field Laboratory, affiliated with the College of Engineering at Florida A&M University-Florida State University. He holds dual professorships in Mechanical Engineering and Materials Science & Engineering. His research focuses on superconducting materials' structure-property relationships and their applications in high-field magnets, particularly for advanced accelerators and fusion energy systems. Dr. Larbalestier earned his B.S. (1965) and Ph.D. (1970) in Physical Metallurgy from Imperial College London. He has authored over 1,000 publications and holds patents in superconducting materials processing. His work emphasizes optimizing critical current density, vortex pinning, and mechanical resilience in materials like Nb3Sn, Bi-2212, and REBCO. He leads efforts to develop ultra-high-field magnets (e.g., 45 T magnets) and has pioneered overpressure processing techniques for Bi-2212 wires. His honors include Fellowship in the Royal Academy of Engineering, National Academy of Engineering membership, and the Cryogenic Materials Career Achievement Award. Key projects include the 40 T superconducting magnet at NHMFL and strategic initiatives for U.S. fusion magnet infrastructure. His lab collaborates globally on advanced superconductor manufacturing and magnet design for next-generation particle colliders and energy systems.

Shonda Bernadinمشاهده پروفایل

دانشیار

• Digital Signal Processing
• Speech Recognition
• Artificial Intelligence
• +۷ مورد دیگر

Shonda Bernadin, Ph.D., is an Associate Professor in the Department of Electrical & Computer Engineering at the FAMU-FSU College of Engineering, a joint institution of Florida Agricultural and Mechanical University and Florida State University. She holds a B.S. from Florida A&M University, an M.S. from the University of Florida, and a Ph.D. from Florida State University. Her research spans digital signal processing, speech recognition, artificial intelligence, autonomous vehicles, and engineering education. She directs the Speech Processing and Data Analysis Laboratory (SPADAL) and focuses on broadening STEM participation through K-12 outreach, including ACEE summer camps and CROP-ENG programs. Dr. Bernadin’s work emphasizes engineering education innovation, including evidence-centered assessment design and strategies to improve retention and diversity in engineering. She has authored numerous peer-reviewed publications on topics like neural networks, sensor-based defect detection, and cybersecurity threats in AI systems. Her teaching philosophy prioritizes creating inclusive, effective learning environments through engaging methods and technology integration. Professional activities include leadership in engineering education reform and collaborations with organizations such as ASTERIX to enhance STEM workforce diversity. Her lab’s research often intersects technology development with societal impact, addressing challenges in healthcare, autonomous systems, and additive manufacturing quality control.

Walajabad S. Sampathمشاهده پروفایل

استاد

• Thin-Film Photovoltaics
• CdTe Solar Cells
• Manufacturing Systems
• +۲ مورد دیگر

Walajabad S. Sampath is Professor of Mechanical Engineering at Colorado State University and Director of the NSF Center for Next Generation Photovoltaics. His research advances CdTe thin-film solar technology, achieving record 20.14% efficiency. With 100+ publications and 17 patents, he focuses on sustainable energy manufacturing. Education: Ph.D. (Arizona State). Awards recognize innovation in photovoltaic commercialization. Articles demonstrate breakthroughs in materials design and solar module architecture. International collaborations include Loughborough University and the Asian Institute of Technology.

William Kirkhamمشاهده پروفایل

استاد

• Construction Engineering
• Structural Engineering
• Disaster Resilience
• +۳ مورد دیگر

William Kirkham is a Professor of Practice and Program Director at the University of Kansas Edwards Campus. His expertise lies in construction engineering, structural safety, and disaster resilience. He focuses on improving construction quality, mitigating risks in wood-frame structures, and enhancing seismic and wind-resistant design practices. His research spans topics such as tornado vulnerability, timber building defects, and residential diaphragm performance. Dr. Kirkham’s work integrates practical applications with academic rigor, addressing real-world challenges in construction standards, forensic analysis, and building codes. He has contributed to advancing methodologies for horizontal diaphragm design, roof system mechanics, and error prevention in timber construction. Though no specific awards or grants are listed, his extensive publications reflect a dedication to resolving structural issues in residential and commercial buildings. His affiliation with the Edwards Campus highlights engagement with regional and applied engineering challenges.

Ozgur Kelesمشاهده پروفایل

استادیار

• Additive Manufacturing
• Materials Discovery
• Hierarchical Materials
• +۶ مورد دیگر

Ozgur Keles is an Assistant Professor in the Department of Chemical and Materials Engineering at San José State University (SJSU), where he has worked since August 2015. He previously held a Lecturer and Senior Research Associate position at Illinois Institute of Technology from 2013 to 2015 after completing his Ph.D. in Materials Engineering at Purdue University (2013). His research focuses on developing AI-driven discovery machines for new materials, leveraging active learning and high-throughput methods to explore uncharted chemical and structural spaces. He investigates processing-structure-property-design (PSP-D) interrelationships in multi-functional materials, combining additive manufacturing with data-driven numerical approaches to control hierarchical structures from sub-nano to macro-scale. B.S. in Metallurgical and Materials Engineering from Middle East Technical University, Turkey (2005) M.S. in Metallurgical and Materials Engineering from Middle East Technical University, Turkey (2008) Ph.D. in Materials Engineering from Purdue University (2013) His research interests span artificial intelligence in materials discovery , graphene quantum dots in epoxy composites , sustainable design for smart cities , and virtual reality in engineering education . He uses molecular dynamics, finite element analysis, and vibration-assisted 3D printing to enhance mechanical reliability in composites. Recent projects include NSF CAREER grant-funded work on multi-scale mechanical behavior of quantum dot nanocomposites and an NEA grant for 3D printing cultural heritage artifacts . His publications highlight advancements in additive manufacturing , nanocomposite toughening , and machine learning for structural analysis . Notable contributions include studies on the effects of raster angle on 3D printed parts , thermal conductivity enhancement via GQDs , and stochastic fracture of porous composites . Scientific Awards: ASME Rising Star of Mechanical Engineering (2025) 2023 College of Engineering Award for Excellence in Scholarship 2019 Advisor of the Year at SJSU Keles collaborates extensively, securing grants such as the NSF MRI for a metal AM system and DOE PARC Xerox for ceramic alignment studies. His lab engages students in hands-on research, and he promotes engineering education through virtual reality modules .

• Embedded Systems
• Multimedia Computing
• VLSI Design
• +۶ مورد دیگر

Professor Hua Harry Li serves in the Department of Computer Engineering at San José State University, teaching specialized courses including Embedded Hardware Systems (CMPE 242), Embedded Software (CMPE 244), and Embedded Wireless Systems (CMPE 245). His academic profile spans semiconductor physics, real-time control systems, and multimedia hardware implementation. Education Background: Doctor of Philosophy, University of Iowa, 1989 Master of Science in Electrical and Computer Engineering, University of Iowa, 1984 Bachelor of Science in Electronics Engineering, Tianjin University, 1981 Graduate Studies in Electronic/Electrical Engineering, Tsinghua University, 1982 Li's research integrates embedded systems with intelligent control methodologies , particularly focusing on fuzzy logic applications in semiconductor manufacturing and neural network implementations for real-time processing. His work bridges theoretical algorithms and hardware constraints, evidenced by publications on vision chips, wafer defect detection, and pH neutralization control systems. The Encyclopedia of Electrical and Electronics Engineering features his contributions to neural fuzzy control techniques for semiconductor equipment. Analysis of his 1993-2005 publications reveals three distinct phases: early neural network applications (1993-1994) in wafer manufacturing and radar systems, mid-career expansion into video compression and vision chips (1995-1997), and mature work on embedded video processing systems (2001-2005). This trajectory demonstrates consistent focus on hardware-constrained intelligent systems while adapting to emerging technologies in wireless communications and multimedia computing. Key Honors: Industrial Neural Network Award (1994 World Congress Neural Network Conference) Who’s Who in Science and Engineering (4th Edition, 1999) Who is Who in America (53rd Edition) Professor Li contributes significantly to academic discourse as Guest Editor for IEEE Transactions on CPMT Special Emerging Technology Section (1994, 1996) and encyclopedia contributor. While specific grant details aren't documented, his sustained publication record and industry-recognized awards indicate substantial research funding, particularly in semiconductor process control and embedded vision systems. His teaching portfolio reflects direct alignment with research expertise through advanced embedded systems courses. Current work appears focused on embedded multimedia hardware systems with practical applications in semiconductor manufacturing and real-time control, though explicit details about active research teams or laboratory facilities aren't provided in available materials.

Frank Liمشاهده پروفایل

استاد

• Electrical Engineering
• RF Engineering
• Autonomous Power Conversions
• +۴ مورد دیگر

Dr. Frank Li serves as Professor and Director of the Rayen School of Engineering at Youngstown State University, holding a concurrent position as Chair of the Department of Electrical and Computer Engineering. His academic leadership spans multiple institutional roles including department chair since 2019. His educational background includes: Ph.D. in Electrical Engineering (2005, Case Western Reserve University) M.S. in Electrical Engineering (1999, Youngstown State University) B.S. in Electrical Engineering (1995, Ohio State University) Research focuses on RF engineering, autonomous power conversions, and applied magnetic fields with significant contributions to microelectronics security, wireless sensor networks, and structural health monitoring. His work bridges theoretical advancements with practical applications in battery technology, antenna design, and semiconductor verification. Recent publications demonstrate strong emphasis on terahertz antenna fabrication, trusted microelectronics, and novel sensor development. Key scientific recognitions include: Youngstown State University Distinguished Chairperson (2023) NASA Glenn Summer Faculty Fellowship (2016, 2017) As an educator, Dr. Li has mentored over ten graduate students and developed innovative low-cost laboratory systems for engineering education. His externally funded research includes collaborations with NASA and MIT's Francis Bitter Magnetic Laboratory where he served as visiting scientist (2014-2015). Current work involves advanced manufacturing techniques for RF components and security verification of integrated circuits.

Rachel Oliverمشاهده پروفایل

استاد

• Materials Science
• Gallium Nitride (GaN)
• Semiconductors
• +۷ مورد دیگر

Prof Rachel Oliver is a Professor of Materials Science at the University of Cambridge , affiliated with the Department of Materials Science & Metallurgy . She serves as Director of the Cambridge Centre for Gallium Nitride and Chief Scientific Officer of the spinout company Poro Technologies . Education: MEng, University of Oxford DPhil, University of Oxford Her research focuses on the characterization and engineering of GaN-based materials for optoelectronic and electronic devices. Key areas include defect analysis in nitride semiconductors, quantum dot development for single-photon sources, and porous GaN applications. She employs advanced techniques like atom-probe tomography , cathodoluminescence , and electron microscopy to study structure-property relationships. Recent publications highlight trends in solar cell efficiency optimization, quantum well dynamics, and multi-microscopy characterization of defects. Her work addresses challenges in nitride materials, such as efficiency droop and defect passivation. Scientific Awards: Fellow of the Royal Academy of Engineering (FREng) Rachel Oliver leads the Cambridge Centre for Gallium Nitride, a key player in the EPSRC National Epitaxy Facility , providing nitride materials to UK academics. Her team collaborates on projects involving quantum cryptography , power electronics , and novel device concepts .