جست‌وجوی استاد و پژوهشگر

• Laser Polishing
• CNC Machining
• CAD/CAM Systems
• +۵ مورد دیگر

O. Remus Tutunea-Fatan is a Professor in the Department of Mechanical & Materials Engineering at Western University, with cross appointments in Biomedical Engineering and Electrical and Computer Engineering. His work focuses on laser polishing, CNC machining, and surface structuring for drag reduction and biomedical applications. Ph.D. in Mechanical Engineering, The University of Western Ontario M.E.Sc. and B.E.Sc. in Mechanical Engineering, Transilvania University, Romania Research interests include: Advanced CAD/CAM frameworks Laser remelting process optimization Biomedical device design Composite manufacturing techniques Surface topography analysis Artificial intelligence in process control Recent publications indicate expertise in: Laser polishing of metallic surfaces Riblet microstructures for drag reduction AI-driven process monitoring 5-axis machining error compensation Scientific recognition includes: Edward G. Pleva Award for Excellence in Teaching (Western University, 2023) Dr. Terry Base Memorial Teaching Award (2022 co-winner, 2021, 2019) R. Mohan Mathur Award (Faculty of Engineering, 2020) University Students' Council Teaching Honour Roll (2011-2012) Prof. Tutunea-Fatan serves as Associate Chair for Graduate Research Programs (2025-2027) Acting Associate Dean for Undergraduate Studies (2023-2024) Acting Chair, Department of Mechanical and Materials Engineering (2021-2022) He supervises over 40 graduate students and collaborates with industry partners including DuPont Safety and Construction, General Motors, and Active Industrial Solutions Inc.

Nan Zhangمشاهده پروفایل

پژوهشگر ارشد

• Precision Manufacturing
• Microfluidics
• Nanotechnology
• +۳ مورد دیگر

Dr. Nan Zhang is a research leader at the UCD School of Mechanical and Materials Engineering , focusing on precision manufacturing technologies for micro/nano-scale devices. His work bridges lab-scale prototyping and industrial mass production, with applications in medical devices, microfluidics, and functional surfaces. Research Keywords : Precision Manufacturing, Microfluidics, Nanotechnology, Materials Science, Medical Devices, Advanced Manufacturing Research Trends : Recent publications highlight advancements in digital light processing (DLP) 3D printing, machine learning-optimized microfabrication, liquid metal antenna technologies, and scalable nanocomposite mold development. His work emphasizes industrial feasibility, biocompatibility, and surface engineering. Scientific Awards : Smurfit Kappa Newman Fellowship Award ERC Grants (contextual institutional affiliation) Labs & Collaborations : Based at the UCD Engineering and Materials Science Centre, Dr. Zhang’s research involves partnerships with industry and academic networks, focusing on precision tooling, microfluidic scale-up, and novel material applications (e.g., bulk metallic glasses, bio-plastics).

• Additive Manufacturing
• Nondestructive Evaluation
• Ultrasonics
• +۳ مورد دیگر

Luz Sotelo is an Assistant Professor of Mechanical Engineering at Purdue University, located in West Lafayette, Indiana. She is affiliated with the College of Engineering's Department of Mechanical Engineering, conducting research in advanced manufacturing and materials science. Her work focuses on multi-process additive manufacturing, nondestructive evaluation, ultrasonics, and acoustic metamaterials. She holds a Ph.D. from the University of Nebraska-Lincoln and a B.S. from the University of Texas Rio Grande Valley. Research interests include developing novel techniques for evaluating additively manufactured components using ultrasonic methods, studying material properties of advanced composites, and exploring bio-inspired solutions for fluid dynamics challenges. Her research bridges fundamental science with engineering applications in convergent manufacturing and acoustics. Notable articles explore ultrasonic evaluation of AM materials, fatigue performance of laser-fused components, and bio-inspired flow control strategies. Her work emphasizes practical applications of ultrasonics in real-time manufacturing monitoring and material characterization. Awards: NASEM Research Assistantship Program (2021-22) Society of Hispanic Professional Engineers STAR Award (2020) Great Minds in STEM Leadership Award (2019) NSF Graduate Research Fellowship (2018-21) Professor Sotelo's advising and grant activities focus on advancing additive manufacturing and nondestructive evaluation technologies. She collaborates with industry partners to translate research into practical solutions for aerospace and biomedical applications. Her lab, located in MMRL 1900D, investigates cutting-edge materials and manufacturing processes.

• Computational Process Engineering
• Pharmaceutical Manufacturing
• Process Optimization and Planning
• +۳ مورد دیگر

Gintaras Reklaitis is the Burton and Kathryn Gedge Distinguished Professor of Chemical Engineering at Purdue University's Davidson School of Chemical Engineering. He joined Purdue in 1970 and holds a B.S. from Illinois Institute of Technology (1965) and M.S./Ph.D. from Stanford University (1969). His research focuses on applying computing and systems technology to optimize processing systems, particularly in pharmaceutical manufacturing and integrated energy systems. Key areas include batch process design, enterprise-wide planning, and robust scheduling under uncertainty. Professor Reklaitis has been recognized with prestigious awards, including National Academy of Engineering membership (2007) and the Professional Achievement Award from Illinois Institute of Technology (2006). He has co-advised multiple graduate students, including Megha Das, Zachary Hillman, Shrivatsa Korde, and Dalton Yu. His work appears in journals like Computers & Chemical Engineering and Journal of Pharmaceutical Sciences . Research highlights include developing frameworks for real-time quality assurance in pharmaceutical manufacturing, integrating data management systems, and advancing continuous manufacturing technologies. His contributions also span editorial roles, including Editor-in-chief of Computers & Chemical Engineering (1986–2008). Current projects emphasize digital design tools, techno-economic analysis, and sensor-driven process monitoring.

• Biomedical Engineering
• Placental Biology
• Vascular Physiology
• +۴ مورد دیگر

Nikhilesh Bappoo is an Adjunct Research Fellow at the UWA Medical School, affiliated with the UWA Centre for Medical Research and the Harry Perkins Institute of Medical Research. He holds a Doctor of Philosophy (PhD) student status alongside a Master of Professional Engineering (2018) and a Bachelor of Philosophy (Hons) (2017), both from the University of Western Australia. His research focuses on placental vascular structure and hemodynamics, fetal growth restriction, and computational modeling of vascular diseases such as abdominal aortic aneurysms. Key areas include understanding how hemodynamic factors like shear stress influence placental function and aneurysm progression. He employs multidisciplinary approaches blending biomechanics, medical imaging, and computational simulations. Notable awards include the Materialise Mimics Innovation Award (2017), ASME Best Student Paper (2018), and a Convocation Postgraduate Research Travel Award (2019). His work contributes to UN Sustainable Development Goals related to good health and well-being. Research outputs span vascular network modeling, aneurysm biomechanics, and placental oxygen diffusion. Collaborations involve institutions globally, with recent studies exploring rare vascular conditions like pancreaticoduodenal artery aneurysms.

Daniel W. Apleyمشاهده پروفایل

استاد

• Industrial and engineering statistics
• Statistical learning and data mining
• Predictive analytics
• +۷ مورد دیگر

Daniel W. Apley is Professor of Industrial Engineering and Management Sciences at the McCormick School of Engineering and Applied Science, Northwestern University, where he has served since 2003. He is Editor-in-Chief-Elect of Technometrics and previously Editor-in-Chief of the Journal of Quality Technology . He is also affiliated with Northwestern’s Master of Science in Machine Learning and Data Science Program. Education PhD Mechanical Engineering, University of Michigan, Ann Arbor MS Electrical Engineering, University of Michigan, Ann Arbor MS Mechanical Engineering, University of Michigan, Ann Arbor BS Mechanical Engineering, University of Michigan, Ann Arbor Research Interests Professor Apley is an industrial statistician whose work sits at the intersection of engineering modeling, statistical analysis, and predictive analytics. His major thrusts include statistical modeling of complex engineering and enterprise systems, machine learning for manufacturing data, quality engineering and Six Sigma methodologies, and computer-experiment–based design optimization under uncertainty. Recent applications span healthcare risk modeling, credit-risk analytics, materials microstructure prediction, and autonomous process control. Scientific Awards NSF CAREER Award IIE Transactions Best Paper Award (Quality & Reliability) Wilcoxon Prize for best practical application paper in Technometrics Teaching & Advising At Northwestern he teaches undergraduate courses in Statistical Methods for Quality Improvement, Introductory Statistics, and Statistical Tools for Data Mining, as well as graduate courses in Predictive Analytics, Engineering Applications of Data Mining, and Intermediate Statistics. His research has been supported by numerous industrial partners and federal agencies, underscoring a strong record of funded graduate and post-doctoral advising. Leadership & Service Beyond editorial roles, Professor Apley has chaired the Quality, Statistics & Reliability Section of INFORMS and served as Director of the Manufacturing and Design Engineering Program at Northwestern, shaping interdisciplinary curriculum and research initiatives.

• Healthcare Infrastructure Delivery
• Civil Engineering
• Architecture
• +۷ مورد دیگر

Professor Grant Mills is the Faculty Lead for Health at University College London's Bartlett School of Sustainable Construction. His research focuses on advanced healthcare infrastructure delivery, interdisciplinary design, and project management, with funding from EPSRC, ESRC, NIHR, and international bodies. He leads initiatives like Project HERCULES and explores topics such as digital twins, BIM adoption, and modular healthcare design. Education: PhD from Loughborough University (2013), Master of Science from De Montfort University (2001). Previous roles include Senior Lecturer and Lecturer at UCL, and Senior Research Associate at Loughborough University. Research Interests: Healthcare infrastructure innovation, sustainable construction, BIM implementation challenges, modular design, and governance frameworks for large projects. His work addresses healthcare facility adaptability, AI integration in emergency departments, and post-pandemic healthcare systems. Grants & Funding: Department of Health, European Investment Bank, WHO, and EPSRC grants. Active in megaproject collaborations and strategic asset management for NHS infrastructure. Lab/Teams: Leads Bartlett Health-related research groups, collaborating with global institutions on healthcare infrastructure projects and digital twin applications.

Maria Yangمشاهده پروفایل

استاد

• early stage design process
• design methods
• mechanics
• +۵ مورد دیگر

Maria Yang is a Professor and the William E. Leonhard Professor/Interim Dean of the School of Engineering at the Massachusetts Institute of Technology (MIT), affiliated with the Department of Mechanical Engineering. Her research focuses on early stage design processes , design methods , and system-level engineering design , with applications spanning consumer products, complex systems, and sustainable technologies. Educational Background: B.Sc., MIT (1991) M.Sc., Stanford University (1994) Ph.D., Stanford University (2000) Yang's research explores the theoretical foundations of design , emphasizing sketching , prototyping , and design cognition . Her work addresses global challenges in sustainability , emerging markets , and human-computer interaction , as demonstrated by collaborations with NASA, IBM, and Ferrari. Recent publications highlight trends in design-by-analogy , 3D printing of transparent glass , and information flow in complex systems . Her research bridges mechanical engineering , bioengineering , and computational design . Scientific Awards: 2024 ASME Design Theory and Methodology Award 2024 ASME Design Theory and Methodology Best Paper Award 2017 MacVicar Faculty Fellow 2016 Bose Excellence in Teaching Award 2014 ASEE Fred Merryfield Design Award 2013 ASME Fellow Yang mentors students through courses like 2.00B Toy Product Design and 2.009 Product Engineering Processes , and leads the MIT Ideation Laboratory , which investigates transformational design strategies for global competitiveness and sustainability.

• Human-Robot Interaction
• Assistive Robotics
• Machine Learning in Robotics
• +۵ مورد دیگر

Prof. Dongheui Lee is a Full Professor at TU Wien's Institute of Computer Technology, Faculty of Electrical Engineering and Information Technology, and leads the Human-centered Assistive Robotics Group at the German Aerospace Center (DLR). She holds a PhD from the University of Tokyo (2007) and has held academic roles at Technical University of Munich (TUM), the University of Tokyo, and KIST. Her research focuses on human-robot interaction, assistive robotics, and machine learning applications in robotics. Education: PhD, Information Science and Technology, University of Tokyo, 2007 MS, Kyung Hee University, 2003 Research Interests: Her work spans human motion understanding, assistive robotics, human-robot collaboration, and control systems. Key areas include robotic balance assistance, motion imitation, and safety-aware robotics. She has pioneered methods for light touch support in human-robot interaction and developed frameworks for dynamic task execution. Recent Trends in Publications: Recent work emphasizes variable stiffness control, motion retargeting, and multimodal anomaly detection. Publications highlight advancements in assistive robotics, human motion prediction, and reinforcement learning for locomotion. Articles often integrate robotics with machine learning to improve safety and adaptability in human-robot systems. Awards: Carl von Linde Fellowship (TUM Institute for Advanced Study, 2011) Helmholtz professorship prize (2015) Best Intelligence Paper Award (2024) Projects & Grants: Leads projects like LunarAssembly (robotic assembly on the Moon) and INVERSE (interactive robots through reasoning). Funded initiatives include EU Horizon, BMBF, and industry collaborations. Coordinates teams for projects like PERSEO (service-oriented robotics) and SOLAR (body representation studies). Labs/Teams: Directs the Human-centered Assistive Robotics Group at DLR and collaborates with TU Wien's Autonomous Systems unit. Her teams focus on real-world applications in healthcare, manufacturing, and human-centered robotics.

• Geotechnical Engineering
• Soil Mechanics
• Rock Mechanics
• +۶ مورد دیگر

Dr. Budi Zhao is a Lecturer/Assistant Professor in the School of Civil Engineering at University College Dublin since August 2020. He holds a PhD from City University of Hong Kong (2017) and has held academic positions at Imperial College London (Research Associate, 2019–2020) and King Abdullah University of Science and Technology (Postdoctoral Fellow, 2017–2019). His research focuses on multi-physics processes in soil and rock, employing advanced techniques like X-ray micro-tomography (μCT), microfluidics, and numerical modeling (e.g., DEM and CFD-DEM). Key areas include crushable sands, desiccation cracking, fines migration, and energy geotechnics. He serves on ISSMGE committees TC105 and TC308, and is a member of the editorial board of the Journal of Rock Mechanics and Geotechnical Engineering . His research outputs span topics such as 3D printed composites, microplastic transport, and internal erosion mechanisms. Notable projects include grants on multi-scale analysis of clays and salt precipitation effects. Dr. Zhao coordinates modules like Geotechnical Engineering and Soil Mechanics at UCD, emphasizing innovative teaching methods like flipped classrooms. His work bridges fundamental science and engineering applications, with a focus on sustainable geotechnical solutions. Education: PhD (City University of Hong Kong, 2017), B.Eng (Chongqing University), Professional Certificate in University Teaching (UCD). Grants: Includes funding for offshore wind energy anchors and carbon geological storage projects. Advising: Supervises multiple PhD students in geomechanics and energy geotechnics. Labs/Teams: Leads research using state-of-the-art facilities for μCT imaging and microfluidics.

Zhen Liمشاهده پروفایل

استادیار

• Multiscale/Multiphysics modeling
• Soft matter and Smart materials
• Biophysics and Collective dynamics
• +۷ مورد دیگر

Dr. Zhen Li is an Assistant Professor in the Department of Mechanical Engineering at Clemson University's College of Engineering, Computing and Applied Sciences. He joined Clemson in August 2019 after serving as a research associate professor at Brown University and a postdoctoral research associate at University of California, Merced. Education: Ph.D. in Fluid Mechanics, Shanghai University, 2012 MS in Fluid Mechanics, Shanghai University, 2008 BS in Engineering Mechanics, Wuhan University, 2005 Dr. Li's research focuses on multiscale modeling of soft matter, complex fluids, biophysics, and collective dynamics using both bottom-up (coarse-grained molecular modeling) and top-down (from continuum descriptions to fluctuating hydrodynamics) approaches, along with high-performance computing. His work spans mathematical theory for coarse-graining and model reduction, statistical methods and machine-learning approaches applied to multiscale modeling, memory effects in complex fluids, and concurrent coupling of heterogeneous solvers for scale-bridging. Analysis of Dr. Li's recent publications reveals a strong trend toward integrating machine learning with traditional computational methods, particularly neural operators for multiscale problems. His work spans diverse applications from bubble dynamics and blood flow to materials science and bioprinting, demonstrating the versatility of his computational approaches across multiple disciplines in engineering and physics. Awards and Recognition: CECAS Dean's Professor Award (2024) Award of Excellence - Junior Faculty (2021-2022) Best Research Poster Award at SC19 (2019) 2nd Place Award of Best Poster Presentation at DOE/EFRC AIM for Composites meeting (2024) Dr. Li actively mentors PhD students including Miles Lu, Ryan Wan, Haizhou Wen, and Ali Mohammadi, who have published significant research in computational mechanics. His research is supported by multiple grants including an NSF Elements grant as PI for 'SciMem: Enabling High Performance Multi-Scale Simulation on Big Memory Platforms', an NSF CDS&E grant as co-PI for 'HAM3R: Heterogeneous Automated Management of Multiscale Methods and Resources', a DOE/EFRC grant as Thrust lead co-PI for 'AIM for Composites', and a NASA EPSCoR grant as Science-PI. Dr. Li leads the MuthComp (Multiscale theory and Computation) research group, which focuses on developing interfaces between Engineering, Applied Mathematics, Physics-based Machine Learning, and High Performance Scientific Computing. The group has active collaborations with institutions including Idaho National Laboratory, University of Tokyo, and Brown University, and has developed open-source software including USERMESO for GPU-accelerated DPD simulations.

Luca Di Gasperoمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Combinatorial Optimization
• Metaheuristics
• +۱ مورد دیگر

Luca Di Gaspero is an Associate Professor of Information Technology at the University of Udine, specializing in metaheuristic optimization techniques. His research enhances combinatorial optimization through hybridization of algorithms for scheduling, routing, and industrial applications. Research spans artificial intelligence in optimization, scheduling algorithms for manufacturing/healthcare, and metaheuristic framework development. Recent publications focus on LLMs in optimization, parallel batch scheduling, and energy-efficient manufacturing. Key Contributions: Developed EasyLocal++ framework for local search algorithms Advanced multi-neighborhood simulated annealing techniques Applied metaheuristics to healthcare logistics and emergency services

Augusto Luís Barros Lopesمشاهده پروفایل

استادیار

• Materials Science and Engineering
• Electron Microscopy
• Microstructure Analysis
• +۳ مورد دیگر

Augusto Luís Barros Lopes is an Assistant Professor in the Materials and Ceramic Engineering Department at the University of Aveiro since January 2009. Previously, he served as an Invited Assistant Professor at the same department (2004–2008). He holds a PhD in Materials Science and Engineering from the University of Aveiro (2001) and a Bachelor's in Ceramic and Glass Engineering (1989). He has been the Senior Technician responsible for the Electron Microscopy Service at the department (1991–2004). His research focuses on Materials Science and Engineering , with expertise in electron microscopy (SEM/TEM and EDS/PEELS) , microstructure-property relationships , and plastic deformation of materials . He teaches courses on metals, ceramics, characterization techniques, and mechanical properties. Key publications include studies on dual-phase steels, asymmetric rolling of aluminum alloys, and nanocomposite synthesis. He leads projects like EcoCerâmica (enhancing ceramics/crystal sector competitiveness) and FOCO (optimizing cabinet cooling). He advises PhD students and has collaborated internationally on materials processing and characterization. His work spans structural materials, energy-related materials, and advanced manufacturing techniques.

Selen Cremaschiمشاهده پروفایل

استاد

• Process synthesis, design, and operations
• Optimization under uncertainty
• Energy systems engineering
• +۲ مورد دیگر

Selen Cremaschi is a Professor and the B. Redd & Susan W. Redd Eminent Scholar Chair in the Department of Chemical Engineering at Auburn University (College of Engineering). She earned her Ph.D., M.S., and B.S. in Chemical Engineering from Purdue University and Bogazici University respectively. Education: Ph.D. Chemical Engineering, Purdue University M.S. Chemical Engineering, Bogazici University B.S. Chemical Engineering, Bogazici University Research Interests: Process synthesis, design, and operations Optimization under uncertainty Energy systems engineering Techno-economic and life cycle analysis Cancer care engineering Recent Articles Trends: Her work spans biomedical applications (e.g., stem cell cardiac differentiation), CO2 capture, process intensification, and stochastic programming. Key areas include sustainable chemical processes, computational biology, and hybrid modeling frameworks. Scientific Awards: B. Redd & Susan W. Redd Eminent Scholar Chair 2018 Class of Influential Researchers Grants & Collaborations: She co-led a $23.8M DOE project on CO2 emission reduction in pulp and paper mills and a $1.5M NSF grant for heart tissue engineering. She contributes to interdisciplinary teams and has been interviewed on the award-winning #GINNing Podcast about her leadership role.

Yazhou Tuمشاهده پروفایل

استادیار

• Cyber-Physical System Security
• Side Channel Analysis
• Sensing and Automation Security
• +۳ مورد دیگر

Yazhou Tu is an Assistant Professor in the Department of Computer Science and Software Engineering at Auburn University. He specializes in Cyber-Physical System Security, Side Channel Analysis, and Privacy in embedded systems. His work focuses on addressing vulnerabilities in sensors, actuators, and IoT devices to enhance security and privacy in critical systems. Education: Ph.D. Computer Science, University of Louisiana at Lafayette M.S. Software Engineering, Tsinghua University B.S. Software Engineering, Wuhan University Research Interests: Dr. Tu’s research explores cutting-edge topics such as adversarial control of embedded systems, acoustic and magnetic side-channel attacks, and privacy risks in robotic and biomedical systems. He develops novel defense mechanisms like ADC-Bank and Transduction Shield to counteract physical signal injection attacks. Key Contributions: His work spans sensor security, IoT exploitation, and healthcare technology, with notable studies on 3D printer IP theft, vehicle control via smart glasses, and keystroke tracking via audio. He also investigates physics-informed ML for porous media and glucose monitoring systems. Awards & Grants: No specific awards or grants listed in the provided data, but his prolific publication record highlights sustained research excellence. Labs & Collaborations: Engaged in Auburn’s Center for Artificial Intelligence and Cybersecurity Engineering and other interdisciplinary initiatives focused on secure embedded systems and cyber-physical infrastructure.