جست‌وجوی استاد و پژوهشگر

Marat I. Latypovمشاهده پروفایل

استادیار

• Materials Science
• Computational Materials Science
• Materials Informatics
• +۴ مورد دیگر

Marat I. Latypov serves as Assistant Professor in the Department of Materials Science and Engineering at the University of Arizona's College of Engineering. He is also a member of the Applied Mathematics Graduate Interdisciplinary Program and leads the Materials Informatics Lab. His research spans computational materials science, sustainable alloy design, and machine learning applications for materials development. Dr. Latypov holds a PhD in Materials Science and Engineering from Pohang University of Science and Technology (POSTECH, South Korea, 2014) and a Dipl.-Ing. in Engineering Physics from Ufa State Aviation Technical University (Russia, 2011). His postdoctoral training included appointments at Georgia Tech/CNRS in France and the University of California, Santa Barbara. His research focuses on materials informatics , physics-informed machine learning , and sustainable structural alloys . Key methodologies include graph neural networks for polycrystal mechanics, vision transformers for microstructure representation, and adaptive experimental design for materials optimization. Recent work emphasizes circular economy applications through construction waste recycling and copper mine tailings valorization. Analysis of his publication record reveals strong emphasis on computational microstructure-property linkages (35% of recent work), machine learning for materials design (30%), and sustainable materials processing (25%), with growing integration of large language models for materials knowledge extraction. NSF CAREER Award (2025) : For damage control in recycled aluminum alloys ISTI Distinguished Faculty Scholar (2024) : At Los Alamos National Laboratory Novelis Hackathon First Prize (2021) : Computer vision application Acta Materialia Outstanding Reviewer (2018) Young Researcher Award (2017) : NanoSPD7 Conference Dr. Latypov advises PhD students including Herbold Fellow Zhuocheng Huang and leads projects funded by NSF and the Grantham Foundation. Current initiatives include chalcopyrite leaching optimization for copper mining and graph neural network development for fatigue prediction. His Materials Informatics Lab maintains collaborations with Los Alamos National Laboratory, MIT, and industry partners including Novelis. The lab operates at the intersection of metallurgy , machine learning , and high-performance computing , with capabilities spanning deep learning, Bayesian inference, and cloud-based computational infrastructure. Recent news highlights participation in CODAS-HEP summer school and publication of vision transformer work in Acta Materialia.

• Business Process Management
• Process Mining
• Complex Event Processing
• +۵ مورد دیگر

Prof. Dr. Matthias Weidlich is a faculty member at Humboldt University of Berlin within the Institute of Computer Science under the Faculty of Mathematics and Natural Sciences . His research focuses on Process Mining , Complex Event Processing , and Data Privacy with applications in Business Process Management and Scientific Workflows . Research Interests: Business Process Management and Process Mining Complex Event Processing and Stream Data Analysis Data Privacy and Security in Process Systems Scientific Workflow Systems and User Behavior Heterogeneous Network Embeddings Algorithm Design and Optimization Recent Publications (2023-2025) demonstrate expertise in: Efficient stream processing techniques Privacy-preserving process mining frameworks Scientific workflow analysis tools Graph neural network applications Multi-modal data integration Adaptive querying systems Contact: Office: Unter den Linden 6, 10099 Berlin Phone: 030 2093-41277 Email: matthias.weidlich@hu-berlin.de Web: hu.berlin/data

• Global Navigation Satellite Systems (GNSS)
• Autonomous Systems
• Sensor Fusion
• +۴ مورد دیگر

Patrick Henkel is a Professor at the Technical University of Munich (TUM) affiliated with the TUM School of Engineering and Design and the Chair of Communication and Navigation. He holds a professorship in Satellite Geodesy under Prof. Hugentobler. His research focuses on advanced positioning technologies, including Global Navigation Satellite Systems (GNSS), autonomous systems, and sensor fusion. He develops algorithms for precise positioning in challenging environments such as urban areas, alpine regions, and indoor spaces. His work also extends to environmental applications, such as snow hydrology and climate monitoring using GNSS signals. Henkel’s contributions include innovations in real-time kinematic (RTK) positioning, UAV navigation, and multi-sensor integration for robotics and autonomous vehicles. His research is supported by collaborations with industry and academic partners, addressing both theoretical and applied challenges in geodesy and navigation. Henkel leads projects on GNSS signal processing, satellite-based environmental monitoring, and autonomous driving technologies. He has contributed to the Galileo HAS service and developed methodologies for snow water equivalent estimation using multi-frequency GNSS signals. His expertise spans hardware-software co-design for navigation systems and algorithm optimization for high-precision positioning in dynamic environments. He actively publishes in top-tier journals and conferences, with a focus on advancing the reliability and accuracy of navigation systems across various domains. His advising and grants include funding for projects on sensor fusion, UAV-based measurements, and satellite receiver development. He collaborates with teams at TUM’s Navigation Lab and the Professur für Satellitengeodäsie, contributing to both academic and industrial applications. His work on low-bandwidth RTK dissemination and laser-tracker verified UAV positioning highlights his commitment to bridging theoretical advancements with real-world implementation.

Cristina Torres-Machiمشاهده پروفایل

استادیار

• Infrastructure Asset Management
• Sustainability and Resilience in Transportation
• Decision-Making and Optimization Systems
• +۳ مورد دیگر

Cristina Torres-Machi is an Assistant Professor of Civil, Environmental and Architectural Engineering at the University of Colorado Boulder, holding the Beavers Professorship of Construction Engineering. She earned her PhD in Civil Engineering from Universitat Politècnica de Valencia and Universidad Católica de Chile (2015), a MSc in Planning and Management in Civil Engineering (2012) and BSc in Civil Engineering (2008) from Universitat Politècnica de Valencia. Her research focuses on infrastructure asset management, sustainability/resilience in transportation, and decision-making optimization systems. She leads the Innovation for Resilient Infrastructure (IRI) research group, advancing methodologies for long-term infrastructure management. Recognized with awards including the Abertis International Award (2016) and excellence in PhD dissertation (2015/2017), she serves as Chair of ASCE’s Construction Research Council and Vice-Chair of TRB’s Transportation Asset Management committee. Her work integrates machine learning, predictive analytics, and data science to improve pavement performance and lifecycle cost analyses. Professional affiliations include the American Society of Civil Engineers (ASCE) and active roles in TRB committees. Research emphasizes pavement rehabilitation strategies, flood impact modeling, and equitable infrastructure adoption trends. Over 60 publications (60+ citations) span journal articles, conference proceedings, and book chapters, with projects funded by public/private agencies. Current projects explore satellite-based monitoring, EV infrastructure impacts, and disaster-resilient traffic systems. Her recent work addresses procurement fallacies in design-build projects and integrates social vulnerability assessments in natural hazard planning.

Patrick S. Marketمشاهده پروفایل

استاد

• Synoptic and Mesoscale Dynamics
• Winter Weather
• Heavy Rainfall
• +۶ مورد دیگر

Dr. Patrick S. Market is a Professor of Atmospheric Science and currently serves as the Director of the School of Natural Resources at the University of Missouri. He also acts as Interim Co-Director of the Missouri Water Center. His research focuses on synoptic and mesoscale dynamics, particularly winter weather, heavy rainfall, flash flooding, and severe local storms. He has contributed to advancements in precipitation efficiency studies and operational forecasting techniques. His work explores the role of artificial intelligence in weather prediction and communication, emphasizing the continued importance of human expertise in an automated forecast process. Dr. Market has secured grants for data stream maintenance and digital equity planning, and he has led educational initiatives integrating research into synoptic meteorology classrooms. Notable collaborations include projects with the National Weather Service and studies on the Ozark Plateau's topographical influence on weather systems.

Frederic Boscheمشاهده پروفایل

استاد

• Construction Informatics
• Civil Engineering
• Building Information Modeling (BIM)
• +۵ مورد دیگر

Dr. Frederic Bosche is a Reader in Construction Informatics at the University of Edinburgh's School of Engineering, leading the CyberBuild Lab. His research focuses on advancing digital construction technologies, including BIM, sensing systems, and digital twinning to enhance infrastructure management and workforce safety. Education: PhD in Civil Engineering (University of Waterloo), M.Sc. from University of Texas at Austin, and M.Eng. from Ecole Centrale de Lille. Research interests include automated construction processes, data-driven infrastructure lifecycle management, and integrating emerging technologies like AI and IoT into construction workflows. His CyberBuild Lab has pioneered projects in defect detection, roof monitoring, and smart construction inspection. Notable contributions include over 100 publications, 12 research projects (e.g., 'Digital Facility' and 'Monitoring Roofs of Traditional Buildings'), and awards such as the Charles M. Eastman Top PhD Paper Award. He actively engages in public outreach through science festivals and collaborates internationally with institutions like ETH Zurich and Heriot-Watt University.

Lokukaluge Prasad Pereraمشاهده پروفایل

استاد

• Maritime Technology
• Offshore Systems
• Advanced Data Analytics
• +۶ مورد دیگر

Lokukaluge Prasad Perera is a Professor in Maritime Technology at UiT The Arctic University of Norway and a Senior Research Scientist in Smart Data at SINTEF Digital . He holds a BSc in Mechanical Engineering from Oklahoma State University (1999), MSc in Systems & Controls from the same institution (2001), and a PhD in Naval Architecture and Marine Engineering from Technical University of Lisbon (2012). His research focuses on Maritime and Offshore Systems , Advanced Data Analytics , Autonomous Navigation , Energy Efficiency , and Digital Twin Applications . He has published over 100 peer-reviewed papers and was recognized in the World's Top 2% Scientists (2021-2022) by Stanford University. Key professional experiences include roles at SINTEF Ocean (2014–2017), Center for Marine Technology and Engineering in Portugal (2008–2012), and Wärtsilä Finland (2012–2014). He has also held academic positions at Naval & Maritime Academy and Ocean University of Sri Lanka . His work addresses challenges in emission reduction , renewable energy integration , and safety-critical systems for maritime operations. Current projects emphasize trustworthiness of autonomous ships and data-driven decision frameworks for energy efficiency.

David Wanikمشاهده پروفایل

استادیار

• Data Science
• Natural Hazards
• Remote Sensing
• +۳ مورد دیگر

David Wanik is an Assistant Professor in the Department of Operations and Information Management and Associated Faculty in the Department of Civil and Environmental Engineering at the University of Connecticut. He serves as Academic Director for Business Data Analytics at the Stamford campus and conducts research in the Eversource Energy Center, focusing on data science, natural hazards, remote sensing, and IoT applications in utility systems. PhD, MS, and BS in Environmental Engineering from University of Connecticut His research bridges natural hazard prediction, power grid resilience, and environmental data science. Key themes include: Machine learning for power outage prediction Climate change impact on energy demand Remote sensing for population and environmental monitoring IoT-enabled infrastructure hardening Recent publications emphasize deep learning for nighttime light imagery analysis, hybrid physics-data-driven models for grid resilience, and climate-integrated demand forecasting. His work integrates satellite data, LiDAR, and utility infrastructure records for predictive analytics. Teaching includes courses in business analytics, Python-based data science, and deep learning for the MS Business Analytics and Project Management program.

Marjan Alaviمشاهده پروفایل

استادیار

• Fault Diagnosis
• Prognosis
• Power Electronics
• +۳ مورد دیگر

Dr. Marjan Alavi is an Assistant Professor at McMaster University's W Booth School of Engineering Practice and Technology, affiliated with the Mechanical Engineering department as an Associate Member. She holds a Professional Engineer (P.Eng.) license in Ontario and has over 15 years of academic and industrial experience in electrical engineering. Her research focuses on model-based and data-driven approaches for fault diagnosis, prognosis, and fault-tolerant control in hybrid systems, with applications in power electronics, energy systems, and smart infrastructure. Education: B.Sc. (2004) from K.N. Toosi University of Technology, M.Sc. (2007) from Sharif University of Technology, Ph.D. (2014) from Nanyang Technological University (Singapore), and a Postdoc (2015) at the University of Toronto's Energy Systems Group. Teaching: Instructs courses on Real-Time Systems (SEP 6ES3, SFWRTECH 4ES3), Smart Cities and Communities (SMRTTECH 4SC3), integrating real-world engineering challenges with theoretical frameworks. She emphasizes hands-on learning through remote labs and experiential projects. Professional Contributions: Serves as IEEE Toronto Section Executive Member, Technical Reviewer for IEEE Transactions on Industrial Electronics, and Vice Chair of IEEE Industrial Applications Society (2015). Founded Intelligent Diagnosis Corporations, a Canadian startup focused on research and innovation in diagnostics technologies. Key Projects: Developed fault diagnosis strategies for electro-hydraulic actuators, vehicle-mounted infrastructure monitoring systems, and remote laboratory platforms for emergency traffic control. Research spans predictive maintenance, smart city technologies, and railway systems certification benefits. Awards: Recipient of the Singapore International Graduate Award (SINGA) 2010. Recognized for her work in bridging academic research with industrial applications, particularly in enhancing system reliability through advanced control methodologies.

• Remote Sensing
• Civil Engineering
• Transportation Engineering
• +۵ مورد دیگر

Ayman Habib is the Thomas A. Page Professor of Civil Engineering at Purdue University's College of Engineering. He serves as Co-Director of the Civil Engineering Center for Applications of UAS for a Sustainable Environment (CE-CAUSE) and Associate Director of the Joint Transportation Research Program. His work focuses on integrating remote sensing technologies like LiDAR and UAV systems into infrastructure monitoring, environmental management, and transportation engineering. Key areas include sensor calibration, mobile mapping systems, and applications in forest inventory, pavement maintenance, and stockpile monitoring. Research interests span remote sensing, geomatics, and UAV-based solutions for civil engineering challenges. He actively develops methodologies for automated data processing, LiDAR intensity normalization, and machine learning-driven infrastructure assessment. His projects address sustainability through precise environmental and transportation systems analysis. Selected publications highlight advancements in LiDAR-based road cracking detection, forest reconstruction via neural networks, and UAV calibration for agricultural and environmental applications. His work emphasizes scalable solutions for infrastructure maintenance and environmental monitoring, leveraging interdisciplinary approaches in civil engineering and computer science.

Valeria Bruschiمشاهده پروفایل

پژوهشگر

• Audio Engineering
• Signal Processing
• Spatial Audio
• +۵ مورد دیگر

Valeria Bruschi is a Researcher at the Department of Information Engineering (DII) within the Faculty of Engineering at Università Politecnica delle Marche (UNIVPM) in Ancona, Italy. Her academic profile was last updated on April 13, 2024, and she maintains her office at the Engineering Faculty on via Brecce Bianche, with contact information including phone +39 071-220-4486 and email v.bruschi@staff.univpm.it. Dr. Bruschi's research spans multiple domains within audio and signal processing, with particular expertise in spatial audio systems, automotive human-computer interaction, and biomedical signal applications. Her work bridges theoretical signal processing techniques with practical implementations across diverse fields including automotive safety systems, hearing aid technology, sleep medicine, and agricultural monitoring. She has made significant contributions to head-related transfer function (HRTF) processing, real-time audio enhancement algorithms, and innovative monitoring systems that utilize acoustic signals for various applications. Analysis of Dr. Bruschi's recent publications reveals a strong trajectory in developing practical audio processing solutions with real-world applications. Her work shows increasing integration of machine learning techniques with traditional signal processing approaches, particularly in areas like driver monitoring systems, snoring detection and cancellation, and spatial audio rendering. A notable trend is her focus on creating lightweight, real-time implementations suitable for embedded systems and practical deployment scenarios, while maintaining high performance standards. Her research consistently demonstrates interdisciplinary collaboration, connecting audio engineering with fields as diverse as automotive safety, sleep medicine, and agricultural technology. Dr. Bruschi actively contributes to advancing audio engineering through her research on equalization techniques, noise reduction systems, and immersive audio technologies. Her work on pulse compression techniques for hearing aid distortion measurement represents an important contribution to audiological assessment methodologies. Her publication record demonstrates consistent scholarly output with increasing impact across multiple application domains, reflecting her ability to translate theoretical signal processing concepts into practical engineering solutions.

Changyang Liمشاهده پروفایل

مدرس

• Robotics
• Fusion Reactor Engineering
• Remote Maintenance Systems
• +۲ مورد دیگر

Changyang Li serves as a University teacher in the Department of Mechanical Engineering at LUT University's School of Energy Systems in Lappeenranta, Finland. His institutional contact includes email Li.Changyang@lut.fi and phone +358 50 301 7482. Dr. Li's research specializes in robotics for nuclear fusion infrastructure, with emphasis on remote maintenance systems for tokamak reactors. His work addresses critical engineering challenges in vacuum vessel assembly, port-based maintenance, and heavy-duty manipulator design for next-generation reactors like DEMO and CFETR. Key methodologies include multi-objective optimization, kinematic mechanism analysis, and data-driven modeling of robotic systems operating in high-radiation environments. Analysis of his 15 publications (2019-2025) reveals concentrated expertise in DEMO reactor maintenance robotics, particularly mobile parallel mechanisms and cable-driven systems. His research demonstrates consistent focus on enhancing remote maintainability through innovations in elephant trunk robots, port closure tools, and in-situ machining solutions, directly supporting international fusion energy initiatives. No scientific awards are documented in available sources. No information is available regarding student supervision or research grant acquisitions. Specific laboratory affiliations or research team structures are not disclosed in the source materials.

Olga Oleinikovaمشاهده پروفایل

دانشیار

• Migration Studies
• Eastern European Migration
• Democracy Studies
• +۷ مورد دیگر

Dr. Olga Oleinikova is an Associate Professor and Director of the Social Impact Technologies and Democracy Research Hub (SITADHub) within the School of Communication at the University of Technology Sydney (UTS), Australia. Internationally recognized for her contributions to research and social impact, she has been named among Forbes Top 40 Global Ukrainians and Forbes 30 Under 30 Asia. She was also a finalist for the Australian Council of Humanities, Arts and Social Sciences (CHASS) Future Leader Award. Her educational background includes a PhD in Sociology from the University of Sydney (2016), with prestigious research fellowships at Oxford University's European Studies Centre (2018-2019), Charles University in Prague (2023-2024), and the WZB Berlin Social Science Center (2015). Dr. Oleinikova's research focuses on migration studies (particularly Eastern European migration to Australia), democracy studies, diaspora politics, and social impact technologies. Her work examines life strategies of migrants navigating displacement, democratic performance in Ukraine and Europe, and the intersection of technology and democracy. She has developed a theoretical framework distinguishing between 'achievement life strategies' and 'survival life strategies' among migrants from crisis regimes. Her publication portfolio includes several acclaimed works, with her most recent book 'New Eastern European Migration to Australia: From Ukraine, Czech Republic and Hungary' (Palgrave, 2023) examining new migration patterns. Her research demonstrates consistent focus on Eastern European migration, diaspora politics, and democratic development, with increasing attention to technology's role in democratic processes. Forbes Top 40 Global Ukrainians Forbes 30 Under 30 Asia CHASS Future Leader Award Finalist Visa People's Choice Award Anthill 30 Under 30 Winner Dr. Oleinikova has secured over $3 million in funding for social and commercial initiatives. She serves on several nonprofit boards, acts as an advisor to the Australia-Ukraine Chamber of Commerce, and mentors through the 1991 Open Data Incubator and Future Schools Australia. She founded the SITAD Visiting Fellowship Program, supporting Ukrainian early-career researchers and postgraduate students. Her media reach is substantial, with expert commentary featured in BBC News, Bloomberg, ABC News, CNA, The Conversation, Politico, SBS, and KyivPost, reaching an estimated 9.1 million people. She has delivered more than 30 keynote and invited talks at leading institutions worldwide. SITADHub, which she founded and directs, is a dynamic networked research center with 170 associates across 16 countries actively researching democracy, human-computer interaction, and global mobility, with a focus on Ukraine and broader Eastern Europe. The hub conducts unique research and maintains university partnerships throughout Europe and the Asia Pacific, including with WZB Berlin Social Science Research Centre, University of Oxford, and University of Sydney.

• Modelling and Control of Electrical and Electromechanical Systems
• HVDC Systems and DC Grids
• High Power AC/DC and DC/DC Converters
• +۳ مورد دیگر

Dr. Aliakbar Jamshidi Far is a Lecturer at the School of Engineering, University of Aberdeen, since December 2017. Previously, he served as a Research Fellow at the Aberdeen HVDC Centre (2012-2017) and as an Assistant Professor at the Iranian Research Organization for Science and Technology (2008-2012). Dr. Jamshidi Far holds a PhD in Electrical Engineering from AmirKabir University (2008), an MSc from Iran University of Science and Technology (1996), and a BSc from Sharif University of Technology (1992). He is an IET Chartered Engineer, Senior Member of IEEE, and member of CIGRE Working Group B4.76. His research focuses on Modeling and control of HVDC systems and DC grids High-power AC/DC and DC/DC converters Hybrid DC circuit breakers Ultrasound applications in Oil & Gas Renewable energy integration Recent publications highlight trends in Modular Multilevel Converters (MMC) for DC grids Flux Switching Machine optimization Ultrasound-based scale removal technology Wave energy for remote islands Smart microgrids for Indonesia and Nigeria Advanced DC circuit breaker designs Dr. Jamshidi Far has secured significant funding including £204k from the Oil & Gas Technology Centre (2019-2021, Co-PI) £42k Consultancy from BP PLC (2019-2020, PI) EU Horizon 2020 PROMOTion Project (2016-2017, Research Fellow) SSE-funded DC converter research (2015-2016, Research Fellow) ERC-funded DC systems modeling (2012-2014, Research Fellow) Teaching responsibilities include Undergraduate: EE3579 - Electrical and Electronic Engineering Design Postgraduate: EG551K/55M5 - Renewable Energy Integration to Grid (Coordinator) EG503V/503W - Solar Energy (Coordinator) EG501H/504B - Electrical Systems for Renewable Energy (Coordinator) He supervises MEng/BEng and MSc students in Renewable Energy, Oil & Gas, and Subsea programs.

• Construction Engineering
• Computing in Civil Engineering
• Project Planning and Scheduling
• +۶ مورد دیگر

Ming Lu is a Professor in the Department of Civil and Environmental Engineering at the University of Alberta, Faculty of Engineering. Specializing in Construction Engineering and Management (CEM), he leads the Construction Automation Lab (AutoLab) since 2010, focusing on integration, automation, and optimization in construction. Dr. Lu holds professional engineering licensure (PEng) in Alberta and has extensive academic experience across Canada, Hong Kong, and China. PhD in Civil Engineering (University of Alberta, 2000) B.Eng. in Road & Traffic Engineering (Tongji University, 1994) His research spans Construction Automation , Project Scheduling , and Resource Optimization , with over 150 publications in top journals. Recent work emphasizes model trees , time-window constraints , and labor cost regression . Publications appear in Automation in Construction , Journal of Computing in Civil Engineering , and ASCE Journal of Construction Engineering and Management . Notable awards include the 2022/23 CSCE Stephen G. Revay Award , Fiatech STAR Award (2013) , and multiple Best Paper Awards from ASCE. His software tools like SDESA and S3 revolutionized construction simulation and resource-constrained scheduling. Dr. Lu supervised numerous graduate students in projects involving BIM applications , earthwork optimization , and steel fabrication scheduling . He developed key courses like CIV E 406 (Construction Estimating) and CIV E 607 (Productivity Modeling), integrating simulation-based learning into construction education.