جست‌وجوی استاد و پژوهشگر

Mohit Bholaمشاهده پروفایل

پژوهشگر

• Fluid Power
• Hydraulic Systems
• Wind Turbine Technology
• +۲ مورد دیگر

Mohit Bhola is a Researcher at AAU Energy within the Faculty of Engineering and Science at Aalborg University, Denmark. His work focuses on fluid power systems engineering with specialization in hydraulic components for wind turbines and heavy machinery applications. His primary research domains include Fluid Power Engineering (100% fingerprint match), Hydraulic System Design (50%), and Wind Turbine Technology . Key sub-specialties encompass hydrostatic transmission optimization, fault diagnosis in pitch systems, compressed air motors, and energy efficiency in fluid power applications. His fingerprint analysis confirms strong concentration in hydraulic cylinder engineering (49%) and pump displacement systems (38%). Recent publications (2024-2025) reveal a strategic shift toward comprehensive reviews of fault detection methodologies for wind turbine hydraulic pitch systems, alongside optimization studies for front-end loader transmissions. His collaborative work demonstrates increasing industry integration, particularly with energy giant Vattenfall in reliability-focused research. Dr. Bhola actively participates in the HyRel project (2022-2027), a Vattenfall-funded initiative targeting 20% reduction in wind energy costs through pitch system fault mitigation. This €2.1M project involves cross-disciplinary collaboration with experts in hydrostatic transmission and condition monitoring.

Foto N. Afratiمشاهده پروفایل

استاد

• Parallel and distributed computation
• Processing of very large data
• MapReduce
• +۶ مورد دیگر

Professor Foto N. Afrati is a Distinguished Faculty Member at the National Technical University of Athens, specifically within the School of Electrical and Computing Engineering and the Division of Communication, Electronic and Information Engineering. She has held this position since 1993, following previous academic ranks at the same university as Associate Professor (1989-1993), Assistant Professor (1985-1989), Lecturer (1982-1985), and Research Fellow (1980-1982). She completed her PhD in Electrical Engineering at Imperial College of the University of London in March 1980, with a dissertation focused on Error Correcting Codes by Algorithms. Her academic journey also included a Diploma from Imperial College (March 1980) and an earlier Diploma in Electrical and Mechanical Engineering from the National Technical University of Athens (June 1976). Professor Afrati's research interests span several critical areas in computer science: Parallel and distributed computation Processing of very large data (including MapReduce) Data and web mining Database Systems Information integration Query optimization Computation and complexity of algorithms Approximation algorithms Her most recent publications demonstrate expertise in MapReduce environments, query optimization with views, and data exchange frameworks. These works are published in prestigious venues like EDBT, VLDB, PODS, and ICDT, with specific focus areas including adaptive sampling techniques, data source integrity, and algorithm complexity in database environments. Professor Afrati has received significant recognition in her field, including Fellow of the Association for Computing Machinery (ACM) Best Paper Award at the International Conference on Database Theory (ICDT) 2009 She has advised numerous PhD students throughout her career, including Theodoros Mitakos, Ezz Hattab, Nikos Kiourtis, and Angelos Vasilakopoulos. Her current PhD students include Victor Kyritsis and Nikos Stassinopoulos. Professor Afrati maintains strong professional networks through her various visiting positions at institutions such as Google, Stanford University, IBM Research Center, University of Helsinki, University of Paris, DIMACS, and others. She has served as associate editor and reviewer for major academic journals and conferences including IEEE TKDE, ACM Transactions of Database Systems (TODS), Journal of ACM (JACM), and Theoretical Computer Science (TCS). Her extensive work in research projects spans both national and international initiatives, with funding from sources including the European Union's Thalis project, ESPRIT working groups, HCM networks, and Greek General Secretariat of Research and Technology grants.

Hussein Gharakhaniمشاهده پروفایل

استادیار

• Agricultural Robotics
• Automation in Agriculture
• Artificial Intelligence
• +۳ مورد دیگر

Hussein Gharakhani is an Assistant Professor in the Department of Agricultural and Biological Engineering at Mississippi State University. He specializes in agricultural robotics and automation, focusing on robotic cotton harvesting systems, sensor integration, and precision agriculture applications. His research addresses challenges in end-effector design, object detection, and field testing of robotic prototypes. Dr. Gharakhani holds a Ph.D. in Biosystems Engineering from Mississippi State University, an M.S. in Mechanical Engineering of Agricultural Machinery from the University of Tehran, and a B.S. in Agricultural Machinery Engineering from the University of Tabriz. His academic background includes roles as a graduate research and teaching assistant, as well as industry experience as a research and application engineer. His research interests span robotic manipulators, artificial intelligence, 2D/3D perception, and off-road robotics. Key projects include developing vision-guided robotic harvesters, evaluating end-effectors, and exploring UAV applications in cotton farming. His work emphasizes practical solutions to enhance agricultural efficiency and sustainability through automation. No scientific awards or grants are explicitly listed in the provided text. Dr. Gharakhani’s advising and mentorship activities are not detailed here, though his academic role suggests involvement in graduate student guidance. His research is centered on advancing robotic systems for precision agriculture, with a particular focus on cotton production challenges and robotic harvesting innovations.

• Bayesian Statistics
• Reliability Engineering
• Risk Analysis
• +۴ مورد دیگر

Ahmad BahooToroody is an Academy Research Fellow at Aalto University’s Department of Energy and Mechanical Engineering, specializing in Bayesian statistics, reliability engineering, and risk analysis for autonomous maritime systems. He is actively involved with the Marine and Arctic Technology research group and leads projects that integrate machine learning with safety-critical applications in the maritime and offshore sectors. Research Interests Bayesian statistical methods for reliability and risk modeling Machine learning and deep learning for anomaly detection in autonomous systems Safety assessment of offshore installations and maritime operations Prognostic health management of marine renewable energy systems Human factors and expert judgment in sociotechnical maritime systems His work often incorporates advanced techniques such as Gaussian processes, LSTM-based neural networks, and dynamic Bayesian networks to address uncertainties in complex engineering systems operating in harsh marine environments. Publication Trends Across 2022–2025, BahooToroody’s publications reveal a strong trajectory toward integrating data-driven models with physics-based simulations. Dominant themes include real-time risk monitoring of autonomous ships, failure prognosis for unattended machinery, and safety assessment frameworks for offshore structures. His collaborative outputs span high-impact journals such as Reliability Engineering & System Safety and Safety Science , underscoring his leadership in maritime safety analytics. Research Groups & Labs Marine and Arctic Technology Research Group, Aalto University Academy Research Fellow network within the Department of Energy and Mechanical Engineering Doctoral Supervision & Grants While specific grant details are not listed, his role as Doctoral Candidate Supervisor since 2020 indicates active mentorship of PhD researchers. He is also the Principal Investigator on projects funded under the Academy of Finland Fellowship scheme, supporting next-generation maritime risk analytics.

Juha Pyrhönenمشاهده پروفایل

استاد

• Electric Machines
• Motor Design
• High-Speed Motors
• +۷ مورد دیگر

Juha Pyrhönen serves as Professor of Electrical Engineering at the School of Energy Systems, Lappeenranta-Lahti University of Technology (LUT University) in Lappeenranta, Finland. His research focuses on advanced electric machine design for high-performance applications, with particular expertise in traction motors, synchronous reluctance machines, and thermal management systems. Contact information includes email Juha.Pyrhonen@lut.fi and phone +358 40 571 1645. Professor Pyrhönen's research spans critical areas in electric machine development including high-speed motor design for aerospace and automotive applications, mitigation of parasitic effects like bearing currents, and innovative cooling techniques such as direct liquid cooling. His work addresses electromagnetic design challenges in drum-winding machines, variable reluctance resolvers for position sensing, and material selection for rotors operating under extreme conditions. Recent investigations examine agricultural tractor electrification and compact energy conversion systems for onboard machinery. Analysis of his 2025 publications reveals strong emphasis on improving power density through multidisciplinary approaches that integrate electromagnetic, thermal, and mechanical considerations. Key trends include advanced bearing current mitigation strategies, optimization of axially-laminated rotors, and precision measurement techniques under magnetic saturation. His research consistently targets sustainable solutions for electric propulsion across transportation sectors. No scientific awards were documented in the provided information. Details regarding student supervision, research grants, or collaborative projects were not specified in the available materials. The absence of such information suggests either non-disclosure in the source materials or potential focus on independent research activities. While specific laboratory facilities weren't mentioned, his research scope implies access to advanced testing infrastructure for high-speed machinery, electromagnetic characterization equipment, and thermal validation systems at LUT University's energy research facilities.

• Automation Engineering
• Mechanical Engineering
• Robotics
• +۴ مورد دیگر

Pauli Mustalahti is a Research Fellow at Tampere University's Automation Technology and Mechanical Engineering department. His expertise lies in advanced control systems for heavy-duty robotic manipulators, hydraulic systems, and model-based control design. Mustalahti holds a Master of Science (Technology) in Automation Engineering from Tampere University (2016) and a Bachelor of Science (Technology) in the same field (2013). His research focuses on optimizing automated operations for industrial manipulators through innovative control strategies, including bilevel optimization frameworks, vision-aided positioning, and robust safety-constrained systems. Key contributions include improving long-reach manipulator accuracy via local calibration and enhancing electric linear actuator performance with safety protocols. Research interests: Robotics, Hydraulic Systems, Model-Based Control, Industrial Automation Notable achievements: Doctoral thesis on modular model-based control design for heavy-duty manipulators (2023) Collaborations: Global Fluid Power Society, IEEE, and international researchers in automation Mustalahti's work aligns with UN Sustainable Development Goals related to Industry, Innovation, and Infrastructure. His publications span peer-reviewed journals like IEEE Transactions on Automation Science and Engineering and conferences such as PEMC, addressing challenges in actuator safety, real-time control, and energy efficiency.

• Control of Dynamic Systems
• System Identification
• Optimal Estimation and Control
• +۳ مورد دیگر

David M. Bevly is an Assistant Professor in the Department of Mechanical Engineering at Auburn University, where he has been on the faculty since 2001. He directs the GPS and Vehicle Dynamics Laboratory (GAVLAB) and teaches a range of courses spanning system dynamics, vehicle dynamics, optimal estimation and control, and GPS navigation. Education Ph.D. Mechanical Engineering, Stanford University, 2001 M.S. Mechanical Engineering, Massachusetts Institute of Technology, 1997 B.S. Mechanical Engineering, Texas A&M University, 1995 Research Interests His research integrates control theory with real-world vehicle applications, focusing on control of dynamic systems, optimal estimation and control, GPS and sensor fusion, vehicle dynamics and control, and vehicle state estimation . Combining low-cost GPS receivers with inertial sensors, he develops algorithms that enable precise state estimation for passenger cars, agricultural tractors, and off-road platforms, enhancing safety and autonomy. Publication Trends Between 1999 and 2004, Bevly authored or co-authored more than a dozen journal and conference papers that collectively advance the fields of GPS-aided vehicle control and precision agriculture. The works explore theoretical contributions—such as dead-reckoning error analysis and yaw-dynamic modeling—and demonstrate practical implementations on farm tractors and high-speed ground vehicles. Awards & Recognition Best Paper of Session, 2000 ION-GPS Meeting SAE Arch T. Colwell Award (Myers Award) for Outstanding Student Paper, 2000 Laboratory & Teams As head of the GPS and Vehicle Dynamics Laboratory (GAVLAB) at Auburn, Bevly leads interdisciplinary projects that integrate mechanical design, real-time embedded systems, and field experimentation. The lab collaborates with industry partners and federal agencies to transition research results into commercial vehicle-safety and agricultural-autonomy products.

• Artificial Intelligence
• Smart Manufacturing
• Fault Diagnosis
• +۶ مورد دیگر

Dr. M M Manjurul Islam is a Research Associate in Artificial Intelligence for Smart Manufacturing at Ulster University's School of Computing, Engineering and Intelligent Systems. His research focuses on applying advanced AI techniques to solve critical challenges in manufacturing systems, with particular expertise in fault diagnosis, predictive maintenance, and semiconductor production optimization. His research interests span Artificial Intelligence , Smart Manufacturing , Fault Diagnosis , Machine Learning , Deep Learning , Predictive Maintenance , and Semiconductor Manufacturing . He has made significant contributions to the application of convolutional neural networks, support vector machines, and generative adversarial networks in industrial settings, particularly for bearing fault diagnosis and wafer defect classification. Dr. Islam's recent publications (2023-2025) demonstrate a strong focus on practical AI applications in manufacturing, with multiple chapters in the Springer Series in Advanced Manufacturing. His work shows an evolving trajectory from traditional machine learning approaches to more sophisticated deep learning and explainable AI techniques, with increasing emphasis on semiconductor manufacturing challenges and trustworthy AI systems. His research contributes to UN Sustainable Development Goals, particularly in industrial innovation and infrastructure. He is an active member of professional organizations including IEEE and Advance HE, serving as Chair for both networks. According to Scopus data, Dr. Islam has accumulated 1,706 citations with an h-index of 16, reflecting the impact of his research in the field. His publication record shows consistent productivity, with research outputs spanning from 2015 to anticipated publications in 2025.

• Electrical Engineering
• Motor Diagnostics
• Condition Monitoring
• +۳ مورد دیگر

Lorenzo Mantione is a Researcher at the Department of Industrial and Information Engineering, University of Pavia. His work focuses on electrical energy engineering, with a specialization in fault detection and diagnostics of electrical machines, particularly induction motors. He investigates advanced techniques like time-frequency analysis and stray flux monitoring to address issues such as broken rotor bars and interturn short circuits under closed-loop control conditions. His research integrates power electronics, control systems, and electromagnetic analysis to enhance reliability and efficiency in electrical drives and motor systems. Recent publications highlight his contributions to motor diagnostics in both healthy and fault conditions, including single-phasing scenarios and closed-loop inverter-fed configurations. No scientific awards or grants are explicitly mentioned. No advising students or lab affiliations are listed in the provided information.

• Mechanical Engineering
• Materials Science
• Technical Mechanics
• +۳ مورد دیگر

Jan Camphausen is a Professor of Technical Mechanics and Drive Technology at the Georg Agricola University of Applied Sciences (THGA) since 2013. Previously, he worked as a Calculation Engineer at Vestas Nacelles Deutschland GmbH (2009-2012) and as a Research Associate at Ruhr University Bochum (2003-2009), where he completed his doctoral studies on fatigue strength analysis of volumetric components. Education: Mechanical Engineering studies (1997-2003) and doctoral research (2003-2009) at Ruhr University Bochum. His research focuses on Mechanical Engineering and Materials Science , with expertise in technical drawing dynamics, transmission and drive technology, and strength of materials. His work emphasizes industrial applications such as wind turbine drivetrains and multiphase screw pumps, where he investigates fatigue analysis, vibration mitigation, and component optimization. Recent publications highlight his contributions to multibody simulations , corrosion phenomena in mechanical systems , and parametric design for reliability , particularly in offshore and industrial contexts. He is a member of the VDI (Verein Deutscher Ingenieure) and maintains active collaborations in mechanical engineering research.

Valerie Sessionsمشاهده پروفایل

استاد مدعو

• data quality
• development of exoskeleton standards
• video management systems
• +۱ مورد دیگر

Valerie Sessions serves as an Adjunct Professor of Computer Science and is concurrently employed by the Naval Information Warfare Center (NIWC), Atlantic as a computer scientist. Her academic appointments and defense sector work demonstrate active engagement in both higher education and applied technology fields. Her educational qualifications are: PhD in Computer Science and Engineering from the University of South Carolina MS in Computer and Information Science from the University of Charleston and the Citadel BS in Computer Science from the College of Charleston with minors in Mathematics and Physics Dr. Sessions' research spans critical computer science domains with strong defense applications. Her focus on data quality addresses reliability in information systems, while exoskeleton standards development intersects robotics and military technology. She also pioneers video management systems and video analytics , emphasizing real-time data processing for security contexts. These interests reflect practical innovation in national defense and information infrastructure. Her notable recognitions include: 40 Under 40 award by the Charleston Regional Business Journal Crow of the Year from the Palmetto Roost Chapter of the Association of Old Crows Stuart Madnick Best Paper Award at the International Conference on Information Quality (MIT) Dr. Sessions provides significant professional service through advisory roles. She contributes to the U.S. Department of Justice's Global Privacy and Information Quality Working Group (GPIQWG), serves as Board Member for Charleston Women in Tech, and acts as Educational Director for the Palmetto Roost Chapter of the Association of Old Crows. She also participates in the Program Committee for the International Conference on Information Quality and maintains membership in the Association of Computing Machinery (ACM), highlighting leadership in both academic and defense communities. Her dual affiliation with academia and NIWC Atlantic positions her within defense-focused research teams addressing information warfare challenges. The Palmetto Roost Chapter involvement specifically ties her to electronic warfare and signals intelligence initiatives, leveraging her technical expertise in government contexts.

Stathis Ioannidesمشاهده پروفایل

استاد مهمان

• Tribology
• Rolling Element Bearings
• Rolling Contact Fatigue
• +۵ مورد دیگر

Stathis Ioannides serves as a Visiting Professor in the Department of Mechanical Engineering at Imperial College London and concurrently holds the position of Product R&D Director at SKF Engineering & Research Centre in The Netherlands. He is an active member of the Tribology Group within the department, maintaining his office at South Kensington Campus (Room 585c). His research focuses on critical tribological phenomena with industrial applications: Rolling contact fatigue mechanisms in bearing systems Elastohydrodynamic lubrication under extreme conditions Contaminant effects on lubricant performance Probabilistic modeling of bearing lifetimes Dynamics of rotating machinery components Dr. Ioannides' work bridges theoretical tribology with practical engineering solutions for the bearing industry. His research demonstrates consistent focus on reliability engineering and performance optimization in mechanical systems through both experimental and computational approaches. Professional recognition includes: Fellowship in the Institution of Mechanical Engineers (IMechE) Fellowship in the American Society of Mechanical Engineers (ASME) He maintains active engagement with the global tribology community through editorial roles in major journals including Tribology International, Wear, and Journal of Tribology (ASME), while serving on councils of the International Tribology Council and Society of Tribologists and Lubrication Engineers.

• Software Engineering
• Software Testing
• Program Analysis
• +۴ مورد دیگر

Alessandro (Alex) Orso is the Dean and Professor at the University of Georgia College of Engineering , starting in 2025. Previously, he spent 25 years at Georgia Institute of Technology , where he served as a Professor in the College of Computing , Director of the Scientific Software Engineering Center , and Associate Dean for Off-Campus and Special Initiatives . Education: Ph.D. in Computer Science – Politecnico di Milano, Italy M.S. in Electrical Engineering – Politecnico di Milano, Italy B.S. in Electrical Engineering – Politecnico di Milano, Italy Research Focus: Alex Orso is a leading expert in software engineering , with a focus on software testing , program analysis , and debugging . His work aims to improve software reliability, security, and trustworthiness , and has been validated on real-world systems. He has led initiatives to integrate AI and large language models into testing workflows, particularly for REST APIs and mobile applications . Scientific Recognition: Distinguished Member of the Association for Computing Machinery (ACM) Fellow of the Institute of Electrical and Electronics Engineers (IEEE) ISSTA Impact Paper Award (2021) Research Funding & Leadership: Orso has secured major funding from Google, IBM, Microsoft , and government agencies. In 2021, he led the acquisition of $11 million from Schmidt Futures to establish the Scientific Software Engineering Center at Georgia Tech, where he served as inaugural director. Teaching & Innovation: He was an early advocate of Georgia Tech’s Online Master of Science in Computer Science (OMSCS) and has taught a virtual software engineering course since its launch in 2014.

Yaguang Zhangمشاهده پروفایل

استادیار بالینی

• Data Science
• Digital Agriculture
• UAV-Aided Wireless Communication Systems
• +۴ مورد دیگر

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 .

David Mbaمشاهده پروفایل

استاد

• Mechanical Engineering
• Predictive Maintenance
• Fault Detection
• +۳ مورد دیگر

Professor David Mba is the Vice-Chancellor of Birmingham City University (BCU), appointed in October 2023. He leads strategic vision development and oversees the University’s 2030 Strategy. Previously, he served as Deputy Vice-Chancellor for Research at the University of the Arts London and Pro Vice-Chancellor at De Montfort University, holding roles including Dean of Engineering and Faculty Pro Vice-Chancellor. Educated at Cranfield University, he holds a PhD in Mechanical Engineering, awarded the Lord King Norton Gold Medal for his doctoral thesis. His research focuses on mechanical systems, fault detection, and predictive maintenance, with over 300 publications. He chairs the Birmingham Cultural Compact and co-chairs the Black Leaders in HE network, while serving as a Royal Academy of Engineering Fellow and Principal Fellow of the Higher Education Academy. His research interests span mechanical engineering, predictive maintenance, and acoustic-based diagnostics, with a focus on gearbox dynamics, bearing fault prognosis, and vibration analysis. Collaborations include commercial, EU, and EPSRC-funded projects. He actively contributes to industry-relevant technologies, such as acoustic metamaterials for signal enhancement and condition monitoring frameworks for rotating machinery. Awards include prestigious academic honors and leadership roles in higher education networks. His work bridges academia and industry, emphasizing practical solutions for mechanical system reliability and safety.