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Alborz Shokrani ChaharsooghiView profile

Professor

• Innovative Manufacturing
• Advanced Machining Processes
• Surface Integrity
• +4 more

Alborz Shokrani Chaharsooghi is a Professor at the University of Bath's Department of Mechanical Engineering. He leads research in advanced manufacturing technologies, with a focus on sustainable and circular manufacturing, innovative machining processes, and digital manufacturing systems. He is actively involved in projects funded by EPSRC, Innovate UK, and EU Horizon, including initiatives like the Made Smarter Innovation Centre for People-Led Digitalisation and the I-Break ATI with Airbus collaboration. Education: Doctor of Philosophy in Mechanical Engineering (University of Bath, 2014) Research Interests: His work bridges traditional manufacturing with emerging technologies, emphasizing cryogenic machining of titanium alloys, additive manufacturing optimization, and machine learning applications in intelligent manufacturing. Recent projects explore energy-efficient processes and data analytics for process monitoring. Grants & Projects: EPSRC-funded research on additive layer manufacturing of high-performance alloys Horizon Europe-funded Twinning IZTECH in Robotics Manufacturing Systems Innovate UK project on cost modeling for additive manufacturing Teaching: Specializes in manufacturing processes, discrete event simulation, and optimization techniques for engineering systems.

Cagdas OnalView profile

Associate Professor

• Soft Robotics
• Printable Robotics
• Bio-inspiration
• +3 more

Cagdas Onal is an Associate Professor of Robotics Engineering at Worcester Polytechnic Institute (WPI). He holds a BS and MS from Sabanci University (2003, 2005) and a PhD in Robotics from Carnegie Mellon University (2009). His research focuses on soft robotics, bio-inspired systems, and control theory , emphasizing the development of flexible robotic components for healthcare, industry, and sustainable applications. He leads the Soft Robotics Lab and the Future of Robots in the Workplace (FORW-RD) initiative, advancing human-centric robotics solutions. Research interests include designing bio-inspired soft robots (e.g., origami-inspired snake robots), developing modular actuation systems with embedded sensors, and exploring applications in medical devices and assistive technology. His work aligns with UN Sustainable Development Goals, particularly in healthcare access (SDG 3), quality education (SDG 4), and innovation (SDG 9). Recent projects include origami-based robotic arms for wheelchair users , self-contained underwater robots, and haptic interfaces for teleoperation. His lab collaborates on国家级 grants like the NSF-funded NRT Program and has secured patents for actuator designs (e.g., Hydro Muscle). Labs/Teams: Soft Robotics Lab, FORW-RD, NRT Program. Notable media coverage includes Worcester Telegram & Gazette and Spectrum News for innovations in human-friendly robotics.

Jann WeinandView profile

Research Professor

• Energy System Optimization
• Renewable Energy Resource Assessment
• Complexity Management
• +4 more

Dr. Jann Michael Weinand is the head of the Integrated Scenarios department at the Institute of Climate and Energy Systems (ICE-2) within Forschungszentrum Jülich GmbH. He leads a team of 30 scientists, PhD students, and master students focusing on energy system analysis, complexity management, and AI integration. His work addresses regional and international energy systems, emphasizing renewable energy resource assessment and techno-economic feasibility. Dr. Weinand holds a Dr.-Ing. from the Karlsruhe Institute of Technology (2020) and a Mechanical Engineering and Business Administration degree from RWTH Aachen University (2016). His research spans energy autonomy, renewable resource optimization, and the socio-technical challenges of energy transitions. Key research areas include energy system modeling, geothermal and wind energy potential, and data-driven methodologies. He coordinates interdisciplinary projects with academic and industrial partners, contributing to high-impact journals like Nature Energy and Joule. His team develops open-source tools (e.g., ETHOS workflows) for reproducible energy assessments and advocates for spatially disaggregated energy planning. Publications highlight trade-offs in energy system design, AI risks, and land-use conflicts for renewables. He emphasizes integrating social, technical, and environmental factors into energy policy frameworks.

Chen XiaodongView profile

Professor

• Materials Science
• Flexible Electronics
• Nanotechnology
• +5 more

Professor Chen Xiaodong is a Distinguished University Professor at Nanyang Technological University (NTU), Singapore, holding primary appointment in the School of Materials Science & Engineering with courtesy appointments in the Lee Kong Chian School of Medicine and School of Chemistry, Chemical Engineering and Biotechnology. He serves as Deputy Director of the Institute for Digital Molecular Analytics and Science (IDMxS) and Director of both the Innovative Centre for Flexible Devices (iFlex) and Max Planck-NTU Joint Lab for Artificial Senses. His research spans mechanomaterials science and engineering, flexible electronics, sense digitalization, cyber-human interfaces and systems, and carbon-negative technology. Professor Chen's work focuses on developing methods for controlling materials architecture at 1-100 nm scale to solve fundamental and applied problems in energy, environment, and healthcare. His group integrates expertise from materials science, chemistry, biology, physics, and engineering to create innovative solutions. His scientific contributions have been recognized through numerous prestigious awards including the Singapore President's Science Award, National Research Foundation Investigatorship and Fellowship, Friedrich Wilhelm Bessel Research Award, Dan Maydan Prize in Nanoscience and Nanotechnology, and election to multiple national academies including Singapore National Academy of Science, Academy of Engineering Singapore, and German National Academy of Sciences Leopoldina. Professor Chen serves as Editor-in-Chief of ACS Nano and sits on editorial boards of numerous prestigious journals including Advanced Materials, Chemical Reviews, and Matter. He has mentored numerous PhD students and research fellows who have gone on to faculty positions at institutions worldwide. His laboratory develops cutting-edge technologies in flexible electronics, bio-inspired materials, and nano-bio interfaces, with strong industry collaborations and translational research focus.

• Chemistry
• Chemical Engineering
• Artificial Intelligence in Chemistry
• +5 more

Daniel Paul Armstrong is a Doctoral Assistant at the Laboratory of Artificial Chemical Intelligence (LIAC) within the Institute of Chemical Sciences and Engineering (ISIC) at École polytechnique fédérale de Lausanne (EPFL). He is concurrently enrolled as a doctoral student in the Doctoral Program in Chemistry and Chemical Engineering (EDCH) at EPFL, indicating an active research and academic trajectory in the domain of chemistry and advanced materials. His academic training and research are situated within the School of Basic Sciences, focusing on the integration of artificial intelligence with chemical discovery and materials design. The interdisciplinary environment of LIAC suggests a strong emphasis on computational modeling, machine learning for molecular systems, and innovation in functional chemical materials. Although no publications authored by Daniel Paul Armstrong are listed in the provided data, the research output of the broader group includes significant contributions in organic semiconductors, perovskite materials, electrochemical transistors, and advanced polymer systems. These areas reflect the likely thematic context of his doctoral work, particularly at the intersection of AI-driven chemical design and electronic materials. No scientific awards or recognitions are mentioned in the available information. As a doctoral researcher, he is likely involved in collaborative projects, possibly advising or mentoring junior students indirectly, though no formal advisees are listed. There is no mention of independent grants, but he may be supported through institutional or group-level funding associated with the LIAC laboratory. The Laboratory of Artificial Chemical Intelligence (LIAC) serves as his primary research environment, promoting innovation in intelligent systems for chemical synthesis, materials optimization, and molecular engineering, aligning with EPFL’s leadership in interdisciplinary science and technology.

Mohammad Yazdani-AsramiView profile

Lecturer

• Electrification of Transportation
• Cryo-electrification
• Applied Superconductivity
• +12 more

Dr. Mohammad Yazdani-Asrami is a Lecturer in Electrically Powered Aircraft and Operations at the Autonomous Systems & Connectivity (ASC) division of the James Watt School of Engineering, University of Glasgow. He leads research in electrification and cryo-electrification of transportation, particularly in aviation, leveraging applied superconductivity and AI techniques. His research interests span the Electrification and cryo-electrification of power and transportation systems Design of superconducting components (machines, cables, fault current limiters) for aviation Application of AI, machine learning, and big data in engineering and superconductivity Hydrogen electrolysis, production, and integration in aerospace and power networks His recent publications demonstrate a strong trend toward intelligent modeling and AI-driven solutions in superconducting technologies, with a focus on electric aircraft, fault protection, and thermal management using cryogenic fluids. Dr. Yazdani-Asrami has received notable scientific recognition, including: UK Royal Academy of Engineering Global Talent (2021) Young Professional of the Year, Cryogenic Society of America (2023) He actively supervises PhD students and hosts visiting researchers. His advising portfolio includes Alireza Sadeghi, Kerr Smith, Dedao Yan, Giacomo Russo, and Fábio Gregório. He has secured funding from the EPSRC, University of Glasgow, and CSC for PhD students. He also supports postdoctoral fellowships from the Royal Academy of Engineering, Leverhulme Trust, and Marie Skłodowska-Curie actions. He is involved in several research groups and collaborations, particularly within the Aerodynamics, Propulsion and Electrification group. His editorial roles include serving on the boards of Superconductor Science and Technology , World Journal of Engineering , Aerospace Systems , and others. He regularly contributes to major conferences such as the Applied Superconductivity Conference and the International Conference on Magnet Technology.

• Additive Manufacturing
• Process Monitoring
• Control Systems
• +6 more

Tegoeh Tjahjowidodo is a Senior Lecturer at the Faculty of Industrial Engineering Sciences , KU Leuven , affiliated with the Department of Mechanical Engineering and the Manufacturing Processes and Systems (MaPS) unit at Campus De Nayer. He serves as Head of Education for Electromechanics programs and leads Subdivision 17 at the campus. Research Areas: Additive Manufacturing (Wire-Arc Additive Manufacturing), Process Monitoring, Control Systems, Laser Micromanufacturing, Wear Analysis, Robotics, and Condition Monitoring. Publication Trends: Focus on in-situ monitoring of laser micromanufacturing, machine learning for abrasive belt grinding, WAAM parameter optimization , and multi-sensor fusion for process control. Scientific Contributions: Co-promotor for MultiTRIBO (tribology), Promotor for WAAM structural integrity and pedicle screw surgical simulators . Active in international collaborations (e.g., 25th International Symposium on Laser Precision Microfabrication, Spain 2024).

Victoria Webster-WoodView profile

Associate Professor

• Biohybrid Robotics
• Organic Robotics
• Biologically Inspired Robotics
• +10 more

Victoria Webster-Wood is an Associate Professor at the College of Engineering , Carnegie Mellon University , where she leads the Biohybrid and Organic Robotics Group (B.O.R.G) . Her research integrates organic materials into robotics as structures, actuators, sensors, and controllers for biohybrid robots and prosthetics. Education: Ph.D., Mechanical Engineering, Case Western Reserve University (2017) M.S., Mechanical Engineering, Case Western Reserve University (2013) B.S., Mechanical Engineering, Case Western Reserve University (2012) Research Interests focus on biohybrid robotics , biologically inspired systems , soft robotics , additive manufacturing , biomechanics , and computational modeling . Her work spans applications in medical robotics , micro/nano manufacturing , and environmental monitoring . Scientific Awards include being named to ASME’s 2025 MechE Watch List and awarded MIT Technology Review’s 35 Innovators Under 35 (2023) . Collaborations involve projects like neurodegenerative disease therapy tools and soft robotic tactile sensors for manufacturing , supported by the Manufacturing Futures Institute and NextManufacturing Center .

Alexandros KontogiannisView profile

Research Fellow

• Fluid Dynamics
• Applied Mathematics
• Bayesian Inference
• +10 more

Alexandros Kontogiannis is a research fellow at the University of Cambridge, Department of Engineering, specializing in fluid dynamics and applied mathematics. His work combines Bayesian inference, machine learning, and physics-informed algorithms to solve inverse problems in magnetic resonance velocimetry (MRV) and fluid-structure interaction. EPSRC National Fellow in Fluid Dynamics Member of Energy, Fluids and Turbomachinery Division Research Focus: Development of digital twin frameworks that integrate MRV data with Navier-Stokes equations to reconstruct flowfields, infer rheological parameters in non-Newtonian fluids, and estimate hidden quantities like pressure and wall shear stress. Key innovations include: Physics-informed compressed sensing for sparse MRV data Simultaneous boundary shape and flowfield estimation Bayesian turbulence model parameter learning Scientific Awards: ASME Fluids Engineering Division Graduate Student Scholar (2021) Technical Chamber of Greece (TEE) Award (2018) Limmat Foundation Academic Excellence (2017) Mentzelopoulos Scholarship for international studies (2017) Greek State Scholarships Foundation Award (2012) Key Contributions: Algorithms for 3D flow reconstruction with adaptive discretization, viscous signed distance field regularization, and multi-objective aerodynamic shape optimization. His methodologies enable 27x reductions in MRI scanning time while maintaining diagnostic accuracy.

• Open Innovation
• Technology Transfer
• Food Industry Innovation
• +4 more

Barbara Bigliardi is an Associate Professor at the Department of Engineering and Architecture, University of Parma, with national scientific qualification for full professor in Economic-Management Engineering (SSD ING-IND/35). She serves as President of the Management Engineering Program at University of Parma and Director of Bachelor's/Master's programs at University of San Marino, co-leading double-degree initiatives between the two institutions. Over 100 publications (57 SCOPUS-indexed) with H-index=20 Editorial roles: Cambridge Scholars Publishing (2019), MDPI Sustainability, Sci, European Journal of Innovation Management Key research areas: Open Innovation, Technology Transfer, Food Industry Innovation, Industry 4.0, Supply Chain Sustainability Recent Publications (2024-2025) demonstrate leadership in: Industry 4.0 integration with circular economy AI applications in public administration and healthcare Digitalization of food supply chains Green startup resource orchestration Simulation-based optimization in remanufacturing Sustainable additive manufacturing Scientific Recognition : 2005 Emerald Highly Commended Award 2013 Most Cited Paper in Trends in Food Science & Technology 2019 Highly Cited Paper in Review of Policy Research Research Leadership includes: National Observatory on Start-ups (President since 2021) National Observatory on Reputation (Vice President since 2019) INAIL-funded mobile risk assessment systems (2018-2020) INAF space technology transfer projects (2018-present) Academic Contributions : Supervised over 300 theses Deputy Coordinator of Industrial Engineering Doctoral Program Director of Management Engineering Programs (Parma & San Marino) Founder of academic spin-offs: Sistemi per il marketing di contenuto S.r.l. (2016-present), Univenture SrL (2006-2010)

Jie ChenView profile

Assistant Professor

• Advanced Manufacturing
• Design Optimization
• Machine Learning
• +4 more

Jie Chen is an Assistant Professor in the Department of Mechanical Engineering at Virginia Tech's College of Engineering. Their research bridges machine learning with engineering analysis and design under uncertainty, focusing on process-structure-property-performance relationships. PhD, Mechanical Engineering (2022) – Arizona State University MS, Civil Engineering (2018) – Beihang University BS, Civil Engineering (2015) – Beihang University Research interests include: physics-informed machine learning, uncertainty quantification, predictive maintenance, materials design, and advanced manufacturing. The SEAD Lab develops methods to integrate engineering analysis into stochastic machine learning algorithms and uses AI for knowledge discovery in uncertain environments. Recent publications emphasize: Digital twin frameworks combining machine learning and Bayesian optimization Graph neural networks for high-entropy alloy and molecular mixture property prediction Physics-guided neural networks for fatigue life analysis of additively manufactured alloys Uncertainty quantification in imbalanced regression tasks and multi-fidelity data fusion Real-time imaging of polymer deformation mechanisms The lab actively mentors students, including PhD candidate Yisheng Lu, and manages projects in predictive maintenance, fatigue modeling, and materials design.

• Biomaterials
• Biomechanics
• Materials Science
• +4 more

Cecilia Persson is a Professor at Uppsala University in the Department of Materials Science and Engineering; Biomedical Engineering. She leads the BioMaterial Systems (BMS) research group within the Division of Biomedical Engineering, focusing on the development of new biomaterials through additive manufacturing. She also directs a Competence Centre in Additive Manufacturing for the Life Sciences and the national Research Technology Platform WISE Additive. 2018, Professor in Materials Science, Uppsala University 2015, Docent (Assoc. Prof.) in Engineering Science with Specialization in Materials Science, Uppsala University 2009, PhD in Mechanical Engineering, University of Leeds 2004, MSc in Materials Engineering, European degree (EEIGM) with triple diploma Persson's research focuses on biomaterials, biomechanics, materials science, and additive manufacturing. Her work takes an integrated approach to solving clinical and sustainability problems, combining materials science, mechanical and biological engineering with new technologies like 3D printing and machine learning. Key research areas include magnesium-based alloys for bone substitutes, titanium-based alloys for permanent implants, and machine learning methods to enhance manufacturing efficiency. Analysis of her recent publications shows a strong emphasis on additive manufacturing of biomaterials, particularly magnesium and titanium alloys. Her work explores microstructure control, mechanical properties optimization, antibacterial properties, and patient-specific implant design. The research demonstrates a clear trajectory toward more sustainable, patient-adapted medical solutions using advanced manufacturing techniques. Persson has received funding from prestigious organizations including the Swedish Research Council (VR), the Knut and Alice Wallenberg Foundation (KAW), the Swedish Foundation for Strategic Research (SSF), Sweden's Innovation Agency (VINNOVA), and the EU. As an academic leader, Persson has served as Section Dean of Engineering (2020-2023), President of the Scandinavian Society of Biomaterials (2019-2023), and Coordinator of EU Innovative Training Network NU-SPINE (2019-2023). Her BioMaterial Systems research group takes an integrated approach to solving clinical and sustainability problems, bridging fundamental scientific mechanisms with high societal relevance.

Mohamed EzzeldinView profile

Associate Professor

• Structural Engineering
• Seismic Risk Assessment
• Machine Learning in Construction
• +3 more

Mohamed Ezzeldin is an Associate Professor in the Department of Civil Engineering at McMaster University. His work integrates structural engineering, seismic resilience, and machine learning for infrastructure risk management. Research Interests: Seismic behavior of reinforced concrete and masonry structures, blast mitigation systems, urban resilience modeling, and AI applications in construction risk prediction. Teaching: Instructor for courses including Structural Mechanics (CIVENG 2C04), Modern Methods of Structural Analysis (CIVENG 4K04), and Seismic Behavior and Design of Reinforced Concrete Systems (CIVENG 716). His publications focus on hybrid simulation testing, data-driven risk assessment, and bio-inspired structural designs. Recent work (2025) includes advancements in seismic analysis of nuclear facilities and urban resilience frameworks.

Yu ZhangView profile

Lecturer

• Text Mining
• Information Management
• Social Computing
• +12 more

Dr. Yu Zhang is a Lecturer of Data Science at the School of Business, UNSW Canberra. His academic career focuses on text mining, knowledge and information management, social computing, and bibliometric analysis, with interdisciplinary applications in areas such as sustainable logistics, supply chain management, and net-zero energy solutions. Fields of Interest: Text Mining, Information Management, Social Computing, Bibliometric Analysis, Machine Learning for Information Systems, Heterogeneous Network Analysis, Data Mining for Asset Management, Sustainable Logistics, Supply Chain Management, Net-zero Energy in Green Buildings, and Transportation. Grants: Served as CI in projects like "Online health monitoring in Li-ion batteries via trustworthy AI" (ACT Government, $1.22M) and "Delivering net-zero energy buildings" (TRaCE Lab to Market, $1.05M). Awards: Best Paper Award (Runner-up) at ADMA 2024 and Excellent Paper Award at ICEBE 2024. Teaching: Coordinated courses in Data Analytics, Workforce Planning Research, Business Capstone, and Logistics Intelligence with Big Data Analysis. Supervision: Guided research on topics like federated learning for healthcare fraud detection, blockchain-based carbon offset management, and tier-based supply chain visibility. His publications span materials science and photovoltaic technologies, with a focus on thin-film solar cells and defect passivation methods. For collaboration or supervision inquiries, contact him at m.yuzhang@unsw.edu.au .

Qing XiaoView profile

Professor

• Computational Fluid Dynamics
• Biomimetics
• Marine Renewable Energy
• +3 more

Professor Qing Xiao is a faculty member in the Department of Naval Architecture, Ocean and Marine Engineering at the University of Strathclyde . With over 25 years of expertise in Computational Fluid Dynamics (CFD) , they focus on bio-inspired fluid dynamics and marine renewable energy systems. Their research includes modeling flapping-wing aerodynamics, tidal turbines, and floating wind turbines with coupled aero-hydrodynamic simulations. Research Themes: Bio-inspired robotics, offshore renewable energy, fluid-structure interaction, vortex-induced vibrations. Collaborations: EPSRC-funded projects, Supergen ORE Hub partnerships, and industrial alliances. Recent Work: AI-driven surrogate models for floating offshore wind turbines, hyperelastic material applications in wave energy converters, and digital twin frameworks for structural health monitoring. Scientific Recognition: OMAE Subrata Chakrabarti Young Professional Award (2017) Strathclyde Teaching Excellence Award (2013) Students & Supervision: Advising PhD candidates like Kobe Hoi Yin Yung and Hoi Yin Yung, with graduates Xiang Li and Yang Luo contributing to bio-inspired robotics and CFD-FSI studies. Labs & Teams: Leads an interdisciplinary CFD-FSI research group at Strathclyde, fostering academic-industrial cooperation and hosting visiting researchers.