Erfan Shojaei Barjuei – Automated planning and scheduling Award – Top Researcher Award

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Erfan Shojaei Barjuei – Automated planning and scheduling Award – Top Researcher Award

Dr. Erfan Shojaei Barjuei distinguished academic and researcher in the field  Automated Planning and Scheduling. Throughout my career journey, I’ve traversed diverse roles and geographical locations, accumulating a wealth of experience in research and engineering. From delving into the intricacies of mechatronics engineering at institutions like the Italian Institute of Technology and the Sant’Anna School of Advanced Studies in Italy, to contributing to cutting-edge research in mechanical and automation engineering at the National Institute of Applied Sciences in France, I’ve always been driven by a passion for innovation and problem-solving.

My academic pursuits have taken me across borders, from pursuing a research fellowship in robotics and artificial intelligence at Sapienza University of Rome to my current role as a postdoctoral researcher in mechanical and manufacturing engineering at the University of Calgary in Canada. These experiences have not only deepened my understanding of the field but also honed my skills in tackling complex challenges and pushing the boundaries of technological advancement.

In addition to my academic endeavors, I’ve also had the opportunity to apply my expertise in industry settings. As a part-time mechatronics engineering consultant at Halo Beauty in the USA, I provided valuable insights and solutions, leveraging my expertise to contribute to the company’s projects. Currently, as a product software engineer at Cure Data in the USA, I am engaged in developing software products with a focus on data analysis, leveraging my diverse background to drive innovation and deliver impactful solutions.

My journey has been characterized by a relentless pursuit of knowledge and a commitment to excellence, and I look forward to continuing to contribute to the forefront of research and innovation in the years to come.

🌐 Professional Profiles

Educations📚📚📚

He pursued his academic journey with zeal and dedication, starting with a Bachelor of Science in Electrical Engineering from Azad University in Iran, where he laid the foundation for his future endeavors. Building upon this strong base, he pursued a Master of Science in Mechatronics Engineering at Sharif University of Technology in Iran from 2006 to 2008, delving into the interdisciplinary realm of engineering. Eager to deepen his knowledge further, he embarked on a PhD in Industrial and Information Engineering with a focus on Mechatronics Curricula at the University of Udine in Italy from 2013 to 2016, where he honed his research skills and expertise. Continuing his pursuit of academic excellence, he completed a Master of Science in Computer Engineering with a specialization in Human-Computer Interaction & Artificial Intelligence Curricula at the University of Genoa in Italy from 2018 to 2022, further broadening his horizons and enhancing his proficiency in cutting-edge technologies. Through his academic endeavors, he has demonstrated a relentless commitment to learning and growth, equipping himself with the knowledge and skills to thrive in the ever-evolving field of engineering and technology.

RESEARCH INTERN

During his time as a research intern at Karlstad University in Sweden from August 2015 to December 2015, he immersed himself in the field of assistive robotics. Focused on the design of a human-friendly walking assist robot vehicle, he dedicated his efforts to refining control systems and variable stiffness mechanisms. Through his internship, he gained valuable hands-on experience in the development of innovative solutions aimed at enhancing mobility and accessibility. His contributions during this period underscored his commitment to leveraging technology for the betterment of society, particularly in improving the quality of life for individuals with mobility impairments.

 

He has a keen interest in a wide array of research areas within the realm of engineering and technology. His primary focus lies in robotics and mechatronic systems, where he explores the intricate dynamics and control mechanisms governing these complex systems. With a passion for advancing the field, he dedicates his efforts to refining models and control algorithms to optimize the performance of mechatronic systems. Additionally, he delves into the realm of artificial intelligence, leveraging cutting-edge techniques to enhance the capabilities of autonomous systems and intelligent agents. His research also extends to advanced manufacturing, where he explores innovative approaches to streamline production processes and improve efficiency. Furthermore, he is fascinated by the potential of vision systems in industrial automation, investigating novel techniques to enhance perception and decision-making capabilities in automated systems. Through his research endeavors, he continually seeks to push the boundaries of engineering innovation and contribute to the development of transformative technologies.

INDUSTRIAL PROJECTS

In his current role at Cure Data in the USA from February 2024 to the present, he collaborates closely with a multidisciplinary R&D team comprising engineers, scientists, and physicians. Together, they are dedicated to the development of an extensive digital twin, a digital replica used for modeling and simulating human organs. His contributions to this project involve leveraging his expertise in various fields to enhance the accuracy and functionality of the digital twin, aiming to revolutionize medical research and treatment approaches.

During his tenure at Halo Beauty in the USA from September 2023 to December 2023, he played a pivotal role in developing core aspects of control and electrical engineering, as well as a vision system for an automated hair braider. Working in tandem with a mechanical engineering team, he focused on refining the end-effector, sensor-based controls, and retraction systems. His collaborative efforts ensured the seamless integration of electrical and control components, optimizing the performance and efficiency of the automated hair braider.

AWARDS AND HONORS

Throughout his career, he has garnered recognition for his outstanding achievements and contributions to the field of engineering. Notably, in September 2019, he received the Best Conference Paper Award at the IEEE International Conference on Cyborg and Bionic Systems (CBS 2019) held in Munich, Germany, showcasing his excellence in academic research and innovation. His dedication to excellence was further acknowledged with an Internship Fellowship at Karlstad University in Sweden from August 2015 to December 2015, providing him with valuable practical experience in the field.

In March 2015, he was honored with the NI (National Instruments) Engineering Impact Awards 2015 for Best Application in Advanced Research, recognizing his significant contributions to the advancement of engineering technologies. This accolade was bestowed upon him during NIDays 2015 in Milan, Italy, highlighting his innovative approaches and impactful research endeavors.

Additionally, he was awarded a Winter School Scholarship in February 2015 to attend the SAPHARI NMMI Winter School in Rome, Italy, demonstrating his commitment to continuous learning and professional development. His academic prowess was evident during his master’s studies, as he successfully completed the Master’s Degree Honors Program at Sharif University of Technology in Iran in July 2008, attesting to his exceptional academic performance and dedication to scholarly pursuits.

Moreover, his leadership abilities and accomplishments were recognized early in his career when he received a Travel Grant in November 2003 for his successful leadership of the executive team in the National Robotic Race of Intelligent Devices at Azad University in Iran, underscoring his capability to excel in both academic and practical domains, as well as his adeptness in leading collaborative endeavors.

📝🔬Publications📝🔬
  • Meghdari.A, Mirfakhree.F, Akrami.S.M, Shojaei Barjuei.E
    Introduction to Robotics: Mechanics and Control (By: Craig.J.J)
    Third Edition, Sharif University Press, Iran, 2009 (ISBN: 978‐964‐208-019‐9)
  • Akrami.S.M, Shojaei Barjuei.E
    Mechatronics: Dynamics of Electromechanical and Piezoelectric Systems (By:Preumont.A)
    Fan Afzar press, Tabriz, Iran, 2009 (ISBN: 978-964-8150-24-9).
  • Shojaei Barjuei.E, Shin. J, Kim. K, Lee. J
    Precision improvement of robotic bioprinting via vision-based tool path compensation
    Accepted in Scientific Reports.
  • Shojaei Barjuei.E, Capitanelli.A, Bertolucci.R, Courteille.E, Mastrogiovanni.F, Maratea.M
    Digital Workflow for Printability and Prefabrication Checking in Robotic Construction 3D Printing
    Based on Artificial Intelligence Planning
    Engineering Applications of Artificial Intelligence, vol. 133, p. 108254, 2024.
  • Shojaei Barjuei.E, Courteille.E, Rangeard.D, Marie.F, Perrot.A
    Real-time vision-based control of industrial manipulators for layer-width setting in concrete 3D
    printing applications
    Advances in Industrial and Manufacturing Engineering (2022): 100094.
  • Bianchi.F, Masaracchia.A, Damone.A, Falotico.F, Shojaei Barjuei.E, Oddo.C, Dario.P, Ciuti.G
    Hybrid 6-DoFs magnetic localization for robotic capsule endoscopes compatible with high-grade
    magnetic field navigation
    IEEE Access 10 (2021): 4414-4430.
  • Shojaei Barjuei.E, Darwin.G.C, Ortiz.J
    Bond Graph Modeling and Kalman Filter Observer Design for a Back-Support Exoskeleton
    Designs 4.4 (2020): 53.
  • Shojaei Barjuei.E, Ortiz.J
    A Comprehensive performance comparison of Linear Quadratic Regulator (LQR) controller, Model
    Predictive Controller (MPC), H∞ loop shaping and μ-synthesis on spatial compliant linkmanipulators
    International Journal of Dynamics and Control 9 (2021): 121-140.
  • Bianchi.F, Masaracchia.A, Shojaei Barjuei.E, Menciassi.A, Arezzo.A, Koulaouzidis.A, Stoyanov.D,
    Oddo.C, Dario.P, Ciuti.G
    Localization strategies for robotic endoscopic capsules: a review
    Expert review of medical devices 16.5 (2019): 381-403.
  • Li.J, Shojaei Barjuei.E, Ciuti.G, Hao.Y, Zhang.P, Shi.Q, Menciassi.A, Huang.Q, Dario.P
    Magnetically-driven medical robots: an analytical magnetic model for endoscopic capsules design
    Journal of Magnetism and Magnetic Materials 452 (2018): 278-287.
  • Shojaei Barjuei.E
    Hybrid position/force control of a spatial compliant mechanism
    International Journal of Automotive and Mechanical Engineering, ISSN: 2229-8649 (Print); ISSN:
    2180-1606 (Online); Volume 14, Issue 3 pp. 4531-4541 September 2017
  • Shojaei Barjuei.E, Boscariol.P, Gasparetto.A, Vidoni.R
    Robust control of Three-Dimensional Compliant Mechanisms
    Journal of Dynamic Systems, Measurement & Control, 2016, 138, 101009-1-14.
  • Abdolshah.S, Shojaei Barjuei.E
    Linear Quadratic Optimal Control of Cable-Driven Parallel Robots
    Journal of Frontiers of Mechanical Engineering, FME-15038-AS, vol.10, no. 4, pp. 344–351, 2015

Guangli Wu – Video Summarization – Best Researcher Award

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Guangli Wu – Video Summarization

prof Dr. Guangli Wu  distinguished academic and researcher in the field  Video summarization.  The existence of software vulnerabilities will cause serious network attacks and information leakage problems. Timely and accurate detection of vulnerabilities in software has become a research focus on the security field. Most existing work only considers instruction-level features, which to some extent overlooks certain syntax and semantic information in the assembly code segments, affecting the accuracy of the detection model. In this paper, we propose a binary code vulnerability detection model based on multi-level feature fusion. The model considers both word-level features and instruction-level features. In order to solve the problem that traditional text embedding methods cannot handle polysemy, this paper uses the Embeddings from Language Models (ELMo) model to obtain dynamic word vectors containing word semantics and other information. Considering the grammatical structure in the assembly code segment, the model randomly embeds the normalized assembly code segment to represent it. Then the model uses bidirectional Gated Recurrent Unit (GRU) to extract word-level sequence features and instruction-level sequence features respectively.

Eduvation

He pursued his academic journey with a solid foundation in computer science and technology, earning a Bachelor’s degree from Shandong Technology and Business University in 2003. Building upon this, he delved into the realm of Computer Application Technology, completing his Master’s degree at Northwest Minzu University in 2007. Driven by a passion for cultural diversity and linguistic exploration, he further expanded his expertise by attaining a doctoral degree in Chinese Minority Ethnic Languages and Literature from Northwest Minzu University in 2011. This educational trajectory reflects his commitment to a multidisciplinary approach, seamlessly blending computer technology with a profound understanding of language and culture.
Professional Profiles:

RESEARCH INTEREST

⚫ Video Summarization
⚫ Temporal Language Localization in videos
⚫ Botnet Detection
⚫ Binary Code Vulnerability Detection
⚫ Video Abnormal Event Detection
FUND PROJECTS
1. Natural Science Foundation of Gansu Province (17JR5RA161, 21JR7RA570)
2. Gansu University of Political Science and Law Major Scientific Research and Innovation Projects
(GZF2020XZDA03)
3. Young Doctoral Fund Project of Higher Education Institutions in Gansu Province (2022QB-123)
4. Gansu Province Higher Education Innovation Fund Project (2017A-068)
5. University-level Innovative Research Team of Gansu University of Political Science and Law
6. Longyuan Youth Innovation and Entrepreneurship Talent Project (2022QB-123)

MAIN SCIENTIFIC PUBLICATIONS

1. Guangli Wu,ShengTao Wang,Shipeng Xu. “Feature fusion over hyperbolic graph convolution networks for
video summarization.” IET Computer Vision,2023.
2. Guangli Wu,Tongjie Xu. “Video Moment Localization Network Based on Text Multi-semantic Clues
Guidance.” Advances in Electrical and Computer Engineering,2023,23(3):85-92.
3. Guangli Wu,Huili Tang. “Binary Code Vulnerability Detection Based on Multi-Level Feature Fusion.” IEEE
Access,2023,11: 63904-63915.
4. Guangli Wu,Shanshan Song,Leiting Li. “Video Summarization Generation Model Based on Transformer
and Deep Reinforcement Learning.” in 2023 8th International Conference on Computer and
Communication Systems (ICCCS). IEEE, 2023: 916-921.
5. Guangli Wu,Shengtao Wang,Liping Liu. “Fast Video Summary Generation Based On Low Rank Tensor
Decomposition.” IEEE Access,2021,9:127917-127926.
6. Guangli Wu,Zhenzhou Guo,Mianzhao Wang,Leiting Li and Chengxiang Wang. “Video Abnormal Event
Detection Based on CNN and Multiple Instance Learning.” in twelfth international conference on signal
processing systems. SPIE,2021:134-139.
7. Guangli Wu,Zhenzhou Guo,Leiting Li and Chengxiang Wang. “Video Abnormal Event Detection Based on
CNN and LSTM.” in 2020 IEEE 5th International Conference on Signal and Image Processing (ICSIP).
IEEE,2020: 334-338.
8. Guangli WU,Leiting LI,Zhenzhou GUO,Chengxiang WANG and Yanpeng, YAO. “Video summarization
Based on ListNet Scoring Mechanism.” in 2020 5th International Conference on Computer and
Communication Systems (ICCCS). IEEE,2020: 281-285.
9. Guangli WU,Liping LIU,Chen Zhang and Dengtai TAN. “Video Abnormal Event Detection Based on ELM.”
in 2019 IEEE 4th International Conference on Signal and Image Processing (ICSIP).IEEE,2019: 367-371

 

Maria Pregnolato – Causal mapping

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Assoc Prof Dr. Maria Pregnolato – Leading Researcher in Causal mapping

Dr Maria Pregnolato is a Civil Engineer and holds a MSc in Building Engineering and Architecture from the University of Pavia (Italy) and the Tongji University of Shanghai (China), a PhD in Civil Engineering from Newcastle University (UK) and MSc in Strategy, Leadership and Change from the University of Bristol (UK). Her work focuses on infrastructure resilience and risk management from natural hazards, in particular the impact of flooding to road networks, bridges and buildings. She held an EPSRC (Engineering and Physical Sciences Research Council, UK) Fellowship to investigate the impact of extreme flooding to bridges, including hydrodynamic modelling and scour risk management. In recent years, she has been

Education📚

🎓 Maria Pregnolato’s educational and professional journey is a testament to her dedication and expertise. From November 2020 to November 2022, she pursued her Master of Science in Strategy, Change, and Leadership at the School of Management, University of Bristol, UK, laying the groundwork for her proficiency in strategic management and leadership.

🏗️ Building on this, from January 2014 to November 2017, Maria embarked on a transformative research venture, earning her Doctorate in Urban Infrastructure Resilience at the School of Engineering, Newcastle University, UK. This impactful journey was funded by EPSRC, with contributions from ESRC, iBUILD EP/K012398/1, and EU H2020 RAMSES no. 308497. Her thesis, “Risk analysis of the disruption to urban transport networks from pluvial flooding,” showcased her commitment to understanding and mitigating risks in urban environments.

Rewinding to her earlier years, from October 2007 to December 2012, Maria pursued a Master of Science in Building Engineering-Architecture, earning the distinction of magna cum laude. This joint degree, funded by MIUR and a collaboration between the Università degli Studi di Pavia (Italy) and Tongji University of Shanghai (China), was a platform for her thesis, “Architecture and Structure: a new relation with Landscape,” where she explored innovative connections between architecture and the environment.

Professional Profiles:
ACADEMIC AND RESEARCH EXPERIENCE

🌐 Since March 2023, she has been serving as an Associate Professor in Flood Risk Management and Resilient Infrastructure at TU Delft in the Netherlands. This role, based in Delft, involves contributing to the Faculty of Civil Engineering & Geosciences within the Department of Hydraulic Engineering. Additionally, she holds an Honorary Associate Professor position in Infrastructure Resilience at the University of Bristol in the UK, fostering collaborative ties between these two esteemed institutions.

🏛️ Before her current position, from August 2022 to March 2023, she served as a Senior Lecturer in Civil Engineering at the University of Bristol, contributing to the Department of Civil Engineering within the School of Civil, Aerospace, and Mechanical Engineering (CAME). This role followed her tenure as a Lecturer in Civil Engineering from November 2018 to August 2022, where she actively engaged in shaping the academic landscape.

👩‍🏫 Her academic journey includes a significant role as an EPSRC Fellow from March 2018 to May 2022, supported by the Engineering and Physical Sciences Research Council. During this time, she conducted personal research and contributed to advancements in the field.

✈️ The global scope of her academic endeavors includes visiting assistant professorships in various locations. In June 2022, she contributed to TU Delft in the Netherlands, followed by a stint in Milan, Italy, from February to May 2022, at the Polytechnic of Milan’s Department of Architecture, Built Environment, and Construction Engineering. Her international experiences also extend to a visiting assistant professor role at the University of Washington in Seattle, USA, from May to September 2019.

🔬 Earlier in her career, from March 2017 to March 2018, she served as a Research Associate at Newcastle University in the UK, contributing to the EPSRC ITRC-MISTRAL project (EP/N017064/1) within the School of Engineering.

🌟 Maria Pregnolato’s academic and research journey reflects a commitment to excellence, collaboration, and contributing to the fields of flood risk management, resilient infrastructure, and civil engineering on both national and international stages.

 

SPECIAL AWARDS, HONOURS

In 2023, she received the IABSE (International Association for Bridge and Structural Engineering) Outstanding Paper Award in the Scientific Paper category for the work by Orcesi et al. in 2022. This recognition highlights the excellence and impact of her research in the field.

In 2021, she was honored with the European Geoscience Union (EGU) Outstanding Early Career Award, acknowledging her contributions to the geoscience community.

Since 2019, she has held the prestigious position of an EPSRC Fellow of the Women in Engineering Society (WES), reflecting her commitment to advancing women’s participation and recognition in the engineering field.

In 2019, she achieved 1st place at the “Italy Made Me” UK Early-career Awards, underlining the recognition of her early-career achievements.

The year 2018 brought further accolades, including the EPSRC RISE (Recognizing Inspirational Scientists and Engineers) Award, acknowledging her inspirational contributions to the field. Additionally, she secured 2nd place at the ABTA UK Doctoral Researcher Awards, further highlighting the quality and impact of her doctoral research.

In 2016, she was honored with the Young Author Award for the best oral presentation at FLOODrisk 2016 in Lyon, recognizing the excellence of her work in the field of flood risk management.

Her contributions were further acknowledged in 2017 when she became a shortlisted finalist at STEM for Britain, an event hosted at the House of Commons in London, demonstrating the recognition of her work at a national level. These awards collectively reflect her dedication to advancing knowledge and making significant contributions to the scientific community.

COMMITTEE and MEMBERSHIPS

2023-now –   Board Member of 4TU Resilience Engineering Centre (4TU.RE)
2022-now  – Board Member of NERC Digital Research and Infrastructure Group (DRIG)
2016-now –  Member of the European Geoscience Union
2022-23  –  UKCRIC Soil-Foundation-Structure Interaction (SoFSI) Executive Board member
2021-23 –  Co-leader for the Met Office Academic Partnership (MOAP)
2021-23  – Board member of the Brunel Institute
2021-22  – Digital Environment Fellow ofthe NERC UKRI ‘Constructing a Digital Environment’ Programme
2020-21 –  Board member of the GW4 Water Security Alliance

Publications:

  • Kumar, V., Gunner, S., Pregnolato, M., Tully, P., Georgalas, N., Oikonomou, G., Karatzas, S. and Tryfonas, T. (accepted October 2023). From IoT sensors and Open Data Platforms to Urban Observatories. IET Smart Cities, in press.
  • Evans, B., Lam, A., West, C., Ahmadian, R., Djordjevic, S., Chen, A.S. and Pregnolato, M. (2023). A combined stability function to quantify flood risks to pedestrians and vehicle occupants. Science of the Total Environment, 168237. Link
  • Beevers, L., Popescu, I., Pregnolato, M., Liu, Y. and Wright, N. (2022). Identifying hotspots of hydro-hazards under global change: a worldwide review. Frontiers in Water, 4: 1-14. Link
  • Pregnolato, M., Gunner, S. D., Voyagaki, E., De Risi, R., Gavriel, G., Carhart, N.J., Macdonald, J.H.G., Tryfonas, T. and Taylor, C. A. (2022). Towards Civil Engineering 4.0: concept, workflow and application of Digital Twins for existing infrastructure. Automation in Construction, 141: 104421. Link
  • Pregnolato, M., Winter, A.O., Mascarenas, D., Sen, A.D., Bates, P. and Motley, M.R. (2022). Assessing flooding impact to riverine bridges: an integrated analysis. Nat. Hazards Earth Syst. Sci, 22: 1559–1576. Link
  • Jaroszweski, D., Wood, R., Chapman, L., …, Pregnolato, M., … et al. (2021). Infrastructure. In: The Third UK Climate Change Risk Assessment Technical Report. [Betts, R.A., Haward, A.B., Pearson, K.V. (eds)] Prepared for the Climate Change Committee, London. Link
  • **Arrighi, C., Pregnolato, M. and Castelli, F. (2021). Indirect flood impacts and cascade risk across interdependent linear infrastructures. Nat. Hazards Earth Syst. Sci., 21: 1955–1969. [Link](https://doi.org/10.5194/nhess-21-1955-202