Enio-Vasconcelos Filho-Machine Learning for Computer Vision-Editorial Board Member

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Enio-Vasconcelos Filho-Machine Learning for Computer Vision-Editorial Board Member

CISTER - Research Centre in Real-Time Computing & Embedded Computing Systems-Portugal

Author Profile

Early Academic Pursuits

Enio Prates Vasconcelos Filho began his academic journey at the University of Brasilia (UNB), earning a Bachelor's degree in Mechatronic Engineering in December 2006. During his undergraduate studies, he focused on the simulation of robot soccer games using reconfigurable architectures based on FPGA-PCI boards, which culminated in his thesis. He continued his academic pursuits at UNB, obtaining a Master's degree in Mechatronic Systems in January 2013. His master's thesis involved the development of a trajectory planner and open-loop control system for a spherical robotic manipulator, embedded in an FPGA platform.

Professional Endeavors

Following his academic achievements, Enio gained valuable industry experience. He worked as a Senior Engineer at Innovix Services and Commerce S.A. in Brazil from August 2008 to June 2015. During this period, he participated in energy efficiency, security, and telemetry projects, demonstrating proficiency in C, C++, and C# programming. Additionally, he managed teams for developing software and hardware for web access control systems and telemetry based on IoT devices.

Contributions and Research Focus

Enio pursued a Ph.D. in Electrical and Computer Engineering at the Faculty of Engineering of Porto (FEUP) from September 2018 to May 2023. His research focused on the development of an Evaluation Framework for Safe Cooperative Vehicle Platooning, utilizing ROS (Robot Operating System). This comprehensive research included the integration of software, hardware in the loop, and robotic testbeds. Enio's contributions encompassed two book chapters, four journal papers, eight congress papers, two extended abstracts, and two posters. Notably, he received the ICARSC 2020 Highly Commended Paper Award and the DCE 2019 Best Poster Presentation Award.

Accolades and Recognition

Enio's dedication to research and innovation has been acknowledged with several honors and awards. In 2019, he received the Best Poster Presentation at the 3rd Doctoral Symposium in Engineering from the Faculty of Engineering of Porto University. In 2020, his paper was recognized with the Highly Commended Paper award at the IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC).

Impact and Influence

As a Senior Engineering Science Researcher at CISTER Research Centre in Real-Time & Embedded Computing Systems (October 2018 to September 2022), Enio played a key role in studying real-time systems for vehicular control in cooperative cyber-physical systems. He led a team in the Horizon 2020 project ADACORSA, contributing to specifications and use case designs. His work also involved the development of a ROS simulator for evaluating control and communication models.

Legacy and Future Contributions

Enio Prates Vasconcelos Filho currently works as a Software Engineer at Critical Techworks in Porto, Portugal, focusing on automation and safety-driven systems. With a rich background in academia, industry, and research, Enio continues to make significant contributions to the fields of robotics, automation, and safety. His extensive experience, coupled with his passion for teaching as an Invited Assistant Professor at Instituto Superior de Engenharia do Porto, reflects a commitment to shaping the next generation of engineers. As he progresses in his career, Enio is poised to leave a lasting legacy in the realms of safety engineering and automation.

Notable Publication

Husna Sarirah-Husin-Applications of Computer Vision-Women Researcher Award

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Husna Sarirah-Husin-Applications of Computer Vision-Women Researcher Award

Taylor's University-Malaysia

Author Profile

Early Academic Pursuits

Dr. Husna Sarirah Husin embarked on her academic journey with a solid foundation in computer science. She holds a Doctor of Philosophy (Ph.D.) degree from RMIT University Melbourne, Australia, with a focus on analyzing user behavior on an online newspaper using web server logs. Prior to her Ph.D., she obtained a Master of Science in Information Management from University Technology MARA (UiTM) and a B.Sc. (Honours) in Computer Science from Coventry University.

Professional Endeavors

With a rich blend of academic and industrial experience spanning over 22 years, Dr. Husna Sarirah Husin has made significant contributions to both sectors. She has served in various academic and managerial roles in universities, with a current position as a Senior Lecturer at Taylor’s University since October 2023. Previously, she held the position of Senior Lecturer at Universiti Kuala Lumpur, Malaysian Institute of Information Technology (UniKL-MIIT) for nearly 18 years.

In her industrial tenure, Dr. Husna worked as a Systems Analyst for the e-Tanah Project Team at the Ministry of Natural Resources & Environment, and as a Programmer at New Straits Times Press Bhd.

Contributions and Research Focus

As an active researcher, Dr. Husna has secured multiple research grants and has an impressive list of publications. Her research encompasses various areas, including data mining, process mining, online learning behavior, technology acceptance in healthcare business operations, and more. Notably, her Ph.D. dissertation focused on the analysis of user behavior on an online newspaper using web server logs.

Dr. Husna has contributed to numerous conferences and journals, presenting papers on diverse topics such as sensing matrix design, capital management of family businesses, GAN-based COVID-19 classification, and process mining for online learning behavior analysis.

Accolades and Recognition

Dr. Husna has been recognized as a Senior IEEE Member and holds memberships in organizations like MBOT (Malaysian Board of Technologists). Her ORCID ID and Scopus Author ID reflect her commitment to academic and research standards.

She has also received research grants as a Principal Investigator and has been involved in various capacities such as being the Director of the Center for Alumni and Career Services at Universiti Kuala Lumpur.

Impact and Influence

Dr. Husna's impact extends beyond her academic and research achievements. She has served as the Research Coordinator at Universiti Kuala Lumpur, where she played a pivotal role in organizing research webinars, workshops, and fostering collaboration with various institutions.

As a director and coordinator, she has influenced the academic landscape through her involvement in research centers, editorial roles, and project leadership.

Legacy and Future Contributions

Dr. Husna Sarirah Husin's legacy lies in her extensive contributions to academia, research, and industry. Her diverse skill set in database management, statistical analysis, data mining, and visualization positions her as a valuable asset in shaping the future of technology and education.

In the future, one can expect Dr. Husna to continue making significant contributions to the fields of information technology, data analytics, and education, leaving a lasting impact on the next generation of researchers and professionals.

Notable Publication

Human Pose Estimation

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Introduction of Human Pose Estimation

Human Pose Estimation research is a pivotal area within computer vision that focuses on the accurate localization and tracking of human body key points and joints in images and videos. This technology has far-reaching applications, including gesture recognition, action analysis, sports analytics, and healthcare, making it an essential field in understanding human movements and interactions with machines.

Subtopics in Human Pose Estimation:

  1. 2D Human Pose Estimation: Researchers work on algorithms that can estimate the 2D coordinates of key body joints in images or video frames, allowing for applications like human-computer interaction and motion analysis.
  2. 3D Human Pose Estimation: This subfield involves estimating the three-dimensional positions of body keypoints, enabling applications in virtual reality, augmented reality, and biomechanics.
  3. Real-Time Pose Estimation: The development of real-time and low-latency pose estimation methods that can operate efficiently on embedded devices, essential for applications like robotics and gaming.
  4. Multi-Person Pose Estimation: Researchers tackle the challenge of estimating the poses of multiple individuals in crowded scenes or group settings, facilitating applications in surveillance and social analysis.
  5. Pose Estimation for Healthcare: Human pose estimation is applied in healthcare for posture analysis, fall detection, and rehabilitation monitoring, assisting in patient care and physical therapy.

Human Pose Estimation research continues to advance our understanding of human movement and interaction with technology, enabling a wide range of applications across various domains. These subtopics represent the key directions within this dynamic field.

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