A S M Ahsanul Sarkar Akib | Cyber Threat | Best Researcher Award

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Mr. A S M Ahsanul Sarkar Akib | Cyber Threat | Best Researcher Award

Managing Director at Robo Tech Valley, Bangladesh

Mr. A.S.M. Ahsanul Sarkar Akib is a highly accomplished robotics and technology expert based in Bangladesh. He holds a Bachelor of Science in Engineering from the Bangladesh University of Business and Technology, specializing in Computer Science and Engineering. With a strong passion for robotics, IoT, and drone development, he has gained extensive experience in the field through roles such as Technical Director at the Japan-Bangladesh Robotics and Advanced Technology Research Centre, and Robotics Trainer at various universities. Additionally, he is the Founder & CEO of Dhopa Elo Online Laundry Service and Robo Tech Valley & Shop. Mr. Akib has also earned several accolades, including multiple championships in robotics competitions such as Ureckon 19 in India and Technocracy 2019 in Bangladesh. His innovative projects include humanoid robots, self-learning AI educational robots, and IoT-based solutions for water turbines and smart door systems.

 

Profile

Google Scholar

ORCID

Education

Mr. A.S.M. Ahsanul Sarkar Akib has a robust academic foundation, highlighted by his Bachelor of Science (B.Sc.) in Engineering from the Department of Computer Science and Engineering at Bangladesh University of Business and Technology. His academic journey is marked by exceptional achievements, including a GPA of 4.94 in his Higher Secondary Certificate (HSC) examinations from Cantonment Public School and College (BUSMS) under the Dinajpur Board, specializing in science. He also excelled in his Secondary School Certificate (SSC) examinations, attaining a GPA of 4.75 from the same institution. These accomplishments reflect his strong analytical abilities and dedication to academic excellence.

 Experience

Mr. A.S.M. Ahsanul Sarkar Akib has a diverse and extensive professional background in robotics, technology, and entrepreneurship. He has been serving as the Technical Director at the Japan-Bangladesh Robotics and Advanced Technology Research Centre since May 2018, where he plays a key role in advancing research and development in robotics. Additionally, he worked as a Robotics Trainer at BGC Trust University (Chattogram) and the National Academy for Computer Training and Research (NACTAR) in 2020. Mr. Akib also served as a Project Coordinator and Researcher at the Bangladesh Advance Robotics Research Center in 2018 and worked as a Robotics Engineer at Rafusoft Software and Robotics Firm between 2017 and 2018. Throughout his career, he has contributed to various robotics workshops across leading universities in Bangladesh, including Dhaka University, NSU, and Brac University. As an entrepreneur, Mr. Akib is the Founder & CEO of Dhopa Elo Online Laundry Service and the Founder & Managing Director of Robo Tech Valley & Shop, where he continues to drive innovation in both technology and business.

Research Interests

Mr. A.S.M. Ahsanul Sarkar Akib’s research interests lie in the fields of robotics, Internet of Things (IoT), and drone development. He focuses on developing cutting-edge technologies such as self-learning AI systems, humanoid robots, and IoT-based automation solutions. His work includes designing innovative projects like the Humanoid Bangla AI Robot “Bongo,” a self-learning educational robot, and various robotics systems for renewable energy applications, including hydro power water turbines and automated fish farming solutions. Mr. Akib is also passionate about developing IoT-based systems for smart home automation, water monitoring, and waste management. Through his research, he aims to push the boundaries of robotics and IoT technologies to improve daily life and contribute to sustainable development.

Skills

Mr. A.S.M. Ahsanul Sarkar Akib possesses a diverse set of technical skills, with expertise in robotics, IoT, and drone development. He is proficient in programming languages such as C, C++, Java, and Python, and has hands-on experience with Robotics Operating Systems (ROS). His technical skills also include working with Latex for documentation, and he is adept at designing and developing complex robotics systems. Additionally, Mr. Akib has specialized knowledge in the creation of self-learning AI models and the development of IoT-based solutions for smart homes, water monitoring systems, and renewable energy projects. His skills in project coordination and leadership, coupled with his deep understanding of cutting-edge technology, have made him a valuable asset in various robotics and technology-driven initiatives.

 

Publications

Artificial Intelligence Humanoid Bongo Robot in Bangladesh

  • Conference: 2019 1st International Conference on Advances in Science, Engineering, and Technology
  • Cited By: 22
  • Year: 2019

Future Micro Hydro Power: Generation of Hydroelectricity and IoT-Based Monitoring System

  • Conference: 2021 International Conference on Innovation and Intelligence for Informatics
  • Cited By: 4
  • Year: 2021

Precision Fish Farming to Mitigate Pond Water Quality Through IoT

  • Conference: 2024 IEEE 3rd International Conference on Computing and Machine Intelligence
  • Cited By: 1
  • Year: 2024

Computer Vision-Based IoT Architecture for Post-COVID-19 Preventive Measures

  • Journal: Journal of Advances in Information Technology
  • Volume: 14 (1), Pages: 7-19
  • Cited By: 5
  • Year: 2023

IoT-Based Smart Remote Door Lock and Monitoring System Using an Android Application

  • Journal: Engineering Proceedings
  • Volume: 76 (1), Pages: 85
  • Year: 2024

Conclusion

Mr. A.S.M. Ahsanul Sarkar Akib’s academic excellence, innovative research, and diverse professional achievements make him a strong candidate for the Best Researcher Award. His groundbreaking projects, technical expertise, and dedication to advancing robotics and IoT position him as a leader in his field, deserving of recognition for his contributions to science and technology.

Yuxing Yang | Detection and Prevention | Best Researcher Award

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Dr. Yuxing Yang | Detection and Prevention | Best Researcher Award

Postdoctoral at Xi’an Jiaotong-Liverpool University, China

Dr. Yuxing Yang is a dedicated researcher specializing in abnormal event detection, human action recognition, and multi-feature detection frameworks. He is currently pursuing his PhD in Engineering at Newcastle University, UK, focusing on developing novel frameworks for detecting abnormal events in video. Dr. Yang holds a Master’s degree in Electrical and Electronics Engineering from Newcastle University and a Bachelor’s degree in the same field from the University of Liverpool. His research experience spans signal processing, machine learning, and deep learning, with numerous publications in top-tier journals and conferences. Dr. Yang has also served as a Teaching Assistant and Research Assistant, mentoring students and contributing to key projects in multimodal security and video surveillance. His technical expertise, coupled with his leadership in academic and social initiatives, has earned him several accolades, including recognition for outstanding research presentations.

Profile:

Education:

Dr. Yuxing Yang has an extensive academic background in electrical and electronics engineering. He is currently pursuing a PhD in Engineering at Newcastle University, UK, where his research focuses on developing novel frameworks for multi-feature abnormal event detection in video. His PhD work addresses complex challenges in video anomaly detection, employing advanced signal processing and information fusion techniques under the supervision of Dr. Syed Mohsen Naqvi. Dr. Yang also holds a Master of Electrical and Electronics Engineering degree from Newcastle University, where he worked on a dissertation titled “PHD Filter for Multiple Human Tracking.” During his Master’s program, he studied modules such as Signal Processing, Modulation and Coding, Internet of Things, and Wireless Network Technologies. Dr. Yang earned his Bachelor’s degree in Electrical and Electronics Engineering from the University of Liverpool, where his dissertation explored the use of fluorescence for monitoring water quality. His academic journey has equipped him with deep expertise in embedded systems, digital and wireless communications, and engineering management.

Professional Experience:

Dr. Yuxing Yang has gained valuable professional experience through his research and teaching roles at Newcastle University, UK. From 2018 to 2023, he served as an MSc Research Assistant with the Intelligent Sensing and Communications (ISC) research group. In this role, he guided MSc students on projects related to signal processing, machine learning, and video anomaly detection. He played a crucial role in advising students, refining their research findings, and supporting the presentation of their work. Additionally, Dr. Yang worked as a Research Assistant on the 2021 EPSRC IAA project titled “Multimodal Human Security,” where he contributed to enhancing detection accuracy in security surveillance using multimodal data. His work on this project led to a publication at the IEEE International Conference on Information Fusion. Furthermore, Dr. Yang held a position as a Teaching Assistant and Lab Demonstrator at Newcastle University from 2018 to 2022, where he taught and mentored undergraduate and master’s students, providing instruction on theoretical concepts, lab equipment, and experiment conduction, while also assisting with grading and course evaluations.

Research Interests:

Dr. Yuxing Yang’s research interests lie at the intersection of video anomaly detection and human behavior analysis, with a particular focus on advanced techniques in machine learning and signal processing. His work includes multiple human tracking, image segmentation, human action recognition, and multi-feature abnormal event detection in video. Dr. Yang is passionate about developing novel frameworks that enhance the accuracy and efficiency of video surveillance systems, especially in detecting abnormal events in complex environments. His research contributes to advancements in security systems, where multi-modal data fusion and real-time anomaly detection are critical for improving public safety and monitoring.

Skills:

Dr. Yuxing Yang possesses a diverse skill set, with expertise in programming languages and tools critical to his research in video anomaly detection and signal processing. He is proficient in Python, particularly in machine learning frameworks such as Keras, TensorFlow, and PyTorch. Additionally, Dr. Yang is skilled in MATLAB, which he uses extensively for algorithm development and data analysis. His experience with Latex allows him to efficiently prepare academic papers, while his knowledge of Linux Basics ensures a strong foundation in system operations and scripting. These technical skills enable him to develop and implement advanced algorithms for human-related abnormal event detection and security surveillance.

Conclusion:

Dr. Yuxing Yang’s solid academic background, innovative research in abnormal event detection, and extensive teaching experience, coupled with his leadership and contributions to community awareness, make him a suitable and competitive candidate for the Best Researcher Award. His dedication to advancing knowledge in video surveillance and anomaly detection is evident through his numerous publications, research contributions, and awards.

Publication Top Noted:

Abnormal event detection for video surveillance using an enhanced two-stream fusion method

  • Authors: Y. Yang, Z. Fu, S. M. Naqvi
  • Journal: Neurocomputing
  • Year: 2023
  • Volume: 553, Article 126561
  • Cited by: 15
  • DOI: 10.1016/j.neucom.2023.126561

Enhanced adversarial learning-based video anomaly detection with object confidence and position

  • Authors: Y. Yang, Z. Fu, S. M. Naqvi
  • Conference: 2019 13th International Conference on Signal Processing and Communication
  • Year: 2019
  • Cited by: 14
  • DOI: 10.1109/icspcc46631.2019.8962857

A two-stream information fusion approach to abnormal event detection in video

  • Authors: Y. Yang, Z. Fu, S. M. Naqvi
  • Conference: ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing
  • Year: 2022
  • Cited by: 13
  • DOI: 10.1109/icassp43922.2022.9746515

Pose-driven human activity anomaly detection in a CCTV-like environment

  • Authors: Y. Yang, F. Angelini, S. M. Naqvi
  • Journal: IET Image Processing
  • Year: 2023
  • Volume: 17, Issue 3, Pages 674-686
  • Cited by: 10
  • DOI: 10.1049/ipr2.12876

Video anomaly detection for surveillance based on effective frame area

  • Authors: Y. Yang, Y. Xian, Z. Fu, S. M. Naqvi
  • Conference: 2021 IEEE 24th International Conference on Information Fusion (FUSION)
  • Year: 2021
  • Cited by: 8
  • DOI: 10.23919/fusion49465.2021.9626892

Skeleton-based fall events classification with data fusion

  • Authors: L. Xie, Y. Yang, F. Zeyu, S. M. Naqvi
  • Conference: 2021 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)
  • Year: 2021
  • Cited by: 5
  • DOI: 10.1109/MFI52462.2021.9604344

One-shot medical action recognition with a cross-attention mechanism and dynamic time warping

  • Authors: L. Xie, Y. Yang, Z. Fu, S. M. Naqvi
  • Conference: ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing
  • Year: 2023
  • Cited by: 4
  • DOI: 10.1109/icassp49357.2023.10095933

Action-based ADHD diagnosis in video

  • Authors: Y. Li, Y. Yang, S. M. Naqvi
  • Platform: arXiv preprint
  • Year: 2024
  • Cited by: 2
  • DOI: arXiv:2409.02261

Position and Orientation-Aware One-Shot Learning for Medical Action Recognition from Signal Data

  • Authors: L. Xie, Y. Yang, Z. Fu, S. M. Naqvi
  • Platform: arXiv preprint
  • Year: 2023
  • Cited by: 1
  • DOI: arXiv:2309.15635