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

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.

 

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

  • Conference2019 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

  • Conference2021 International Conference on Innovation and Intelligence for Informatics
  • Cited By: 4
  • Year: 2021

Precision Fish Farming to Mitigate Pond Water Quality Through IoT

  • Conference2024 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

  • JournalJournal 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

  • JournalEngineering 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.

Ali Raza | Network Attacks | Best Researcher Award

Mr. Ali Raza | Network Attacks | Best Researcher Award

Lecturer at The University Of Lahore, Pakistan

Mr. Ali Raza is an accomplished computer science professional and researcher with a strong academic foundation and expertise in machine learning, cybersecurity, and software development. He completed his MS in Computer Science with a high CGPA of 3.93 from Khwaja Fareed University of Engineering and Information Technology (KFUEIT), where he also earned his bachelor’s degree. Mr. Raza has experience as a Lecturer at the University of Lahore, teaching software engineering courses, and as a Visiting Lecturer at KFUEIT, covering subjects like machine learning and data structures. His industry experience as a Full Stack Python Developer at BuiltinSoft involved developing web applications using Python Django and machine learning frameworks. Mr. Raza has published several impactful research articles in high-ranking journals, focusing on network attack detection, health risk prediction, and cyber-attack prevention. His work combines deep technical skills and a commitment to advancing applied research in computer science.

Education:

Mr. Ali Raza holds an impressive academic background, having completed his Master of Science (MS) in Computer Science at Khwaja Fareed University of Engineering and Information Technology (KFUEIT) with a remarkable CGPA of 3.93 in 2023. During his studies, KFUEIT achieved a ranking of #258 in the Asian University Rankings for Southern Asia, underscoring the institution’s reputation for academic excellence. Prior to this, he earned his Bachelor of Science (BS) in Computer Science from the same university, graduating with a CGPA of 3.47 in 2021. This solid educational foundation has equipped Mr. Raza with the necessary knowledge and skills to excel in the fields of computer science and machine learning, fostering his commitment to furthering research and innovation in technology.

Professional Experience:

Mr. Ali Raza has built a solid professional background in academia and industry, contributing to both teaching and software development. Currently, he serves as a Lecturer in the Department of Software Engineering at the University of Lahore, ranked #40 in the Asian University Rankings for Southern Asia, where he specializes in Object-Oriented Programming. Prior to this role, he was a Visiting Lecturer at Khwaja Fareed University of Engineering and Information Technology (KFUEIT) from 2021 to 2023, where he taught a wide range of courses, including Introduction to ICT, Programming Fundamentals, Database Systems, Machine Learning, Data Structures, and Algorithms. Complementing his academic roles, Mr. Raza gained valuable industry experience as a Full Stack Python Developer at BuiltinSoft from 2020 to 2022. In this role, he developed business web applications using Python Django and integrated machine learning frameworks, further enhancing his practical expertise in application development. This blend of academic and industry experience has equipped Mr. Raza with both a deep theoretical foundation and hands-on technical skills.

Research Interests:

Mr. Ali Raza’s research interests center on advancing methodologies in machine learning, cybersecurity, computer vision, and signal processing. He is particularly focused on leveraging machine learning algorithms to enhance network security, developing predictive models to detect cyber threats, and optimizing feature engineering for data-driven health risk analysis. Additionally, his work in computer vision, particularly using deep learning techniques, explores novel approaches for identifying genetic disorders from facial images, providing valuable tools in the field of medical diagnostics. His research contributions demonstrate a commitment to developing innovative, practical solutions that address complex challenges in technology and healthcare.

Conclusion:

Ali Raza’s strong academic background, extensive teaching and industry experience, and impactful research contributions make him a highly suitable candidate for the Best Researcher Award. His interdisciplinary approach, particularly in applying machine learning to pressing challenges in cybersecurity and healthcare, demonstrates a commitment to both innovation and societal impact. His work aligns well with the goals of the award, making him a deserving candidate for recognition.

Publication Top Noted:

A novel deep learning approach for deepfake image detection

  • Authors: A. Raza, K. Munir, M. Almutairi
  • Journal: Applied Sciences
  • Volume: 12
  • Issue: 19
  • Article: 9820
  • Year: 2022
  • Citations: 80

Predicting employee attrition using machine learning approaches

  • Authors: A. Raza, K. Munir, M. Almutairi, F. Younas, MMS Fareed
  • Journal: Applied Sciences
  • Volume: 12
  • Issue: 13
  • Article: 6424
  • Year: 2022
  • Citations: 77

Ensemble learning-based feature engineering to analyze maternal health during pregnancy and health risk prediction

  • Authors: A. Raza, H.U.R. Siddiqui, K. Munir, M. Almutairi, F. Rustam, I. Ashraf
  • Journal: Plos One
  • Volume: 17
  • Issue: 11
  • Article: e0276525
  • Year: 2022
  • Citations: 63

A novel approach for polycystic ovary syndrome prediction using machine learning in bioinformatics

  • Authors: S. Nasim, M.S. Almutairi, K. Munir, A. Raza, F. Younas
  • Journal: IEEE Access
  • Volume: 10
  • Pages: 97610-97624
  • Year: 2022
  • Citations: 39

A performance overview of machine learning-based defense strategies for advanced persistent threats in industrial control systems

  • Authors: M. Imran, H.U.R. Siddiqui, A. Raza, M.A. Raza, F. Rustam, I. Ashraf
  • Journal: Computers & Security
  • Volume: 134
  • Article: 103445
  • Year: 2023
  • Citations: 29

Novel class probability features for optimizing network attack detection with machine learning

  • Authors: A. Raza, K. Munir, M.S. Almutairi, R. Sehar
  • Journal: IEEE Access
  • Year: 2023
  • Citations: 28

Effective feature engineering technique for heart disease prediction with machine learning

  • Authors: A.M. Qadri, A. Raza, K. Munir, M.S. Almutairi
  • Journal: IEEE Access
  • Volume: 11
  • Pages: 56214-56224
  • Year: 2023
  • Citations: 27

A novel methodology for human kinematics motion detection based on smartphones sensor data using artificial intelligence

  • Authors: A. Raza, M.R. Al Nasar, E.S. Hanandeh, R.A. Zitar, A.Y. Nasereddin, et al.
  • Journal: Technologies
  • Volume: 11
  • Issue: 2
  • Article: 55
  • Year: 2023
  • Citations: 24

LogRF: An approach to human pose estimation using skeleton landmarks for physiotherapy fitness exercise correction

  • Authors: A. Raza, A.M. Qadri, I. Akhtar, N.A. Samee, M. Alabdulhafith
  • Journal: IEEE Access
  • Year: 2023
  • Citations: 22

A novel ensemble method for enhancing Internet of Things device security against botnet attacks

  • Authors: A. Arshad, M. Jabeen, S. Ubaid, A. Raza, L. Abualigah, K. Aldiabat, H. Jia
  • Journal: Decision Analytics Journal
  • Volume: 8
  • Article: 100307
  • Year: 2023
  • Citations: 21