Oussama Mounnan | Computer Science | Best Researcher Award

Mr. Oussama Mounnan | Computer Science | Best Researcher Award

Mr. Oussama Mounnan, Paris 8 University, France

Based on the detailed information provided about Mr. Oussama Mounnan, he appears to be a strong candidate for the “Best Researcher Award” due to his extensive experience and achievements in the field of cybersecurity, deep learning, and biometric access control. Below is a summary of his qualifications and contributions:

Publication profile

Professional Experience

Mr. Mounnan has been working as a Security Engineer since October 2015 at Weberfly-group in Marrakech, Morocco. He is responsible for managing, administering, and configuring network security systems, including firewalls, routers, switches, and VPN access. His role also includes performing network traffic analysis, implementing security policies, conducting security audits, and managing incidents. Additionally, he has experience in ethical hacking and penetration testing using various tools. Previously, he co-founded OussamaWeb, where he focused on IT maintenance, web development, and application creation from 2007 to 2015.

Research and Academic Background

Mr. Mounnan is currently pursuing a PhD in Computer Science at Ibn Zohr University-Agadir, Morocco, in collaboration with Paris 8 University, France. His research focuses on speech recognition using deep learning for biometric access control, a field that intersects artificial intelligence and cybersecurity. He has previously conducted research at the Oscar laboratory of Cadi Ayyad University, where he designed and tested systems for access control within the context of Big Data.

Technical Skills and Certifications

He has a comprehensive skill set covering programming languages (HTML, C, Python, Java), network security, system administration, virtualization, and data management tools. His certifications include ITIL V4, Prince2 Foundation, and various cybersecurity and machine learning credentials from Google, Coursera, and Fortinet. These certifications underline his commitment to staying updated in the rapidly evolving fields of IT security and data science.

Education

Mr. Mounnan holds a Master’s degree in Services, System Security, and Networks from the University of Lorraine, France, and a Bachelor’s degree in Networks and Telecommunications from Université Littoral Côte d’Opale, France. He has also completed specialized training in software engineering and information systems.

Additional Skills and Interests

He is proficient in English, French, and German at an advanced level. His interests include swimming, martial arts, reading, music, and scientific research, reflecting a well-rounded personality committed to both personal and professional development.

Publication Top Notes

  • Privacy-aware and authentication based on blockchain with fault tolerance for IoT enabled fog computing 🌐🔐 | Cited by: 21 | Year: 2020
  • Decentralized access control infrastructure using blockchain for big data 📊🔗 | Cited by: 10 | Year: 2019
  • Using blockchain based authentication solution for the remote surgery in tactile internet 🏥🖥️ | Cited by: 5 | Year: 2021
  • Anomaly detection for big data security: a benchmark 🔍🔒 | Cited by: 3 | Year: 2021
  • Efficient Distributed Access Control using Blockchain for Big Data in Clouds ☁️📈 | Cited by: 3* | Year: 2019
  • A novel approach based on blockchain to enhance security with dynamic policy updating 🔄🔐 | Cited by: 1 | Year: 2020
  • A Review on Deep Anomaly Detection in Blockchain 📚🛡️  Year: 2024
  • Deep Speech Recognition System Based on AutoEncoder-GAN for Biometric Access Control 🎤🧠  Year: 2023
  • Deep Learning-Based Speech Recognition System using Blockchain for Biometric Access Control 🧠🔗 Year: 2022
  • Towards a Privacy preserving Machine Learning based Access Control for the Internet of Things 🌐🤖  Year: 2022


Conclusion

Mr. Oussama Mounnan’s blend of practical experience, academic research, and extensive certifications make him a suitable candidate for the “Best Researcher Award.” His work in cybersecurity and deep learning, particularly in speech recognition for biometric access, highlights his significant contributions to these fields.

Mr. Shofiqul Islam | Computer Science | Best Researcher Award

Mr. Shofiqul Islam | Computer Science | Best Researcher Award

Mr Shafiqul Islam ,    Deakin University , Australia

Md. Shofiqul Islam, born in May 1989, is a resident of Highton, Geelong, Australia. Originally hailing from Chutipur, Notipota, Dhamuruda-7220, Chuadanga, Bangladesh, he has established himself in Australia while maintaining ties to his permanent address in Bangladesh. Shofiqul Islam is the son of Md. Abdul Khaleque. He stands 5 feet 7.5 inches tall and weighs 78 kilograms. As a male citizen of Bangladesh, he holds a National ID with the number 1813183458130.

Publication profile
Educational Background

Md. Shofiqul Islam is currently pursuing a Ph.D. in AI-Based Haptic Robotic Control in Medical Tele-Surgery at Deakin University, Australia, a program he began in May 2024. Prior to this, he completed a Master of Science (M.Sc) by Research at the Faculty of Computing, Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA), Pahang, Malaysia, in November 2022, achieving an impressive 80% mark. He earned his Bachelor of Science (B.Sc) in Computer Science and Engineering from Islamic University, Kushtia, Bangladesh, in 2014, where he graduated with a CGPA of 3.69 out of 4.00, securing 2nd position among 45 students. His academic journey began at Notipota High School in Dhamurhuda, Chuadanga, Bangladesh, where he obtained his Secondary School Certificate (SSC) in Science in 2005 with a GPA of 4.06 out of 5.00. He then completed his Higher Secondary Certificate (HSC) in Science at Chuadanga Govt. College in 2007, with a GPA of 4.70 out of 5.00.

Research and Work Experience

Md. Shofiqul Islam is currently pursuing a Ph.D. in AI-Based Haptic Robotic Control in Medical Tele-Surgery at Deakin University, Australia, a journey he began in May 2024. Before embarking on his Ph.D., he served as an Assistant Professor in the Department of Computer Science and Engineering at the Military Institute of Science and Technology (MIST) in Dhaka, Bangladesh, from March 2023 to April 15, 2024. Prior to this role, he was a Senior Lecturer at the World University of Bangladesh (WUB) for a brief period from January 2023 to April 2023. His academic career also includes a significant tenure as a Graduate Research Assistant at the Faculty of Computing, Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA), where he contributed to research from October 2018 to June 2022. Earlier, he held positions as a Lecturer in Computer Science and Engineering at Atish Dipankar University of Science and Technology from October 2016 to September 2018, and at First Capital University of Bangladesh (FCUB) from February 2015 to June 2016. His extensive experience in academia reflects his deep commitment to advancing knowledge in computer science and engineering.

 

Awards and Recognitions

Md. Shofiqul Islam has been awarded a prestigious fully funded Ph.D. scholarship from the Australian Government, supporting his research at Deakin University from May 2022 to May 2027. This scholarship enables him to pursue advanced studies in AI-Based Haptic Robotic Control in Medical Tele-Surgery. Prior to this, he received a Graduate Research Assistantship (GRA) at Universiti Malaysia Pahang, Malaysia, where he contributed to significant research projects from March 2018 to November 2022. His academic excellence was also recognized during his undergraduate studies, where he received a Merit Scholarship each year from 2009 to 2014 while pursuing a B.Sc. in Computer Science and Engineering at Islamic University, Bangladesh. These achievements reflect his consistent dedication and outstanding performance throughout his academic career.

Publication Top Notes

  • HARDC: A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention-based dual structured RNN with dilated CNN
    Authors: MS Islam, KF Hasan, S Uddin, JMW Quinn, MA Moni
    Journal: Neural Networks, Volume 162, Pages 271-287, 2023
    Citations: 30
  • A review on video classification with methods, findings, performance, challenges, limitations and future work
    Authors: MS Islam, U Kumar Roy, J Al Mahmud
    Journal: Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI), Volume 6, Pages 47-57, 2020
    Citations: 30
  • New hybrid deep learning approach using BiGRU-BiLSTM and multilayered dilated CNN to detect arrhythmia
    Authors: MS Islam, MN Islam, N Hashim, M Rashid, BS Bari, F Al Farid
    Journal: IEEE Access, Volume 10, Pages 58081-58096, 2022
    Citations: 26
  • A review on recent advances in Deep learning for Sentiment Analysis: Performances, Challenges and Limitations
    Authors: MS Islam, N Ab Ghani, MM Ahmed
    Journal: Journal of COMPUSOFT, 2020
    Citations: 16
  • A Novel BiGRUBiLSTM Model for Multilevel Sentiment Analysis Using Deep Neural Network with BiGRU-BiLSTM
    Authors: MS Islam, NA Ghani
    Book Series: Lecture Notes in Electrical Engineering (LNEE), Springer, 2021
    Citations: 15
  • HARC-New Hybrid Method with Hierarchical Attention Based Bidirectional Recurrent Neural Network with Dilated Convolutional Neural Network to Recognize Multilabel Emotions from Text
    Author: MS Islam
    Journal: Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI), Volume 7, April 2021
    Citations: 14
  • Machine Learning-Based Music Genre Classification with Pre-Processed Feature Analysis
    Authors: MS Islam, MM Hasan, MA Rahim, AM Hasan, M Mynuddin, I Khandokar, …
    Journal: Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI), Volume 7, Issue 3, Pages 491-502, 2021
    Citations: 10
  • Applications of Artificial Neural Networks in Engine Cooling System
    Authors: MM Hasan, MS Islam, SA Bakar, MM Rahman, MN Kabir
    Conference: 2021 International Conference on Software Engineering & Computer Systems (ICSECS), IEEE
    Citations: 7
  • Challenges and future in deep learning for sentiment analysis: a comprehensive review and a proposed novel hybrid approach
    Authors: MS Islam, MN Kabir, NA Ghani, KZ Zamli, NSA Zulkifli, MM Rahman, …
    Journal: Artificial Intelligence Review, Volume 57, Issue 3, Pages 62, 2024
    Citations: 6
  • Machine Learning Methods to Predict and Analyse Unconfined Compressive Strength of Stabilised Soft Soil with Polypropylene Columns
    Authors: HRS Ikramul Hoque, Muzamir Hasan, Shofiqul Islam, Moustafa Houda, Mirvat Houda
    Journal: Cogent Engineering, Volume 10, Issue 1, 2023
    Citations: 6
  • New Hybrid Deep Learning Method to Recognize Human Action from Video
    Authors: MS Islam, MJ Islam
    Journal: Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI), Volume 7, Pages 306-313, 2021
    Citations: 4