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

Google Scholar

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

Syed MuhammadMohsin | Computer Science Award | Best Researcher Award

Mr. Syed MuhammadMohsin, Syed Muhammad Mohsin, Pakistan

👨‍🎓 Syed Muhammad Mohsin, a dedicated PhD scholar at COMSATS University Islamabad, Pakistan, focuses on energy-efficient cloud technologies. With expertise in computer science and a solid academic background, including MS and BS degrees, he has published extensively in renowned journals and presented at international conferences. Mohsin’s research delves into topics like IoT network security, renewable energy forecasting, and smart grid management. Alongside his scholarly pursuits, he serves as an Assistant Technical Officer at the Pakistan Atomic Energy Commission and holds visiting lecturer positions at various universities. His multifaceted skills encompass coding, network administration, and project management.

Publication Top Notes

Education

Mr.Syed Muhammad Mohsin, a dedicated scholar

, embarked on his academic journey by earning a Bachelor’s degree in Computer Science from Virtual University of Pakistan. He furthered his knowledge with a Master’s degree from the same institution, delving into the intricacies of Service Oriented Architecture for Cloud of Things. Driven by his passion for research, he pursued a PhD from COMSATS University Islamabad, focusing on energy-efficient cloud migration. His academic odyssey, complemented by numerous publications and professional experiences, reflects his unwavering commitment to advancing knowledge in computer science and technology.

Research Focus

Mr.Syed Muhammad Mohsin is a highly accomplished PhD scholar specializing in the field of energy-efficient cloud computing. With a strong background in computer science and extensive experience in academia and industry, Mohsin’s research focus lies at the intersection of green computing and intelligent migration strategies for traditional energy sources. His work, highlighted by numerous publications and contributions to prestigious conferences, demonstrates a deep understanding of emerging technologies like IoT, AI, and blockchain, applied to energy forecasting, network optimization, and security. Mohsin’s expertise and dedication make him a valuable asset in shaping the future of sustainable computing.