JAYABRABU RAMAKRISHNAN | Clustering | Best Researcher Award

Dr. JAYABRABU RAMAKRISHNAN | Clustering | Best Researcher Award

Associate Professor at Clustering,  JAZAN UNIVERSITY , Saudi Arabia

Dr. Jayabrabu Ramakrishnan is an accomplished academic professional with a strong background in information technology, cybersecurity, and related fields. Currently serving as an Associate Professor at Jazan University, Saudi Arabia, since 2014, he holds a Ph.D. in Computer Science from Bharathiar University, India. Dr. Ramakrishnan has received recognition for his research, including the Scientific Research Cash Award from Jazan University. He is also actively involved in industry collaborations, aiming to bridge the gap between academia and industry. Dr. Ramakrishnan’s expertise and dedication to his field make him a valuable asset to the academic community.

Professional Profiles:

Academic and Professional Positions:

Dr. Jayabrabu Ramakrishnan has a rich academic and professional background, currently serving as an Associate Professor in the Department of Information Technology and Security at the College of Computer Science and Information Technology, Jazan University, Saudi Arabia, since January 2024. Prior to this, he held the position of Assistant Professor in the same department from September 2014 to December 2023. Dr. Ramakrishnan’s academic journey began as an Assistant Professor at Karunya University, Coimbatore, India, from June 2008 to July 2008, followed by his role as an Associate Professor in the Department of Computer Applications at Dr. NGP Institute of Technology, Coimbatore, India, from August 2008 to October 2014. Before joining academia, he served as a Lecturer in the Department of Computer Applications at Rajiv Gandhi College of Engineering and Technology, Pondicherry, India, from September 2004 to June 2008.

Education:

Dr. Jayabrabu Ramakrishnan has pursued a diverse educational journey, culminating in a Ph.D. in Computer Science from Bharathiar University, Coimbatore, India, which he completed in 2013. Prior to this, he obtained an M.Phil. in Computer Science from Annamalai University, India, in 2007. Dr. Ramakrishnan’s academic pursuits began with a Master of Computer Applications (MCA) from Pondicherry University, India, in 2004, following his Bachelor of Science degree from Madras University, India, in 2000. Recently, in 2023, he further enhanced his expertise by completing a Postgraduate Program in Artificial Intelligence and Machine Learning (PGP-AIML) from The University of Texas, Austin.

Teaching:

Dr. Jayabrabu Ramakrishnan has a strong background in teaching, with extensive experience in delivering high-quality education in the field of information technology and security. He has taught a variety of courses at both undergraduate and graduate levels, including subjects such as data mining, artificial intelligence, machine learning, and cybersecurity. Dr. Ramakrishnan is known for his innovative teaching methods and his ability to engage students in the learning process. He is committed to providing students with a solid foundation in theoretical concepts while also imparting practical skills that are relevant to the industry. Dr. Ramakrishnan’s passion for teaching and his dedication to student success make him a highly respected educator in his field.

Awards and Achievements:

Dr. Jayabrabu Ramakrishnan has been recognized for his exceptional contributions in research, receiving the Scientific Research Cash Award from Jazan University for the years 2019, 2020, and 2021. He established the International Certification Academy within the College of Computer Science and Technology at Jazan University and was honored with the Best Techno Faculty Award in 2014. Dr. Ramakrishnan has signed memorandums of understanding with numerous industries to strengthen industry-institute relationships. He has coordinated conferences and served as a chairperson at various national and international events. Additionally, Dr. Ramakrishnan is a Certified Cisco Networking Associate (CCNA) Instructor Trainer and serves as a reviewer for several international journals and conferences.

Research Experience:

Dr. Jayabrabu Ramakrishnan has a wealth of research experience in the field of information technology and security. His research interests span a wide range of topics, including data mining, artificial intelligence, machine learning, and cybersecurity. Dr. Ramakrishnan has published extensively in peer-reviewed journals and conferences, contributing to the advancement of knowledge in his field. He has also been actively involved in supervising research projects and mentoring students, fostering a culture of research excellence. His research experience reflects his commitment to academic and scholarly pursuits, making him a valuable asset to the research community.

Publications:

  1. A comprehensive and systematic review of the network virtualization techniques in the IoT
    J Ramakrishnan, MS Shabbir, NM Kassim, PT Nguyen, D Mavaluru
    International Journal of Communication Systems 33 (7), e4331
    Year: 2020
    Citations: 61
  2. A new efficient design for random access memory based on quantum dot cellular automata nanotechnology
    A Mubarakali, J Ramakrishnan, D Mavaluru, A Elsir, O Elsier, K Wakil
    Nano Communication Networks 21, 100252
    Year: 2019
    Citations: 45
  3. Fog-based delay-sensitive data transmission algorithm for data forwarding and storage in cloud environment for multimedia applications
    A Mubarakali, AD Durai, M Alshehri, O AlFarraj, J Ramakrishnan, …
    Big Data 11 (2), 128-136
    Year: 2023
    Citations: 23
  4. Brain–computer interface for amyotrophic lateral sclerosis patients using deep learning network
    J Ramakrishnan, D Mavaluru, RS Sakthivel, AS Alqahtani, A Mubarakali, …
    Neural Computing and Applications, 1-15
    Year: 2020
    Citations: 21
  5. An enhanced network intrusion detection system for malicious crawler detection and security event correlations in ubiquitous banking infrastructure
    S Eswaran, V Rani, D Daniel, J Ramakrishnan, S Selvakumar
    International Journal of Pervasive Computing and Communications 18 (1), 59-78
    Year: 2021
    Citations: 10
  6. A framework for fraud detection system in automated data mining using intelligent agent for better decision making process
    R Jayabrabu, V Saravanan, JJ Tamilselvi
    2014 International Conference on Green Computing Communication and …
    Year: 2014
    Citations: 9
  7. Investigation of hybrid spectrum slicing-wavelength division multiplexing (SS-WDM) in transparent medium for mode division multiplexing applications
    AS Alqahtani, UA Kumar, J Ramakrishnan, P Parthasarathy, A Mubarakali, …
    Optical and Quantum Electronics 55 (3), 243
    Year: 2023
    Citations: 8
  8. A framework: Cluster detection and multidimensional visualization of automated data mining using intelligent agents
    R Jayabrabu, V Saravanan, K Vivekanandan
    arXiv preprint arXiv:1202.1945
    Year: 2012
    Citations: 8

 

Mr. Muhamamd Arslan Rauf | Software Engineering | Best Researcher Award

Mr. Muhamamd Arslan Rauf | Software Engineering | Best Researcher Award

PhD Scholar at Software Engineering, University of Electronic Science and Technology of China

Mr. Muhammad Arslan Rauf is a Ph.D. scholar in the final year with a focus on Recommendation Systems, Zero-Shot Learning, and Deep Learning. He has a robust foundation in cutting-edge research methodologies and a passion for technological innovation. His 18 years of comprehensive education, culminating in a Master’s degree, have equipped him with deep analytical skills and a keen eye for detail. With experience in both research and teaching, he is adept at distilling complex concepts into understandable insights. He is eager to contribute his expertise to a dynamic team, driving forward advancements in computer science and fostering an environment of continuous learning and innovation.

Professional Profiles:

👨‍🎓 EDUCATION AND TRAINING:

🎓 Doctorate in Software Engineering (PhD)
University of Electronic Science and Technology of China
[10/09/2020 – Current]
Thesis: Zero-shot learning for Cold-strat Recommendation

🎓 Master of Science in Computer Science
National Textile University, Faisalabad, Pakistan
[28/10/2017 – 28/10/2019]
Thesis: Extraction of Strong and Weak regions of Cricket Batsmen through Text-commentary Analysis
Major: Machine Learning, NLP, Computer Vision

🎓 Bachelor of Science in Computer Science
Government College University, Faisalabad, Pakistan
[10/09/2013 – 14/09/2017]
Core Subjects: Algorithm, Database, OOP, Data Structure, Operating System, Automata

💼 WORK EXPERIENCE

💻 Lecturer (Computer Science)
Riphah International University, Faisalabad, Pakistan
[24/09/2019 – 31/03/2021]

🗣️ LANGUAGE SKILLS

🗣️ Urdu (Mother tongue)
Levels: A1 and A2: Basic user; B1 and B2: Independent user; C1 and C2: Proficient user

🌐 DIGITAL SKILLS

🖥️ Programming language: Python / C, C++, C#
📊 Microsoft Office (Microsoft)
🐍 Python libraries: NumPy, Pandas, Keras, Sci-Kit Learn, TensorFlow, Matplolib, Seaborn
🗄️ Database: Oracle, MYSQL, SQL+, Access
📝 Microsoft SQL and Oracle SQL
📚 End Note
📑 Overleaf & LaTeX
🔧 VSCode, Visual Studio

Publications:

  1. Fabric weave pattern recognition and classification by machine learning
    • Authors: MA Rauf, M Jehanzeb, U Ullah, U Ali, M Kashif, M Abdullah
    • Conference: 2022 2nd international conference of smart systems and emerging technologies
    • Citations: 2
    • Year: 2022
  2. Content-Based Venue Recommender Approach for Publication
    • Authors: M Umair, S Jabbar, MA Rauf, M Rafiq, T Mahmood
    • Conference: International Conference on Engineering Software for Modern Challenges
    • Citations: 2
    • Year: 2021
  3. An Efficient Ensemble approach for Fake Reviews Detection
    • Authors: A Iqbal, MA Rauf, M Zubair, T Younis
    • Conference: 2023 3rd International Conference on Artificial Intelligence (ICAI)
    • Citations: 1
    • Year: 2023
  4. Extraction of Strong and Weak Regions of Cricket Batsman through Text-Commentary Analysis
    • Authors: MA Rauf, H Ahmad, CMN Faisal, S Ahmad, MA Habib
    • Conference: 2020 IEEE 23rd International Multitopic Conference (INMIC)
    • Citations: 1
    • Year: 2020
  5. BCE4ZSR: Bi-encoder empowered by teacher cross-encoder for zero-shot cold-start news recommendation
    • Authors: MA Rauf, MMY Khalil, W Wang, Q Wang, MANU Ghani, J Hassan
    • Journal: Information Processing & Management
    • Citations: Not provided
    • Year: 2024
  6. Occupational radiation dose to workers in a cancer hospital.
    • Authors: MU Ghani, KU Khan, T Khan, A Bahadur, M Rauf
    • Journal: Pakistan Journal of Nuclear Medicine
    • Citations: Not provided
    • Year: 2022
  7. An Effective Technique for Detecting Defecting Parts of Fabric in Digital Image
    • Authors: MA Rauf, M Abubakar, U Ullah, NU Haq
    • Conference: 2021 International Conference on Innovative Computing (ICIC)
    • Citations: Not provided
    • Year: 2021

 

 

 

Prof Dr. Tony Quek | Networking | Best Researcher Award

Prof Dr. Tony Quek | Networking | Best Researcher Award

Professor at Networking , Singapore University of Technology and Design, Singapore

👨‍🎓He remarkable academic journey, extensive research contributions, and dedication to the field of psychology are truly commendable. Your wealth of knowledge and diverse skill set reflect a deep commitment to understanding and addressing critical issues such as bullying, inclusion, and socialization.

🔬 He successful completion of a PhD in Psychology, along with the numerous advanced courses and workshops, showcases your continuous pursuit of excellence and expertise in your field.

🏆 The awards and recognitions, including the First Place in the Poster Award at the University of Stavanger, underscore the impact of your research and the high regard it holds in the academic community.

Professional Profiles:

Education:

Prof. Dr. Tony Quek pursued his academic journey with a Bachelor of Engineering in Electrical & Electronics Engineering from Tokyo Institute of Technology, Tokyo, Japan, graduating in 1998. He furthered his studies at the same institution, completing a Master of Engineering in Information Processing from April 1998 to March 2000, focusing on Multiuser Detection for DS-CDMA Mobile Communication Systems under the guidance of Professor Hiroshi Suzuki. Dr. Quek’s academic pursuits led him to Massachusetts Institute of Technology (MIT), Cambridge, MA, where he obtained his Ph.D. in Electrical Engineering and Computer Science from September 2002 to February 2008. His doctoral research centered on Efficient Approaches to Robust and Cooperative Wireless Network Design, mentored by Professor Moe Z. Win.

Research Interest:

Dr. Tony Quek’s general research interests revolve around applying mathematical, optimization, learning, and statistical theories to various communication, networking, signal processing, and resource allocation problems. His current research topics include wireless communications and networking, network intelligence, non-terrestrial networks, open radio access networks, and 6G technology. He explores innovative approaches to enhance the efficiency, reliability, and intelligence of communication systems, with a focus on advancing the capabilities of future wireless networks.

Awards & Honors:

Dr. Tony Quek has received numerous honors and awards for his outstanding contributions to the field of electrical engineering and computer science. In 2023 and 2022, he was recognized as one of the World’s Top 2% Scientists. In 2022, he was elected as a Fellow of the Academy of Engineering Singapore and received the IEEE Signal Processing Society Best Paper Award. The year 2021 brought further accolades, including the OpenGov Recognition of Excellence and another recognition as one of the World’s Top 2% Scientists. In 2020, Dr. Quek was awarded the Nokia Visiting Professorship, recognized as a Clarivate Analytics Highly Cited Researcher, and received the IEEE Stephen O. Rice Prize in the Field of Communications Theory, among other honors. His contributions have been consistently recognized, including being elected as an IEEE Fellow in 2018 for his contributions to heterogeneous and wireless networks. Dr. Quek has also served as a Distinguished Lecturer for the IEEE Communications Society.

Experience:

Dr. Tony Quek has held several significant roles in academia and research. Since December 2022, he has served as the STEngineering Distinguished Professor at Singapore Technologies Engineering. Prior to this, Dr. Quek was appointed as the Director of the Future Communications R&D Programme at the Singapore University of Technology and Design (SUTD) in May 2021. He also served as the Interim Programme Director for the Design and Artificial Intelligence Programme at SUTD from April 2020 to December 2020. In March 2020, Dr. Quek was appointed as a Full Professor in the Information Systems Technology and Design Pillar at SUTD, where he currently holds the position of Head of Pillar. His work in these roles has contributed significantly to the advancement of research and education in the field of electrical engineering and computer science.

Teaching Experience:

Dr. Tony Quek has an extensive teaching experience at the Singapore University of Technology and Design (SUTD) in the ISTD and ESD Pillars. Since January 2013, he has taught several courses including “Modelling the Systems World” (Term 3, 2013, 2014, 2015), “The Digital World” (Term 3, 2014, 2016), and “Introduction to Probability and Statistics” (Term 5, 2018, 2019). His teaching contributions have been instrumental in shaping the learning experiences of students in the areas of modelling, digital systems, and probability and statistics, helping them develop a strong foundation in these subjects.

Publications:

  1. Enhanced intercell interference coordination challenges in heterogeneous networks
    • Authors: D Lopez-Perez, I Guvenc, G De la Roche, M Kountouris, TQS Quek, …
    • Citations: 1306
    • Year: 2011
  2. Federated learning with differential privacy: Algorithms and performance analysis
    • Authors: K Wei, J Li, M Ding, C Ma, HH Yang, F Farokhi, S Jin, TQS Quek, HV Poor
    • Citations: 1244
    • Year: 2020
  3. Offloading in mobile edge computing: Task allocation and computational frequency scaling
    • Authors: TQ Dinh, J Tang, QD La, TQS Quek
    • Citations: 881
    • Year: 2017
  4. Energy efficient heterogeneous cellular networks
    • Authors: YS Soh, TQS Quek, M Kountouris, H Shin
    • Citations: 676
    • Year: 2013
  5. Sensor OpenFlow: Enabling software-defined wireless sensor networks
    • Authors: T Luo, HP Tan, TQS Quek
    • Citations: 614
    • Year: 2012
  6. Scheduling policies for federated learning in wireless networks
    • Authors: HH Yang, Z Liu, TQS Quek, HV Poor
    • Citations: 522
    • Year: 2019