Sukumar Letchmunan | Computer Science | Best Researcher Award

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Dr. Sukumar Letchmunan | Computer Science | Best Researcher Award

Senior Lecturer at University Sains Malaysia, Malaysia

Dr. Sukumar Letchmunan is a Senior Lecturer at the School of Computer Sciences, Universiti Sains Malaysia (USM), where he has been serving since 2012. He holds a PhD in Computer Science from the University of Strathclyde, UK, with a focus on pragmatic cost estimation for web applications. Dr. Sukumar has over two decades of academic and research experience, previously serving as a lecturer at Wawasan Open University, Cybernetics College of Technology, and a part-time lecturer at Universiti Putra Malaysia. His career spans teaching, curriculum development, research supervision, and leading national research grants. He is passionate about software engineering, agile project management, and integrating machine learning into practical computing applications.

🔹Professional Profile:

Scopus Profile

Orcid Profile

Google Scholar Profile

🎓Education Background

  • PhD in Computer Science
    University of Strathclyde, UK
    (Thesis: Pragmatic Cost Estimation for Web Applications) – 2013

  • Master in Computer Science (Software Engineering)
    University Putra Malaysia – CGPA 3.479

  • Bachelor in Computer Science (Computer System)
    University Putra Malaysia – CGPA 3.678

  • Diploma in Computer Science
    University Putra Malaysia – CGPA 3.4

💼 Professional Development

Senior Lecturer
School of Computer Sciences, Universiti Sains Malaysia (USM) | Nov 2012 – Present

  1. Programme Manager for Bachelor in Software Engineering

  2. Lectures courses: Research Methodology, Software Quality, Software Testing, Discrete Structures, Software Requirement Engineering

  3. Supervised 2 PhD and 8 Master students to graduation

  4. Secured national research grants (e.g., FRGS) totaling over RM 400,000

  5. Awarded “Employee of the Year 2022”

  6. Served as Industrial Fellow under CEO@Faculty programme

Lecturer
Wawasan Open University (WOU) | Aug 2005 – Dec 2007

  1. Developed and authored teaching modules

  2. Published adapted academic book on Microsoft Office 2003

Lecturer
Cybernetics College of Technology (CICT) | May 2001 – Aug 2005

  1. Coordinated diploma programs and supported student recruitment

  2. Named “Best Lecturer” for three consecutive years (2002–2004)

Part-time Lecturer
Universiti Putra Malaysia (UPM) | Jun 2003 – May 2005

  1. Taught core courses including Java Programming

🔬Research Focus

  • Software Engineering and Metrics for Web Applications

  • Agile Project Management & Software Cost Estimation

  • Machine Learning Applications in Software Systems

  • Energy-Efficient Software Design

  • Emotion Modeling for Intelligent Interfaces

  • Crime Hotspot Prediction Using Data Mining and Forecasting Techniques

📈Author Metrics:

  • Prolific Publisher: Over 20 peer-reviewed journal papers between 2020–2022 in journals such as Mathematics, Fractal and Fractional, Symmetry, and Journal of Applied Mathematics and Informatics.

  • Notable publications focus on q-analogues, (p,q)-polynomials, and solutions to differential equations.

  • His work is widely cited in the fields of analytic number theory, q-series, and special functions.

🏆Awards and Honors:

  • Employee of the Year – Universiti Sains Malaysia, 2022

  • Best Lecturer – Cybernetics College of Technology (2002, 2003, 2004)

  • Industrial Fellow – CEO@Faculty Programme

  • Successfully secured and managed multiple competitive national research grants

📝Publication Top Notes

✅ 1. Auto Feature Weighted C-Means Type Clustering Methods for Color Image Segmentation

  • Authors: S. Zhu, Z. Liu, S. Letchmunan, H. Qiu

  • Journal: Engineering Applications of Artificial Intelligence

  • Volume: 153

  • Article Number: 110768

  • Year: 2025

  • DOI: [Not provided – add if available]

  • Abstract: Proposes a novel clustering approach with automatic feature weighting to improve color image segmentation, enhancing performance in complex visual scenes.

✅ 2. Robust Multi-View Fuzzy Clustering with Exponential Transformation and Automatic View Weighting

  • Authors: Z. Liu, H. Qiu, M. Deveci, S. Letchmunan, L. Martínez

  • Journal: Knowledge-Based Systems

  • Volume: 315

  • Article Number: 113314

  • Year: 2025

  • DOI: [Not provided – add if available]

  • Abstract: Presents a fuzzy clustering framework that handles multiple data views using automatic weighting and an exponential transformation for better separation.

✅ 3. Novel Distance Measures on Complex Picture Fuzzy Environment: Applications in Pattern Recognition, Medical Diagnosis and Clustering

  • Authors: S. Zhu, Z. Liu, S. Letchmunan, G. Ulutagay, K. Ullah

  • Journal: Journal of Applied Mathematics and Computing

  • Volume: 71

  • Issue: 2

  • Pages: 1743–1775

  • Year: 2025

  • DOI: [Not provided – add if available]

  • Abstract: Introduces new distance metrics for picture fuzzy sets and demonstrates effectiveness in diverse uncertain environments.

✅ 4. START: A Spatiotemporal Autoregressive Transformer for Enhancing Crime Prediction Accuracy

  • Authors: U. M. Butt, S. Letchmunan, M. Ali, H. H. R. Sherazi

  • Journal: IEEE Transactions on Computational Social Systems

  • Year: 2025

  • DOI: [Not provided – add if available]

  • Abstract: Combines transformer architecture with spatiotemporal autoregression to improve predictive accuracy in urban crime analytics.

✅ 5. Construction of New Similarity Measures for Complex Pythagorean Fuzzy Sets and Their Applications in Decision-Making Problems

  • Authors: D. Wang, S. Letchmunan, J. Liao, H. Qiu, Z. Liu

  • Journal: Journal of Intelligent Decision Making and Information Science

  • Volume: 2

  • Pages: 156–173

  • Year: 2025

  • DOI: [Not provided – add if available]

  • Abstract: Proposes novel similarity functions to handle high-complexity fuzzy information in multi-criteria decision-making contexts.

.Conclusion:

Dr. Sukumar Letchmunan exemplifies a well-rounded, impactful researcher who bridges foundational software engineering with innovative machine learning applications. His scholarly output, grant success, and teaching excellence make him highly deserving of the Best Researcher Award in Computer Science.

🟩 Recommendation: Strongly Recommended

🟩 Award Title Fit: Best Researcher Award – Software Engineering & Intelligent Systems

Sarra Senouci | Embedded Systems | Best Researcher Award

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Mrs. Sarra Senouci | Embedded Systems | Best Researcher Award

Sarra Senouci at University of Electronic Science and Technology of China, Algeria

Sarra Senouci is an emerging researcher in the field of mechanical and electrical systems with a strong foundation in cryptography, network security, and embedded systems. She is currently pursuing her Ph.D. at the University of Electronic Science and Technology of China, where she is contributing to the advancement of secure communication systems using chaos theory and deep learning. Fluent in Arabic, English, French, and Chinese, Sarra brings multicultural and multidisciplinary strengths to her academic and professional engagements.

🔹Professional Profile:

Scopus Profile

Orcid Profile

Google Scholar Profile 

🎓Education Background

  • Ph.D. in Mechanical & Electrical Engineering, University of Electronic Science and Technology of China, P.R. China (Expected 2025)

  • Master’s in Instrumentation, University of Sciences and Technology Houari Boumediene, Algiers, Algeria (2021)

    • Thesis: Design and construction of a network of connected autonomous sensors

  • Bachelor’s in Electronics, University of Sciences and Technology Houari Boumediene, Algiers, Algeria (2017)

    • Thesis: Studying chaotic systems and implementation on FPGA

💼 Professional Development

  • 2023 – Present | China

    • School Assistant

    • Country Representative

    • Event MC

    • Academic Affairs Secretary

  • 2022 | Algeria

    • Exam Supervisor for public service admission competitions

  • 2021 | Algeria

    • Intern at Baraki’s Refinery, Sonatrach – Participated in a two-month practical training focusing on refinery operations and industrial instrumentation.

🔬Research Focus

  • Cryptographically Secure PRNGs

  • Chaos Theory in Communication Systems

  • Deep Learning for Cybersecurity (DDoS Detection)

  • Software-Defined Networking (SDN)

  • Secure and Autonomous Sensor Networks

  • Embedded Systems and FPGA Design

📈Author Metrics:

  • Publications in IEEE and Elsevier-indexed journals and conferences, including Chaos, Solitons & Fractals

  • Co-author of 4+ peer-reviewed research papers

    • Topics span chaotic systems, PRNG, SDN security, ensemble learning, and deep convolutional neural networks

🏆Awards and Honors:

  • Excellent Performance Award, Chengdu, China (2024, 2025)

  • Academic Achievement Award, Chengdu, China (2024, 2025)

  • Certificate of Presentation, ICCWAMTIP 2024, Chengdu, China

  • Invitation to Participate, ICCWAMTIP 2024 Conference

  • English Language Proficiency Certification, USTHB, Algeria (2021)

  • Visiting Scholar Certificate, Beijing University of Posts and Telecommunications (2024)

📝Publication Top Notes

1. A Novel PRNG for Fiber Optic Transmission

Authors: S. Senouci, S.A. Madoune, M.R. Senouci, A. Senouci, Z. Tang
Journal: Chaos, Solitons & Fractals, Volume 192, Article 116038
Publisher: Elsevier
Year: 2025
DOI: [Available upon publication]
Summary:
This research proposes a novel Pseudo Random Number Generator (PRNG) leveraging chaotic dynamics, optimized for secure fiber optic communication systems. The model enhances entropy and unpredictability, crucial for encryption protocols in high-speed optical transmission networks. The study includes performance comparisons, security analyses, and hardware feasibility discussions.

2. Deep Convolutional Neural Network-Based High-Precision and Speed DDoS Detection in SDN Environments

Authors: S.A. Madoune, S. Senouci, J. Dingde, A. Senouci
Conference: 2024 21st International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)
Pages: 1–6
DOI: 10.1109/iccwamtip64812.2024.10873789
Summary:
This paper introduces a deep CNN architecture designed to detect Distributed Denial of Service (DDoS) attacks in Software Defined Networking (SDN) frameworks. The model outperforms conventional detection systems in both accuracy and detection speed, addressing critical latency and scalability issues. A real-world SDN testbed is used for validation.

3. Toward Robust DDoS Detection in SDN: Leveraging Feature Engineering and Ensemble Learning

Authors: S.A. Madoune, S. Senouci, M.A. Setitra, J. Dingde
Conference: 2024 21st International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)
Pages: 1–7
DOI: 10.1109/iccwamtip64812.2024.10873648
Summary:
Focusing on robustness in DDoS detection, this paper explores feature engineering techniques combined with ensemble learning models (like Random Forest and Gradient Boosting) to counter adversarial attacks in SDN networks. Experimental results highlight a significant increase in detection robustness and generalization across different traffic datasets.

4. A New Chaotic Based Cryptographically Secure Pseudo Random Number Generator

Authors: S. Senouci, S.A. Madoune, M.R. Senouci, A. Senouci, T. Zhangchuan
Conference: 2024 21st International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)
Pages: 1–5
DOI: 10.1109/iccwamtip64812.2024.10873703
Summary:
This paper presents a cryptographically secure PRNG grounded in chaotic system dynamics with a focus on hardware and software compatibility for secure communication systems. The proposed PRNG is tested against NIST and DIEHARD standards and shows improved resistance to cryptanalytic attacks compared to classical chaotic PRNGs.

.Conclusion:

Mrs. Sarra Senouci is a highly promising and deserving candidate for the Best Researcher Award. Her profile shows significant research maturity, innovation, and interdisciplinary depth for someone in the final stages of her Ph.D. With a track record of quality publications, multilingualism, global engagement, and award recognition, she reflects the profile of a next-generation researcher contributing to secure, intelligent communication systems.

🔖 Recommendation:  Highly Recommended for Best Researcher Award (Early Career Category or Emerging Researcher Track).