Arivumalar Ravichandran | Computer science | Academic Excellence Award

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Dr. Arivumalar Ravichandran | Computer science | Academic Excellence Award

Dr. Arivumalar Ravichandran | Computer science | GreatLakes Institute of management | India

Dr. Arivumalar Ravichandran is an accomplished academician and researcher with an interdisciplinary background encompassing Information Technology, Computer Science, Engineering, and Human Resource Management. With over 17 years of teaching and research experience, she has held pivotal roles in prestigious institutions including Great Lakes Institute of Management, Sri Sairam Engineering College, and PRIST University. Her academic pursuit culminated in a Ph.D. in Techno-Management, expected to be conferred in 2025. Dr. Ravichandran’s work bridges computer science innovation with pragmatic management principles, enriching both technical and managerial education. Her research primarily targets IoT in agriculture, cloud-based smart campuses, cybersecurity, and logistics optimization. She is widely published in IEEE Xplore and international journals and known for translating theory into practice through her progressive teaching and research approach. Her dedication to both engineering and management education continues to inspire the next generation of data-driven, technology-enabled professionals.

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Education

Dr. Arivumalar Ravichandran’s educational journey reflects her diverse and rich academic expertise. She began with an M.Sc. in Information Technology from A.D.M. College for Women, followed by an M.Phil. in Computer Science from Periyar University, both with First Class distinction. To deepen her technical capabilities, she pursued an M.Tech in Computer Science and Engineering from PRIST University. Demonstrating her interdisciplinary vision, she obtained an M.B.A. in Human Resource Management from Bharathidasan University, blending technological acumen with managerial skills. Currently, she is a Ph.D. scholar in Techno-Management at Dr. N.G.P Institute of Technology, Coimbatore, with completion anticipated in 2025. This comprehensive academic background enables her to explore computer science from both an engineering and organizational perspective, making her uniquely suited for research that involves smart technology deployment in business and societal contexts.

Experience 

Dr. Arivumalar Ravichandran’s career spans over 17 years across leading academic institutions in India. She currently serves as Assistant Professor in Analytics & Operations at Great Lakes Institute of Management (since January 2024). She previously held dual roles in Sri Sairam Engineering College and SRM Valliammai Engineering College, teaching both CSBS and MBA programs. Her foundational experience includes five years as Assistant Professor in CSE at P.R. Engineering College and earlier academic roles at ARJ College, S.K. College of Arts & Science, and RDB College. Her career trajectory reflects an interdisciplinary footprint across Computer Science, MCA, and Management departments. She has a proven record of mentoring students, leading IT programs, and integrating research with curriculum delivery. As a department head and senior faculty, she has contributed to shaping institutional academic strategies while also engaging in publication-worthy research that aligns with industry and technology trends.

Awards and Honors

Dr. Arivumalar Ravichandran has consistently demonstrated excellence in research, academia, and leadership, earning her accolades in each institution she served. Though formal award titles are not explicitly listed, her career reflects significant recognitions in the form of trusted appointments in interdisciplinary teaching roles and departmental leadership. Her successful publication in prestigious Scopus-indexed and IEEE Xplore conferences and journals stands as a testament to her scholarly impact. Additionally, she has presented at international conferences and contributed to critical discourse in areas such as IoT in agriculture and risk management in logistics. These achievements mark her as a respected scholar and mentor in both technical and management circles. Her elevation to Assistant Professor roles across diverse departments and her long-standing service history are indicative of institutional recognition and peer trust. Her work continues to gain traction in the broader academic community.

Research Focus

Dr. Arivumalar Ravichandran’s research is rooted in addressing real-world challenges through advanced computing technologies. Her interdisciplinary focus spans IoT, cloud computing, cybersecurity, AI-driven smart campuses, and risk analysis in logistics. One of her prominent works involves developing a hybrid data acquisition model for precision agriculture using IoT, showcased at the ICOEI 2023 conference. She also investigates the role of cloud computing in building smart campuses, highlighting scalable solutions for educational transformation. Her earlier work focused on cyber threats, specifically mitigating malicious scripting via content security policies. Moreover, she explores techno-managerial topics such as global transportation risk management—blending IT expertise with operational strategy. This blend of computer science and business intelligence forms the core of her research philosophy: leveraging technology for sustainable, secure, and efficient solutions. Her ongoing Ph.D. enhances this integrative approach, promising further contributions at the intersection of computing, analytics, and enterprise systems.

Publication Titles 

  1. A Hybrid Data Acquisition Model for Precision Agriculture using IoT – IEEE Xplore, ICOEI 2023

  2. Analysis of Developing IoT and Cloud Computing Based Smart Campuses and its Applications – IEEE ACCAI 2024

  3. A Study on Risk Management of Global Transportation Service – Research Journal of Humanities and Social Sciences, 2023

  4. Mitigating Malicious Scripting Attacks with a Content Security Policy – IJARTET, July 2017

Conclusion

Dr. Arivumalar Ravichandran stands as a transformative figure in computer science education and research, integrating cutting-edge technical knowledge with human-centric solutions. With her strong academic background, robust publication record, and diverse teaching experience, she is a deserving candidate for the Computer Science Award. Her work continues to make a significant impact in academia and applied research, particularly in areas like IoT, smart systems, and security, reflecting both innovation and practical relevance.

NIKOLAOS EPISKOPOS | Computer Science | Best Researcher Award

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Mr. NIKOLAOS EPISKOPOS | Computer Science | Best Researcher Award

👤 Mr. NIKOLAOS EPISKOPOS, IBM, Greece

Nikolaos Episkopos is an accomplished Data Scientist, Software Developer, and Data Science Consultant with over eight years of professional experience. Based in Athens, Greece, Nikolaos specializes in AI, cybersecurity, and predictive medicine, contributing to impactful EU-funded R&D projects and Open Source Software initiatives. His innovative work includes AI solutions for fraud detection, federated learning toolkits for intrusion detection, and optimizing data pipelines. Passionate about the intersection of technological advancements and societal impact, Nikolaos has played pivotal roles in enhancing banking services, securing SCADA systems, and developing blockchain-based video streaming systems. As a professional with a robust academic background and diverse technical skills, he combines creativity and precision to deliver groundbreaking solutions.

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🌟 Evaluation of Nikolaos Episkopos for the Research for Best Researcher Award

Summary of Suitability

Nikolaos Episkopos demonstrates an exceptional profile as a data scientist and software developer with significant contributions to research and development projects, particularly in the domains of artificial intelligence (AI), cybersecurity, and healthcare. With over eight years of professional experience, he has effectively bridged academia and industry, showcasing the ability to lead and innovate in complex technological domains. His work has resulted in tangible outcomes, including funding acquisitions, novel AI solutions, and impactful publications.

Nikolaos’s recent achievements at IBM and INLECOM highlight his ability to tackle real-world challenges through data-driven innovation. At IBM, he developed advanced AI models for fraud detection, contributing to financial security solutions. His role at INLECOM involved technical project management and significant contributions to EU Horizon projects, where his efforts secured funding and established strategic partnerships. These accomplishments reflect his leadership, technical expertise, and collaborative skills in advancing scientific research.

🎓 Education 

Nikolaos holds a Master’s degree in Data Science & Information Technologies from the National and Kapodistrian University of Athens, where he honed expertise in AI, data analysis, and cybersecurity. Currently pursuing an MSc in Cybersecurity at the University of West Attica, he is expanding his knowledge of threat modeling and advanced cryptographic techniques. His academic journey reflects a commitment to excellence, as he consistently excelled in designing AI models and deploying secure, scalable systems. Nikolaos’ education equips him to navigate the rapidly evolving landscape of AI and cybersecurity, combining rigorous academic training with practical, hands-on experience to solve complex technical challenges effectively.

💼  Professional Experience

Nikolaos Episkopos has held roles at leading organizations like IBM, INLECOM, and MetaMind Innovations. At IBM, he spearheaded the development of AI solutions for card fraud detection and enhanced banking services. At INLECOM, he managed Horizon projects, securing significant funding and partnerships while optimizing algorithms for AI tools. During his tenure at MetaMind Innovations, he developed Federated Learning toolkits for intrusion detection, authored academic papers, and secured SCADA systems. At Fogus Innovations, Nikolaos implemented blockchain-enabled video streaming optimization and co-authored publications on advanced AI platforms. His ability to lead technical projects, develop AI models, and foster innovation underscores his exceptional contribution to the tech industry.

🏅 Awards and Recognition 

Nikolaos has been recognized for his contributions to EU-funded Horizon projects, which have brought substantial funding and technological advancements to his organizations. He co-authored papers published in prestigious journals like IEEE Transactions on Mobile Computing and Computer Science Review, highlighting his expertise in AI and cybersecurity. Additionally, his innovative solutions in fraud detection and SCADA security have been acknowledged within the tech community. Nikolaos’ commitment to open-source projects on GitHub further demonstrates his dedication to knowledge sharing and continuous improvement. His achievements reflect a career driven by excellence and societal impact.

🌍 Research Skills On Computer Science

Nikolaos excels in designing and deploying AI-driven solutions across domains such as cybersecurity, predictive medicine, and fraud detection. His expertise encompasses Federated Learning, blockchain integration, and data analysis using tools like TensorFlow, PyTorch, and Spark. Skilled in optimizing algorithms and building scalable data pipelines, Nikolaos has delivered solutions that reduce execution time and enhance efficiency. His academic research, coupled with industry application, positions him as a thought leader in leveraging AI for societal impact.

📖 Publication Top Notes

1. A comprehensive survey of Federated Intrusion Detection Systems: Techniques, challenges and solutions
  • Author(s): Ioannis Makris, Aikaterini Karampasi, Panagiotis Radoglou-Grammatikis, Nikolaos Episkopos, Eider Iturbe, Erkuden Rios, Nikos Piperigkos, Aris Lalos, Christos Xenakis, Thomas Lagkas, et al.
  • Citation: Computer Science Review, 2025-05
2. To DASH, or Not to DASH? Optimal Video Bitrate Selection and Edge Network Caching in MEC-Empowered Slice-Enabled Networks
  • Author(s): Dionysis Xenakis, Nikolaos Episkopos
  • Citation: IEEE Transactions on Vehicular Technology, 2024-04
3. PEER-TO-PEER VIDEO CONTENT DELIVERY OPTIMIZATION SERVICE IN A DISTRIBUTED NETWORK
  • Author(s): Nikolaos Episkopos
  • Citation: Dissertation/Thesis, 2022-10-24
4. Cache-Aware Adaptive Video Streaming in 5G networks
  • Author(s): Nikolaos Episkopos
  • Citation: Dissertation/Thesis, 2021-05-04
5. SECONDO: A Platform for Cybersecurity Investments and Cyber Insurance Decisions
  • Author(s): Aristeidis Farao, Sakshyam Panda, Sofia Anna Menesidou, Entso Veliou, Nikolaos Episkopos, George Kalatzantonakis, Farnaz Mohammadi, Nikolaos Georgopoulos, Michael Sirivianos, Nikos Salamanos, et al.
  • Citation: Trust, Privacy and Security in Digital Business (TrustBus), 2020-09-14
6. On-device caching of popular video content on Android-powered devices
  • Author(s): Nikolaos Episkopos
  • Citation: Dissertation/Thesis, 2018-08-14

Syed Mohammod Minhaz Hossain | Computer Science | Best Researcher Award

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Assoc. Prof. Dr. Syed Mohammod Minhaz Hossain | Computer Science | Best Researcher Award

👤 Assoc. Prof. Dr. Syed Mohammod Minhaz Hossain, Premier University, Bangladesh

Syed Mohammod Minhaz Hossain is a passionate researcher and IT professional dedicated to advancing the field of Computer Science and Engineering. He is currently pursuing a Ph.D. in Computer Science & Engineering at Chittagong University of Engineering & Technology (CUET). With a strong academic background, he earned his M.Sc. and B.Sc. in Computer Science & Engineering from CUET, securing notable positions. Hossain is committed to skillful learning and aims to create a synergy between industry and academia. He has published numerous research papers and contributed significantly to the scientific community, particularly in the areas of AI, machine learning, and environmental studies. Apart from his academic journey, he is a fervent advocate of education, believing in the power of teaching to shape well-rounded professionals who can contribute to society’s progress.

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 🌟  Suitability of Syed Mohammod Minhaz Hossain for the Research for Best Researcher Award:

Syed Mohammod Minhaz Hossain demonstrates strong academic and professional qualifications, making him a highly suitable candidate for the Research for Best Researcher Award. His dedication to academic excellence and research is reflected in his substantial academic achievements, including a Ph.D. in Computer Science and Engineering from Chittagong University of Engineering & Technology (CUET), and his outstanding undergraduate and postgraduate performance. His consistent recognition, such as the UGC Ph.D. Fellowship and multiple scholarships, underscores his commitment to research and academic growth.

Hossain has made notable contributions to the research community, particularly in the fields of artificial intelligence, machine learning, and environmental science. His extensive publication record includes numerous articles in high-impact journals such as PLoS ONE, Chemosphere, and Annals of Data Science, with a variety of topics ranging from water quality assessments to disease classification and COVID-19 detection using deep learning. His research not only focuses on technological advancements but also addresses pressing societal challenges, such as public health, environmental sustainability, and cybersecurity.

🎓  Education

Syed Mohammod Minhaz Hossain’s academic journey is marked by consistent excellence. He is currently pursuing his Ph.D. in Computer Science & Engineering at Chittagong University of Engineering & Technology (CUET). Prior to that, he completed his M.Sc. in Computer Science & Engineering at CUET in 2022, where he earned a CGPA of 3.42. He also holds a B.Sc. in the same field from CUET, securing a remarkable CGPA of 3.56. His foundation in education started at Chittagong Collegiate School, where he excelled with a GPA of 4.63 in his SSC and later earned a GPA of 4.50 in his HSC at Chittagong College. Throughout his academic career, Hossain has received multiple scholarships, including the UGC PhD Fellowship (2021-2022) and various merit-based awards, underlining his dedication and outstanding performance in the field of Computer Science.

💼 Professional Experience

Syed Mohammod Minhaz Hossain’s professional experience blends academia and industry, underscoring his passion for teaching and research. As a faculty member at Premier University, Bangladesh, Hossain conducts web system and program applications courses, integrating real-world industry skills into the classroom. His expertise is further demonstrated through his role in various research projects, focusing on areas such as artificial intelligence, deep learning, and environmental science. Hossain’s experience includes collaborating with international researchers, contributing to high-impact journals and conferences. His role in designing and developing academic curricula reflects his commitment to fostering future IT professionals who are not only skilled but also socially responsible. Additionally, Hossain’s involvement in the University of Technology, Sydney (UTS) College’s academic programs highlights his global outlook and the application of advanced research in practical teaching settings.

🏅 Awards and Recognitions 

Syed Mohammod Minhaz Hossain’s journey is characterized by numerous academic and research accolades. He received the prestigious UGC PhD Fellowship for 2021-2022, showcasing his commitment to advancing knowledge in Computer Science. Hossain earned the fourth position in his B.Sc. at CUET and was a recipient of the Board Scholarship in his HSC in 2003. He was also honored with the Junior Merit Scholarship in 1998 and the Primary Merit Scholarship in 1995, underlining his consistent academic excellence from an early age. His research contributions have been widely recognized, with multiple publications in high-impact journals such as PLoS ONE, Annals of Data Science, and Chemosphere. Furthermore, Hossain’s work on machine learning models for health-related issues and his involvement in international book chapters reflect his growing influence in the global research community.

🌍 Research Skills On Computer Science

Syed Mohammod Minhaz Hossain possesses a broad range of research skills that span artificial intelligence, machine learning, deep learning, and data science. His expertise includes applying these advanced technologies to solve complex problems in areas like health diagnostics, environmental monitoring, and cybersecurity. Hossain has developed proficiency in using deep neural networks, self-attention mechanisms, and convolutional models, as seen in his research on plant leaf disease recognition and heart disease prediction. Additionally, he has contributed to studies focused on the detection of COVID-19 fake news, Parkinson’s disease classification, and coastal water quality assessment. His research methodology includes leveraging large datasets, conducting statistical analyses, and employing advanced algorithms to create efficient and scalable solutions. Hossain’s ability to integrate interdisciplinary knowledge into his projects further enhances his capability to make impactful contributions to both academic and practical fields.

📖 Publication Top Notes

  • Cyber Intrusion Detection Using Machine Learning Classification Techniques
    • Authors: H Alqahtani, IH Sarker, A Kalim, SMM Hossain, S Ikhlaq, S Hossain
    • Citations: 189
    • Year: 2020
  • A Data-Driven Heart Disease Prediction Model Through K-Means Clustering-Based Anomaly Detection
    • Authors: RC Ripan, IH Sarker, SMM Hossain, MM Anwar, R Nowrozy, MM Hoque
    • Citations: 66
    • Year: 2021
  • Rice Leaf Diseases Recognition Using Convolutional Neural Networks
    • Authors: SMM Hossain, MMM Tanjil, MAB Ali, MZ Islam, MS Islam, S Mobassirin
    • Citations: 49
    • Year: 2021
  • Plant Leaf Disease Recognition Using Depth-Wise Separable Convolution-Based Models
    • Authors: SMM Hossain, K Deb, PK Dhar, T Koshiba
    • Citations: 34
    • Year: 2021
  • Amassing the Covid-19 Driven PPE Wastes in the Dwelling Environment of Chittagong Metropolis and Associated Implications
    • Authors: MJ Abedin, MU Khandaker, MR Uddin, MR Karim, MSU Ahamad
    • Citations: 22
    • Year: 2022
  • Assessment of Coastal River Water Quality in Bangladesh: Implications for Drinking and Irrigation Purposes
    • Authors: MR Uddin, MU Khandaker, S Ahmed, MJ Abedin, SMM Hossain
    • Citations: 13
    • Year: 2024
  • Spam Filtering of Mobile SMS Using CNN–LSTM Based Deep Learning Model
    • Authors: SMM Hossain, JA Sumon, A Sen, MI Alam, KMA Kamal, H Alqahtani
    • Citations: 13
    • Year: 2021
  • Plant Leaf Disease Recognition Using Histogram-Based Gradient Boosting Classifier
    • Authors: SMM Hossain, K Deb
    • Citations: 13
    • Year: 2021
  • Content-Based Spam Email Detection Using an N-gram Machine Learning Approach
    • Authors: NJ Euna, SMM Hossain, MM Anwar, IH Sarker
    • Citations: 9
    • Year: 2023
  • Trash Image Classification Using Transfer Learning-Based Deep Neural Network
    • Authors: D Das, A Sen, SMM Hossain, K Deb
    • Citations: 9
    • Year: 2022

 

Sheeja Rani S | Computer Science Award | Best Researcher Award

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Dr. Sheeja Rani S | Computer Science Award | Best Researcher Award

👤 Dr. Sheeja Rani S, American University of Sharjah, United Arab Emirates

Dr. Sheeja Rani S is a visionary researcher and academician specializing in Computer Science and Engineering, with a strong focus on Wireless Sensor Networks, IoT, and Smart Grids. She earned her Ph.D. from Noorul Islam Centre for Higher Education in 2023, where her thesis emphasized energy-efficient clustering algorithms for wireless sensor networks. Her academic journey is complemented by over a decade of teaching and research experience, where she worked on innovative solutions in cybersecurity, cloud computing, and machine learning. Currently serving as a Postdoctoral Research Assistant at the American University of Sharjah, Dr. Sheeja collaborates with leading experts on cutting-edge projects. With over 20 journal papers, numerous conference contributions, and a passion for impactful research, she strives to advance technology and foster intellectual growth. Her mission is to combine her expertise and mentorship skills to inspire future innovators while contributing to meaningful explorations in academia and beyond.

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🌟 Evaluation of Dr. Sheeja Rani S for the Research for Best Researcher Award

Summary of Suitability

Dr. Sheeja Rani S stands out as a highly qualified candidate for the “Research for Best Researcher Award,” showcasing an exceptional academic trajectory, prolific research output, and impactful contributions to multiple interdisciplinary domains. With a Ph.D. in Computer Science and Engineering focusing on improving energy efficiency in wireless sensor networks (WSNs), her research has addressed critical challenges in IoT, cloud computing, and smart grid technologies. These fields are not only contemporary but also pivotal for sustainable and secure technological advancements.

🎓 Education 

  • Ph.D. in Computer Science and Engineering (2023)
    Noorul Islam Centre for Higher Education
    Thesis: Improving Energy Efficiency Based on Clustering Algorithms for Wireless Sensor Networks.
  • M.E. in Computer Science and Engineering (2012)
    Noorul Islam Centre for Higher Education
  • M.Sc. Integrated Software Engineering (2009)
    Anna University, Chennai

Dr. Sheeja’s academic pursuits are rooted in innovation, particularly in optimizing computational techniques for energy efficiency and data security. Her Ph.D. research laid a foundation for creating advanced clustering mechanisms in wireless sensor networks, while her postgraduate and undergraduate studies focused on mastering computer science fundamentals and software engineering. She remains committed to lifelong learning and applying her knowledge to address emerging technological challenges.

💼  Professional Experience 

  • Postdoctoral Research Assistant (2023-Present)
    American University of Sharjah

    • Research on cybersecurity, smart grids, and cloud computing.
    • Published 12 journal papers in high-impact areas like IoT and machine learning.
  • Research Assistant (2022-2023)
    University of Sharjah

    • Focused on IoT, WSNs, and cloud computing.
    • Published 11 journal papers on financial distress prediction and IoT advancements.
  • Assistant Professor (2012-2021)
    John Cox Memorial CSI Institute of Technology

    • Taught advanced programming and database systems.
    • Managed academic coordination and examination processes.

Dr. Sheeja’s professional journey showcases a blend of teaching, research, and academic leadership, reflecting her dedication to advancing the field of computer science.

🏅 Awards and Recognitions 

  • Best Researcher Award (2023) – Recognized for impactful research in IoT and WSN.
  • Academic Excellence Award (2021) – Awarded for outstanding teaching and mentorship.
  • Research Grant Award (2022) – Funded for innovative studies on machine learning and cybersecurity.
  • Publication Excellence Award (2023) – Honored for prolific contributions to reputed journals.

Dr. Sheeja has consistently received accolades for her exceptional academic and research contributions. Her achievements reflect her dedication to excellence and her ability to produce innovative solutions that address global challenges.

🌍  Research Skills On Computer Science Award 

Dr. Sheeja’s research expertise spans:

  • Wireless Sensor Networks (WSN): Energy-efficient routing and clustering.
  • IoT: Developing secure and scalable architectures for smart environments.
  • Machine Learning: Applying predictive models for financial and cybersecurity domains.
  • Smart Grids: Integration of AI for optimal energy distribution.
  • Cloud Computing: Enhancing reliability and fault tolerance in virtualized environments.

📖 Publication Top Notes

Improved buffalo optimized deep feed forward neural learning based multipath routing for energy-efficient data aggregation in WSN
    • Authors: SS Rani, KS Sankar
    • Citation: Measurement: Sensors 27, 100662
    • Cited by: 8
    • Year: 2023
Optimized deep learning for Congestion-Aware continuous target tracking and boundary detection in IoT-Assisted WSN
    • Authors: AM Khedr, SS Rani, M Saad
    • Citation: IEEE Sensors Journal 23 (7), 7938-7948
    • Cited by: 8
    • Year: 2023
Enhancing Supply Chain Management with Deep Learning and Machine Learning Techniques: A Review
    • Authors: SSR Khedr, Ahmed M
    • Citation: Journal of Open Innovation: Technology, Market, and Complexity, 100379
    • Cited by: 5
    • Year: 2024
Hybridized Dragonfly and Jaya algorithm for optimal sensor node location identification in mobile wireless sensor networks
    • Authors: AM Khedr, SS Rani, M Saad
    • Citation: The Journal of Supercomputing 79 (15), 16940-16962
    • Cited by: 4
    • Year: 2023
Enhancing financial distress prediction through integrated Chinese Whisper clustering and federated learning
    • Authors: AI Al Ali, AM S S Rani Khedr
    • Citation: Journal of Open Innovation: Technology, Market, and Complexity 10 (3), 100344
    • Cited by: 2
    • Year: 2024