Tajunisha N | Computer Science | Best Faculty Award

Dr. Tajunisha N | Computer Science | Best Faculty Award

Dr. Tajunisha N, Sri Ramakrishna College of Arts & Science for Women, India

Dr. N. Tajunisha is a distinguished academician and researcher in Computer Science, currently serving as Professor and Head of the Department at Sri Ramakrishna College of Arts & Science for Women. With over 27 years of academic experience and 23 years of research expertise, she specializes in Data Mining, Machine Learning, Big Data Analytics, and Networks. She earned her Ph.D. from Mother Teresa Womenโ€™s University, Kodaikanal, and has been an influential figure in research and development. As a leader, she has held key positions such as Research Coordinator, IQAC Coordinator, and Institution Innovation Cell (IIC) President. Her contributions to academia include publishing research papers in prestigious journals, securing research funding, and mentoring Ph.D. scholars. Recognized with the Senior Educator and Scholar Award, she actively collaborates with institutions like IBM, Rently, and L&T EDUTECH. Her work continues to shape the future of Computer Science education and research.

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Suitability of Dr. N. Tajunisha for the Research for Best Faculty Award

Dr. N. Tajunisha is a distinguished academic leader with a strong record of excellence in teaching, research, and institutional development. With 27 years of academic experience and 23 years of research expertise, she has significantly contributed to the fields of Data Mining, Machine Learning, Big Data Analytics, and Networks. As a Professor and Head of the Department of Computer Science at Sri Ramakrishna College of Arts & Science for Women, she has played a crucial role in shaping the institution’s academic and research landscape.

Her research contributions are noteworthy, with 34 journal publications, 25 conference papers, and 9 SCOPUS-indexed papers, along with securing Rs. 3.17 lakhs from UGC for a Minor Research Project and Rs. 76 lakhs for a DST-FIST project. Dr. Tajunishaโ€™s role as a Ph.D. guide, having successfully mentored three doctoral scholars and currently supervising five more, reflects her dedication to research mentorship. Her collaborations with IBM, Rently, L&T EDUTECH, Easy Design System, and VConnect highlight her industry engagement, while her participation in Doctoral Committees, Board of Studies (BOS), and Programme Advisory Committees showcases her leadership in academic governance.

๐ŸŽ“ Education

Dr. N. Tajunisha has an extensive educational background in Computer Science and Mathematics. She earned her Ph.D. in Computer Science from Mother Teresa Womenโ€™s University, Kodaikanal, in 2013, focusing on advanced research methodologies. Before that, she completed her M.Phil. in Computer Science from Bharathiar University, where she developed expertise in data analysis and computational techniques. Her academic journey began with a Master of Computer Applications (MCA) and a Bachelor’s degree in Mathematics from Madurai Kamaraj University, providing her with a strong mathematical foundation essential for algorithm development and computational problem-solving. Her diverse academic background has equipped her with critical analytical skills, enabling her to contribute significantly to the fields of Data Mining and Machine Learning. Her education and continuous professional development have played a crucial role in her ability to drive research innovations and mentor future scholars in Computer Science.

๐Ÿ’ผ Professional Experience

Dr. N. Tajunisha has over 27 years of academic experience and 23 years in research, significantly shaping Computer Science education. As the Professor & Head of the Department of Computer Science at Sri Ramakrishna College of Arts & Science for Women, she has spearheaded numerous academic and research initiatives. From 2013 to 2018, she served as the Research Coordinator, facilitating advanced research projects and securing substantial funding, including a Rs. 76 lakh DST-FIST grant. She has also played a pivotal role as the IQAC Coordinator (2018-2022), ensuring institutional excellence. Additionally, she has served as the Institution Innovation Cell (IIC) President, fostering entrepreneurship and innovation. Her industry collaborations with IBM, Rently, and L&T EDUTECH have enriched student learning experiences. She has contributed as a Board of Studies member in multiple colleges and played an active role in doctoral committees and inspection commissions under Bharathiar University.

๐Ÿ… Awards and Recognition

Dr. N. Tajunishaโ€™s contributions to academia have been widely recognized through numerous awards and honors. She received the prestigious Senior Educator and Scholar Award from NFED in 2017 for her outstanding contributions to Computer Science education. She has also been honored with the Best Paper Award at the IEEE International Conference held at Satyabhama University in 2010. Her research excellence is reflected in her extensive publication record, including nine Scopus-indexed journal papers. Her leadership in institutional development led to Sri Ramakrishna College of Arts & Science for Women achieving an A+ grade in NAAC Cycle II under her tenure as IQAC Coordinator. Additionally, she has been an invited session chair at international conferences and serves as a reviewer for top-tier journals. Her commitment to fostering innovation and research has positioned her as a thought leader in Data Mining, Machine Learning, and Big Data Analytics.

๐ŸŒ Research Skills On Computer Science

Dr. N. Tajunishaโ€™s research expertise spans Data Mining, Machine Learning, Big Data Analytics, and Networks. She has successfully guided three Ph.D. scholars and is currently mentoring five more, contributing to advancements in computational intelligence and predictive analytics. Her research has secured substantial funding, including a Rs. 3.17 lakh UGC Minor Research Project and Rs. 76 lakh for a DST-FIST project. With 34 journal papers, 25 conference papers, and two books to her credit, she has made significant contributions to her field. She actively collaborates with industry leaders like IBM, Rently, and L&T EDUTECH, ensuring practical applications of her research. Her ability to integrate academic knowledge with real-world solutions makes her a leading researcher in her domain. She has also been a reviewer for international journals and a committee member in doctoral research evaluations, further enhancing her impact in the field.

๐Ÿ“– Publication Top Notes

  • Performance analysis of k-means with different initialization methods for high-dimensional data
    Author(s): VSN Tajunisha
    Journal: International Journal of Artificial Intelligence and Applications
    Citations: 35
    Year: 2010

  • An efficient method to improve the clustering performance for high dimensional data by principal component analysis and modified K-means
    Author(s): N Tajunisha, V Saravanan
    Journal: International Journal of Database Management Systems
    Citations: 20
    Year: 2011

  • An increased performance of clustering high dimensional data using Principal Component Analysis
    Author(s): N Tajunisha, V Saravanan
    Conference: 2010 First International Conference on Integrated Intelligent Computing
    Citations: 19
    Year: 2010

  • A study on evolution of data analytics to big data analytics and its research scope
    Author(s): S Sruthika, N Tajunisha
    Conference: 2015 International Conference on Innovations in Information, Embedded and โ€ฆ
    Citations: 14
    Year: 2015

  • Predicting Student Performance Using MapReduce
    Author(s): N Tajunisha, M Anjali
    Journal: International Journal of Emerging and Computer Science
    Citations: 14
    Year: 2015

  • A new approach to improve the clustering accuracy using informative genes for unsupervised microarray data sets
    Author(s): N Tajunisha, V Saravanan
    Journal: International Journal of Advanced Science and Technology
    Citations: 10
    Year: 2011

  • Automatic classification of ovarian cancer types from CT images using deep semi-supervised generative learning and convolutional neural network
    Author(s): N Nagarajan, P.H. Tajunisha
    Journal: Revue d’Intelligence Artificielle
    Citations: 9
    Year: 2021

  • Classification of cancer datasets using artificial bee colony and deep feed-forward neural networks
    Author(s): M Karunyalakshmi, N Tajunisha
    Journal: International Journal of Advanced Research in Computer and Communication โ€ฆ
    Citations: 8
    Year: 2017

  • Concept and Term-Based Similarity Measure for Text Classification and Clustering
    Author(s): B Sindhiya, N Tajunisha
    Journal: IJERST
    Citations: 7
    Year: 2014

  • Optimal Parameter Selection-Based Deep Semi-Supervised Generative Learning and CNN for Ovarian Cancer Classification
    Author(s): PH Nagarajan, N Tajunisha
    Journal: ICTACT Journal on Soft Computing
    Citations: 5
    Year: 2023

Ahona Ghosh | Computer Science | Best Researcher Award

Ms. Ahona Ghosh | Computer Science | Best Researcher Award

๐Ÿ‘ค Ms. Ahona Ghosh, Maulana Abul Kalam Azad University of Technology, West Bengal, India

Ahona Ghosh is a promising researcher in the field of Computer Science and Engineering with a focus on artificial intelligence, machine learning, and rehabilitation technologies. Currently completing her Ph.D. at Maulana Abul Kalam Azad University of Technology, West Bengal, Ahona has made significant strides in the academic and research community. Her work involves a blend of deep learning, cognitive rehabilitation, and IoT-based systems for improving quality of life. With several publications in prestigious international journals and conferences, she has earned recognition for her contributions to the scientific community. Ahona has been awarded the Best Paper Award for her work on IoT-based waste management and has ranked highly in various competitions like MAKATHON’22. She is passionate about leveraging technology for social good, particularly in healthcare and rehabilitation systems.

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๐ŸŒŸย Ms. Ahona Ghosh, Summary of Suitability

Dr. Ahona Ghosh is an outstanding candidate for the Research for Best Researcher Award, demonstrating exceptional academic accomplishments, innovative research contributions, and consistent excellence throughout her career. Her extensive academic background includes a Ph.D. in Computer Science and Engineering from Maulana Abul Kalam Azad University of Technology, West Bengal, with her pre-submission and viva completed, reflecting her advanced expertise and dedication to her field. She has received accolades for her academic and research endeavors, such as the Best Paper Award for her IoT-based waste management system and the Academic Excellence Award from Brainware University.

Her robust portfolio of research contributions includes an impressive array of international journal articles, conference papers, patents, and book chapters. Dr. Ghosh’s work spans cutting-edge topics such as deep learning, cognitive rehabilitation, IoT applications, and fuzzy systems, addressing societal challenges like healthcare, rehabilitation, and sustainable development.

๐ŸŽ“ Educationย 

Ahona Ghosh has a strong academic background, with a Ph.D. in Computer Science and Engineering from Maulana Abul Kalam Azad University of Technology (MAKAUT), where she is in the final stages of her thesis submission. She completed her Master of Technology (M.Tech.) in the same field at MAKAUT in 2019, with a CGPA of 8.73. Her Bachelor’s degree in Computer Science and Engineering (B.Tech.) was awarded by Techno India College of Technology in 2017, where she achieved a CGPA of 7.66. Ahonaโ€™s early education includes Higher Secondary in Science from Taki House Government Sponsored Girls High School, with an aggregate of 67.4%. She also passed the Madhyamik Pariksha (Class 10) from Duff High School for Girls with a remarkable score of 82.88%. Ahona is also certified in NTA-NET for the years 2018 and 2019.

๐Ÿ’ผย ย Professional Experience

Ahona Ghosh has worked extensively in academia and research, focusing on artificial intelligence, IoT, and healthcare applications. Currently, she is a Doctoral Fellow at Maulana Abul Kalam Azad University of Technology (MAKAUT). Her research includes contributions to cognitive rehabilitation using machine learning and EEG-based sensor systems. She has also been involved in various projects concerning IoT-based solutions for healthcare, such as designing smart systems for cognitive rehabilitation and enhancing data-driven rehabilitation methods. In addition, Ahona has been a part of multiple international conferences where she presented papers, co-authored patents, and contributed to the scientific community with impactful research. Her teaching experience includes mentoring undergraduate students and guiding research projects, as well as working on industry collaborations in technology development. Ahona’s expertise in both theoretical and applied aspects of Computer Science has shaped her as a versatile professional in the field.

๐Ÿ…ย Awards and Recognition

Ahona Ghosh has received several accolades for her academic and research achievements. She won the Best Paper Award at the IETE Eastern Zonal Seminar with ISF Congress in 2017 for her paper on “Waste Management System Based on Internet of Things (IoT)”. Her innovative contributions earned her the Academic Excellence Award from Brainware University in January 2020, based on exceptional student feedback. She also achieved 2nd place in the MAKATHON’22 competition organized by MAKAUTโ€™s Innovation Council. Ahona’s recognition extends beyond awards, as she is a prominent figure in academic circles, having presented her research at several prestigious IEEE conferences. Her qualifications include passing the NTA-NET exams in 2018 and 2019, reinforcing her academic prowess. Ahonaโ€™s dedication to research and innovation continues to receive recognition, making her an influential presence in her field.

๐ŸŒ Research Skills On Computer Scienceย 

Ahona Ghosh has developed a comprehensive set of research skills, particularly in the areas of Artificial Intelligence, Machine Learning, Deep Learning, and Cognitive Rehabilitation. Her expertise extends to using IoT for healthcare applications, including creating systems for rehabilitative therapy and mental health analysis. Ahona is proficient in data analysis, algorithm design, and modeling for both real-time and research-driven applications. Her experience with neural networks, sensor systems, and signal processing further enhances her ability to tackle complex problems. Ahona has contributed to developing innovative frameworks using fuzzy logic, sensor networks, and electroencephalography (EEG) in health-related projects. She excels in academic writing, having published in numerous peer-reviewed journals and international conferences. Additionally, she is well-versed in patent filing, research methodology, and project management, which are crucial in carrying out high-impact scientific work.

๐Ÿ“– Publication Top Notes

Scope of Sentiment Analysis On News Articles Regarding Stock Market and GDP in Struggling Economic Condition
  • Authors: S Biswas, A Ghosh, S Chakraborty, S Roy, R Bose
    Journal: International Journal of Emerging Trends in Engineering Research, 8 (7), 3594
    Citation: 30
    Year: 2020
A Detailed Study on Data Centre Energy Efficiency and Efficient Cooling Techniques
  • Authors: D Mukherjee, S Chakraborty, I Sarkar, A Ghosh, S Roy
    Journal: International Journal of Advanced Trends in Computer Science and Engineering
    Citation: 26
    Year: 2020
Recognition of hand gesture image using deep convolutional neural network
  • Authors: KM Sagayam, AD Andrushia, A Ghosh, O Deperlioglu, AA Elngar
    Journal: International Journal of Image and Graphics, 22 (03), 2140008
    Citation: 22
    Year: 2022
Service aware resource management into cloudlets for data offloading towards IoT
  • Authors: D Guha Roy, B Mahato, A Ghosh, D De
    Journal: Microsystem Technologies, 1-15
    Citation: 21
    Year: 2022
Mathematical modelling for decision making of lockdown during COVID-19
  • Authors: A Ghosh, S Roy, H Mondal, S Biswas, R Bose
    Journal: Applied Intelligence
    Citation: 17
    Year: 2021
Secured Energy-Efficient Routing in Wireless Sensor Networks Using Machine Learning Algorithm: Fundamentals and Applications
  • Authors: A Ghosh, CC Ho, R Bestak
    Journal: Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks
    Citation: 12
    Year: 2020
A survey on Internet-of-Thing applications using electroencephalogram
  • Authors: D Chakraborty, A Ghosh, S Saha
    Book: Emergence of Pharmaceutical Industry Growth with Industrial IoT Approach, 21-47
    Citation: 12
    Year: 2020
Rehabilitation using neighbor-cluster based matching inducing artificial bee colony optimization
  • Authors: S Saha, A Ghosh
    Conference: 2019 IEEE 16th India Council International Conference (INDICON), 1-4
    Citation: 12
    Year: 2019
Dtnma: identifying routing attacks in delay-tolerant network
  • Authors: S Chatterjee, M Nandan, A Ghosh, S Banik
    Book: Cyber Intelligence and Information Retrieval: Proceedings of CIIR 2021, 3-15
    Citation: 11
    Year: 2022
Emotion detection using generative adversarial network
  • Authors: S Das, A Ghosh
    Book: Generative Adversarial Networks and Deep Learning, 165-182
    Citation: 10
    Year: 2023

Raghad K Mohammed | Computer Science | Academic Excellence Award

Dr. Raghad K Mohammed | Computer Science | Academic Excellence Award

๐Ÿ‘ค Dr. Raghad K Mohammed, College of Computer Science and Information Technology, Iraq

Raghad Khaled Mohammed, born on September 29, 1978, is a dedicated academic professional specializing in Computer Networks. She serves as a Lecturer at the College of Dentistry, University of Baghdad, where she has contributed significantly to education and research since 2005. A Muslim, married, and a mother of two, Raghad has consistently balanced her personal and professional life with distinction. Her academic journey began with a Bachelor’s degree from Al-Rafidain in 2002, followed by a Master’s in Computer Networks from the University of Technology in 2005. She is currently pursuing a PhD in Computer Science and Information Technology at the University of Anbar. Her professional roles have included leadership positions, such as Head of the Planning and Quality Assurance Units, showcasing her commitment to academic excellence and institutional development.

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๐ŸŒŸย Suitability for the Research for Academic Excellence Award

Summary of Suitability
Raghad Khaled Mohammedโ€™s extensive academic journey and professional accomplishments demonstrate her dedication to higher education and research, making her a strong candidate for the Research for Academic Excellence Award. With a career spanning nearly two decades, her contributions as a lecturer at the University of Baghdadโ€™s College of Dentistry, along with leadership roles in quality assurance, planning, and continuing education, reflect her commitment to fostering academic and institutional excellence.

๐ŸŽ“ย ย Education

Raghad Khaled Mohammed’s academic qualifications reflect her dedication to advancing knowledge in Computer Science. She earned her Bachelorโ€™s degree in 2002 from Al-Rafidain, laying the foundation for her career. In 2005, she completed a Masterโ€™s degree in Computer Networks from the Informatics Institute for Graduate Studies, University of Technology, Baghdad. This specialization equipped her with technical expertise in designing and managing network systems. Currently, she is pursuing a PhD in Computer Science and Information Technology at the University of Anbar, demonstrating her commitment to lifelong learning and academic growth. Her academic progression highlights her passion for integrating innovative solutions and knowledge-sharing within the field of computer science, with a focus on practical applications that benefit both academia and industry.

๐Ÿ’ผย ย Professional Experience

Raghad Khaled Mohammed has a rich professional journey at the University of Baghdad. She started as an Assistant Lecturer in 2005, demonstrating a strong foundation in teaching and academic research. From 2006 to 2009, she led the Planning Department, showcasing her organizational and strategic planning skills. In 2010, she was promoted to Lecturer, reflecting her academic and professional growth. Between 2016 and 2018, she excelled as the Head of the Quality Assurance Unit, where she implemented initiatives to enhance educational standards. Her leadership continued in 2024 as the Head of the Continuing Education Unit, focusing on faculty and student skill development. Raghad’s multifaceted roles underline her expertise in education, administration, and her dedication to fostering an environment of continuous improvement and innovation.

๐Ÿ…ย Awards and Recognition

Raghad Khaled Mohammed’s career is marked by achievements and recognition in academia. Her contributions to quality assurance earned her institutional accolades during her tenure as the Head of the Quality Assurance Unit. Her innovative initiatives in the Planning Department were lauded for their impact on academic progress and administrative efficiency. As a researcher and educator, she has been acknowledged for her role in advancing the field of Computer Networks, earning respect among peers and students alike. Raghad has also been recognized for her leadership in Continuing Education, where she played a pivotal role in professional development programs. These accolades affirm her commitment to academic excellence and her ability to inspire positive change within her institution.

๐ŸŒ Research Skills On Computer Science

Raghad Khaled Mohammed possesses diverse research skills, particularly in Computer Networks and Information Technology. Her expertise includes network architecture design, security protocols, and system optimization. She is skilled in using advanced simulation tools and programming languages to develop innovative solutions for complex networking challenges. Raghad’s research focuses on bridging the gap between theoretical concepts and real-world applications, aiming to enhance efficiency and cybersecurity in digital systems. Her ability to integrate interdisciplinary approaches, coupled with her technical expertise, ensures impactful contributions to academia and industry. With ongoing doctoral studies, her research skills continue to evolve, driving advancements in Computer Science and Information Technology.

๐Ÿ“– Publication Top Notes

Title: U-Net for Genomic Sequencing: A Novel Approach to DNA Sequence Classification
  • Authors: Mohammed, R.K.; Alrawi, A.T.H.; Dawood, A.J.
    Year: 2024
    Journal: Alexandria Engineering Journal
    Volume and Pages: 96, pp. 323โ€“331
    Citations: 0
Title: Optimizing Genetic Prediction: Define-by-Run DL Approach in DNA Sequencing
  • Authors: Mohammed, R.K.; Alrawi, A.T.H.; Dawood, A.J.
    Year: 2023
    Journal: Journal of Intelligent Systems
    Volume and Pages: 32(1), Article ID: 20230130
    Citations: 0
Title: Detecting Damaged Buildings on Post-Hurricane Satellite Imagery Based on Transfer Learning
  • Authors: Al-Saffar, R.; Mohammed, R.K.; Abed, W.M.; Hussain, O.F.
    Year: 2022
    Journal: NeuroQuantology
    Volume and Pages: 20(1), pp. 105โ€“119
    Citations: 1

Sheeja Rani S | Computer Science Award | Best Researcher Award

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

๐Ÿ‘คย 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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๐ŸŒŸย 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.

๐ŸŽ“ย Educationย 

  • 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.

๐Ÿ’ผย ย Professional Experienceย 

  • 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.

๐Ÿ…ย Awards and Recognitionsย 

  • Best Researcher Award (2023) โ€“ Recognized for impactful research in IoT and WSN.
  • Academic Excellence Award (2021) โ€“ Awarded for outstanding teaching and mentorship.
  • Research Grant Award (2022) โ€“ Funded for innovative studies on machine learning and cybersecurity.
  • Publication Excellence Award (2023) โ€“ 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.

๐ŸŒ ย Research Skills On Computer Science Awardย 

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.

๐Ÿ“– 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