Supritha Nagendra | Big data analytics | Best Researcher Award

Posted on by Academic achievements

Mrs. Supritha Nagendra | Big data analytics | Best Researcher Award

Mrs. Supritha Nagendra | Big data analytics- Research scholar at BMSIT&M, India

Supritha N is a dedicated academic professional with extensive experience in the field of Computer Science and Engineering (CSE). With a career spanning over 8.6 years in teaching and research, she has worked across several reputed institutions, contributing immensely to the academic and research community. Currently pursuing her Ph.D. at BMSIT&M, she has established herself as an innovative researcher with a focus on Big Earth Analytics, remote sensing, and active learning models. Supritha’s dedication to her work and her ability to blend academic and research excellence make her a deserving candidate for various accolades in the field of research and education.

Profile:

Orcid

Education:

Supritha holds a robust academic background, with a Ph.D. in Computer Science and Engineering from BMSIT&M. She completed her M.Tech. in the same field from A.P.S.C.E, securing an impressive 76%. Prior to this, she earned her B.E. from JVIT, with a 71% score. Her academic journey also includes a strong foundation in basic sciences, as evidenced by her outstanding performance during her P.U.C. and SSLC years, where she achieved high marks in her respective board examinations. Supritha’s consistent academic performance highlights her strong analytical skills, determination, and commitment to continuous learning.

Experience:

Supritha N brings over 8.6 years of professional experience, primarily in teaching and research roles. Her career began as a Lecturer at JVIT, where she worked from 2009 to 2011, before transitioning to a more extensive role as an Assistant Professor. She served at East West Institute of Technology from 2017 to 2021 and at RNS Institute of Technology from 2021 to 2024. Throughout her tenure in these positions, Supritha has mentored students, taught various undergraduate and postgraduate courses, and played a pivotal role in guiding student projects. Her comprehensive teaching portfolio includes subjects such as Digital Design and Computer Organization, Big Data Analytics, Microprocessors and Embedded Systems, and Cryptography, among others. Her experience in teaching has been marked by her innovative approach to complex subjects, enabling students to grasp critical concepts with ease.

Research Interests:

Supritha’s research interests lie at the intersection of Big Data Analytics, Remote Sensing, and Artificial Intelligence. She is particularly focused on developing resource-efficient models for Big Earth Spatial Data Management and Analytics (BESDMA). Her Ph.D. research aims to design sparse image representation models to improve remote sensing applications and resource efficiency in Earth observation systems. Additionally, Supritha has worked on various projects related to machine learning and active learning, emphasizing the importance of quality-sensitive solutions in data processing and analysis. Her innovative work in these fields has led to the publication of several impactful papers, furthering knowledge in her areas of research.

Awards:

Supritha N has earned numerous accolades throughout her career, underscoring her dedication and excellence in both research and teaching. She was awarded the Best Paper Award for her paper on “Object Placement Using Augmented Reality” at the 2nd National Conference on Computing Technology in 2022. Additionally, her work on “Communication for Motor Neuron Disease Patients via Eye Blink to Voice Recognition” received the Best Paper Award at the 14th National Conference in 2019. Her contributions to research have been recognized not only in academic circles but also through her active participation in national and international conferences and her ability to translate her research into real-world applications.

Publications:

Supritha N has authored and co-authored several research papers, many of which have been published in esteemed journals and conferences. Some of her key publications include:

  1. “Deep Spatio-textural feature driven multi-constraints pool-based active learning model for resource-efficient big earth observations” (2025), International Journal of Remote Sensing 🌍📚 [Cited by: 15 articles]
  2. “A Comprehensive Study on Satellite based Data Communication for Big Earth Observation Systems” (2024), IEEE International Conference on Knowledge Engineering and Communication Systems 🌐📈 [Cited by: 7 articles]
  3. “A Comparative Study of The CNN Based Models Used for Remote Sensing Image Classification” (2023), IJEER Journal 🛰️📄 [Cited by: 10 articles]
  4. “The Scope of Artificial Intelligence in Agriculture and Healthcare Sectors – A Comprehensive Review” (2022), Advanced Engineering Sciences 🤖🌾 [Cited by: 5 articles]

Conclusion:

Supritha N’s journey in academia and research reflects a high level of commitment, excellence, and passion for innovation. Her career trajectory, marked by substantial teaching experience and groundbreaking research, places her in a strong position for recognition in the field of Computer Science and Engineering. Her research work, particularly in Big Earth Analytics, remote sensing, and AI-driven models, has not only advanced academic understanding but also shown promise for real-world applications. With multiple publications, awards, and a demonstrated commitment to mentoring students, Supritha N is a deserving nominee for the Best Researcher Award. Her work continues to inspire peers and students alike, and she remains focused on pushing the boundaries of knowledge in her field.

Majdi Khalid | Machine learning | Best Researcher Award

Posted on by Academic achievements

Assoc Prof. Dr. Majdi Khalid | Machine learning | Best Researcher Award 

Associate Professor at Umm Al-Qura University

Assoc. Prof. Dr. Majdi Khalid is an esteemed researcher in the field of machine learning with a focus on deep learning, artificial intelligence, and their applications in various domains such as computer vision, natural language processing, and bioinformatics. He is currently an Associate Professor at Umm Al-Qura University, Makkah, Saudi Arabia. Dr. Khalid has made significant contributions to cutting-edge research, particularly in the intersection of AI and bioinformatics, publishing numerous papers in prestigious journals and collaborating with international researchers. His work in AI for drug discovery and healthcare highlights his dedication to using technology to solve complex biological and medical challenges.

Profile:

ORCID

Education:

Dr. Khalid holds a Ph.D. in Computer Science from Colorado State University, USA, which he completed in 2019. His doctoral research centered on advanced computational models and machine learning algorithms, laying the foundation for his future endeavors in AI and deep learning. Prior to his Ph.D., Dr. Khalid earned his Master of Computer Science (M.C.S.) from the same institution in 2013, and a Bachelor of Science (B.S.) in Computer Science from Umm Al-Qura University in 2006. His academic training has equipped him with the technical and theoretical expertise necessary to excel in both academia and applied research.

Experience:

Dr. Khalid’s academic career began as an Instructor at the Technical College in Al Baha, Saudi Arabia, from 2007 to 2008. After earning his graduate degrees, he joined Umm Al-Qura University as an Assistant Professor in 2019, where he has since been engaged in teaching and research. Throughout his academic journey, Dr. Khalid has focused on mentoring students, leading cutting-edge research projects, and publishing extensively in the areas of machine learning and AI. His collaboration with national and international research teams has further enriched his experience, making him a valuable contributor to the global AI research community.

Research Interests:

Dr. Khalid’s research interests span various applications of machine learning and deep learning. He specializes in developing computational models for computer vision, natural language processing, bioinformatics, and brain-computer interfaces. His work in AI-driven drug discovery has led to the development of innovative tools for identifying epigenetic proteins and other biomarkers, which are critical for advancing modern medicine. Dr. Khalid is also actively exploring how AI can enhance healthcare systems and improve diagnostic accuracy, with a strong focus on interdisciplinary collaboration between AI and biological sciences.

Awards:

Dr. Khalid has received numerous recognitions for his research excellence, including university-level awards for outstanding research performance. His contributions to the fields of AI and machine learning have been acknowledged by both academic institutions and international conferences. While he has yet to secure a large-scale international research award, his continued dedication to advancing the field positions him as a prime candidate for future accolades.

Publications:

  1. Ali, Farman, Abdullah Almuhaimeed, Majdi Khalid, et al. (2024). “DEEPEP: Identification of epigenetic protein by ensemble residual convolutional neural network for drug discovery.” Methods.
    • Cited by articles focusing on the intersection of AI and drug discovery methodologies.
      Read the article here
  2. Khalid, Majdi, Farman Ali, et al. (2024). “An ensemble computational model for prediction of clathrin protein by coupling machine learning with discrete cosine transform.” Journal of Biomolecular Structure and Dynamics.
    • Cited by researchers investigating protein structure prediction and AI’s role in molecular biology.
      Read the article here
  3. Alsini, Raed, Abdullah Almuhaimeed, et al. (2024). “Deep-VEGF: deep stacked ensemble model for prediction of vascular endothelial growth factor by concatenating gated recurrent unit with 2D-CNN.” Journal of Biomolecular Structure and Dynamics.
  4. Alohali, Manal Abdullah, et al. (2024). “Textual emotion analysis using improved metaheuristics with deep learning model for intelligent systems.” Transactions on Emerging Telecommunications Technologies.
    • Cited in studies focusing on emotion recognition through AI in intelligent systems.
      Read the article here
  5. Majdi Khalid (2023). “Advanced Detection of COVID-19 through X-ray Imaging using CovidFusionNet with Hybrid CNN Fusion and Multi-resolution Analysis.” International Journal of Advanced Computer Science and Applications.
  1. Ali, Muhammad Umair, Majdi Khalid, et al. (2023). “Enhancing Skin Lesion Detection: A Multistage Multiclass Convolutional Neural Network-Based Framework.” Bioengineering, 10(12): 1430.
    • Cited by papers focusing on AI applications in medical diagnostics and image analysis for dermatology.
      Read the article here
  2. Alghushairy, Omar, Farman Ali, Wajdi Alghamdi, Majdi Khalid, et al. (2023). “Machine learning-based model for accurate identification of druggable proteins using light extreme gradient boosting.” Journal of Biomolecular Structure and Dynamics, 2023: 1-12.
    • Cited by studies dealing with protein-drug interactions and machine learning applications in bioinformatics.
      Read the article here
  3. Obayya, Marwa, Fahd N. Al-Wesabi, Rana Alabdan, Majdi Khalid, et al. (2023). “Artificial Intelligence for Traffic Prediction and Estimation in Intelligent Cyber-Physical Transportation Systems.” IEEE Transactions on Consumer Electronics, 2023.
    • Cited by research on AI-enhanced traffic systems and predictive modeling in smart cities.
      Read the article here
  4. Alruwais, Nuha, Eatedal Alabdulkreem, Majdi Khalid, et al. (2023). “Modified Rat Swarm Optimization with Deep Learning Model for Robust Recycling Object Detection and Classification.” Sustainable Energy Technologies and Assessments, 59: 103397.
    • Cited by works in sustainable technologies and AI for recycling and waste management.
      Read the article here
  5. Adnan, Adnan, Wang Hongya, Farman Ali, Majdi Khalid, et al. (2023). “A Bi-Layer Model for Identification of piwiRNA using Deep Neural Learning.” Journal of Biomolecular Structure and Dynamics, 2023: 1-9.
  • Cited by articles focused on non-coding RNA identification and AI-driven molecular biology research.
    Read the article here

Conclusion

Assoc. Prof. Dr. Majdi Khalid is a highly deserving candidate for the Best Researcher Award due to his extensive research contributions in machine learning and artificial intelligence. His innovative work in applying machine learning to critical fields such as drug discovery, COVID-19 detection, and biomolecular prediction makes him a thought leader in his domain. With minor improvements in real-world application and cross-disciplinary collaboration, Dr. Khalid’s potential to lead global innovations in machine learning is undeniable. His current achievements already solidify his place as one of the leading researchers in his field, making him an outstanding candidate for this prestigious award.