Sajja Tulasi Krishna | Computer Science | Research Excellence Award

Published-on by Indian Scientist

Dr. Sajja Tulasi Krishna | Computer Science | Research Excellence Award

Koneru Lakshmaiah Education Foundation | India

Dr. Sajja Tulasi Krishna is a distinguished researcher and academician in Computer Science and Engineering, currently serving as an Assistant Professor at Koneru Lakshmaiah Education Foundation. She has extensive teaching experience in areas including CI/CD, Cloud DevOps, Python Full Stack Development, MERN Stack Web Development, Deep Learning, and Data Structures. Dr. Krishna earned her Ph.D. in Computer Science and Engineering and holds advanced degrees in M.Tech and B.Tech, reflecting a strong academic foundation. Her research focuses on deep learning, machine learning, biomedical image processing, and intelligent systems, with contributions in multi-omics integration, lung cancer detection, COVID-19 diagnosis, and medicinal plant classification. She has published 18 research articles in SCIE, Scopus, and IEEE journals, achieving a total of 488 citations with an h-index of 5 and an i10-index of 5. Dr. Krishna has presented her work at multiple national and international conferences, serving as a reviewer for reputed journals and conferences. She has received multiple awards recognizing her excellence in teaching, research, and technical contributions, including Best Teacher, International Excellence, and Young Researcher Awards. With her expertise, she continues to advance innovative research while mentoring students and contributing to the academic community globally.

Profiles: Google Scholar | Scopus | Orcid

Featured Publications

Krishna, S. T., & Kalluri, H. K. (2019). Deep learning and transfer learning approaches for image classification. International Journal of Recent Technology and Engineering (IJRTE), 7(5S4), 427–432.

Sajja, T. K., Devarapalli, R. M., & Kalluri, H. K. (2019). Lung cancer detection based on CT scan images by using deep transfer learning. Traitement du Signal, 36(4), 339–344.

Sajja, T. K., & Kalluri, H. K. (2020). A deep learning method for prediction of cardiovascular disease using convolutional neural network. Revue d’Intelligence Artificielle, 34(5), 601–606.

Sajja, T. K., & Kalluri, H. K. (2021). Image classification using regularized convolutional neural network design with dimensionality reduction modules: RCNN–DRM. Journal of Ambient Intelligence and Humanized Computing, 12(10), 9423–9434.

Sajja, T. K., & Kalluri, H. K. (2019). Gender classification based on face images of local binary pattern using support vector machine and back propagation neural networks. Advances in Modelling and Analysis B, 62(1), 31–35.

Tejinder Kaur | Computer Science | Best Researcher Award

Published-on by Indian Scientist

Dr. Tejinder Kaur | Computer Science | Best Researcher Award

MM Institute of Computer Technology & Business Management | India

Dr. Tejinder Kaur is an accomplished academic and researcher in Computer Science and Engineering, currently serving as an Associate Professor with extensive teaching and research experience in artificial intelligence, machine learning, big data, and software engineering. She holds a Ph.D. from Thapar University and an M.Tech from Chandigarh University, with postdoctoral research in progress from a reputed public university. Her work has earned significant scholarly recognition with over 54,815 citations, an h-index of 65, and an i10-index of 148, reflecting her impactful contributions to scientific research and innovation. Dr. Kaur has authored and reviewed numerous research papers and book chapters and has guided several postgraduate theses in areas like vehicular networks, routing protocols, and wireless sensor networks. Her research interests span artificial intelligence, IoT, cybersecurity, and advanced computing systems. She has published over 277 papers, filed and been granted multiple national and international patents, and received prestigious awards, including honors from IEEE, Infosys, and SAP. A committed educator and innovator, Dr. Kaur continues to inspire through academic excellence and research leadership. Her outstanding academic record, extensive publication portfolio, and technological innovations highlight her as a dynamic professional dedicated to advancing computing and intelligent systems.

Profiles: Google Scholar | Scopus

Featured Publications

Abbott, B. P., Abbott, R., Abbott, T. D., Abernathy, M. R., Acernese, F., Ackley, K., et al. (2016). Observation of gravitational waves from a binary black hole merger. Physical Review Letters, 116(6), 061102. https://doi.org/10.1103/PhysRevLett.116.061102

Aasi, J., Abbott, B. P., Abbott, R., Abbott, T., Abernathy, M. R., Ackley, K., Adams, C., et al. (2015). Advanced LIGO. Classical and Quantum Gravity, 32(7), 074001. https://doi.org/10.1088/0264-9381/32/7/074001

Abbott, B. P., Abbott, R., Abbott, T. D., Abernathy, M. R., Acernese, F., Ackley, K., et al. (2016). GW151226: Observation of gravitational waves from a 22-solar-mass binary black hole coalescence. Physical Review Letters, 116(24), 241103. https://doi.org/10.1103/PhysRevLett.116.241103

Abbott, R., Abbott, T. D., Acernese, F., Ackley, K., Adams, C., Adhikari, N., et al. (2023). GWTC-3: Compact binary coalescences observed by LIGO and Virgo during the second part of the third observing run. Physical Review X, 13(4), 041039. https://doi.org/10.1103/PhysRevX.13.041039

Abbott, B. P., Abbott, R., Abbott, T. D., Abernathy, M. R., Acernese, F., Ackley, K., et al. (2016). Tests of general relativity with GW150914. Physical Review Letters, 116(22), 221101. https://doi.org/10.1103/PhysRevLett.116.221101

Chaitanya Kulkarni | Computer Science | Outstanding Educator Award

Published-on by Indian Scientist

Dr. Chaitanya Kulkarni | Computer Science | Outstanding Educator Award

Vidya Pratishthan’s Kamalnayan Bajaj Institute of Engineering and Technology, Baramati | India

Dr. Chaitanya Shrikant Kulkarni is a distinguished academician and Head of the Department of Artificial Intelligence and Data Science at Vidya Pratishthan’s Kamalnayan Bajaj Institute of Engineering & Technology, Baramati. With extensive experience in undergraduate and postgraduate teaching, he has contributed significantly to curriculum development, research, and innovation in AI, machine learning, and data-driven technologies. His research portfolio spans AI-powered mental health monitoring, predictive maintenance, and financial forecasting. He has authored research papers in reputed indexed journals, published books, and filed multiple patents. His role as an editor and reviewer reflects his active engagement in the academic and research community.

Professional Profile

Scopus

Education

Dr. Chaitanya Kulkarni earned his Bachelor’s degree in Computer Engineering from Shivaji University and a Master of Technology in Computer Engineering from Bharati Vidyapeeth, Pune. He later completed his doctoral studies in Computer Engineering, focusing on advancements in artificial intelligence and machine learning applications. His academic journey has been enriched through participation in various short-term training programs, quality improvement programs, and faculty development initiatives sponsored by recognized educational and professional bodies. These academic achievements have built a strong foundation for his teaching, research, and leadership in emerging technologies, allowing him to mentor students and guide research projects effectively across diverse domains.

Professional Experience

Dr. Chaitanya Kulkarni has a rich career in academia, beginning as a lecturer and advancing to senior faculty and departmental leadership roles. He has served in reputed engineering institutions, contributing to teaching at both undergraduate and postgraduate levels. His responsibilities have included curriculum design, thesis review, and mentoring research initiatives. As a Principal Investigator, he has successfully executed projects in sonar sediment classification and automated silkworm egg counting using image processing. His consultancy work with industry stakeholders has provided practical applications for academic research. Additionally, he has been actively involved in organizing academic programs and fostering interdisciplinary collaboration.

Awards and Recognition

Dr. Chaitanya Kulkarni has received recognition for his scholarly contributions, academic leadership, and innovative research. His work has been published in prominent indexed journals, and he has authored a book with an ISBN registration. He has published and filed several patents, reflecting his focus on translating research into practical solutions. His appointment as an editor for a multidisciplinary research journal and as a reviewer for prestigious international publications, including IEEE Access, highlights his expertise and professional standing. He is also a member of professional bodies, which enables him to stay connected with the broader research and technology community.

Research Skills

Dr. Chaitanya Kulkarni possesses strong research skills in artificial intelligence, machine learning, and data science, with applications in healthcare, industrial maintenance, and financial analytics. His expertise includes developing predictive models, designing intelligent systems, and applying image processing techniques for problem-solving. He has led projects that bridge the gap between theoretical research and industry requirements, ensuring practical applicability of solutions. His publications in Scopus-indexed journals and his patents demonstrate his ability to contribute original and impactful work. He is also adept at supervising postgraduate research, reviewing scholarly articles, and maintaining high standards of academic integrity in his research endeavors.

Notable Publication

Enhanced ubiquitous system architecture for securing healthcare IoT using efficient authentication and encryption
Journal: International Journal of Data Science and Analytics
Year: 2025
Citations: 2

Conclusion

Dr. Chaitanya Kulkarni’s career reflects a blend of academic excellence, research innovation, and leadership in emerging technologies. His commitment to integrating advanced AI and machine learning techniques into practical solutions has led to meaningful contributions in diverse sectors. With his extensive teaching experience, strong research background, and industry collaborations, he continues to mentor the next generation of engineers and researchers. His published works, patents, and editorial roles demonstrate his dedication to knowledge dissemination and scholarly engagement. Dr. Kulkarni remains focused on advancing technological research, fostering academic growth, and contributing to the evolving landscape of artificial intelligence and data science.

Computer Science

Published-on by Indian Scientist

Computer Science

Computer Science:

Introduction of Computer Science:

Computer Science research is at the forefront of technological advancement, exploring the principles, algorithms, and applications that underpin the digital age. This dynamic field is dedicated to solving complex problems, developing innovative software and hardware solutions, and shaping the future of information technology.

Here are five suitable subtopics in Computer Science:

  1. Artificial Intelligence (AI): AI research focuses on creating intelligent systems that can perceive, reason, learn, and interact with their environments. Subfields include machine learning, natural language processing, computer vision, and robotics.
  2. Cybersecurity and Information Assurance: Cybersecurity experts develop strategies and technologies to protect digital systems and data from unauthorized access, attacks, and breaches. Research in this area is essential to safeguarding the integrity and confidentiality of information.
  3. Data Science and Big Data: Data scientists explore methods for collecting, analyzing, and extracting valuable insights from vast datasets. This subfield plays a crucial role in business intelligence, healthcare, and scientific research.
  4. Computer Networks and Distributed Systems: Computer networking research focuses on the design, management, and optimization of communication networks. Researchers develop protocols, routing algorithms, and network architectures to enable efficient data transmission.
  5. Human-Computer Interaction (HCI): HCI research seeks to improve the interaction between humans and computers, making technology more user-friendly and accessible. Topics include user interface design, usability testing, and augmented/virtual reality interfaces.

Computer Science research continually drives innovation, influencing everything from the devices we use daily to the algorithms that power critical systems. Researchers in this field contribute to the development of cutting-edge technologies and solutions that have a profound impact on society, business, and the way we live and work.

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