Mr. Dasari-Siva Krishna-Deep Learning-Young Scientist Award 

GMR Institute of Technology-India 

Author Profile

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Early Academic Pursuits

Mr. Dasari-Siva Krishna embarked on his academic journey with a strong foundation laid during his schooling years at Venus Public School, Rajam, where he secured an impressive 77% in his S.S.C. examinations. His dedication and diligence continued through his intermediate education at Sri Veda Gayathri Junior College, Rajam, where he achieved remarkable distinction with a score of 91% in MPC.

His passion for technology and computing led him to pursue a B.Tech. in Information Technology at GMR Institute of Technology(A), Rajam, where he demonstrated his aptitude by securing 68%. This period laid the groundwork for his future academic and professional pursuits, fostering a deep interest in the field of computer science.

Professional Endeavors

After completing his undergraduate studies, Mr. Dasari-Siva Krishna ventured into the realm of academia, starting as an Assistant Professor in the Department of CSE at Sai Ganapathi Engineering College, Visakhapatnam, where he honed his teaching skills and gained valuable experience. He then transitioned to his current role as Assistant Professor at GMR Institute of Technology(A), Rajam, where he has been contributing significantly since November 2016.

Contributions and Research Focus

Throughout his academic career,Mr. Dasari-Siva Krishna has demonstrated a keen interest in research and academia. His pursuit of knowledge led him to pursue an M.Tech. in Computer Science & Technology at Andhra University College of Engineering(A), where he secured an impressive CGPA of 8.45. Subsequently, he embarked on the journey towards a Ph.D. in Computer Science & Engineering, under the esteemed guidance of Prof. P.V.G.D. Prasad Reddy at Andhra University College of Engineering(A).

His research interests span a wide array of topics within the realm of computer science, with a focus on areas such as machine learning, artificial intelligence, and data science. His doctoral research, which is currently in the submission phase, promises to contribute valuable insights to the field, further advancing our understanding and applications of cutting-edge technologies.

Accolades and Recognition

Mr. Dasari-Siva Krishna academic prowess has been duly recognized through various accolades and achievements. He has been ratified as an Assistant Professor by JNTU Kakinada, a testament to his expertise and qualifications in the field of computer science. Additionally, he has qualified in prestigious examinations such as UGC-NET and GATE multiple times, showcasing his depth of knowledge and commitment to academic excellence. His exceptional performance also earned him the PG GATE Fellowship from the Ministry of HRD, further underscoring his academic achievements.

Impact and Influence

As an educator and researcher, Mr. Dasari-Siva Krishna has had a significant impact on his students and peers alike. Through his engaging teaching style and mentorship, he has inspired countless students to pursue their passions in computer science and technology. His contributions to research have the potential to drive innovation and advancements in the field, shaping the future of technology and society.

In a remarkable achievement, Dasari Siva Krishna has been honored with the prestigious Deep Learning Award.

Legacy and Future Contributions

Looking ahead, Mr. Dasari-Siva Krishna is poised to continue making meaningful contributions to academia and research. His ongoing efforts in completing his Ph.D. signify his dedication to advancing knowledge and pushing the boundaries of scientific inquiry. As he continues to mentor the next generation of computer scientists and researchers, his legacy of excellence and innovation will endure, leaving an indelible mark on the field of computer science for years to come.

Citations

• Citations      63
• h-index          3
• i10-index       2

Notable Publication

• Novel private cloud architecture: A three tier approach to deploy private cloud using virtual machine manager
• A stacking ensemble approach for identification of informative tweets on twitter data
• Feature extraction based ensemble stacking for combating cyber threat in phishing URLs
• Disaster tweet classification: A majority voting approach using machine learning algorithms
• A deep parallel hybrid fusion model for disaster tweet classification on Twitter data