Dharmapuri Siri | Deep Learning Award | Best Researcher Award

Posted on by ScienceFather

Dr. Dharmapuri Siri | Deep Learning Award | Best Researcher Award

Dr. Dharmapuri Siri, Gokaraju Rangaraju Institute of Engineering and Technology, India

Based on Dr. Dharmapuri Siri’s resume, here is a conclusion on his suitability for the Research for Best Researcher Award:

Publication profile

Scopus

Career Experience

Dr. Dharmapuri Siri has extensive teaching experience spanning over 11 years across various institutions, including TRR Engineering College, TRR College of Engineering, and Malla Reddy Engineering College for Women. His role as an Assistant Professor in Computer Science and Engineering highlights a solid foundation in academic and practical knowledge.

Educational Background

Dr. Siri’s educational qualifications are robust, with a Ph.D. in Computer Science and Engineering from JJT University, an M.Tech from JNTU Hyderabad, and a B.Tech from JNTU Hyderabad. His academic background demonstrates a strong commitment to his field and a continual pursuit of advanced knowledge.

Research 

Dr. Siri has made significant contributions to research, particularly in the areas of software quality, machine learning, and image analysis. His journal publications and conference presentations reflect a broad range of research interests, from bug prediction models to sentiment analysis and cancer diagnosis. Notable papers include his work in IEEE Access and various webE3S conferences.

Workshops and Training

He has actively participated in multiple workshops and refresher courses, focusing on cloud computing, innovative teaching methods, and problem-solving techniques. This engagement in continuous professional development underscores his dedication to staying current in his field.

Patent and Projects

Dr. Siri holds a patent for a “Vehicle with Smart Biometric Device,” showcasing his ability to apply theoretical knowledge to practical solutions. His Ph.D. thesis on “Bug Prediction Model For Software Quality Using Machine Learning Techniques” further emphasizes his research focus and expertise.

Conclusion

Dr. Dharmapuri Siri is a strong candidate for the Research for Best Researcher Award due to his comprehensive academic background, extensive teaching experience, substantial research contributions, and practical innovations. His work in improving software quality through machine learning and his active involvement in professional development make him a suitable candidate for this accolade.

 

Publications Top Notes

Analyzing Public Sentiment on the Amazon Website: A GSK-Based Double Path Transformer Network Approach for Sentiment Analysis

Automated System for Bird Species Identification Using CNN

Dharmapuri Siri | Deep Learning | Best Researcher Award

Posted on by ScienceFather

Dharmapuri Siri | Deep Learning | Best Researcher Award

Assistant Prof Dharmapuri Siri, Gokaraju Rangaraju Institute of Engineering and Technology, india.

Dr. D. Siri is a dedicated academic professional with over 11 years of experience in teaching and research in the field of Computer Science and Engineering. She has served as an Assistant Professor in various prestigious institutions, including TRR Engineering College and Malla Reddy Engineering College for Women. Her work is focused on the intersection of software quality, machine learning, and data analysis.

Profile:

orcid

Education📚:

Dr. D. Siri holds a Ph.D. in Computer Science and Engineering from JJT University, obtained in 2022. She completed her M.Tech in Computer Science and Engineering from JNTU Hyderabad in 2010, and her B.Tech in Information Technology from the same university in 2006.

Professional Experience👩‍🏫:

Dr. Siri began her teaching career in 2008 as an Assistant Professor in the Department of Information Technology at TRR Engineering College, where she worked until 2013. She then transitioned to the Department of Computer Science and Engineering at TRR College of Engineering, continuing her role until 2017. From 2017 to 2019, she served as an Assistant Professor at Malla Reddy Engineering College for Women. Throughout her career, she has gained extensive experience in teaching core subjects like C, C++, Java, DBMS, Software Testing Methodologies, and Software Engineering.

Research Interests🔍:

Dr. Siri’s research interests are primarily focused on software quality improvement, bug prediction using machine learning techniques, and the application of deep learning methods to various domains such as sentiment analysis, medical imaging, and automated systems. Her work in these areas has been presented at numerous national and international conferences.

Awards and Recognitions🏆:

Dr. Siri’s innovation and contributions to the field have been recognized through a published patent titled “A Vehicle with Smart Biometric Device” (Application No. 201841019142-A), which was published in The Patent Office Journal No. 22/2018 on June 1, 2018.

Research Contributions 📚:

Dr. Siri’s research is primarily centered around software quality, machine learning, and data analysis. Her notable works include studies on bug prediction models, software engineering methodologies, and the application of machine learning techniques in software quality improvement. Her Ph.D. thesis on “Bug Prediction Model for Software Quality Using Machine Learning Techniques” reflects her deep commitment to enhancing software reliability and performance.

Publication:

Publications 📝:
Dr. Siri has published several research articles in reputed journals. Here are some of her notable publications:

  1. A Study on Bug Prediction in Determining The Software Quality | History Research Journal | 2019.
  2. Machine Learning Techniques on Historical Software Bugs for Prediction of Software Bugs | Think India Journal | 2019.
  3. Analyzing Public Sentiment on the Amazon Website: A GSK-Based Double Path Transformer Network Approach for Sentiment Analysis | IEEE Access | 2024.
  4. Segmentation Using the IC2T Model and Classification of Diabetic Retinopathy Using the Rock Hyrax Swarm-Based Coordination Attention Mechanism | IEEE Access | 2024.