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Program Coordinator

Program Coordinator

Dr. G Uday Kiran

Associate Professor | Program Coordinator | Member IQAC
udaykiran.goru@bvrit.ac.in

Ph.D.: Data Mining, Jawaharlal Nehru Technical University, Hyderabad, 2022
PG: M.Tech (Neural Networks), Jawaharlal Nehru Technical University, Kakinada, 2010,
UG: B.Tech (CSE), Jawaharlal Nehru Technical University, Hyderabad, 2006.

Teaching Experience: 14 Years 11 Months
Research Experience: 
Industry Experience:

Contact Number: +91 9885172564
BVRITN Employee ID: 381
JNTUH Registration ID: 90150404-115955
AICTE Registration ID: 1-2898618269

Dr. G. Uday Kiran received Ph.D. (Data Mining) from Jawaharlal Nehru Technological University Hyderabad M.Tech (Neural Networks) from Jawaharlal Nehru Technological University Kakinada. Currently, he is working as an Associate Professor in the Department of CSE (Artificial Intelligence and Machine Learning), B V Raju Institute of Technology, and has 14 Years of Teaching Experience.  

  1. Deep Learning
  2. Computer Vision and Image Processing
  3. Speech and Natural Language Processing
  4. Data Mining and Analytics
  5. Theory of Computation and Compilers
  1. Qualified in Faculty Eligibility Test (FET) in Dec 2010 conducted by JNTU Hyderabad.
  2. Completed Two Courses (Speech Signal Processing and Natural Language Processing) in IIIT Hyderabad (PGSSP Monsoon 2013).
  3. Recognized as NPTEL Star – Enthusiasts for July-December 2019. 
  1. Predicting Parkinson’s Disease using Extreme Learning Measure and Principal Component Analysis based Mini SOM, Annals of the Romanian Society for Cell Biology, Vol. 25, Issue 4, pp. 16099-16111, Scopus Indexed, 2021.
  2. Disease Detection using Enhanced K-Means Clustering and Davies-Bouldin Index in Big Data, Journal of Green Engineering, Vol. 10, Issue 12, pp. 13089-13106, Scopus Indexed, 2020.
  3. Overlap Clustering Technique based on the Improved Hierarchical Agglomerative Clustering, Journal of Green Engineering, Vol. 10, Issue 11, pp. 11594–11607, Scopus Indexed, 2020.
  4. A Hybrid Clustering Algorithm to Reduce Dimensions and Optimal Selection of K-Centroids for Healthcare Datasets, Journal of Applied Science and Computations, Vol. 7, Issue 10, pp. 110-119, 2020.
  5. Advanced XML Data Search in Web 2.0, International Journal of Engineering Research & Technology, Vol. 2, Issue 10, pp. 329-332, 2013.
  6. Performance-based Graphics Engine for Smartphones, International Journal of Engineering Research & Technology, Vol. 2, Issue 9, pp. 2933-2936, 2013.
  7. A Novel Approach for Enhancing Direct Hashing and Pruning for Association Rule Mining, Journal of Computer Technology & Applications, Vol. 3, Issue 1, pp. 1-8, 2012. 
  1. Deep learning Support Vector Machine Application Management for Prediction Binding Elements, 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2022, pp. 2493–2497, 2022.
  2. Predicting Heart Diseases using Hierarchical Clustering and Gaussian Mixture Model, International Conference on Advanced Mathematics and Computer Science, 2021.
S.NoCourseDurationMonth & YearGrade
1Python for Data Science4 WeeksApril, 2022Silver
2NBA Accreditation and Teaching – Learning in Engineering (NATE)12 WeeksDecember, 2021Silver
3Data Science for Engineers8 WeeksDecember, 2019Elite
4Accreditation and Outcome-based Learning8 WeeksDecember, 2019Silver
5Natural Language Processing12 WeeksDecember, 2019Pass
6Machine Learning for Engineering and Science Applications12 WeeksApril, 2019Pass
7Introduction to Automata, Languages and Computation12 WeeksApril, 2019Elite
8Programming, Data Structures and Algorithms using Python8 WeeksApril, 2019Pass
9Design and Analysis of Algorithms8 WeeksApril, 2019Elite
10Introduction to Machine Learning8 WeeksNovember, 2018Pass
11Programming, Data Structures and Algorithms using Python8 WeeksNovember, 2018Pass
  1. Half Week FDP for “Python for Data Science”.
  2. One and Half Week FDP for “NBA Accreditation and Teaching – Learning in Engineering (NATE)”.
  3. One Week FDP for “Data Science for Engineers”.
  4. One Week FDP for “Accreditation and Outcome-based Learning”.
  5. One and Half Week FDP for “Natural Language Processing”.
  6. One and Half Week FDP for “Machine Learning for Engineering and Science Applications”.
  7. One and Half Week FDP for “Introduction to Automata, Languages and Computation”.
  8. One Week FDP for “Introduction to Machine Learning”.
  9. Extensive Vision AI 4 Program, The School of AI.
  10. One Week FDP on “Amazon Web Services” from 22-08-2022 to 27-08-2022.
  11. Half-Week FDP on “Data Analysis Using Statistical Learning Techniques” from 21-03-2022 to 26-03-2022.

Industry Certifications:

  • Extensive Vision AI 4 Program

Coursera:

  1. Deep Learning Specialization offered by Deeplearning.ai
  2. Machine Learning Specialization offered by the University of Washington
  3. AWS Fundamentals Offered by AWS

EdX

  • Deep Learning with Python and PyTorch

IIT Bombay EdX Course:

  • LaTeX for Students, Engineers, and Scientists

Funding Proposal:

  • Member of a Funding Project “Virtual Assistant for Mobile Devices using Voice and Gesture Technologies” Technologies, Funded by ITRA, New Delhi.
  • Member – IQAC Institute Committee
  • Member – Board of Studies – CSE
  • CSE Department NBA Coordinator
  • CSE Department NAAC Coordinator
  • CSE Department Curriculum Coordinator