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Program Coordinator

 

Dr. G Uday Kiran
Associate Professor
Member, IQAC
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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

About Program Coordinator

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.  

Fields of Specialization/Areas of Interest

  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

Achievements

  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. 

Publications:

  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. 

Conferences:

  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.

NPTEL Courses 

S.No Course Duration Month & Year Grade
1 Python for Data Science 4 Weeks April, 2022 Silver
2 NBA Accreditation and Teaching - Learning in Engineering (NATE) 12 Weeks December, 2021 Silver
3 Data Science for Engineers 8 Weeks December, 2019 Elite
4 Accreditation and Outcome-based Learning 8 Weeks December, 2019 Silver
5 Natural Language Processing 12 Weeks December, 2019 Pass
6 Machine Learning for Engineering and Science Applications 12 Weeks April, 2019 Pass
7 Introduction to Automata, Languages and Computation 12 Weeks April, 2019 Elite
8 Programming, Data Structures and Algorithms using Python 8 Weeks April, 2019 Pass
9 Design and Analysis of Algorithms 8 Weeks April, 2019 Elite
10 Introduction to Machine Learning 8 Weeks November, 2018 Pass
11 Programming, Data Structures and Algorithms using Python 8 Weeks November, 2018 Pass

FDPs/ Workshops/Seminars/Training Programs:

  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.

Certifications:

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.

Roles and Responsibilities:

  • Member – IQAC Institute Committee
  • Member – Board of Studies – CSE
  • CSE Department NBA Coordinator
  • CSE Department NAAC Coordinator
  • CSE Department Curriculum Coordinator

 Our Campuses