Dr. Radhika K R
Associate Professor
Qualification : BE, M.Tech , Ph.D
Teaching Experience : 17 Years
Research Experience : 7 Years
Industry Experience : 1 Years
Specialization : Computer Science and Engineering
Worked as Trainee Executive
- IEEE
- MIE
- Technical:Data structure
- OOPS
- Operating Systems
- Unix System Programming
- Database Management System
- Advanced DBMS
- Advanced Computer Architecture
- Artificial Intelligence and Machine Learning
- Data Mining
- Deep Learning for Visual Computing
- IoT applications with Blockchain Techniques
- Huawai Developers Mobile App Development Foundation course
- Frontiers in Machine Intelligence and Soft Computing
- Time Table Co-ordinator
- Department PBL(Project Based Learning) Co-ordinator
- Department Project Coordinator
- Department Internship coordinator
- Department Seminar Coordinator
- Institute level PBL coordinator
- PG-NBA criteria 3 coordinator
| Journal Name | Journal Type | Volume Number | Issue Number | ISSN ISBN | Paper Title |
|---|---|---|---|---|---|
| International Journal of Scientific & Engineering Research | Research Journal | 6 | 11 | ISSN 2229-5518 | Insights to Existing Techniques of Subspace Clustering in High-Dimensional Data |
| International Journal of Engineering & Technology | International | 7 | 4 | doi: 10.14419/ijet.v7i4.15229 | Framework for novel subspace clustering using search optimization methodology |
| Conference Name | Venue | Date | Paper Title |
|---|---|---|---|
| 2016 International Conference on Computational Techniques in Information and Communication Technologies (ICCTICT) | GuruGobinda Indraprastha University, Delhi | 2016-09-15 | EDSC: Efficient Document Subspace Clustering Technique for H i g h -Dimensional Data |
| 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017 | Manipal University, Manipal | 2017-01-16 | RMSC: Robust Modeling of Subspace Clustering for High Dimensional Data |
| Lecture Notes in Networks and Systems | ICT , Goa | 2020-07-05 | A Computer Vision Based Approach for Subspace Clustering and Lagrange Multiplier Optimization in High-Dimensional Data |
- Machine Learning by Stanford University - Coursera