Dr. Venkateswara Rao Kagita

Assistant Professor

Department of Computer Science And Engineering

National Institute of Technology, Warangal - 506004, Telangana, INDIA

: venkat.kagita@nitw.ac.in

: 6281746931

Interests: Recommender Systems; Machine Learning; Deep Learning; Data Mining;

Venkateswara Rao Kagita is an Assistant Professor at NIT Warangal in the department of CSE. He
has obtained Ph.D from university of Hyderabad. His research interests are Data Mining and
Machine Learning, with a specific focus on machine learning techniques for recommender
systems. His research works have been published in various reputed journals and conference
proceedings such as Pattern Recognition, Pattern Recognition Letters, Information Sciences,
Expert Systems with Applications, Journal of Approximate Reasoning, AAI, PRICAI, etc. He
has also delivered various guest lectures in several International and National workshops at IIT
Hyderabad, Central University of Rajasthan etc.

Course Taught Previously

Data Science

Machine Learning 

Data Mining 

Design and Analysis of Algorithms

Operating Systems

Software Project Management

Unified Modeling Language

Distributed Computing 

Publications

 Journals

2019

Pattern Recognition, Vikas Kumar, Arun K Pujari, Venkateswara Rao Kagita, and Vineet Padmanabhan, Group Preserving Label Embedding for Multi-label classification, 90, pages 23–34.

2019

Pattern Recognition Letters, Venkateswara Rao Kagita, Arun K Pujari, Vineet Padmanabhan, and Vikas Kumar, Skyline Recommendation with Uncertain Preferences, submitted the revised version.

2018

Expert Systems with Applications, Vikas Kumar, Arun K Pujari, Vineet Padmanabhan, Sandeep Kumar Sahu, and Venkateswara Rao Kagita, Multi-label Classification Using Hierarchical Embedding, 91, pages 263–269.

2017

Information Sciences, Venkateswara Rao Kagita, Arun K Pujari, Vineet Padmanabhan, Sandeep Kumar Sahu, and Vikas Kumar, Conformal Recommender System, 405, pages 157–174.

2017

Journal of Approximate Reasoning, Venkateswara Rao Kagita, Arun K Pujari, Vineet Padmanabhan, Bounds on Skyline Probability for Databases with Uncertain Preferences, 80, pages 199-213.

2017

Information Sciences, Vikas Kumar, Arun K Pujari, Sandeep Kumar Sahu, Venkateswara Rao Kagita, and Vineet Padmanabhan, Collaborative Filtering Using Multiple Binary MMMFs, 380, pages 1–11.

2017

Pattern Recognition Letters, Vikas Kumar, Arun K Pujari, Sandeep Kumar Sahu, Venkateswara Rao Kagita, and Vineet Padmanabhan, Proximal Maximum Margin Matrix Factorization for Collaborative Filtering, 86, pages 62–67.

2015

Information Sciences, Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Virtual user approach for group recommender systems using precedence relations, 294, pages 15-30.

2015

Information Sciences, Arun K. Pujari, Venkateswara Rao Kagita, Anubhuti Garg, Vineet Padmanabhan, Efficient computation for probabilistic skyline over uncertain preferences, 324, pages 146-162.

 

 

Conferences

2018

PACIE, Venkateswara Rao Kagita, Arun K Pujari and Vineet Padmanabhan, Justified Group Recommender Systems, pages 479-488.

2016

PRICAI, Venkateswara Rao Kagita, Arun K Pujari, Vineet Padmanabhan, Vikas Kumar, and Sandeep Kumar Sahu, Threshold-based Direct Computation of Skyline Objects for Database with Uncertain Preferences, pages 193–205.

2015

CALDAM, Arun K. Pujari, Venkateswara Rao Kagita, Anubhuti Garg, Vineet Padmanabhan, Bi-directional Search for Skyline Probability, pages 250-261.

2015

NCVPRIPG, Sandeep Kumar Sahu, Arun K Pujari, Vikas Kumar, Venkateswara Rao Kagita, and Vineet Padmanabhan, Greedy Partitioning based Tree Structured Multiclass SVM for Odia OCR, pages 1–4.

2015

ICIT, Sandeep Kumar Sahu, Arun K Pujari, Venkateswara Rao Kagita, Vikas Kumar, and Vineet Padmanabhan, GP-SVM: Tree Structured Multiclass SVM with Greedy Partitioning, pages 142–147.

2015

ICIT, Venkateswara Rao Kagita, Krishna Charan Meka, Vineet Padmanabhan, A Novel Social-Choice Strategy for Group Modeling in Recommender Systems, pages 153-158.

2015

ICAPR, T.V.R.Himabindu, Vineet Padmanabhan, Venkateswara Rao Kagita, Arun K. Pujari, Recommender system algorithms: A comparative analysis based on monotonicity, pages 1-6.

2014

SMC, Sowmini Devi, Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Collaborative filtering by PSO-based MMMF, pages 569-574.

2013

2013 AAI, Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Group Recommender Systems: A Virtual User Approach Based on Precedence Mining, pages 434-440.

2013

PReMI, Venkateswara Rao Kagita, Vineet Padmanabhan, Arun K. Pujari, Precedence Mining in Group Recommender Systems, pages 701-707.

PHDs Supervised

 

Workshops/Conferences

 

Projects

 

Awards and Honors

 

Additional Responsibility