Faculty Personal and Academic Profile

Faculty Department Computer Science and Engineering(AIML) (CSE AIML)
Faculty Name Dr. P. RAGHUNADH
Professional Email drraghunadhcse@mrec.ac.in
Personal Email drpraghunadh1506@gmail.com
Registration Number 1016-200229-221341
Teaching / Work Experience
I am pursuing my PDF(part time) in the area of Machine Learning, from Srinivas University, Karnataka. I did my Ph.D. from University of Hyderabad, and my research area is Machine Learning. As part of my Ph.D., I have worked on Nearest Neighbor Search Problem and proposed two algorithms which are pivot or reference point based algorithms for improving the speed of Nearest Neighbor Search. I have studied different dimensionality reduction techniques for processing high-dimensional data and to find hidden patterns in the data. In order to improve the pattern recognition task, we need to reduce the dimensionality to a sufficient and comfortably small. We have proposed two variants for IRP-K-means algorithm for improving clustering accuracy in the reduced feature space, and demonstrated this by conducting experiments on various low-dimensional and high-dimensional data sets. In another chapter of my thesis, we have proposed a projection matrix generation by using a small sample from the given data. We have tested this proposed method by varying reduced dimension, and also by varying the sample size taken for constructing the projection matrix. I have worked in a collaboration project with ANURAG, DRDO and University of Hyderabad. As part of this research project, we have developed an algorithm for Quilt PCA, which addresses mainly two issues: one is selecting then number of cluster centroids (K), second one is selecting initial K centroids from the given data itself. I was a Project Fellow at ANURAG DRDO/ University of Hyderabad from 2017-2018 (1.5 Yrs) Worked as an Assistant Professor in CSE Dept. Ramappa Engineering College, Warangal from 2008-2010 (2yrs). Worked as an Assistant Professor in CSE Dept. Vivekananda Institute of Technology & Science (VITS II) Karimnagar from 2006-2007 (1 Yr). I was a Teaching Assistant to Prof. Vineeth Padmanabhan Nair, School of Computer and Information Sciences, University of Hyderabad in 2013 (6 months). I was a Senior Research Fellow in School of Computer & Information Sciences, University of Hyderabad, from 2012-2016. I was a Junior Research Fellow in School of Computer & Information Sciences, University of Hyderabad, from 2010-2012. Publications: 1. Y Narsimhulu, Raghunadh Pasunuri, Vadlamudi China Venkaiah, "Nearest Neighbors via a Hybrid Approach in Large Datasets : A Speed Up" Third International Conference on Computational Intelligence and Data Engineering (ICCIDE-2020) 8-9 August 2020. Vasavi College of Engineering, Hyderabad. LNDECT, Springer 2. Y Narasimhulu, Ashok Suthar, Raghunadh Pasunuri and Vadlamudi China Venkaiah, "CKD-Tree: An improved KD-Tree Construction Algorithm Using Coresets for k-NN based Classification" Proceedings of ISIC 2021: International Semantic Intelligence Conference, February 25–27, 2021, New Delhi, India CEUR-WS.org/Vol-2786/Paper28.pdf 3. RAGHUNADH PASUNURI, VADLAMUDI CHINA VENKAIAH , "A Computationally Efficient Data-Dependent Projection for Dimensionality Reduction" In : Bansal J., Gupta M., Sharma H., Agarwal B. (eds) Communication and Intelligent Systems. ICCIS 2019. Lecture Notes in Networks and Systems, vol 120. Springer, Singapore. pp. 339-352. (indexed by SCOPUS) 4. Pasunuri, Raghunadh, Vadlamudi China Venkaiah, and Amit Srivastava. "Clustering High-Dimensional Data: A Reduction-Level Fusion of PCA and Random Projection." Recent Developments in Machine Learning and Data Analytics. Springer, Singapore, 2019. 479-487. 5. Pasunuri, Raghunadh, Vadlamudi China Venkaiah, and Bhaskar Dhariyal. "Ascending and descending order of random projections: comparative analysis of high-dimensional data clustering." Harmony Search and Nature Inspired Optimization Algorithms. Springer, Singapore, 2019. 133-142. 6. Pasunuri, Raghunadh, and Vadlamudi China Venkaiah. "An optimal proximity method for nearest neighbor search in high dimensional data." 2016 2nd International Conference on Contemporary Computing and Informatics (IC3I). IEEE, 2016. 7. RAGHUNADH PASUNURI, “A Novel Algorithm for Nearest Neighbor Search in High Dimensional Spaces”, IJAER, Vl 10, No. 86, pp. 247-253, 2015 (SCOPUS) PATENTS: 1. An efficient MRF Models for Detection of Brain Abnormality Based on MRI Images, Publication Date: 11/12/2020 , Application No. 202041052252. Professional Body Memberships: 2. Life Member of ISTE 3. SDIWC 4. CSTA 5. EAI 6. IAENG FDPs/Workshops attended: AY 2020-21: 1. One week FDP on Big Data Analytics using Hadoop Framework Tools, organized by Department of Computer Science and Engineering, School of Engineering, Presidency University, Bengaluru, held from 3-8 August, 2020. 2. ONE WEEK STTP ON DEEP LEARNING TECHNIQUES FOR ELECTRONIC HEALTH RECORD ANALYSIS” at Malla Reddy Engineering College for Women, Hyderabad, during 16th to 21st November, 2020. 3. Faculty Development Program on Machine Learning for Intelligent Systems conducted by the Department of Computer Science and Engineering from 01-12-2020 to 05-12-2020. 4. Five days online Faculty Development Program on Internet of Things and its Applications organized by Centre for Continuing Education, National Institute of Technology, Warangal in association with School of Computer Science and Engineering, REVA University, Bengaluru from 21-12-2020 to 25-12-2020. 5. ONE WEEK FDP on Data Science in Real Time Applications, conducted by Dept. of IT, Sreenidhi Institute of Science & Technology, Ghatkesar, Hyderabad, from 23-28 November, 2020. 6. Five Day International Workshop on "Building Data-Driven Solutions Using Data Analytics with ML and DL Algorithms" held virtually during 24-28 June 2021, by Dept. of CSE CBIT (A), Hyderabad. 7. Forty hour Online FDP on Deep Learning Algorithms Implementation in Cloud Technology, conducted by E & ICT Academy NIT Warangal & MREC (A) Hyderabad during 1-10 July 2021. 8. Six Day National level Workshop on "REACTS JS" from 5-10 July, 2021, organized by Dept. CSE, Teegala Krishna Reddy Engineering College, Hyderabad. 9. Six Day National level Online FDP on "Multi Technology" from 28th June -3 July, 2021, organized by Dept. CSE, Teegala Krishna Reddy Engineering College, Hyderabad.
Other Achievements
Qualified for UGC NET (Lectureship) in the subject Computer Science & Applications in 2012. Qualified AP SET (Lectureship) in the subject Computer Science & Applications in 2012.
Teaching Achievements
Current Designation Assoc Professor
Area of Specialization Machine Learning / Dimensionality Reduction or Subspace Learning
Joining Date 20-07-2020
Total Experience in this Institution 4 Years
Total Experience in other Institutions 12 Years
Specialized Skills
Research Methodology , LATEX Document Writing , MATLAB, Python Programming
UG Qualifications B.Tech Graduation Year, University
2005,
JNTU Hyderabad
PG Qualifications M.Tech Graduation Year, University
2009, JNTU Hyderabad
PhD Qualifications Completed Graduation Year, University
2020, UNIVERSITY OF HYDERABAD (HCU)