Resume of Raja Sarath Kumar Boddu

E-Mail: acz5ev@r.postjobfree.com

Phone No. +91-986*******

RAJA SARATH KUMAR BODDU, Ph.D.

Principal, Lenora College of Engineering

Rampachodavaram, E. G. District, A.P.

Fellow, IE(India),

Senior Member, IEEE,

Senior Member, ACM,

Prof. Raja Boddu (http://www.rajaboddu.com) highly motivated, self-driven, moderate educator and administrator with 17 years experience in Engineering Education. At present, he is working as a Professor, CSE Department and Principal at Lenora College of Engineering (http://www.lce.ac.in). 19 PG dissertations supervised, 27 peer-reviewed publications published and 3 International Conferences addressed.

Prof. Raja Boddu is having memberships of high profile program committees, review boards, as a Fellow of IEI, as a Life Member of IETE, ISCA and CSI, as a Senior Member of IEEE and ACM and as a Reviewer for IEI-Springer Series-B Journals, SAI Organization journals and Springer’s Journal of Supercomputing.

1. Personal Details

Name : Raja Sarath Kumar Boddu

Nationality : Indian

Academic Position : Professor and Principal, Lenora College of

Engineering, Rampachodavaram, East

Godavari District, Andhra Pradesh, India.

2. Academic Qualifications

Ph. D Computer Science and AUCE, Andhra University 2013

Systems Engineering Visakhapatnam

M. Tech Computer Science and AUCE, Andhra University 2001

Systems Engineering Visakhapatnam

B.E Civil Engineering AUCE, Andhra University 1995

Visakhapatnam

3. Academic Experience

Professor & Principal Lenora College of Engineering 2008-Present

Professor Lenora College of Engineering 2006-2008

Associate Professor Lenora College of Engineering 2002-2006

4. Countries Visited on Research Work

Countries visited Malaysia - Presented research paper at IACSIT & IEEE International Conference held at Kuala Lumpur.

U.S.A - Presented research paper at World Congress in Computer Science, Computer Engineering and Applied Computing International Conference held at Las Vegas

Qatar – Presented research paper at Engineering Leaders conference at Doha

Singapore – Presented research paper at ICIEE held at Nanyang University, Singapore

5. Research Publications

Sample publications during last five years

Journals

[1] Raja Sarath Kumar Boddu and Venkata Ramana Bendi “Cyber Crime and Security, a Global Vulnerable Coercion: Obstacles and Remedies” published in International Journal of Information and electronics Engineering (IJIEE),

[2]. A. Sunil Kumar, M. S. Prasad Babu and B. Raja Sarath Kumar “Implementation Hybrid System based on Content Boosted Collaborative Filtering Algorithm” Global Journal of Computational Intelligence Research. ISSN 2249-0000 Volume 3, Number 1 (2013), pp. 11-20

[3]. M.Basava raju, M. S. Prasad Babu and B.Raja Sarath Kumar “Implementation of Simple Bayesian Classifier Algorithm On Model Based Collaborative Filtering” has accepted for publication in “International Journal of Artificial Intelligence and Computational Research” (Jan-June 2013)

[4]. M.S. Prasad Babu, Boddu Raja Sarath Kumar and Mentey Sriraj “Item-based Collaborative Filtering Recommender System”International journal of Academic Research for Multidisciplinary(JIARM), Vol 2(3) 2013, ISSN:2320-5083.

[5]. Maddali Surendra Prasad Babu and Boddu Raja Sarath Kumar, “An Implementation of the user-based Collaborative Filtering Algorithm”, International Journal of Computer Science and Information Technologies (IJCSIT), vol.2(3), 2011, ISSN 0975-9646,1283-1286.

[6]. Boddu Raja Sarath Kumar and Maddali Surendra Prasad Babu, “An Implementation of Content-Boosted Collaborative Filtering Algorithm", International Journal of Engineering Science and Technology (IJEST), ISSN: 0975-5462, Volume-3, Number-4 of April, 2011, pp 2865-2874.

Peer Reviewed Conferences

[7] Venkata Ramana Bendi and Raja Sarath Kumar Boddu “Decision Tree Algorithms for Liver Disease Diagnosis: A comparative Study” International Conference on Information and Electronics Engineering (ICIEE 2017), held at Singapore during February 22-24, 2017.

[8] Raja Sarath Kumar Boddu, “An Integrated Assessment Approach to different Collaborative Filtering Algorithms” IEEE BigData-2016 conference, held at Washington DC, USA, 5-8, December 2016, Year: 2016, Pages: 3954 - 3956, DOI: 10.1109/BigData.2016.7841073,IEEE

[9] B. Raja Sarath Kumar and B. John Ratnam “Evaluation of Collaborative Filtering Personalized Recommendation Algorithms” ICAI’12, International Conference on Artificial Intelligence, held on July 16-19, 2012, WORLDCOMP-2012, Las Vegas, USA.

6. Scientific Recognition and Merit Awards

AWARDS & ACHIEVEMENTS :

1. Recipient of “ISCA Best Poster Presentation Award” in 2007 at 94th Indian Science Congress, Annamalai University, Chidambaram, Tamilnadu.

2. Recipient of “Vignan Prathibha Puraskar” in 2007 at Andhra University Engineering College

7. Professional Organizations Membership

Senior Member 90629097 IEEE

Life Member F-211861 IETE

Senior Member 5025968 ACM

Life Member L 12524 Indian Science Congress Association,(ISCA)

Life Member 00101258 Computer Society of India. (CSI)

Fellow F-1183768 Institute of Engineers (India)

8. Professional Development during last five years

Coordinator for ISTE 2 week ISTE workshop on “Analog Electronics” National Mission on Education through ICT under MHRD Govt. of India from 04th June 14th June 2013

Coordinator for ISTE 2 week ISTE workshop on “Database Management Systems” National Mission on Education through ICT under MHRD Govt. of India from 21st May to 31st May 2013

Patron for “ROBOTRYST-2013” technical paper presentation session held on 08-10-2012

Coordinator for ISTE 2 week ISTE workshop on “Introduction to Research Methodology” National Mission on Education through ICT under MHRD Govt. of India from 25th June 4th July 2012

Patron for “ISME MACHE-2K12” technical paper presentation session held from 14-09-2012 to 15-09-2012

Coordinator for ISTE 2 week ISTE workshop on “Introduction to Research Methodology” National Mission on Education through ICT under MHRD Govt. of India from 11th -21st December -2012

2 Days ISTE Workshop on “Aakash for Education” under MHRD Govt. of India from10th -11th November-2012.

Chair for one day workshop on “Research Oriented issues in cryptography and network security” on 20-12-2011.

Chair for one day workshop on “Concepts & Research Trends in Data Mining” on 27-12-2010

1. Prof. G. V.R. Prasad Raju

acz5ev@r.postjobfree.com

Principal, College of Engineering

JNTU, Kakinada

2. Dr. B V Ramana,

Professor & HOD, Dept. of IT,

Aditya Institute of Technology and Management

Tekkali - 532 201

email: acz5ev@r.postjobfree.com

3.Mr. V.Vijay Kumar, HOD, Department of Computer Science Engineering,

Lenora College of Engineering,

Rampachodavaram, acz5ev@r.postjobfree.com

https://in.linkedin.com/in/rajaboddu

https://facebook.com/rajaskboddu

https://twitter.com/rajaskboddu

http://websarath.blogspot.in/

Flat No. 107; Mahalakshmi Towers,

Balaji Nagar, Visakhapatnam 530003.

Andhra Pradesh, India.

Abstract of the doctoral thesis entitled

Some studies on Personalized Recommendation Algorithms with Collaborative Filtering

An explosive growth of enormous information on the web, created the universe as global village. It is a big problem for getting the relevant information from the internet. Personalized Recommendation Systems may be used to get relevant information from the internet. Recommender System is to generate significant recommendations to a collection of users for items or products that might interest them. This is a powerful new technology for extracting additional value for a business from its user databases and help users find items they want to buy from a business. Real world examples for the recommender systems are amazon.com (for books) and netflix.com (for movies). Collaborative filtering is one of the important techniques in personalized recommendation systems and predicting the interests of a user by collecting preference information from many users.

The Collaborative Filtering models can also hold with the situations where user profiles are supplied by observing user interactions with a system and dealt with user profiles that are obtained by requesting users to rate information items. Broadly, they are classified into (i) Memory-based Collaborative Filtering techniques such as the user-based, item-based and neighborhood-based Collaborative filtering algorithm; (ii) Model-based Collaborative Filtering techniques such as Bayesian belief nets, Clustering, Singular Value Decomposition (SVD) and MDP-based Collaborative filtering; and (iii) Hybrid Collaborative filtering techniques such as the Content-boosted Collaborative Filtering and Personality Diagnosis.

In this thesis, a comprehensive study has been involved to process huge data sets and uses the popular collaborative filtering algorithms as the basis for proposed modifications. In the beginning, the problem of inaccurate finding and falling recommendation quality of the prediction will bring forth. Then, the users’ interest words will be collected to build the user interest model. Finally, modified algorithms have been proposed, they are 1) User based Collaborative Filtering based on Pearson Correlation which is Memory-based technique, 2) Singular Value Decomposition based on Composite Prototypes which is Model-based technique and 3) Hybrid Collaborative Filtering based on the predictions-probabilistic prototype.

The experimentation is done with MovieLens dataset which is available for research purpose provided by the GroupLens Research Project agency at the University of Minnesota. The measured Mean Absolute Error (MAE) of the proposed model is compared with available models from literature and finally the performance analysis is done based on parameter MAE. The comparative analysis and comprehensive study shows that Content-boosted Collaborative Filtering algorithm puts forward for better performance among the other comparative algorithms and hence, feasible solutions will be obtained using Content-boosted Collaborative Filtering recommendation methods instead of other recommendation methods.

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