Dr. Radhakrishnan G

Associate Professor

Department of CSE

CMR Institute of Technology,  Bengaluru.

E-mail ID: radhakrishnan.g@cmrit.ac.in

Profile

Mr. Radhakrishnan G joined CMR Institute of Technology in July 2021. He has over 22 years of industry  experience at organizations like  Motorola India Electronics Ltd and Hewlett Packard India Software Operations and 13 years of teaching experience including 10 years at Amrita Vishwa Vidyapeetham, Bengaluru.

Educational Qualification

B. Tech:  Electrical Engineering,  National Institute of Technology  (formerly REC), Calicut, 1984

M. E.:  Automation (Computer Science), Indian Institute of Science, Bengaluru, 1986

PhD:  Amrita Vishwa Vidyapeetham, Bengaluru, 2022

Areas of Interest in Teaching

Data Structures and Algorithms, Design and Analysis of Algorithms, Machine Learning, Data warehouse and Data Mining, Soft Computing, Software Project Management, Software Engineering, Computer Programming.

Areas of Interest in Research

Machine Learning, Robot vision, Algorithms, Natural Language Processing

Recent Publications

1. Gopalapillai, R., Prabhu, S.M. (2023). Prediction of COVID-19 Pandemic Spread Using Graph Neural Networks. In: Kumar, S., Sharma, H., Balachandran, K., Kim, J.H., Bansal, J.C. (eds) Third Congress on Intelligent Systems. CIS 2022. Lecture Notes in Networks and Systems, vol 613. Springer, Singapore. https://doi.org/10.1007/978-981-19-9379-4_5

2. Gopalapillai, R. (2022)  "RGB-D Scene Classification using an Ensemble of Convolutional Neural Networks with Softmax Aggregation," 2nd Asian Conference on Innovation in Technology (ASIANCON), 2022, pp. 1-5, doi: 10.1109/ASIANCON55314.2022.9908897. 

3. Gopalapillai, Radhakrishnan, Deepa Gupta, Mohammed Zakariah, and Yousef A. Alotaibi. 2021. "Convolution-Based Encoding of Depth Images for Transfer Learning in RGB-D Scene Classification" Sensors 21, no. 23: 7950. https://doi.org/10.3390/s21237950 

4. Laxmi P., Gupta D., Gopalapillai R., Amudha J., Sharma K. (2021) A Scalable Multi-disease Modeled CDSS Based on Bayesian Network Approach for Commonly Occurring Diseases with a NLP-Based GUI. In: Paprzycki M., Thampi S.M., Mitra S., Trajkovic L., El-Alfy ES.M. (eds) Intelligent Systems, Technologies and Applications. Advances in Intelligent Systems and Computing, vol 1353. Springer, Singapore. https://doi.org/10.1007/978-981-16-0730-1_11

5. Laxmi P., Gupta D., Radhakrishnan G., Amudha J., Sharma K. (2021) Automatic Multi-disease Diagnosis and Prescription System Using Bayesian Network Approach for Clinical Decision Making. In: Chiplunkar N., Fukao T. (eds) Advances in Artificial Intelligence and Data Engineering. Advances in Intelligent Systems and Computing, vol 1133. Springer, Singapore. https://doi.org/10.1007/978-981-15-3514-7_31

6. Rao S., Gopalapillai R. (2020) Effective Spam Image Classification Using CNN and Transfer Learning. In: Smys S., Tavares J., Balas V., Iliyasu A. (eds) Computational Vision and Bio-Inspired Computing. ICCVBIC 2019. Advances in Intelligent Systems and Computing, vol 1108. Springer, Cham. https://doi.org/10.1007/978-3-030-37218-7_145

7. Radhakrishnan Gopalapillai, Deepa Gupta, "Object Boundary Identification using Two-phase Incremental Clustering", Third International Conference on Computing and Network Communications (CoCoNet’19), Trivandrum, December 2019.

8. Radhakrishnan Gopalapillai, Deepa Gupta, Sudarshan, T. S. B, "Robotic sensor data analysis using stream data mining techniques", International Journal of Engineering & Technology, Vol. 7, No. 4 (2018), pp. 3967-3973

9. Sunil Angadi, Radhakrishnan Gopalapillai, "Mining Network Stream Data for Self Learning Networks", 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT), July 10-12, 2018, Bengaluru, India.

10. Manju Venugopalan, Nalayini G, Radhakrishnan G, Deepa Gupta, "Rating Prediction Model for Reviews Using a Novel Weighted Textual Feature Method", 5th International Conference on Advanced Computing, Networking and Informaics (ICACNI 2017),1-3 Jun 2017, Goa, India

11. Sumi Mathai, Deepa Gupta, Radhakrishnan G, "Iterative Concept Based Clustering of Indian Court Judgments", 2nd International Conference on Computational Intelligence and Informatics, ICCII 2017, 25-27 September 2017, Hyderabad, India.

12. Radhakrishnan Gopalapillai , Deepa Gupta, Sudarshan TSB, “Pattern Identification of Robotic Environments using Machine Learning Techniques”, 7th International Conference on Advances in Computing & Communications, ICACC-2017, 22-24 August 2017, Cochin, India

13. Reshma M, Priyanka C Nair, Radhakrishnan Gopalapillai, Deepa Gupta, Sudarshan TSB, “Multi-view Robotic Time Series Data Clustering and Analysis using Data Mining Techniques”, The second International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS'15), December 16-19, Trivandrum, India.

14. Radhakrishnan G, Deepa Gupta, S Sindhuula, Shrey Khokhawat, Sudarshan TSB, "Experimentation and Analysis of Time Series Data from Multi-path Robotic Environment", 2015 IEEE International Conference on Electronics, Computing and Communication Technologies (IEEE CONECCT 2015), 10-11 July 2015, Bangalore.

Other Responsibilities

     Head, Centre of Excellence in Natural Language Processing

Professional Memberships

ACM Professional Member

IEEE Senior Member

Scopus Link: https://www.scopus.com/authid/detail.uri?authorId=57196260935

Google scholar: https://scholar.google.com/citations?user=uJSUnSkAAAAJ&hl=en&oi=sra

Patents

None