Portrait of Dr. Muralikrishna SN

Dr. Muralikrishna SN

Associate Professor, School of Computer Engineering
Manipal Institute of Technology, Manipal, India

Computer Vision Medical Image Processing Machine Learning Natural Language Processing

Personal Information

Welcome! Explore my work across computer vision, medical image processing, machine learning, and NLP. Use the tabs above to navigate.

Education

  • Postdoctoral study at MIP Lab, Chosun University, South Korea.
  • Ph.D. in Computer Science and Engineering, Mar 2021, Manipal University
  • M.Tech in Computer Science and Technology, July 2008, University of Mysore
  • M.Sc. in Computer Science, July 2005, Mangalore University
  • B.Sc. in Physics, Mathematics and Computer Science, July 2003, Mangalore University

Areas of Interest

Computer Vision, Medical Image Processing, Machine Learning, and Natural Language Processing

Research Groups

Current funded initiatives spanning Indian language technologies and AI-driven healthcare.

Principal Investigator, Institute Level MeitY, Govt. of India

Centre of Indian Language Data (COIL-D)

COIL-D is a consortium-mode funded project led by IIT Patna with MIT Manipal and other national partners. The project develops language resources for Human Language Technology, including standards, guidelines, benchmarks, and resources for Machine Translation and NLP tools.

  • MIT Manipal contributes parallel corpora for Dravidian languages: Kannada, Tamil, Malayalam, and Telugu.
  • The broader language-technology ecosystem connects with open multilingual translation resources such as AI4Bharat's IndicTrans2.
  • COIL-D datasets are also visible through the coild-aikosh collection on Hugging Face.
COIL-D MIT project note Datasets IndicTrans2
Co-Principal Investigator Ministry of Education, Govt. of India

AI Centre of Excellence in Healthcare at MAHE

The AI Centre of Excellence in Healthcare at MAHE is part of a Government of India-backed national AI-CoE effort. Phase 2 is aligned with TANUH, the Translational AI for Networked Universal Healthcare Foundation hosted at IISc Bengaluru.

  • MAHE works with partners including KMC Manipal, AIIMS Delhi, IIT Delhi, IISc, and IIT Madras.
  • The programme focuses on clinically useful AI tools for healthcare, including deep-learning models for coronary artery disease.
  • TANUH develops point-of-care AI diagnostics and decision-support tools for high-burden non-communicable diseases.
MAHE AI-CoE note TANUH IISc announcement

Teaching

Information about teaching responsibilities and courses.

Collaborations

My supervisors

Prof. Bumshik Lee

Prof. Bumshik Lee

Associate Professor, Korea Institute of Energy Technology (KENTECH, South Korea)

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Dr. Balachandra

Dr. Balachandra

Professor, School of Computer Engineering, MIT–MAHE

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Dr. U. Dinesh Acharya

Dr. U. Dinesh Acharya

Professor, School of Computer Engineering, MIT–MAHE

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Mentor(s)

Dr. Ashalatha Nayak

Dr. Ashalatha Nayak

Professor, School of Computer Engineering, MIT–MAHE

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Collaborators

Prof. Asif Ekbal

Prof. Asif Ekbal

Professor, School of AI & Data Science, IIT Jodhpur (formerly IIT Patna)

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Dr. Manjunath K. N.

Dr. Manjunath K. N.

Associate Professor, MIT–MAHE

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Dr. Ganesh Paramasivam

Dr. Ganesh Paramasivam

Associate Professor, Cardiology, KMC–MAHE

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Dr. Ganesh Bhat

Dr. Ganesh Bhat

Professor & Head, Gastroenterology & Hepatology, KMC–MAHE

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Prof. Neha S. Gandhi

Prof. Neha S. Gandhi

Professor, Biomolecular Modelling & Simulations, MAHE

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Dr. Ashwath Rao B

Dr. Ashwath Rao B

Assistant Professor (Selection Grade), School of Computer Engineering, MIT–MAHE

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Dr. Raghavendra Ganiga

Dr. Raghavendra Ganiga

Associate Professor, School of Computer Engineering, MIT–MAHE

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Dr. Raghurama Holla

Dr. Raghurama Holla

Assistant Professor & School of Computer Engineering & MIT–MAHE

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My Ph.D. scholars

Ms. Sangeetha

Assistant Professor Senior, School of Computer Engineering, MIT–MAHE

2021-

Ms. Mahima

TMA Pai Scholar, School of Computer Engineering, MIT–MAHE

2024-

Ms. Neetha Janis Tellis

TMA Pai Scholar, School of Computer Engineering, MIT–MAHE

2024-

Journal Publications

  • P. Chakraborty, S. Sunderrajan, S. N. Ameen, A. Nayak, and Muralikrishna S. N, "A Unified Framework for Age-Invariant Face Recognition Using GANs and Vision Transformers," IEEE Open Journal of the Computer Society, vol. 7, pp. 889-900, 2026. DOI: 10.1109/OJCS.2026.3688643.
  • T. S. Sangeetha, S. N. Muralikrishna, A. M. Naik, and A. P. Parameswaran, "Evaluation of LSTM, GRU, and ANFIS Models for Ankle Angle and Ankle Moment Prediction Using Biomechanical Data," IEEE Access, vol. 13, pp. 137364–137383, 2025. DOI: 10.1109/ACCESS.2025.3591227.
  • A. V. Vegesna, M. S. Narayanarao, K. Bhamidipati, and T. Indiran, "Q-Learning-Based Multivariate Nonlinear Model Predictive Controller: Experimental Validation on Batch Reactor for Temperature Trajectory Tracking," ACS Omega, vol. 10, no. 26, pp. 28362–28371, 2025. DOI: 10.1021/acsomega.5c03482.
  • S. N. Muralikrishna, R. Ganiga, R. K. Raghavendra, and K. Raghurama Holla, "Medical Named Entity Recognition for Enhanced Electronic Health Record Maintenance," International Journal of Advanced Computer Science and Applications, vol. 16, no. 3, Jan. 2025. DOI: 10.14569/IJACSA.2025.0160383.
  • S. N. Muralikrishna, R. Holla, N. Harivinod, and R. Ganiga, "Cross-Lingual Short-Text Semantic Similarity for Kannada–English Language Pair," Computers, vol. 13, no. 9, p. 236, 2024.
  • S. R. Aithal, S. N. Muralikrishna, R. Ganiga, A. Rao, and G. Hegde, "KannadaLex: A lexical database with psycholinguistic information," ACM Transactions on Asian and Low-Resource Language Information Processing, vol. 23, no. 2, pp. 1-22, Jun. 2024. doi: 10.1145/3670688
  • R. Ganiga, S. N. Muralikrishna, W. Choi, and S. Pan, "ResNet1D-Based Personal Identification with Multi-Session Surface Electromyography for Electronic Health Record Integration," Sensors, vol. 24, no. 10, pp. 3140, 2024.
  • B. S. Baliga, R. Medepalli, and S. N. Muralikrishna, "Securing textual and image data on cloud using searchable encryption," International Journal of Information Technology, vol. 13, no. 3, pp. 1111-1117, 2021.
  • K. K. Todi, S. N. Muralikrishna, and B. A. Rao, "Sentiment classification of review data using sentence significance score optimisation," International Journal of Data Analysis Techniques and Strategies, vol. 13, no. 1-2, pp. 59-71, 2021.
  • S. N. Muralikrishna, B. Muniyal, U. D. Acharya, and R. Holla, "Enhanced human action recognition using fusion of skeletal joint dynamics and structural features," Journal of Robotics, vol. 2020, pp. 1-16, 2020.
  • S. N. Muralikrishna, B. Muniyal, and U. D. Acharya, "Adaptive cluster based model for fast video background subtraction," International Journal of Advanced Computer Science and Applications, vol. 10, no. 12, pp. 689-696, 2019.
  • S. Angle, B. A. Rao, and S. N. Muralikrishna, "Kannada morpheme segmentation using machine learning," International Journal of Engineering & Technology, vol. 7, no. 31, pp. 45-49, 2018.
  • S. Atmakuri, B. Shahi, B. A. Rao, and S. N. Muralikrishna, "A comparison of features for POS tagging in Kannada," International Journal of Engineering & Technology, vol. 7, no. 4, pp. 2418-2421, 2018.
  • K. V. Prema, N. M. Agarwal, M. Krishna, and V. Agarwal, "Stock market prediction using neuro-genetic model," Indian Journal of Science and Technology, vol. 8, no. 35, pp. 1-9, 2015.

Conference Publications

  • S. N. Muralikrishna, V. S. Shrishma Rao, P. Shetty, and A. D. Manezes, "Attention Guided Medical Image Captioning Using ResNet–LSTM," in Proc. 1st Engineering Data Analytics and Management Conference (EAMCON), 2025, pp. 322-331. DOI: 10.2991/978-94-6463-978-0_29.
  • V. S. Shrishma Rao, S. N. Muralikrishna, P. Shetty, and A. D. Manezes, "From Pixels to Words: ResNet–LSTM Based Image Captioning with Greedy and Beam Search," in Proc. 1st Engineering Data Analytics and Management Conference (EAMCON), 2025, pp. 293-304. DOI: 10.2991/978-94-6463-978-0_27.
  • P. Shetty, V. S. Shrishma Rao, and S. N. Muralikrishna, "Assessing Bias in Large Language Models: A Comparative Study of ChatGPT, Gemini, and Claude," in Proc. IEEE Int. Conf. Modeling, Simulation and Intelligent Computing (MoSICom), 2024, pp. 133–137.
  • A. V. Jha, S. R. R. Bommu, V. S. Shrishma Rao, and S. Muralikrishna, "Soft Actor-Critic Algorithm in High-Dimensional Continuous Control Tasks," in Proc. IEEE Int. Conf. Modeling, Simulation and Intelligent Computing (MoSICom), 2024, pp. 535–540.
  • P. P. Teggi, N. Harivinod, and S. N. Muralikrishna, "Assessing Variations in Water Quality Parameters: An Analysis of Variance Study for Environmental Monitoring," in Proc. 8th IEEE Int. Conf. Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER), 2024, pp. 84–89.
  • S. Hebbar, S. N. Muralikrishna, M. Supriya, V. G. Narendra, L. Sobha, and others, "Named Entity Recognition Using BERT Model for Kannada Language," in Proc. 2023 Int. Conf. Recent Advances in Information Technology for Sustainable Development (ICRAIS), pp. 212-216, 2023.
  • D. Verma and S. N. Muralikrishna, "Semantic similarity between short paragraphs using Deep Learning," in Proc. 2020 IEEE Int. Conf. Electronics, Computing and Communication Technologies (CONECCT), pp. 1-5, 2020.
  • F. Faruqi and S. N. Muralikrishna, "Eigen-Based offline handwritten digit recognition using Multi-layer perceptron," Manipal J. Sci. Tech., vol. 2, no. 2, pp. 40-45, 2017.
  • S. N. Muralikrishna, B. Muniyal, and D. U. Acharya, "A survey of image descriptors," 2017.
  • B. A. Rao, C. Murali Krishna, and A. Nayak, "Document Preparation For Engineering Education: A Case Study using LaTeX," 2016.
  • B. A. Rao, S. N. Muralikrishna, and A. Nayak, "Developing a dependency treebank for Kannada," Research Cell: An International Journal of Engineering Sciences, vol. 15, pp. 5-7, 2015.
  • S. N. Muralikrishna, M. Ajith, and K. B. Ajitha Shenoy, "MSB Based New Hybrid Image Compression Technique for Wireless Transmission," Advances in Computing and Information Technology, pp. 749-756, Springer Berlin Heidelberg, 2013.
  • V. Gupta and S. N. MuraliKrishna, "A Fast and Novel Approach for 4D (3D+ T) Cardiac MR Image Segmentation," Computer Vision and Information Technology: Advances and Applications, pp. 257, 2010.

Events

Details about upcoming events and conferences.

Announcements

Recruitment

COIL-D Project Recruitment Updates

COIL-D and the AI-NLP-ML Research Group announce language staff opportunities, freelancer engagement, and temporary technical research positions for the project. Candidates can follow the official COIL-D career page and LinkedIn updates for current openings, application links, and deadlines.

COIL-D MIT Recruitment LinkedIn updates