Radhika Shrimankar is a Ph.D. Candidate and Junior Research Fellow at the Amrita Mind Brain Centre, Amrita Vishwa Vidyapeetham, Amritapuri campus, working on the DST-funded project “Multi-Scale Brain Function India–Italy Network of Excellence.” He holds a Master of Technology (M.Tech.) degree in Computer Science and Engineering from the International Institute of Information Technology (IIIT) Bhubaneswar and has one year of industry experience at QEandA Technology CoE, Cognizant Technology Solutions Private Limited.
His research focuses on the development of biophysically inspired computational models of the brain, with an emphasis on understanding the role of interconnected neural circuits in brain function. He is particularly interested in investigating the somatosensory thalamocortical system and its role in motor control, including the movement of robotic arms. Through computational neuroscience and brain-inspired modeling, his work seeks to bridge fundamental neuroscience research with computer simulations and neurorobotic applications.
Computational Neuroscience, Reinforcement Learning, Machine Learning, Robotics
Conference Paper
Year: 2022
SOFTWARE DEFECT PREDICTION: A COMPARATIVE ANALYSIS OF MACHINE LEARNING TECHNIQUES
Radhika Shrimankar; Madhusree Kuanr; Jayashree Piri; Niranjan Panda, “Software Defect Prediction: A Comparative Analysis of Machine Learning Techniques,”2022 International Conference on Machine Learning, Computer Systems and Security (MLCSS), Bhubaneswar, India, 2022, pp. 38–47, doi: 10.1109/MLCSS57186.2022.00016.
Publisher: 2022 International Conference on Machine Learning, Computer Systems and Security (MLCSS)