Nikesh Bajaj is a Research Associate working with Dr Fu Siong Ng at Myocardial Function group in National Heart & Lung Institute (NHLI).
Nikesh has a PhD in Machine Learning & Signal Processing from Queen Mary University of London in a joint program with University of Genoa. His PhD work was focused on Predictive Analysis of Auditory Attention from Physiological Signals. After PhD, he worked as a postdoctoral research fellow at University of East London on a project funded by InnovateUK. The project was focused on deception detection in conversations using linguistic analysis. The majority of his work is focused around signal processing, machine learning and deeplearning.
Nikesh is also a mentor and a consultant (alpha testers) at Deeplearning.ai for courses & specializations offered at Coursera, such as NLP, GANs, Tensorflow, MLOps. Nikesh has a few python libraries, such as spkit, phyaat, pylfsr.
et al., 2021, Analysis of Factors Affecting the Auditory Attention of Non-native Speakers in e-Learning Environments, Electronic Journal of E-learning, Vol:19, ISSN:1479-4403, Pages:159-169
et al., 2020, Automatic and tunable algorithm for EEG artifact removal using wavelet decomposition with applications in predictive modeling during auditory tasks, Biomedical Signal Processing and Control, Vol:55, ISSN:1746-8094, Pages:101624-101624