Anupam Sharma is a PhD student at department of Computer Science & Engineering at the Indian Institute of Technology, Gandhinagar (IITGN). He previously completed his Bachelors in Technology from Central Institute of Technology Assam and worked as a Project Engineer at the Cyber Defense Center at Wipro Ltd.
His research interests include deep learning, representation learning, meta-learning and its application in Brain-Computer Interface (BCI) domain.
News
Evaluating Fast Adaptability of Neural Networks for Brain-Computer Interface | March 2024
Work with Dr. Krishna Miyapuram | To appear at IJCNN, IEEE World Congress on Computational Intelligence '24 | Arxiv
Electroencephalography (EEG) classification is a versatile and portable technique for building non-invasive Brain-computer Interfaces (BCI). However, the classifiers that decode cognitive states from EEG brain data perform poorly when tested on newer domains, such as tasks or individuals absent during model training. Researchers have recently used complex strategies like Model-agnostic meta-learning (MAML) for domain adaptation. Nevertheless, there is a need for an evaluation strategy to evaluate the fast adaptability of the models, as this characteristic is essential for real-life BCI applications for quick calibration. We used motor movement and imaginary signals as input to Convolutional Neural Networks (CNN) based classifier for the experiments. Datasets with EEG signals typically have fewer examples and higher time resolution. Even though batch-normalization is preferred for Convolutional Neural Networks (CNN), we empirically show that layer-normalization can improve the adaptability of CNN-based EEG classifiers with not more than ten fine-tuning steps. In summary, the present work (i) proposes a simple strategy to evaluate fast adaptability, and (ii) empirically demonstrate fast adaptability across individuals as well as across tasks with simple transfer learning as compared to MAML approach.
IIT Gandhinagar Director's PhD Fellowship | Feb 2024
Received The Director's PhD Fellowship at IIT GN. Extremely thankful to all mentors for making this recognition possible.
“Director’s PhD Fellowship” at the Indian Institute of Technology (IIT) Gandhinagar is intended to encourage top-quality IIT Gandhinagar students to join the PhD programme of the Institute right after completing their degree (BTech/MSc/MA/MTech) at the Institute. Having excelled in their academics at IIT Gandhinagar, such students could transition to their PhD programme with ease and complete the PhD work faster than the other students.
Joined CSE at IITGN as a M.Tech. Student | July 2022
Joined Wipro Ltd as a Project Engineer | Oct 2019