Piyush Agrawal

The advancements in artificial intelligence over the last decade have opened a multitude of avenues for interdisciplinary research. Since the idea of artificial intelligence was inspired by the working of neurons in the brain, it seems pretty practical to combine the two fields and take the help of cognitive data to train AI models. Not only it will help to get a deeper understanding of the technology, but of the brain as well. In this thesis, I conduct novel experiments to integrate cognitive… Show more

The advancements in artificial intelligence over the last decade have opened a multitude of avenues for interdisciplinary research. Since the idea of artificial intelligence was inspired by the working of neurons in the brain, it seems pretty practical to combine the two fields and take the help of cognitive data to train AI models. Not only it will help to get a deeper understanding of the technology, but of the brain as well. In this thesis, I conduct novel experiments to integrate cognitive features from the Zurich Cognitive Corpus (ZuCo) (Hollenstein et al., 2018) with a transformer-based encoder model called BERT. I show how EEG and eye-tracking features from ZuCo can help to increase the performance of the NLP model. I confirm the performance increase with the help of a robustness-checking pipeline and derive a word-EEG lexicon to use in benchmarking on an external dataset that does not have any cognitive features associated with it. Further, I analyze the internal working mechanism of BERT and explore a potential method for model explainability by correlating it with a popular model-agnostic explainability framework called LIME (Ribeiro et al., 2016). Finally, I discuss the possible directions to take this research forward. Show less

Best paper award in track IOT, Image/Signal Processing (ICCI 2021)

Electromyography is used to capture electrical signals produced by skeletal muscle fibers. It is widely used in the medical field for evaluating problems in the nerves and muscles. It has been proven to provide accurate results that can even differentiate movements on a millimeter scale. New applications for EMG are being researched in numerous sectors. Uniqueness in any form of data is a boon for AI applications, and… Show more

Best paper award in track IOT, Image/Signal Processing (ICCI 2021)

Electromyography is used to capture electrical signals produced by skeletal muscle fibers. It is widely used in the medical field for evaluating problems in the nerves and muscles. It has been proven to provide accurate results that can even differentiate movements on a millimeter scale. New applications for EMG are being researched in numerous sectors. Uniqueness in any form of data is a boon for AI applications, and muscle activity generates a unique pattern of electrical signals for different movements like hand pinch or flexing. Artificial intelligence can be leveraged for the data generated by the human body for classification, prediction, and or analysis. Pairing the two together may lead to applications in diverse fields. In this paper, we experimented with applications like detecting motor neuron disease and hand gesture recognition using artificial intelligence with EMG data. We show improvement over the results of previous studies on gesture recognition and ALS detection using one-dimensional time series classification and CNNs. Show less

A review article for my app Pool.
Many college students travel in public transports or walk a long distance to reach college. This is problematic because public transports can be slow and not available everywhere as they have a specific time of arrival in their stops and they have to halt at multiple places in the city which can make it quite time consuming for passengers to reach their destinations. The goal of our project is to reduce this problem by providing a ride sharing application… Show more

A review article for my app Pool.
Many college students travel in public transports or walk a long distance to reach college. This is problematic because public transports can be slow and not available everywhere as they have a specific time of arrival in their stops and they have to halt at multiple places in the city which can make it quite time consuming for passengers to reach their destinations. The goal of our project is to reduce this problem by providing a ride sharing application for institutes. This will be mutually beneficial for the students providing a ride and the students wanting to reach their destination quickly and
cheaply as those who bring their own vehicles anyhow have to go to their homes without anyone sharing the ride with them. This will help them to earn money to at least cover their transportation or fuel cost and in-turn help provide a cheap ride to the ones in need. In this paper, we survey the work that deals with various paradigms of ride sharing and coincides with our idea for the application. Show less

This paper focuses on the tools and algorithms available today and how they can be extended or modified to construct an indoor delivery system by combining delivery drones and a network of indoor tubes.