Fascinated by how AI can help us analyse the world’s data, I enjoy finding creative ways to piece machine learning with geospatial data! My work has been recognized with Best Poster Award at the BioSTAR AI Symposium 2024, and have contributed to publications in venues such as PLOS Digital Health and Springer workshops.
Beyond research, I love attending social and networking events that spark fresh perspectives and collaborations!
This study presents an agile and optimal machine learning approach for detecting inter-ictal states from electroencephalogram (EEG) signals, aiming to enhance epilepsy diagnosis and management. By leveraging advanced feature extraction techniques and a robust classification algorithm, the proposed method achieves high accuracy in identifying inter-ictal patterns, which are crucial for understanding seizure dynamics. The model’s performance is validated on a comprehensive EEG dataset, demonstrating its potential for real-world clinical applications. This research contributes to the growing field of AI-driven healthcare solutions, offering a promising tool for clinicians in the fight against epilepsy.
A novel blockchain framework is proposed in this paper to facilitate agro financing for farmers in South India. The framework leverages the inherent properties of blockchain technology, such as decentralization, transparency, and immutability, to create a secure and efficient platform for managing agricultural loans and transactions. By utilizing smart contracts, the framework automates the loan approval process, ensuring that farmers receive timely access to funds while minimizing the risk of fraud and default. The proposed solution aims to empower farmers by providing them with greater financial inclusion and reducing their dependence on traditional lending institutions.
Gait impairments are prevalent in various neurological and musculoskeletal conditions, significantly affecting individuals’ mobility and quality of life. This study presents a novel approach to classify simulated gait impairments using privacy-preserving explainable artificial intelligence (XAI) techniques applied to mobile phone video data. By leveraging advanced machine learning algorithms, the proposed method accurately identifies different types of gait abnormalities while ensuring user privacy through federated learning and differential privacy mechanisms. The explainability aspect of the model provides insights into the decision-making process, enhancing trust and interpretability for clinicians and patients alike. The results demonstrate the potential of this approach in remote health monitoring and rehabilitation, paving the way for accessible and effective gait analysis solutions.
An interactive choropleth dashboard with D3.js to visualize global DALY rates.
A dedicated platform that integrates event creation, discovery, and venue booking in one cohesive ecosystem.
A RAG style biomedical question-answering system leveraging PubMedBERT, fine-tuned on the BC5CDR dataset, achieving an F1 Score of 62% and an Exact Match score of 48% in extracting chemical-disease relationships
Addresses data scarcity challenges in Electroencephalograpy (EEG) research and enhance the performance of classification models through the incorporation of synthetic data.
A NYTimes mining pipeline that processed 100+ articles to synthesizing insights through clusters by word cloud visualizations
A web app that has a signup/login system that randomly displays one of my favorite movies and allows user to provide reviews and ratings, while also viewing others’ reviews.
Gained insights from leading experts in the field of geosciences and AI, engaging in workshop and discussions spanning from cyberinfrastructure, digital twins for community resilience, wildfire spread, flood prediction, extreme heat adaptation, and novel drones for environment monitoring.
Team photo after obtaining the initial results of breeding sites detected in Ethiopia for the tech enabled arm for the larval source management.
In process of dataset creation for larvae detection AI!
While being the Secretary at the official outreach club of the BMI department at Emory, we introduced the working of a pulse oxometer to a wide group of audience ranging from elementary students to adults at the Atlanta Science Festival 2025.
Awarded 3rd prize for the poster “Characterising simulated Gait disorders using mobile videos” at the BioSTAR AI Symposium, organized by The Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University. The project involved developing a computer vision pipeline to analyze gait patterns from smartphone videos, enabling early detection of movement disorders. Presented findings to a panel of academic and industry experts, highlighting the potential impact of AI-driven tools in biomedical research and healthcare.
Participated in community outreach programs organized by Rotaract Club of Manipal, focusing on education and health awareness for underprivileged children in the local community. Engaged in activities such as tutoring, organizing health camps, and distributing educational materials to promote better learning opportunities and well-being among children.
MIT Manipal director Commander (Dr) Anil Rana observed World Earth Day by planting saplings around MIT Manipal campus with Rotaract Club of Manipal’s volunteers.
2023-2025 Master of Science in Computer ScienceCGPA: 3.72 out of 4Extracurricular Activities:
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Bachelor of Technology in Computer Science & EngineeringCGPA: 9.04 out of 10Extracurricular Activities:
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