Research Papers
Published Research in Advanced Materials and Affective Computing
My research journey reflects a deep interest in exploring how science and technology can drive sustainable and intelligent innovation. Through projects spanning materials science and artificial intelligence, I have worked on topics such as magnetocaloric refrigeration and EEG-based emotion classification. These experiences allowed me to contribute to interdisciplinary research, combining physics, engineering, and data science, while publishing and presenting work recognized by institutions like IEEE and IIT-Delhi. Each project strengthened my ability to translate complex ideas into practical, impactful solutions for real-world challenges.
Magnetocaloric Potential of Heusler Alloys’ Mumbai, Mysuru, India
“Magnetocaloric Potential of Heusler Alloys”, carried out in Mumbai and Mysuru under the mentorship of Professor Devaraj Ranjith (MIT Mysuru). The project focused on developing a prototype that demonstrated the magnetocaloric properties of Heusler alloys, exploring their potential to power advanced, energy-efficient solid-state cooling systems as an alternative to conventional refrigeration methods. Building on this work, I authored a research paper titled “Renewable Powered Solid-State Refrigeration: A Magnetocaloric Approach Using Heusler Alloys for Energy-Efficient Cooling Systems”, which was presented at the International Conference on Emerging Trends in Industry 4.0 Technologies and subsequently published by IEEE Xplore. The project earned multiple accolades, including the British Gold Crest Award, the Be-Visioneers Mercedes-Benz Fellowship (joining a global community of 1000 eco-innovators), and recognition at the IRIS National Fair Finals 2024–25, where the prototype was selected among the top 50 innovative ideas sponsored by Broadcom Inc. This work not only validated the scientific and creative impact of the project but also positioned it as a step forward in sustainable, next-generation cooling technologies.
Electroencephalography-based Emotion Classification
Mumbai; New Delhi, India
From February to November 2023, I collaborated on a research project titled “Electroencephalography-based Emotion Classification” across Mumbai and New Delhi, working under the guidance of Professor C. M. Sharma from IIT-Delhi. As part of this project, I co-authored a bibliometric analysis on the application of deep learning techniques for EEG-based emotion classification, contributing to the understanding of neural signal analysis and its potential in affective computing. Our findings were published on the Qeios platform, providing a valuable resource for researchers exploring the intersection of neuroscience and artificial intelligence. Through a comprehensive review of existing literature and trends, the project highlighted key insights in emotion recognition, demonstrating how deep learning can advance the accuracy and applicability of EEG-based systems. This work not only strengthened my expertise in neural data analysis and machine learning but also contributed meaningfully to the growing field of emotion-aware technologies.