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Education has never been just about earning degrees for me, it has been a journey of curiosity, exploration, and learning how mathematics, computation, and neuroscience connect to solve real-world problems. From building a strong foundation in mathematical thinking to exploring machine learning, artificial intelligence, and neuromorphic computing, every step has shaped the way I approach research and innovation. I believe learning is most meaningful when it inspires creativity, critical thinking, and the courage to work on ideas that can create a real impact.
ABV-Indian Institute of Information Technology and Management Gwalior
ABV-Indian Institute of Information Technology and Management Gwalior
M.S Artificial Intelligence and Data Science
2025-2027
At ABV-IIITM Gwalior, I am advancing my interests in Artificial Intelligence and Data Science with a focus on intelligent systems, machine learning, and emerging computational paradigms. This journey reflects my transition from theoretical mathematics to applied AI research, where I aim to explore innovative ideas in neuromorphic computing, brain-inspired intelligence, and real-world problem solving through technology.
My undergraduate journey at the University of Delhi built the mathematical foundation that shaped my analytical and problem-solving mindset. Through subjects ranging from pure mathematics to applied concepts, I developed a deep interest in computational thinking, modeling, and research-oriented learning. This phase strengthened my curiosity toward interdisciplinary fields where mathematics meets artificial intelligence and neuroscience.
Certifications
Certifications
Understanding the Brain: The Neurobiology of Everyday Life
Understanding the Brain: The Neurobiology of Everyday Life
Currently pursuing this course to gain a deeper understanding of how the human brain shapes thoughts, emotions, perception, decision-making, and everyday behavior. The course explores the biological and neurological foundations behind human experiences, helping me connect concepts from neuroscience with cognition, psychology, and computational thinking. Through this ongoing learning journey, I am developing a broader perspective on how neural systems function, adapt, and influence human intelligence in real-world situations.
This course has further strengthened my interest in interdisciplinary research at the intersection of neuroscience, artificial intelligence, and brain-inspired computing. It continuously inspires me to explore how biological intelligence can influence the development of intelligent computational systems, neuromorphic architectures, and future AI models. As someone coming from a strong mathematical and analytical background, studying neurobiology allows me to approach the brain not only as a biological system but also as a complex information-processing network that can inspire innovative technological solutions.
Instructor - Prof. Peggy Mason
Date - April 2026 – Present
Deep Learning With PyTorch
Deep Learning With PyTorch
Completed IBM's Deep Learning with PyTorch course, gaining hands-on experience in building and training neural networks, implementing CNNs, optimizing deep learning models, and using PyTorch for practical machine learning applications. The course strengthened my foundation in modern AI and deep learning methodologies.
Instructor - Rav Ahuja
Date - April 2026 – May 2026
Computational Neuroscience
Computational Neuroscience
Through this course, I explored how neuroscience and computation intersect to model neural systems and understand brain dynamics. It deepened my curiosity about neural coding, intelligent systems, and neuromorphic computing, while giving me insight into how mathematical modeling and AI can help decode complex brain processes.
Instructor - Rajesh P. N. Rao, Adrienne Fairhall
Date - Nov 2025 – Jan 2026
Introduction to Cognitive Psychology and Neuropsychology
Introduction to Cognitive Psychology and Neuropsychology
This course introduced me to the fascinating relationship between human cognition, behavior, memory, perception, and brain function. It strengthened my interest in understanding how mathematical and computational approaches can contribute to neuroscience and cognitive research, inspiring me to further explore brain-inspired intelligence and learning systems.
Instructor - Dr. Giulia Mangiaracina
Date - Jan 2026 – March 2026
Linear Algebra for Machine Learning
Linear Algebra for Machine Learning
This training program strengthened my understanding of the mathematical foundations behind modern machine learning and artificial intelligence. Through concepts such as vector spaces, matrices, eigenvalues, decompositions, and optimization techniques, I gained deeper insight into how linear algebra powers neural networks, data representation, and computational models. The program further enhanced my analytical thinking and reinforced the importance of mathematics in building intelligent systems and advanced AI research.
Organiser - LDRP Institute of Technology & Research, GTU
Date - 01 Dec, 2025 - 05 Dec, 2025
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