News and Blogs
I am thrilled to announce that I will be presenting one of my papers at the International Symposium at Kathmandu University, Nepal, on 18th April 2025. The symposium focuses on Artificial Intelligence for disaster mitigation in the Himalayan region. I will be attending alongside my mentor, Dr. Amitansu Pattanaik.
Qubit and Qutrit based Quantum Inspired Neural Network: Enhancing Stock Market Prediction
After 8 months of hard work, my paper has been accepted in Nature [Journal: Quantum Information]. This research presents a novel qubit and qutrit-based quantum neural network that demonstrated superior performance with significantly faster training times compared to classical bit neural networks.
Key Achievements:
These findings highlight the potential of quantum-inspired methods in complex prediction tasks.
On 20 December, I was awarded a certificate of reviewing, recognizing my contributions to the academic community through insightful peer reviews.
On 15 October, I was awarded a Raman research Award, recognizing my contributions to the manuscript Advancements in Heart Disease Diagnosis: Harnessing Predictive Modeling Techniques for Cardiovascular Health Management.
I had the privilege of attending the "Residential Training Program on Low Carbon Pathways for Industrial Sectors," held at the Anil Agarwal Environment Training Institute (AAETI) in Nimli, Rajasthan, from July 02-05, 2024. This program focused on the need for industrial sectors to adopt low-carbon pathways to help India meet its 2030 carbon emission reduction target.
The training program aimed to provide participants with the necessary knowledge and skills to enable industries, regulators, and professionals to meet their sustainability goals. The program covered critical decarbonization strategies, including circularity, resource efficiency, carbon capture, utilization and storage (CCUS), and adopting cleaner fuels.
Topics discussed included the future of carbon capture, cleaner fuels like gas, biomass, and hydrogen, the role of circularity in reducing greenhouse gas emissions, energy-efficient technologies, and the role of renewable energy to reduce dependence on coal power. The course was particularly insightful for understanding sector-specific measures to reduce emissions and the potential of international and domestic climate finance for cleaner technologies.
This training helped me gain valuable insights into creating low-carbon pathways for large-scale industries, and it contributed to my overall research work as a Research Fellow at DRDO .
I am honored to have participated in the "Training Programme on Chemical & Industrial Safety: Disaster Risk Reduction," organized by FICCI in collaboration with the National Institute of Disaster Management (NIDM), Ministry of Home Affairs, Government of India. The event took place on June 06-07, 2024, at FICCI, New Delhi. This training focused on disaster risk reduction and the role of AI in enhancing safety measures.
We explored key aspects of chemical and industrial safety, with discussions on how AI technologies can be leveraged for disaster management. The training was led by experts including Prof. (Dr) Anil Kumar Gupta, Head of Division at NIDM, and Sumeet Gupta, Assistant Secretary General at FICCI.
The Federation of Indian Chambers of Commerce and Industry (FICCI) organized the Cold Chain and Logistics Summit: Navigating The Future of Cold Chain Logistics on May 29, 2024, at FICCI, Federation House, New Delhi.
The objective of the summit was to encourage cooperation and innovation in establishing an integrated, sustainable, and effective cold chain ecosystem for India’s perishable goods industry. The discussions focused on the development of sustainable infrastructure to increase energy efficiency, reduce waste, and ensure the integrity and safety of temperature-sensitive goods in supply chain management.
Participants had the opportunity to learn about the latest trends and advancements in cold chain technology and logistics, as well as engage in networking opportunities with key stakeholders. The summit served as an active platform for discussing best practices and strategies to comprehend the technologies and trends that will shape the future of cold chain logistics.
I am excited to share that I have successfully completed the *Introduction to Quantum Information* course, offered by the Korea Advanced Institute of Science and Technology (KAIST) through Coursera. I completed the course on August 7, 2024, with approximately 10 hours of study.
This course provided an insightful introduction to quantum information theory, covering fundamental concepts such as quantum bits (qubits), quantum entanglement, quantum measurement, and the basics of quantum algorithms. It has equipped me with a deeper understanding of the foundational principles that power quantum computing and information science.
By completing this course, I have enhanced my knowledge of quantum mechanics and how it is applied to information theory, which will support my research in quantum computing and quantum artificial intelligence.
On 23rd Mar 2024, I am honored to announce that my paper, titled "Deep Learning for Detecting Manufacturing Defects Using Convolutional Neural Networks" (RAISE2023 Id: 135), has been selected for a special issue of the *International Journal of Advanced Mechatronic Systems*. The paper was selected for its exceptional research and will be included in the special issue on “RAISE2023 Mechatronics Automation and Cyber Physical Manufacturing Systems”.
I am pleased to share that my paper, titled "Predicting Credit Card Defaults with Machine Learning," co-authored with S Vinila Jinny, was presented at the International Conference on Intelligent Systems (AICERA: ICIS 2023) held at Amal Jyothi College of Engineering, Kanjirappally, Kerala, India from 16th to 18th November 2023. I am grateful for the opportunity to participate in this prestigious conference held by IEEE Kerala Section.
I am excited to announce the completion of the *Machine Learning Specialization* on Coursera, offered by Stanford University and DeepLearning.AI. The specialization was taught by renowned instructors Andrew Ng, Aarti Bagul, Geoff Ladwig, and Eddy Shyu. I completed the program on July 5, 2022, after approximately 2 months of study (10 hours per week).
This specialization provided a comprehensive understanding of machine learning concepts, including supervised learning (linear regression, logistic regression, decision trees, and neural networks), unsupervised learning (clustering, anomaly detection), recommender systems, and reinforcement learning. It equipped me with practical skills to apply these concepts to real-world problems, and I gained hands-on experience using tools like NumPy, scikit-learn, and TensorFlow.
The key courses completed include:
This specialization has significantly enhanced my knowledge of machine learning, and I'm excited to apply these skills in AI-driven problem-solving projects.
I am thrilled to announce the successful completion of the *Deep Learning Specialization* on Coursera, offered by DeepLearning.AI. The specialization was taught by experts Andrew Ng, Kian Katanforoosh, Younes Bensouda Mourri, and others. I completed this program on November 20, 2022, after approximately 3 months of study (10 hours per week).
The specialization covered various advanced deep learning topics such as Neural Networks, Convolutional Neural Networks (CNNs), Sequence Models (including RNNs and LSTMs), and Transformers. The course also delved into optimization techniques like Dropout, BatchNorm, and Xavier initialization, all applied using Python and TensorFlow. These skills have equipped me to solve real-world challenges such as speech recognition, natural language processing, and machine translation.
The key courses completed in this specialization include:
This specialization has significantly boosted my deep learning expertise, preparing me for advanced AI applications across various industries.