I earned my MSc in Data Science from Swansea University, UK, and my BE in Computer Science and Engineering from Dayananda Sagar Academy of Technology and Management, India. My professional experience includes working as a Data Analyst at OVO Energy, where I developed user-friendly reports to support performance analysis and strategic decision-making. At Biz Data Inc., as a Business & Data Analyst, I contributed to business analytics and data interpretation, enhancing organizational strategies. While studying for my MSc, I served part-time as a Student Experience and Information Coordinator at Swansea University, effectively communicating complex concepts and providing support to students. My research interests lie in Machine Learning, Neural Networks, Generative AI, and Big Data Analytics, and I have presented development papers and technical paper presentations at various conferences, including the British Academy of Management and NCCSTM-2017. I am passionate about creating innovative learning environments and mentoring students to achieve their full potential. My goal is to integrate industry partnerships into academia to provide students with practical, real-world experience.I aim to develop advanced data science curricula, integrate industry partnerships for real-world projects, and establish a research lab focused on machine learning and big data analytics. I also plan to organize workshops and seminars to keep students and staff updated on industry trends and technological developments. Outside of work, I am interested in Vedic astrology, wellness, trekking, jogging and reading. I actively participate in extracurricular activities and have received several accolades, including a Certificate of Merit in a National Karate Championship.

"Thou hast a right to perform thy prescribed duties, but thou art not entitled to the fruits thereof. Let not the fruits of action be thy motive, neither let there be in thee any attachment to inaction." - Śrī Kṛṣṇa, Śrīmad Bhagavad Gītā 2:47

• Research Summary
• Face Recognition and Retrieval across Age Using Cross-Age Reference Coding (CARC) - Objective: Develop a method for face recognition across different ages using a novel approach called Cross-Age Reference Coding (CARC). - Methodology: Utilizes freely available datasets on the Internet, employs Viola-Jones Object Detection algorithm and Gray Level Co-Occurrence Matrix (GLCM) for feature extraction. - Key Findings: CARC effectively encodes low-level facial features into a reference space, maintaining accuracy despite age variations. Validated using the Cross-Age Celebrity Dataset (CACD), demonstrating promising results. - Applications: Useful for identifying missing persons, tackling child trafficking in forensic applications, and automatic photo annotation. - Future Directions: Focus on improving the performance and accuracy of age-invariant face recognition and reducing the false positive rate.
• Building a Resilient Future Healthcare Sector: A Net Zero Perspective - Objective: Explore the NHS's commitment to achieving net zero greenhouse gas emissions by 2040 and outline a comprehensive framework for environmental sustainability in healthcare. - Methodology: Mixed research approach, including literature review and semi-structured interviews with healthcare professionals. - Key Findings: Emphasizes reducing healthcare demand through health promotion, aligning resources with patient needs, and minimizing emissions from operations. Highlights the importance of integrating carbon emissions into healthcare decision-making. - Applications: Framework applicable to healthcare policy development, promoting sustainable health practices and equitable health outcomes. - Future Directions: Advocates for systemic changes in healthcare policies and practices to achieve net zero emissions, integrating environmental considerations into health technology assessments (HTAs).
• Research Interests
• My research interests are centered around several key areas within data science and technology. I am particularly focused on machine learning and neural networks, where I strive to develop innovative algorithms and models to enhance the efficiency and accuracy of machine learning applications. This includes exploring the use of neural networks for complex pattern recognition and data analysis tasks. Another major area of interest is big data analytics. I specialize in extracting meaningful insights from large datasets, utilizing advanced analytical techniques to support decision-making processes and strategic planning. This work aims to leverage the vast amounts of data generated in various fields to drive better outcomes and innovations. Generative AI is also a significant part of my research. I am fascinated by the potential of generative models to create new data and simulate real-world scenarios. My research in this area covers applications such as image generation, text synthesis, and anomaly detection, where these models can offer substantial benefits. In the realm of face recognition and retrieval, my research has explored the use of Cross-Age Reference Coding (CARC) for recognizing faces across different ages. This method, validated using the Cross-Age Celebrity Dataset (CACD), leverages machine learning and computer vision techniques to improve face detection and recognition accuracy, addressing the challenges posed by age variations. Additionally, I am dedicated to advancing sustainable healthcare systems. My research in this area focuses on integrating environmental sustainability into healthcare practices. I have explored frameworks to achieve net zero emissions in healthcare, emphasizing the importance of health promotion, resource alignment, and reducing emissions from healthcare operations and supply chains. These research interests reflect my commitment to both technological innovation and practical applications, aiming to make significant contributions to the fields of data science and environmental sustainability.

• Immersive Advanced AI Bootcamp by Invento Robotics - Participated in an immersive Advanced AI Bootcamp conducted by Invento Robotics, gaining advanced knowledge in artificial intelligence and robotics.

• Development Paper Submission at British Academy of Management - Presented a development paper at the British Academy of Management, showcasing research in sustainable healthcare systems and net zero emissions.

• Coding Star Certificate from BridgeLabz - Awarded the Coding Star Certificate by BridgeLabz, recognizing proficiency and expertise in coding and software development.

• Python Bootcamp Course by AttainU - Completed the Python Bootcamp Course offered by AttainU, developing foundational and advanced skills in Python programming.

• Global Certificate in Data Science & AI from Accredian (INSAID) - Completed the Global Certificate in Data Science & AI from Accredian (INSAID), enhancing expertise in data science and artificial intelligence.

• Google Analytics Certification - Beginner - Completed the Google Analytics Certification for Beginners, acquiring essential skills in web analytics and data-driven decision-making.

• Certificates of Training - Data Science, Machine Learning, Advanced Excel, IoT - Received multiple certificates of training from Internshala Trainings, covering Data Science, Machine Learning, Advanced Excel, and Internet of Things (IoT).

• ISKCON Communications Course - Successfully completed the ISKCON Communications Course, enhancing communication skills and interpersonal effectiveness.

• Technical Paper Presentation at NCCSTM 2017 - Presented a technical paper at the National Conference on Challenges in Scientific and Technological Management (NCCSTM) 2017, focusing on advancements in data science and machine learning.

• AngularJS & HTML5 - Completed a course on AngularJS and HTML5 from ZenRays Technologies, enhancing web development skills and understanding of front-end technologies.

• Career Guidance - Participated in a Career Guidance program conducted by CIL, receiving insights and advice on career planning and professional development.