Onsite
Key accomplishments
My professional journey in AI research and development is marked by a series of significant achievements that underscore my expertise in the field:
- Advanced Market Volatility Forecasting: Led the creation of a predictive model utilizing LLMs and GANs, setting a new standard in financial analytics for accuracy and insight-driven risk management.
- Medical Imaging Breakthrough: Innovated in medical diagnostics by enhancing MRI image contrast with CycleGAN, contributing to more precise and reliable medical assessments.
- Safety-Enhancing Technologies: Developed a cutting-edge driver drowsiness detection system, integrating eye-tracking with object detection models to bolster vehicular safety.
- E-commerce Innovation: Pioneered a sentiment-based recommendation engine, applying NLP to refine e-commerce product suggestions, thus elevating the consumer shopping experience.
- Global Sentiment Analysis: Crafted a multilingual sentiment analysis tool using LLAMA 2, enabling accurate sentiment interpretation across languages, which is pivotal for international customer service excellence.
- Proactive Fraud Detection: Engineered an autoencoder-based fraud detection system, enhancing credit card security by identifying fraudulent transactions with high precision.
These accomplishments reflect my commitment to leveraging AI for solving complex problems and my continuous pursuit of innovation in technology. My expertise spans from theoretical knowledge to practical applications, making me a valuable asset to any forward-thinking organization in the AI space.
Role 1
Ai engineer
Role 2
Machine learning engineer
Unspecified
Any
Graduate
India
Any
NA
Education
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June 1 2022 - Present
Liverpool John Moores University
Masters Of Science
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May 1 2022 - September 19 2023
International Institute of Information Technology Bangalore - IIITB
Post Graduation - PGDM
Experience
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October 1 2023 - Present
Liverpool John Moores University
AI Researcher
Portfolio
Languages
English
Honors & awards
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2023
Post Graduation - Deep Learning
Recognized for groundbreaking work in advancing medical imaging through AI, leveraging state-of-the-art Generative Adversarial Network (GAN) and modified U-Net architecture. Successfully developed an AI model capable of synthesizing MRI images with varying contrast levels, enhancing diagnostic accuracy and optimizing medical processes. Achieved remarkable results in seamlessly translating T1 weighted MRI images to T2 weighted MRI images and vice versa, contributing to improved patient care and healthcare efficiency.