Responsibilities included:

• Developing cross-platform applications (Android, iOS, and Web) using React Native for Leica Geosystems digital manuals, with integration of AI features to enhance user experience.
• Designing and maintaining NestJS API server, managing S3 buckets, and implementing access policies to support AI training and secure data workflows.

Responsibilities included:

• Designed and implemented 6+ modular ERP modules using NextJS, Supabase, and PostgreSQL, improving inter-departmental data flow efficiency.
• Integrated dynamic filters, role-based dashboards, and 12+ scalable APIs, enabling real-time access to data for 80+ active users across teams.
• Automated 30+ routine workflows with logic-based triggers, reducing manual effort by 50% and setting the foundation for AI-powered insights.

Responsibilities included:

• Implementing the optimal ways to use reinforcement learning to identify high-risk patient conditions and suggest the best treatments in healthcare, while also improving clinical decision-making systems to provide better, personalized care for patients.
• Implemented Wavelet Generative Adversarial Networks (WGANs) to augment limited EEG datasets for motor imagery classification, boosting BCI system accuracy to 72% and providing more signal(synthetic) data for training.
• Applied Q-learning algorithms and reward functions to optimize traffic signal control, aiming to reduce congestion and improve traffic flow by developing a dynamic system that learns from real-time traffic patterns to enhance overall efficiency and minimize wait times at intersections.
• Performed an in-depth analysis of 22 distinct web metrics on data from the Webby Awards (2017–2022) to improve overall web page quality and identified key factors influencing web performance and user experience, driving web page optimization.
• Conducted exhaustive research and developed a framework called CJPR, designed to predict Supreme Court case outcomes and provide relevant case recommendations using NLP and transformer models to accelerate decision-making for faster judgments in complex legal scenarios.

Responsibilities include:

• Designed and implemented end-to-end machine learning pipelines, including data preprocessing, feature engineering, model training, validation, and deployment.
• Collaborated with clients from various countries to understand project requirements, define objectives, and deliver tailored machine learning solutions.
• Worked on Computer Vision, GANs and various Deep Learning Projects showcasing expertise in these domains.

Responsibilities include:

• Developed ISPSO, an optimized image segmentation method using meta-heuristic algorithms, achieving 80% segmentation accuracy. This approach leverages Particle Swarm Optimization (PSO) for enhanced precision in medical and industrial image analysis.
• Built a football match prediction model incorporating Kelly Criterion to optimize betting strategies, achieving 75% accuracy. Analyzed historical match data, odds, and team performance using machine learning for data-driven betting decisions.

Responsibilities include:

• Designed and implemented a robust Computer Vision Algorithm, leveraging OCR Tools such as PaddleOCR & EasyOCR.
• Spearheaded the design and implementation of a mathematical algorithm, resulting in a 20% improvement in system performance.
• This achievement contributed significantly to project enhancements and played a pivotal role in boosting overall operational efficiency in our research.

Responsibilities include:

• Spearheaded a project team of 3 members, overseeing the successful completion of tasks and ensuring alignment with strategic goals.
• Conducted an exhaustive analysis of the Electric Vehicle Market in India, utilizing advanced segmentation techniques and generating a predictive model.