Abhinandan Mukherjee

Lead Data Scientist with extensive experience in designing and deploying AI-driven solutions for predictive maintenance for supply chain logistics. Spearheaded the development of anomaly detection systems utilizing CNNs and LSTM networks; achieved significant reduction in operational downtime.

Designed and executed Generative AI projects, emphasizing the transformative power of AI in modern industrial applications. Championed MLOps practices for seamless model deployment, achieving rapid iterations and timely project deliveries on platforms like GCP and AWS.

Orchestrated the creation of a predictive maintenance scheduling platform, leveraging Deep Reinforcement Learning; elevated productivity by over10%. Led the integration of advanced chatbot systems for maintenance logs, employing fine-tuned large language models; enhanced user query resolution time by 15%.

Pioneered real-time acoustic diagnostic tools for machinery health assessment, leveraging deep learning models for acoustic footprint analysis; marked a 17% decrease in unplanned machinery downtime. Played a key role in anomaly detection projects within large-scale trading systems, focusing on ML system design, continuous monitoring, and optimization.

Proficient in Google Cloud Platform (GCP) and Amazon Web Services (AWS), specializing in the development, deployment, and scaling of advanced AI-driven solutions. Achieved transformative results across sectors, showcasing the ability to bridge the gap between advanced AI technologies and practical industry applications.