Manash Sarkar

Background

About Manash Sarkar

Expertise in Data Analysis, Prediction, and Decision Making using Machine Intelligence Techniques. Confident in skills and qualifications, with more than 10 years of experience working on various real-time projects and international research collaborations. Possess extensive experience in Generative AI (GenAI), including work with Large Language Models (LLMs), Transformer-based Architectures, Fine-Tuning, and Multi-modal Applications. Contributed to cutting-edge research and industry-level projects focused on text generation, conversational AI, document summarization, code generation, and synthetic data creation, leveraging GenAI for automation and insight generation across domains. Hands-on experience includes: • Developing and fine-tuning generative models such as GPT, BERT, T5, and LLaMA for NLP tasks. • Building GenAI-based solutions in recommender systems, finance, and social network analysis to support personalized content generation, sentiment-aware decision-making, and knowledge extraction. • Implementing LLM-based pipelines for real-time applications like chatbots, knowledge assistants, and document analytics using LangChain, Hugging Face Transformers, and OpenAI APIs. • Collaborated on research projects involving GenAI for zero-shot learning, few-shot reasoning, and autonomous decision-making systems in partnership with global research institutions. A highly analytical and strategic thinker, with excellent problem-solving abilities. Demonstrated capability to transform complex data into actionable insights that influence key business decisions. Research Details & hl=en