Sanskar Amgain is a Research Assistant at NAAMII with a focus on federated learning, multimodal learning, and computational genomics. He graduated in Computer Engineering from the Institute of Engineering, Nepal. His current research investigates the effect of client selection strategies in federated learning systems. This work is particularly relevant for developing privacy-preserving AI solutions that can train on distributed data without centralizing sensitive information, with important applications in healthcare and other domains where data privacy is paramount.