Shivam Sharma is a PhD graduate from IIT Delhi, specializing in multimodal machine learning, natural language processing, and harmful content analysis. His doctoral research focuses on detecting, characterizing, and explaining harmful content in memes by integrating vision, language, and knowledge-based reasoning. He has published extensively in top-tier venues, including Nature Machine Intelligence, ACL, AAAI, EACL, NAACL, and IEEE Transactions on Affective Computing, with contributions spanning meme understanding, multimodal reasoning, fake news verification, and affective computing.
Professionally, he has served as a Lead Researcher at Wipro R&D (Lab45), driving industry- research projects on misinformation, hate content, and AI-driven decision systems, and as a Postdoctoral Researcher at TU Darmstadt, working on open-book multimodal document question answering. His background also includes speech and audio processing research (notably infant cry analysis), academic teaching, student supervision, and active service to the NLP and AI research community through shared tasks, workshops, and peer review.