• Automated theorem proving
• AI for mathematical reasoning
• Large language models
• Machine learning
• Neuro-symbolic AI

Ananya Manas is a mathematician and data scientist with a keen interest in applying statistical and machine learning methods to problems in artificial intelligence. His research focuses on large language models, mathematical reasoning and neuro-symbolic AI, particularly on using formal verification and structured feedback to improve the reasoning capabilities of AI systems.

Ananya completed his PhD in Mathematics from University of Delhi, and MSc in Data Science from University of Bath, where he developed expertise in statistical learning, Bayesian machine learning, reinforcement learning, and computational methods. 

His current research interests include improving the mathematical problem-solving abilities of large language models, using formal theorem-proving systems such as Lean to verify and provide feedback on AI-generated solutions, and exploring statistical and machine learning methods for intelligent systems. He is also interested in reinforcement learning and the broader theoretical foundations of machine learning.

Alongside research, Ananya is committed to teaching and mentorship, with an experience of teaching mathematics, probability and statistics, and machine learning to students from diverse disciplinary backgrounds. 

Outside his academic work, he enjoys playing classical guitar, reading, and swimming.