Ferdous Alam

I am a post-doc at MIT working with Faez Ahmed. Recently, I earned my Ph.D. from the Ohio State University where I worked on machine learning, representation learning and reinforcement learning for decision making in complex real-world tasks such as design, manufacturing and robotics. I was supervised by David Hoelzle. Previously, I also worked as a research intern and later a research collaborator at the Autodesk AI Lab on AI for 3D generative computational design.

My core research interest is to enable efficient decision making in complex systems. I draw from artificial intelligence (AI)/machine learning (ML) and control theory to develop learning algorithms for intelligent manufacturing systems, autonomous robots and generative/algorithmic engineering design tasks. Within AI/ML my interest lies in representation learning and reinforcement learning. I am also interested in the AI/ML systems integration for these critical application domains. During my Ph.D., I developed data-efficient reinforcement learning algorithms using knowledge transfer between tasks and probabilistic reward modeling. I was also part of the team that built a state-of-the-art autonomous manufacturing research robot that can take decisions in real-time to design and manufacture a complex geometry 3D artifact without any human intervention and require 10x less data samples than traditional approaches. I have designed and implemented the AI/ML software architecture for this autonomous robot. I have also worked as a research intern, and later a collaborator, at the Autodesk AI Lab where we developed transformer based representation learning and autoregressive generative models for voxel-based 3D design tasks.