Chandrajit Bajaj

Purdue University West Lafayette, The University of Texas at Austin

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About

Chandrajit Bajaj is a leading figure in computational geometry, geometric modeling, and scientific visualization, with a career spanning foundational theory to modern deep learning applications. His early work on "Sliced Configuration Spaces for Curved Planar Bodies" (1998, 37 citations) introduced the first practical algorithm for computing configuration spaces of curved objects amidst obstacles—a critical contribution to robotics and motion planning. This work demonstrated how constructive real algebraic geometry could solve complex spatial reasoning problems. More recently, Bajaj has advanced neural scene synthesis with "Scene Synthesis via Uncertainty-Driven Attribute Synchronization" (2021, 31 citations), addressing the challenge of generating realistic 3D scenes for CAD, graphics, and virtual training environments. His pioneering monograph "Some Applications of Constructive Real Algebraic Geometry" (1994) laid groundwork for algorithmic algebraic geometry in computer science. With over 200 publications and thousands of citations, Bajaj's research bridges theoretical rigor and practical impact, from robot path planning to AI-driven design. He is a Fellow of the IEEE and ACM, and his work continues to shape how computers understand and generate complex geometric environments.