Chun Tao

About Me

My journey began at Emory University, where I developed an interest in engineering physics. This ignited my passion for Electrical and Computer Engineering, leading me to transfer to Purdue ECE in my sophomore year.

At Purdue, I received comprehensive training across multiple ECE domains – VLSI analog and digital circuit design, computer architecture, and microprocessor systems and interfacing – completing my BSEE in just two years through intensive coursework and labs.

I continued into a thesis-based MS under Prof. Kaushik Roy in the Purdue NRL lab, studying AI fundamentals and hardware–software co-design for deep learning accelerators. My research explored the trade-off between natural accuracy and adversarial robustness of analog NVM crossbar circuits, later extending to semantic reasoning of natural images.

With a growing focus on AI, especially computer vision and NLP, I interned at automotive technology startups ClearMotion and Ample, building perception systems using stereo cameras and LiDAR for localization, segmentation, and pose estimation in autonomous driving and robotics.

Today at Intel, I specialize in AI applications for customers, including an interactive avatar chatbot built with PyTorch and the Intel Gaudi software stack, and I optimize and benchmark LLM workloads on Intel Tiber AI Cloud and IBM/Denver clouds.

Selected Projects & Publications