I am an Applied Scientist at Microsoft in Greater Seattle Area. 

My primary research interests are in generative AI and computer vision. Currently, I am developing an generative AI model and multi-modal LLM for advertising images/videos. Especially, I'm interested in few-step distillation of diffusion/flow-matching based image editing models and post-training MLLM or reasoning agents for creative assets. I also worked on post-training multi-modal LLM for video understanding. I'm also interested in robust deep learning, anomaly/out-of-distribution detection, and continual learning algorithms.

I received my PhD degree in 2019 from the Electrical and Computer Engineering department at the University of Texas at Austin (UT Austin). I was advised by Professor Joydeep Ghosh, director of Intelligent Data Exploration and Analysis Laboratory (IDEAL), and was affiliated with the Wireless Networking and Communications Group (WNCG). Prior to joining UT Austin, I received my MSE degree in Electrical Engineering-Systems from University of Michigan, Ann Arbor and completed my BS degree in Electrical Engineering from Korea Advanced Institute of Science and Technology (KAIST). 

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Email: taewankim at microsoft dot com

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