Genentech: Namuk Park | Postdoctoral Fellow, Prescient Design

Scientists / Our Scientists

Awards & Honors

The focus of my research has been on exploiting prior knowledge to improve machine learning systems through a fundamental understanding of deep neural networks. Specifically, I am interested in analyzing the properties of neural networks for proteins, aiming to build generalizable models that can tackle protein design problems by only utilizing small amounts of data. I joined Prescient Design in 2023. Prior to this, I received my Ph.D. from Yonsei University in South Korea.

Featured Publication

How Do Vision Transformers Work?

ICLR (2022)

Park, Namuk, and Songkuk Kim

View Abstract

At Prescient, my area of focus is building self-supervised learning methods for proteins. We expect that a wide range of downstream tasks, including protein design and affinity prediction, can be improved by exploiting such methods.

Yonsei University, South Korea, South Korea,, Ph.D. in Computer Science – 2022
Yonsei University, South Korea, South Korea,, B.S. in Physics – 2011

Winner of Qualcomm Innovative Fellowship South Korea – 2021
National Fellowship from Global Open Source Frontier – 2021
CJK (China–Japan–South Korea) OSS (Open Source/Software) Award – 2019
National Ph.D. Full Ride Fellowship – 2011
Yonsei University Alumni Full Ride Scholarship for Undergraduate Students – 2010

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Namuk Park

Postdoctoral Fellow, Prescient Design

Featured Publication

How Do Vision Transformers Work?