Academia Sinica

KSL lab

Kuo Sheng Lee
https://kuoshenglee.wixsite.com/ksllab

Research Field

Biology

Introduction

My career has consistently reflected overlapping interests in psychology, fundamental biology and applied science. During the past 10 years, I focused heavily on studying sensory systems, especially on somatosensation and vision. In my PhD, I discovered that the neural transformation of spatial information along the visual pathway accounts for the simultaneous generation of cortical columnar organization and new feature detectability in a primate-like animal model, tree shrews. For my postdoctoral research, I tested if the coding principles and dendritic computation I described in the visual system can be generalized to the somatosensory system and assess if it compares across species. Overall, my work partially answered the great mystery about how neural circuits systematically represent multidimensional features, and how the emergence of functional diversity at the single-cell level contributes to this representation. As a fellow with the European Molecular Biology Organization (EMBO) Postdoctoral Fellowship program, I had the unique opportunity to conduct independent and high-risk/high-reward research projects that matched my interests and developmental needs. Through the course of my scientific career, I engaged in many collaborative research projects with local faculty and beyond, yielding multiple first-authored publications in Nature and Neuron. Outside of the lab, I am also an active podcaster on scientific outreach to general public and mid-career scientists across the globe. Our channel “Sky in the wall” (https://linktr.ee/Skyinthewall) has over 20k followers and is one of the most followed podcast programs on scientific topics in the Chinese-speaking community worldwide. 

Research & Projects

Understand the fundamental mechanisms underlying somatosensation

We use approaches in advanced optical imaging/optogenetics, molecular genetics, functional anatomy, electrophysiology, and closed-loop/freely-moving mouse behavior to comprehensively understand the fundamental mechanisms underlying somatosensation.

We are interested to understand the neural circuits underlying information coding, from the earliest sensory transduction at the peripheral organ all the way to the sophisticated cortical computation.

Our laboratory will investigate the neural underpinnings of touch, pain and related affective aspects in the brainstem, and will reverse engineer it to develop sensory neuroprostheses and potentially, an affective brain–machine interface for pain management and mood regulation.


Research Topics

Project 1: Probe the complex process of mechanotransduction at the physiological site in vivo 

Project 2: Investigate the brainstem circuits involved in the integration of somatosensation 

Project 3: Develop the brainstem stimulation as a novel solution for somatosensory neuroprosthesis

Project 4: Brain–machine interface on brainstem networks for pain and mood regulation 


Honor

2024 Career Development Award (CDA) from the Academia Sinica

2022 2030 cross-generation young scholars program from Ministry of Science and Technology (Taiwan): Emerging Young Scholars

2022 FENS-IBRO/PERC Travel Grant for the Federation of European Neuroscience

2020 European Molecular Biology Organization (EMBO) Postdoctoral Fellowship

2018 Best Scientific Talk at Max Planck Florida Institute Scientific Retreat


Educational Background

Postdoc: University of Geneva 

PhD: Max Planck Florida Institute for Neuroscience / Florida Atlantic University 

BS: Psychology at National Taiwan University


Job Description

Academia Sinica offers a vibrant neuroscience community with outstanding research conditions.

​Send your inquiries with CV, a brief statement of research interest and list of references to:  leeku@ibms.sinica.edu.tw

Preferred Intern Education Level

Candidates with backgrounds in neuroscience or related fields such as engineering, mathematics or physics are encouraged to apply.

 

Skill sets or Qualities

Excellent programming skills, steady hands, and a strong analytical background are helpful. Prior experience with imaging, animal behavior, brain machine interface or machine learning methods is a plus.