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Taekjun Kim, Ph.D. #

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  • Research Scientist
  • Department of Neurobiology and Biophysics, Washington National Biomedical Research Center, University of Washington

Professional Summary #

  • Computational Neuroscientist with 15+ years of experience analyzing large-scale neural population activity and visual information processing.
  • Expertise in primate visual hierarchy (V1, V2, V4), with a specific focus on characterizing single-neuron properties, population dynamics, and PFC feedback modulation.
  • Proficient in Python and experienced in working with C++ based experimental control systems and automated data pipelines.
  • Focused on transitioning this multi-region and engineering background toward developing comprehensive, brain-scale computational models.

Education #

  • Ph.D. in Vision Science, University of California, Berkeley
  • M.A. in Biological Psychology, Seoul National University, Korea
  • B.A. in Psychology, Seoul National University, Korea

Research experience #

University of Washington, Washington National Primate Research Center #

Research Scientist (Jun 2025 – Present)

  • PFC–V4 Feedback: Recording simultaneously from V4 and PFC while reversibly inactivating PFC by cooling, to test how prefrontal feedback shapes V4 feature selectivity.
  • Object Recognition in PFC: Examining how PFC represents object identity across viewpoint, noise level, and rendering format.
  • Prospective Remapping: Identifying stimulus-selective anticipatory signals in V4 and modeling neural response adaptation during saccadic eye movements.
  • Chronic Wireless Recording & Microstimulation: Designed a study using chronic wireless microelectrode arrays in macaque V1, V2, and V4 to measure visual percepts evoked by microstimulation (in preparation).

Acting Assistant Professor (Jan 2023 – May 2025)

  • Functional Architecture of V2: Characterized functional clusters for shape, texture, and motion in macaque V2 using high-density Neuropixels recordings ( J. Neurosci., 2026) and multi-photon imaging.
  • High-Throughput Pipelines: Built Python pipelines to process TB-scale electrophysiology data from acquisition to analysis.
  • Modeling Visual Crowding: Comparing V4 population responses in crowding with CNN architectures to identify shared constraints in object recognition.

Acting Instructor (Oct 2019 – Jan 2023)

  • Neural Correlates of Crowding: Showed in awake, fixating macaques that crowding in V4 is driven by salience-based competition among stimuli ( J. Neurosci., 2024).
  • Experimental Control Software: Upgraded the lab’s real-time experimental control software; rewrote C-level software interfaces to add laser and eye-tracking control.
  • Reviews: Co-authored reviews on shape and surface encoding in the ventral visual pathway and on primate V4 function ( Curr. Opin. Neurobiol., 2019; Annu. Rev. Vis. Sci., 2020).

Senior Fellow (Oct 2015 – Sep 2019)

  • Shape & Texture Coding: Identified joint tuning for object shape and surface texture in V4; developed quantitative metrics for natural texture perception ( J. Neurosci., 2019; J. Neurosci, 2022).
  • Motion Processing: Showed dissociated encoding of object versus surface motion using single-electrode and Neuropixels recordings ( Curr. Biol., 2023).

University of California, Berkeley #

Assistant Specialist / Graduate Student Researcher (Aug 2010 – Sep 2015)

  • Neuromodulation (TMS): Measured how TMS changes response selectivity of visual cortical neurons in cats ( Brain Stimul., 2015).
  • Cortical Circuit Dynamics: Separated fast and slow components of surround modulation in visual cortex ( Neuroscience, 2014).
  • Direction Selectivity: Quantified lamina-dependent non-linearity of direction selectivity from a cortical neuron database ( Eur. J. Neurosci., 2016).
  • Binocular Integration: Designed human psychophysics experiments showing binocular fusion is robust to large interocular contrast differences ( Eur. J. Neurosci., 2017).

Seoul National University #

Research Associate (Sep 2008 – Jun 2010)

  • Studied the spatiotemporal selectivity of V1 response using Gabor stimuli that were sequentially presented with a variable stimulus onset asynchrony. Wrote Matlab code for visual stimulus generation, data acquisition, and analysis (published in PLoS One, 2012; PLoS One, 2015)

Graduate Student Researcher (Mar 2006 – Aug 2008)

  • Conducted a human psychophysics study to examine the spatial localization error in visual short-term memory task (published in KCBPA, 2014)
  • Led lab and discussion sessions for psychology students in Neuroscience and Biopsychology classes