About Me
I am currently working at Google in San Diego, CA, USA, as an AI/ML Systems and Silicon Architect.
I received the B.S. degree in Electrical Engineering from Pohang University of Science and Technology (POSTECH), South Korea, in 2018, and the M.S. and Ph.D. degrees in Electrical Engineering from the Korea Advanced Institute of Science and Technology (KAIST), South Korea, in 2020 and 2023, respectively. I was a Postdoctoral Researcher at the KAIST Institute of Information & Electronics from 2023 to 2025.
My research interests are (1) energy-efficient AI/ML system-on-chip design, (2) digital circuit-, architecture-, and software-level AI/ML accelerator design, and (3) custom silicon chip and demonstration system board development.
News
(Updated: June 2025) New Paper Accepted at OJ-SSCS
- The new journal titled “An Overview of AI Hardware Architectures and Silicon for 3D Spatial Computing Systems” is accecpted at IEEE Open Journal of the Solid-State Circuits Society (Early Access)
Abstract: As artificial intelligence (AI) advances, 3D spatial computing has emerged as a key application in various fields. It interprets the 3D space surrounding users and provides them with useful information. This paper presents a survey of AI hardware architectures and silicon solutions for 3D spatial computing systems. The survey categorizes five domains: 3D data capturing, 3D data analysis, 3D hand motion analysis, simultaneous localization and mapping (SLAM), and 3D rendering. Each session analyzes design considerations for domain-specific accelerators. Finally, the paper discusses a next-generation 3D spatial computing platform that integrates various functions of 3D spatial computing systems using AI technologies.
(Updated: Mar 2025) New Career
- Starting a new position as an AI/ML system and silicon architect at Google, San Diego, CA, USA
Past News
- (Updated: Feb 2025) New US Patent Application
- (Updated: July 2024) New Paper Accepted at MICRO-57
- (Updated: Feb 2024) New Paper Accepted at HPCA 2024
First Authored Publications
OJSSCS 2025
IEEE Open Journal of the Solid-State Circuits Society
June 2025
(New) An Overview of AI Hardware Architectures and Silicon for 3D Spatial Computing Systems
Dongseok Im, Gwangtae Park, Junha Ryu, and Hoi-Jun Yoo
MICRO 2024
IEEE/ACM International Symposium on Microarchitecture
November 2024
CamPU: A Multi-Camera Processing Unit for Deep Learning-based 3D Spatial Computing Systems
Dongseok Im and Hoi-Jun Yoo
HPCA 2024
IEEE International Symposium on High-Performance Computer Architecture
March 2024
LUTein: Dense-Sparse Bit-slice Architecture with Radix-4 LUT-based Slice-Tensor Processing Units
Dongseok Im and Hoi-Jun Yoo
Micro Journal
IEEE Micro
May-June 2023
A Mobile 3-D Object Recognition Processor With Deep-Learning-Based Monocular Depth Estimation
Dongseok Im, Gwangtae Park, Zhiyong Li, Junha Ryu, Sanghoon Kang, Donghyeon Han, Jinsu Lee, Wonhoon Park, Hankyul Kwon, and Hoi-Jun Yoo
HPCA 2023
IEEE International Symposium on High-Performance Computer Architecture
March 2023
Sibia: Signed Bit-slice Architecture for Dense DNN Acceleration with Slice-level Sparsity Exploitation
Dongseok Im, Gwangtae Park, Zhiyong Li, Junha Ryu, and Hoi-Jun Yoo
JSSC Journal
IEEE Journal of Solid-State Circuits
January 2023
DSPU: An Efficient Deep Learning-Based Dense RGB-D Data Acquisition with Sensor Fusion and 3-D Perception SoC
Dongseok Im, Gwangtae Park, Junha Ryu, Zhiyong Li, Sanghoon Kang, Donghyeon Han, Jinsu Lee, Wonhoon Park, Hankyul Kwon, and Hoi-Jun Yoo
HOT CHIPS 2022
IEEE Hot Chips Symposium
August 2022
DSPU: A 281.6mW Real-Time Deep Learning-Based Dense RGB-D Data Acquisition with Sensor Fusion and 3D Perception System-on-Chip
Dongseok Im, Gwangtae Park, Zhiyong Li, Junha Ryu, Sanghoon Kang, Donghyeon Han, Jinsu Lee, Wonhoon Park, Hankyul Kwon, and Hoi-Jun Yoo
COOL CHIPS 2022
IEEE Symposium on Low-Power and High-Speed Chips and Systems
April 2022
A Low-power and Real-time 3D Object Recognition Processor with Dense RGB-D Data Acquisition in Mobile Platforms
Dongseok Im, Gwangtae Park, Junha Ryu, Zhiyong Li, Sanghoon Kang, Donghyeon Han, Jinsu Lee, Wonhoon Park, Hankyul Kwon, and Hoi-Jun Yoo
ISSCC 2022
IEEE International Conference on Solid-State Circuits
February 2022
DSPU: A 281.6mW Real-Time Depth Signal Processing Unit for Deep Learning-Based Dense RGB-D Data Acquisition with Depth Fusion and 3D Bounding Box Extraction in Mobile Platforms
Dongseok Im, Gwangtae Park, Zhiyong Li, Junha Ryu, Sanghoon Kang, Donghyeon Han, Jinsu Lee, and Hoi-Jun Yoo
JSSC Journal
IEEE Journal of Solid-State Circuits
February 2022
A Pipelined Point Cloud Based Neural Network Processor for 3-D Vision With Large-Scale Max Pooling Layer Prediction
Dongseok Im, Sanghoon Kang, Donghyeon Han, Sungpil Choi, and Hoi-Jun Yoo
TCAS-1 Journal
IEEE Transactions on Circuits and Systems I: Regular Papers
October 2020
DT-CNN: An energy-efficient dilated and transposed convolutional neural network processor for region of interest based image segmentation
Dongseok Im, Donghyeon Han, Sungpil Choi, Sanghoon Kang, and Hoi-Jun Yoo
S.VLSI 2020
IEEE Symposium on VLSI Technology and Circuits
June 2020
A 4.45 ms Low-latency 3D Point-cloud-based Neural Network Processor for Hand Pose Estimation in Immersive Wearable Devices
Dongseok Im, Sanghoon Kang, Donghyeon Han, Sungpil Choi, and Hoi-Jun Yoo
ISCAS 2019
IEEE International Symposium on Circuits and Systems
May 2019
DT-CNN: Dilated and transposed convolution neural network accelerator for real-time image segmentation on mobile devices
Dongseok Im, Donghyeon Han, Sungpil Choi, Sanghoon Kang, and Hoi-Jun Yoo
3D Video Projects
- 360° 3D VR Videos
This 360-degree 3D VR video projects a single 360-degree video into perspective views corresponding to human eyes with 3D depth effects through AI technology. The left video is captured through a dual-fisheye lens camera, and the right video is synthesized by applying depth to an original left scene. This project is run on a single RTX2080Ti card. The synthesis of a 360-degree 3D VR video takes 1 second per frame without any AI network finetunning. Left and right rendering displays take a total of 50 ms of latency as a view changes. Play VR videos on a Google Cardboard or AR/VR devices.
- 3D VR Videos
This project generates 3D VR videos from a single video through AI technology. The right video is synthesized from the left one fitting in different perspective views of human eyes. This project is run on a single RTX2080Ti card. The Synthesis of the right side video takes 0.3 seconds per frame without any AI network finetunning. Play VR videos on a Google Cardboard or AR/VR devices.
- 3D Glasses Videos
This project generates 3D Glasses videos from a single video through AI technology. Red and Cyan colors are separated from an original video, and pixels corresponding to Cyan colors are shifted based on a depth map for 3D effects. Play this video with Red-Cyan anaglyph glasses.
- 3D Photos
This project generates 3D photos from a single image through AI technology. This 3D effect provides a novel view synthesis that looks left and right.
Work Experience
- AI/ML System and Silicon Architect at Google
Mar. 2025 - Current
- Postdoctoral Researcher at KAIST Information & Electronics Research Institute
[Working Project] Designing high-performance hardware architectures for multi-camera AI-based 3D spatial computing systems
Sep. 2023 - Feb. 2025
Education
- Ph.D. in Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST)
Thesis Title: A Low-Power and Real-Time 3-D Object Recognition System-on-chip
Mar. 2020 - Aug. 2023
Advisor: Hoi-Jun Yoo
- M.S. in Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST)
Feb. 2018 - Feb. 2020
Advisor: Hoi-Jun Yoo
- B.S. in Electrical Engineering, Pohang University of Science and Technology (POSTECH)
Mar. 2014 - Feb. 2018