Donghyeon Han

[Feb, 2024] D. Han won the Best Demo Award for the paper "MetaVRain: A 133mW Real-time Hyper-realistic-3D-NeRF Processor with 1D-2D Hybrid-Neural-Engines for Metaverse on Mobile Devices" at the ISSCC 2024.

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[Dec, 2023] "​A Low-power AI-based 3D Rendering Processor with Hybrid DNN Computing" is accepted by IEEE Micro.

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[Aug, 2023] A book, "On-Chip Training NPU - Algorithm, Architecture and SoC Design​" is published.

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[Jul, 2021] "​MetaVRain: A Mobile Neural 3-D Rendering Processor With Bundle-Frame-Familiarity-Based NeRF Acceleration and Hybrid DNN Computing" is accepted by IEEE Journal of Solid-State Circuits (JSSC).

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[Apr, 2023] Dataset for MetaVRain Project is now released in Github. (https://github.com/DonghyeonHan/MetaVRain_dataset).

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[Apr, 2023] "A Low-power Neural 3D Rendering Processor with Bio-inspired Visual Perception Core and Hybrid DNN Acceleration​" is accepted by IEEE Symposium on Low-Power and High-Speed Chips and Systems (COOLChips).

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[Mar, 2023] D. Han is now working as a postdoctoral associate at MIT.

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[Feb, 2023] D. Han won the Bronze Prize for the paper "MetaVRain: A 133mW Real-time Hyper-realistic-3D-NeRF Processor with 1D-2D Hybrid-Neural-Engines for Metaverse on Mobile Devices" at the 29th SAMSUNG Humantech Paper Award.

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[Feb, 2023] "MetaVRain: A 133mW Real-time Hyper-realistic-3D-NeRF Processor with 1D-2D Hybrid-Neural-Engines for Metaverse on Mobile Devices​" is accepted by IEEE International Solid-State Circuits Conference (ISSCC).

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[Feb, 2023] D. Han won the Award of Ph.D. Students with Excellent Research Performance in Electrical Engineering, KAIST.

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[Jan, 2023] D. Han gave an invited talk entitled "A Real-time DNN Training Processor for Robust Object Detection with Real-World Environmental Adaptation" at the Electronic & Information Research Information Center, Korea.

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[Nov, 2022] "Energy-efficient DNN Training Processors on Micro-AI Systems​" is accepted by IEEE Open Journal of the Solid-State Circuits Society (OJ-SSCS).

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[Aug, 2022] "HNPU-V2: A 46.6 FPS DNN Training Processor for Real-World Environmental Adaptation based Robust Object Detection on Moble Devices​" is accepted by IEEE Hot Chips: A Symposium on High Performance Chips (HotChips).

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[Jun, 2022] D. Han won the Best Live Demo Award at 2022 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS 2022).

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[Jun, 2022] D. Han won the Best Paper Award at 2022 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS 2022).

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[Jun, 2022] "A 0.95 mJ/frame DNN Training Processor for Robust Object Detection with Real-World Environmental Adaptation​" is accepted by IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS).

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[Mar, 2022] "A Mobile DNN Training Processor with Automatic Bit-precision Search and Fine-grained Sparsity Exploitation​" is accepted by IEEE Micro.

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[Apr, 2021] "​An Energy-efficient Deep Neural Network Training Processor with Bit-slice-level Reconfigurability and Sparsity Exploitation" is accepted by IEEE Symposium in Low-Power and High-Speed Chips (COOLChips).

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[Sep, 2021] "​HNPU: An Adaptive DNN Training Processor Utilizing Stochastic Dynamic Fixed-point and Active Bit-precision Searching" is accepted by IEEE Journal of Solid-State Circuits (JSSC).

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[Dec, 2020] "​DF-LNPU: A Pipelined Direct Feedback Alignment-Based Deep Neural Network Learning Processor for Fast Online Learning" is accepted by IEEE Journal of Solid-State Circuits (JSSC).

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[Feb, 2020] D. Han won the Gold Prize for the paper "GANPU: A 135TFLOPS/W Multi-DNN Training Processor for GANs with Speculative Dual Sparsity Exploitation" at the 26th SAMSUNG Humantech Paper Award.

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[Nov, 2019] "Efficient Convolutional Neural Network Training with Direct Feedback Alignment​" is accepted by IEEE International Conference on Computer Vision Workshop (ICCVW).

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[Jun, 2019] "A 1.32 TOPS/W Energy Efficient Deep Neural Network Learning Processor with Direct Feedback Alignment based Heterogeneous Core Architecture​" is accepted by Symposium on VLSI Circuits (SoVC).

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[Feb, 2019] D. Han won the Participation Prize for the paper "LNPU: A Sparse Deep-Neural-Network Learning Processor with Fine-grained Mixed Precision of FP8-FP16" at the 25th SAMSUNG Humantech Paper Award.

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[Nov, 2018] "​A Low-Power Deep Neural Network Online Learning Processor for Real-Time Object Tracking Application" is accepted by IEEE Transactions on Circuits and Systems I: Regular Papers (TCAS-I).

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[Sep, 2018] D. Han won the KAIST Electrical Engineering Best Teaching Assistant Award.

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[May, 2018] "​A 141.4 mW Low-Power Online Deep Neural Network Training Processor for Real-time Object Tracking in Mobile Devices" is accepted by IEEE International Symposium on Circuits and Systems (ISCAS).

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[Feb, 2016] D. Han received 16’ Korea Electric Power Corporation (KEPCO) Scholarship for Electric Engineering Student.

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[Mar, 2014] D. Han received Dean's List in Recognition of Outstanding Scholastic Achievement (Electrical Engineering, KAIST).

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1st Author Conference: 7 Papers (Until Feb, 2023)

1st Author Journal: 5 Papers (Until Feb, 2023)