Now, I’m a Ph D Student in Optimization and Statistical Inference Lab OSI (Advisor: Se-Young Yun, KAIST).

I worked as a PhD student researcher @ Google Research, Qualcomm AI, and DynamoFL (YCW22 selected startup).

📫 Working: KAIST AI (Seoul, Korea).

🔭 My Blog:https://taehyeon.oopy.io/

🤔 LinkedIn:https://www.linkedin.com/in/taehyeon-kim-6a1239207/

💬 Contact:potter32@kaist.ac.kr,kimtaehyeon610@gmail.com (permanant)

I am a research scientist! Feel free to contact me!

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1. FINE_officialFINE_officialPublic

   NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"

   Python 39 14

2. jhoon-oh/kd_datajhoon-oh/kd_dataPublic

   IJCAI 2021, "Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation"

   Jupyter Notebook 40 6

3. KAIST-AI-NeurIPS2019-MicroNet-2nd-place-solutionKAIST-AI-NeurIPS2019-MicroNet-2nd-place-solutionPublic

   NeurIPSCD2019, MicroNet Challenge hosted by Google, Deepmind Researcher, "Efficient Model for Image Classification With Regularization Tricks".

   Python 26 7

4. ssfodssfodPublic

   [Official] NeurIPS 2023, "Navigating Data Heterogeneity in Federated Learning: A Semi-Supervised Approach for Object Detection"

   Shell 20

5. joonkeekim/Instructive-Decodingjoonkeekim/Instructive-DecodingPublic

   Official repository of "Distort, Distract, Decode: Instruction-Tuned Model Can Refine its Response from Noisy Instructions", ICLR 2024 Spotlight

   Python 20

6. dnn_orthogonalitydnn_orthogonalityPublic

   [IEEE Access 2022] Revisiting Orthogonality Regularization: A Study for Convolutional Neural Networks in Image Classification

   Jupyter Notebook 7