General Information
Full Name | Kevin Nam |
Date of Birth | August 7th, 1995 |
Languages | French, English, Korean |
Education
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2019
B.S.
Seoul National University (SNU)
- Electrical and Computer Engineering (ECE)
Research Experience
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2023-Now
NoZero-Error Computing Neural Networks over Encrypted Data:Beyond Mathematical Methods (funded by NRF)
- Research on designing efficient and accurate neural network services over encrypted data using various non-mathematical approaches.
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2023
Neural Network Program to FHE Transpiler (funded by ETRI)
- Designing a transpiling process from neural network programs (e.g., Tensorflow, PyTorch) to FHE programs (e.g., MS SEAL, TFHE-rs).
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2023-Now
Secure and Efficient CKKS Computation on Cloud (funded by CryptoLab)
- This project's goal is to design a secure and efficient technique to compute CKKS on cloud environment. This is a cornerstone research to develop a SaaS on cloud.
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2023-Now
Accurate Privacy-Preserving RNN (funded by National Intelligence Service)
- This project's goal is to design a privacy-preserving RNN. Similar to the previous year's work, we aim to find a new approach in efficiently implementing Privacy Preserving Techniques for accurate RNN computing, which would lead to huge models as transformers.
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2022
Implementing Zero-error PPAI (funded by National Intelligence Service)
- This project was funded by NIS to design a Zero-error Privacy Preserving AI inference framework. The framework is implemented using multiple privacy-preserving techniques.
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2022
FPGA Accelerator for CKKS (funded by CryptoLab)
- This project was funded by CryptoLab to design FPGA accelerator for the well-known specific FHE scheme, CKKS. This is a cornerstone research to develop HW Intellectual Property for CryptoLab.
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2021
FPGA Accelerator for FHE (funded by National Intelligence Service)
- This project was funded by NIS to design HW accelerator to accelerate FHE computation.
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2020-2024
Post-Quantum-Cryptography Hardware Accelerator (w. Samsung LSI)
- This project's goal is to design PQC modules that are to be implemented in devices (e.g., smartphoes, IPTV) as HW components. As co-team manager, I participated in most of the process from algorithm analysis to HW implementation.
Honors and Awards
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2023
- ASK2023 NIPA Director Award, KIPS
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2021
- Undang Academic Award, KIPS
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2021
- ASK2021 Best Paper Award, ASK2021
Academic Interests
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HW Security
- HW monitoring
- Black-boxing HW modules
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Privacy Preserving Techniques
- Fully Homomorphic Encryption (FHE)
- Trusted Execution Environment (TEE)
- Multi-Party Computing (MPC)
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HW Acceleration
- FPGA Accelerators
- Processing in Memory
- Accelerating Privacy Preserving Techniques
Prog. Languages & HW EDA Tools
- C, C++, Python, Verilog, Java, Xilinx(Vivado, Vitis, HLS), Cadence(Xcelium), Synopsys(Design Compiler) etc.
Other Interests
- Hobbies: Baseball, Painting etc.