Home | Philip Chikontwe

Biography

I am a Research Fellow at the Yu Lab, Harvard Medical School and Harvard University, working with Prof. Kun-Hsing Yu. Previously, I worked at the Medical Imaging and Signal Processing Laboratory (MISPL), Daegu Gyeongbuk Institute of Science and Technology with Prof. Sang Hyun Park.

I received my Ph.D. in Robotics and Mechatronics Engineering from DGIST, South Korea in 2023, M.S. degree in Computer Science from Chonbuk National University, South Korea in 2018, and B.S. degree in Computer Science from Abdelhamid Mehri Constantine 2 University, Algeria in 2015.

My research focuses on leveraging machine learning, including large language models (LLMs) and computer vision, to tackle challenges in cancer diagnosis and tumor characterization. Through my interdisciplinary expertise, I strive to push the boundaries of how machine learning and language-based approaches can transform cancer diagnostics and pave the way for novel research in personalized medicine and precision oncology.

Highlight · Nature Portfolio

Biallelic loss of RB1 in hepatocellular carcinoma as synthetic lethal target for artificial intelligence-guided therapy

Signal Transduction and Targeted Therapy, August 2026

Call for papers · Special Issue, Frontiers in Medicine

Multimodal, Foundation and Agent AI for Real-World Clinical Decision Support: Patient-Level Diagnosis, Prognosis, and Treatment Selection

Associate Topic Editor · Submission deadline January 22, 2027

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News

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Sep 2026
service Serving as Associate Topic Editor, with Junhan Zhao, for the Frontiers in Medicine special issue “Multimodal, Foundation and Agent AI for Real-World Clinical Decision Support”. Submissions are open until January 22, 2027. Read →
Sep 2026
Oral Privacy-Preserving Federated Distillation of Foundation Models for Multi-Institutional Pediatric Glioma Recurrence Prediction was selected for an oral presentation at the PedAItrics workshop, MICCAI 2026.
Aug 2026
highlight Our work on AI-guided therapy targeting biallelic RB1 loss in hepatocellular carcinoma is published in Signal Transduction and Targeted Therapy (Nature Portfolio). Read →
Jul 2026
preprint New preprint on arXiv: FDIR, harmonizing fidelity and human–machine preference in lossy compression image restoration. Read →
Mar 2026
preprint New preprint on arXiv: international expert perspectives on computational pathology in the era of foundation and agentic AI. Read →
Jul 2025
paper Paper on subject-adaptive meta-learning for personalized BCI published in Information Fusion. Read →

Selected Publications

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STTT

STTTNature Portfolio

Biallelic loss of RB1 in hepatocellular carcinoma as synthetic lethal target for artificial intelligence-guided therapy

Jihyun An, Wonkyung Kim, Xiumei Zhang, Philip Chikontwe, …, Ju Hyun Shim

Signal Transduction and Targeted Therapy, 2026

Paper

@article{an2026biallelic,
  title = {Biallelic loss of RB1 in hepatocellular carcinoma as synthetic lethal target for artificial intelligence-guided therapy},
  author = {Jihyun An and Wonkyung Kim and Xiumei Zhang and Philip Chikontwe and Jin‐Sung Ju and Bora Oh and Ji‐Hye Oh and Eun Ju Yang and Hyun Namgung and Dakeun Lee and Yue Pu and Lijie Chen and Sang Hyun Park and Joong Sup Shim and Chang Ohk Sung and Ju Hyun Shim},
  journal = {Signal Transduction and Targeted Therapy},
  year = {2026},
  doi = {10.1038/s41392-026-02815-0}
}

MedIA

Efficient one-shot federated learning on medical data using knowledge distillation with image synthesis and client model adaptation

Myeongkyun Kang, Philip Chikontwe, Soopil Kim, Kyong Hwan Jin, Ehsan Adeli, Kilian M. Pohl, Sang Hyun Park

Medical Image Analysis, 2025

Paper

@article{kang2025efficient,
  title = {Efficient one-shot federated learning on medical data using knowledge distillation with image synthesis and client model adaptation},
  author = {Myeongkyun Kang and Philip Chikontwe and Soopil Kim and Kyong Hwan Jin and Ehsan Adeli and Kilian M. Pohl and Sang Hyun Park},
  journal = {Medical Image Analysis},
  year = {2025},
  doi = {10.1016/j.media.2025.103714}
}

IEEE TMI

FR-MIL: Distribution Re-Calibration-Based Multiple Instance Learning With Transformer for Whole Slide Image Classification

Philip Chikontwe, Meejeong Kim, Jaehoon Jeong, Hyun Jung Sung, Heounjeong Go, Soo Jeong Nam, Sang Hyun Park

IEEE Transactions on Medical Imaging, 2024

Paper

@article{chikontwe2024frmil,
  title = {FR-MIL: Distribution Re-Calibration-Based Multiple Instance Learning With Transformer for Whole Slide Image Classification},
  author = {Philip Chikontwe and Meejeong Kim and Jaehoon Jeong and Hyun Jung Sung and Heounjeong Go and Soo Jeong Nam and Sang Hyun Park},
  journal = {IEEE Transactions on Medical Imaging},
  year = {2024},
  doi = {10.1109/tmi.2024.3446716}
}

MICCAI 2024

Low-Shot Prompt Tuning for Multiple Instance Learning Based Histology Classification

Philip Chikontwe, Myeongkyun Kang, Miguel A. Cabra de Luna, Siwoo Nam, Sang Hyun Park

International Conference on Medical Image Computing and Computer-Assisted Intervention, 2024

Paper

@inproceedings{chikontwe2024lowshot,
  title = {Low-Shot Prompt Tuning for Multiple Instance Learning Based Histology Classification},
  author = {Philip Chikontwe and Myeongkyun Kang and Miguel A. Cabra de Luna and Siwoo Nam and Sang Hyun Park},
  booktitle = {International Conference on Medical Image Computing and Computer-Assisted Intervention},
  year = {2024},
  doi = {10.1007/978-3-031-72083-3_27}
}

CVPR 2022

CAD: Co-Adapting Discriminative Features for Improved Few-Shot Classification

Philip Chikontwe, Soopil Kim, Sang Hyun Park

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022

Paper

@inproceedings{chikontwe2022cad,
  title = {CAD: Co-Adapting Discriminative Features for Improved Few-Shot Classification},
  author = {Philip Chikontwe and Soopil Kim and Sang Hyun Park},
  booktitle = {2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
  doi = {10.1109/cvpr52688.2022.01415}
}

MedIA

Weakly supervised segmentation on neural compressed histopathology with self-equivariant regularization

Philip Chikontwe, Hyun Jung Sung, Jaehoon Jeong, Meejeong Kim, Heounjeong Go, Soo Jeong Nam, Sang Hyun Park

Medical Image Analysis, 2022

Paper

@article{chikontwe2022weakly,
  title = {Weakly supervised segmentation on neural compressed histopathology with self-equivariant regularization},
  author = {Philip Chikontwe and Hyun Jung Sung and Jaehoon Jeong and Meejeong Kim and Heounjeong Go and Soo Jeong Nam and Sang Hyun Park},
  journal = {Medical Image Analysis},
  year = {2022},
  doi = {10.1016/j.media.2022.102482}
}

MedIA

Dual attention multiple instance learning with unsupervised complementary loss for COVID-19 screening

Philip Chikontwe, Miguel A. Cabra de Luna, Myeongkyun Kang, Kyung Soo Hong, June Hong Ahn, Sang Hyun Park

Medical Image Analysis, 2021

Paper

@article{chikontwe2021dual,
  title = {Dual attention multiple instance learning with unsupervised complementary loss for COVID-19 screening},
  author = {Philip Chikontwe and Miguel A. Cabra de Luna and Myeongkyun Kang and Kyung Soo Hong and June Hong Ahn and Sang Hyun Park},
  journal = {Medical Image Analysis},
  year = {2021},
  doi = {10.1016/j.media.2021.102105}
}