Bonggun Shin | Neural🦑quid Systems

About Me

I am deeply passionate about creating new innovations by bridging the gap between AI and various domains, including but not limited to biotechnology and novel drug development. I earned my Ph.D. in Computer Science from Emory University, receiving the prestigious Graduate Student Research Award. My research there spanned Natural Language Processing (NLP), healthcare, and the development of new pharmaceuticals. During my Ph.D., I co-founded Deargen, an AI-based drug development company. I played a key role in securing Series A and B funding, and as we finalized the Series B round, we reached a pivotal milestone as Amyloid Solution acquired us. Another major accomplishment was our precise prediction of COVID-19 drug efficacies, showcasing our technological prowess. Throughout my career, I have authored several top-tier papers and filed over ten patents. Currently, I am seeking opportunities to further advance my career and contribute to groundbreaking innovations in various fields.

News

[Nov. 2023] The COVID-19 paper is linked to UN Sustainable Development Goals. More info.
[May. 2023] Paper accepted to UAI'23.
[May. 2022] Paper accepted to KDD'22.
[Feb. 2022] We Raised $17M in Series B Financing Round. [More info].
[Dec. 2021] I secured the top prize in the startup pitch competition hosted by KSEA (news).
[Dec. 2021] Paper accepted to AAAI'21.
[Jun. 2021] Paper accepted to MLHC'21.
[May. 2021] Paper accepted to ADBIS'21.
[Feb. 2021] Paper accepted to ACM Chil'21.
[Nov. 2020] Deargen is acquired by Amyloid Solution. [More info].
[Nov. 2020] We Raised $2.3M in Series A Financing Round. [More info].
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Invited Talks

[Sep. 2023] Talk on "Deep Learning Transformation in Drug Discovery" at ISDD'23.
[Jul. 2023] Talk on "Key considerations in AI for Science" at 2023 STEM Career Talk Concert – Artificial Intelligent.
[Jun. 2023] Talk on "Harnessing the Synergy: Unveiling Critical Factors for Successful AI Adoption in Scientific Applications" at Seoul National University.
[Jun. 2023] Talk on "Harnessing the Synergy: Unveiling Critical Factors for Successful AI Adoption in Scientific Applications" at KIAS.
[Aug. 2022] Seminar on "Deep Learning Transformation in Drug Discovery" at KSEA UKC'22.
[Apr. 2022] Seminar on "Deep Learning Transformation in Drug Discovery" at Emory University School of Medicine.
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Publications Selected All Patent

KR-Patent

Method of learning local-neural network model for federated learning

Yeachan Kim, Bonggun Shin

KR102624299B1, 2024.

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US-Patent

New drug prediction method, and apparatus for performing method

Sungsoo Park, Bonggun Shin, Boram Beck

US20230386604A1, 2023.

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arXiv

Learning From Drift: Federated Learning on Non-IID Data via Drift Regularization

Yeachan Kim, Bonggun Shin* (*Corresponding authors)

Technical Report, 2023.

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KR-Patent

Method for predicting structure of protein using twist-based structure updates

Daeseok Lee, Bonggun Shin

KR102554278B1, 2023.

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WO-Patent

Method for predicting medicine for controlling entrance of virus into host

Yoonjung Choi, Bonggun Shin, Keunsoo Kang, Sungsoo Park, Boram Beak

WO2023033283A1, 2023.

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WO-Patent

Method for training multi-task model

Dongpin Oh, Bonggun Shin

WO2023033282A1, 2023.

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WO-Patent

Data sampling method for active learning

Yeachan Kim, Bonggun Shin

WO2023033280A1, 2023.

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WO-Patent

Method for predicting affinity between drug and target substance

Yeachan Kim, Bonggun Shin

WO2023033281A1, 2023.

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WO-Patent

Curriculum-based active learning method

Yeachan Kim, Bonggun Shin

WO2023027278A1, 2023.

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WO-Patent

Training method for neural network model diversity

Dongpin Oh, Bonggun Shin

WO2023027277A1, 2023.

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arXiv

Boosting Convolutional Neural Networks' Protein Binding Site Prediction Capacity Using SE (3)-invariant transformers, Transfer Learning and Homology-based Augmentation

Daeseok Lee, Jeunghyun Byun, Bonggun Shin* (*Corresponding authors)

Technical Report, 2023.

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UAI

Phase-shifted Adversarial Training

Yeachan Kim, Seongyeon Kim*, Ihyeok Seo*, Bonggun Shin* (*Corresponding authors)

The Conference on Uncertainty in Artificial Intelligence (UAI), 2023.

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arXiv

Improving group robustness under noisy labels using predictive uncertainty

Dongpin Oh, Bonggun Shin* (*Corresponding authors)

Technical Report, 2022.

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KDD

In Defense of Core-set: A Density-aware Core-set Selection for Active Learning

Yeachan Kim, Bonggun Shin* (*Corresponding authors)

Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining (KDD), 2022.

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KR-Patent

Gene expression marker screening method using neural network based on gene selection algorithm

Keunsoo Kang, Sungsoo Park, Bonggun Shin

KR102376212B1, 2022.

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AAAI

Improving evidential deep learning via multi-task learning

Dongpin Oh, Bonggun Shin* (*Corresponding authors)

Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2022.

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MLHC

An Interpretable Framework for Drug-Target Interaction with Gated Cross Attention

Yeachan Kim, Bonggun Shin* (*Corresponding authors)

ProceedingMachine Learning for Healthcare (MLHC), 2021.

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ADBIS

SMAT: An Attention-based Deep Learning Solution to the Automation of Schema Matching

Jing Zhang, Bonggun Shin, Jinho D. Choi, Joyce Ho

Proceedings of the 25th European Conference on Advances in Databases and Information Systems (ADBIS), 2021.

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CHIL

Controlled molecule generator for optimizing multiple chemical properties

Bonggun Shin, Sungsoo Park, JinYeong Bak, Joyce C Ho

The ACM Conference on Health, Inference, and Learning (CHIL), 2021.

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Viruses

Target-Centered Drug Repurposing Predictions of Human Angiotensin-Converting Enzyme 2 (ACE2) and Transmembrane Protease Serine Subtype 2 (TMPRSS2) Interacting Approved Drugs for Coronavirus Disease 2019 (COVID-19) Treatment through a Drug-Target Interaction Deep Learning Model

Yoonjung Choi, Bonggun Shin, Keunsoo Kang, Sungsoo Park, Bo Ram Beck

Viruses, 2020.

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AACR

Molecular optimization of phase III trial failed anticancer drugs using target affinity and toxicity-centered multiple properties reinforcement learning

Sungsoo Park, Yoon Ho Ko, Bora Lee, Bonggun Shin, Bo Ram Beck

The American Association for Cancer Research (AACR), 2020.

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PhD Dissertation

Deep Learning Approaches Towards Computerized Drug Discovery

Bonggun Shin

Computer Science Department, Emory University, 2020.

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CSBJ

Predicting commercially available antiviral drugs that may act on the novel coronavirus (SARS-CoV-2) through a drug-target interaction deep learning model

Bo Ram Beck, Bonggun Shin, Yoonjung Choi, Sungsoo Park, Keunsoo Kang

Computational and Structural Biotechnology Journal (CSBJ), 2020.

PDF Paper recognized as Most Cited and linked to UN Sustainable Development Goals.
MLHC

Self-Attention Based Molecule Representation for Predicting Drug-Target Interaction

Bonggun Shin, Sungsoo Park, Keunsoo Kang, Joyce C Ho

Proceeding Machine Learning for Healthcare (MLHC), 2019.

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US-Patent

System, method, and computer program product for compressing neural network models

Bonggun Shin, Hao Yang

PCT/US2019/014206, 2019.

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Scientific reports

Wx: a neural network-based feature selection algorithm for transcriptomic data

Bonggun Shin✞, Sungsoo Park✞, Won Sang Shim, Yoonjung Choi, Kilsoo Kang, Keunsoo Kang (✞equal contribution)

Nature Scientific reports (Scientific reports), 2019.

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Frontiers in genetics

Cascaded Wx: A novel prognosis-related feature selection framework in human lung adenocarcinoma transcriptomes

Bonggun Shin✞, Sungsoo Park✞, Ji Hyung Hong, Ho Jung An, Sang Hoon Chun, Kilsoo Kang, Young-Ho Ahn, Yoon Ho Ko, Keunsoo Kang ($✞$ equal contribution)

Frontiers in genetics, 2019.

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IJCAI

The Pupil Has Become the Master: Teacher-Student Model-Based Word Embedding Distillation with Ensemble Learning

Bonggun Shin, Hao Yang, Jinho D Choi

International Joint Conference on Artificial Intelligence (IJCAI), 2019.

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IEEE-BHI

Multimodal Ensemble Approach to Incorporate Various Types of Clinical Notes for Predicting Readmission

Bonggun Shin, Julien Hogan, Andrew B Adams, Raymond J Lynch, Rachel E Patzer, Jinho D Choi

IEEE-EMBS International Conference on Biomedical and Health Informatics (IEEE-BHI), 2019.

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WO-Patent

Method and system for determining feature influence

Bonggun Shin

WO2019088759A1, 2019.

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EMNLP-WS

Lexicon integrated cnn models with attention for sentiment analysis

Bonggun Shin, Timothy Lee, Jinho D Choi

EMNLP Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis (WASSA), 2019.

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IJCNN

Classification of radiology reports using neural attention models

Bonggun Shin, Falgun H Chokshi, Timothy Lee, Jinho D Choi

international joint conference on neural networks (IJCNN), 2017.

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arXiv

Bayesian group nonnegative matrix factorization for eeg analysis

Bonggun Shin, Alice Oh

Technical Report, 2012.

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URAI

Pattern-Preserving-based Motion Imitation for Robots

Bonggun Shin, Sungho Jo

International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), 2011.

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ICCAS

Non-invasive brain signal interface for a wheelchair navigation

Bonggun Shin, Taesoo Kim, Sungho Jo

International Conference on Control, Automation and Systems (ICCAS), 2010.

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ICHS

Posture Control of a Free Falling Cat Robotic Cat for Soft Landing Using Reinforcement Learning

Bonggun Shin, Jeong-Jung Kim, Ju-Jang Lee

International Conference on Humanized Systems (ICHS), 2008.

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ICCAS

Fast and robust template matching algorithm in noisy image

Bonggun Shin, So-Youn Park, Ju Jang Lee

International Conference on Control, Automation and Systems (ICCAS), 2007.

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About Me

News

Invited Talks

Publications Selected All Patent

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