Sungroh Yoon

12.8k total citations · 5 hit papers
234 papers, 7.2k citations indexed

About

Sungroh Yoon is a scholar working on Molecular Biology, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Sungroh Yoon has authored 234 papers receiving a total of 7.2k indexed citations (citations by other indexed papers that have themselves been cited), including 71 papers in Molecular Biology, 66 papers in Artificial Intelligence and 53 papers in Computer Vision and Pattern Recognition. Recurrent topics in Sungroh Yoon's work include RNA and protein synthesis mechanisms (19 papers), Genomics and Phylogenetic Studies (15 papers) and Gene expression and cancer classification (15 papers). Sungroh Yoon is often cited by papers focused on RNA and protein synthesis mechanisms (19 papers), Genomics and Phylogenetic Studies (15 papers) and Gene expression and cancer classification (15 papers). Sungroh Yoon collaborates with scholars based in South Korea, United States and Ethiopia. Sungroh Yoon's co-authors include Seonwoo Min, Byunghan Lee, Sunyoung Kwon, Giovanni De Micheli, Seokjoong Kim, Hyun-Soo Choi, Hui Kwon Kim, Hyeyoung Min, Byunggook Na and Jooyoung Choi and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Sungroh Yoon

219 papers receiving 7.0k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Deep learning in bioinformatics

2016 1.0k citations Seonwoo Min, Byunghan Lee et al. profile →
ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models

2021 346 citations Sungroh Yoon et al. profile →
Deep Learning for Anomaly Detection in Time-Series Data: Review, Analysis, and Guidelines

2021 306 citations Jihun Yi, Sungroh Yoon et al. IEEE Access profile →
Spiking-YOLO: Spiking Neural Network for Energy-Efficient Object Detection

2020 272 citations Seongsik Park, Byunggook Na et al. profile →
A comprehensive survey of deep learning for time series forecasting: architectural diversity and open challenges

2025 18 citations Sungroh Yoon et al. profile →

Peers

Countries citing papers authored by Sungroh Yoon

Since Specialization

Citations

This map shows the geographic impact of Sungroh Yoon's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sungroh Yoon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sungroh Yoon more than expected).

Fields of papers citing papers by Sungroh Yoon

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sungroh Yoon. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sungroh Yoon. The network helps show where Sungroh Yoon may publish in the future.

Co-authorship network of co-authors of Sungroh Yoon

This figure shows the co-authorship network connecting the top 25 collaborators of Sungroh Yoon. A scholar is included among the top collaborators of Sungroh Yoon based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sungroh Yoon. Sungroh Yoon is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	Unleashing Multi-Hop Reasoning Potential in Large Language Models through Repetition of Misordered Context 2025 ·(unknown), (unknown), (unknown), (unknown), Junsung Park, Sungroh Yoon	0
2	Applications and Future Perspectives of Large Language Models in Otolaryngology-Head and Neck Surgery: A Comprehensive Survey 2025 ·Clinical and Experimental Otorhinolaryngology ·Ji‐Young Ahn, (unknown), Mun Young Chang, Sungroh Yoon	0
3	Data-driven analysis on perovskite solar cell devices 2024 ·Current Applied Physics ·(unknown), (unknown), Jongbeom Kim, Jino Im, Sungroh Yoon, Sang Il Seok	1
4	Machine learning of metal-organic framework design for carbon dioxide capture and utilization 2024 ·Journal of CO2 Utilization ·(unknown), Sungroh Yoon, Sung Eun Jerng	9
5	Interactive Text-to-Image Retrieval with Large Language Models: A Plug-and-Play Approach 2024 ·(unknown), (unknown), Junsung Park, Jihun Yi, Sungroh Yoon	3
6	GeoT: A Geometry-Aware Transformer for Reliable Molecular Property Prediction and Chemically Interpretable Representation Learning 2023 ·ACS Omega ·(unknown), Ji‐Won Park, Tae-Won Kang, (unknown), Byunghan Lee, Sungroh Yoon	5
7	AIVariant: a deep learning-based somatic variant detector for highly contaminated tumor samples 2023 ·Experimental & Molecular Medicine ·(unknown), (unknown), Byunggook Na, (unknown), Lee Sael, Sun Kim, Sungroh Yoon, Daehyun Baek	1
8	Data Embedding Scheme for Efficient Program Behavior Modeling With Neural Networks 2022 ·IEEE Transactions on Emerging Topics in Computational Intelligence ·(unknown), (unknown), Ho Bae, Sungroh Yoon, Yunheung Paek	2
9	AligNART: Non-autoregressive Neural Machine Translation by Jointly Learning to Estimate Alignment and Translate 2021 ·Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing ·(unknown), Sungwon Kim, Sungroh Yoon	21
10	Generation of a more efficient prime editor 2 by addition of the Rad51 DNA-binding domain 2021 ·Nature Communications ·(unknown), Jung Min Lim, Seonwoo Min, (unknown), Dong Young Kim, Jae‐Sung Woo, Hiroshi Nishimasu, Sung‐Rae Cho, Sungroh Yoon, Seokjoong Kim	65
11	Pre-Training of Deep Bidirectional Protein Sequence Representations With Structural Information 2021 ·IEEE Access ·Seonwoo Min, (unknown), Siwon Kim, Hyun-Soo Choi, Byunghan Lee, Sungroh Yoon	27
12	Protein transfer learning improves identification of heat shock protein families 2021 ·PLoS ONE ·Seonwoo Min, (unknown), Byunghan Lee, Sungroh Yoon	12
13	Learn2Evade: Learning-Based Generative Model for Evading PDF Malware Classifiers 2021 ·IEEE Transactions on Artificial Intelligence ·Ho Bae, (unknown), Yo-Han Kim, Uiwon Hwang, Sungroh Yoon, Yunheung Paek	11
14	Memory-Augmented Neural Networks on FPGA for Real-Time and Energy-Efficient Question Answering 2020 ·IEEE Transactions on Very Large Scale Integration (VLSI) Systems ·Seongsik Park, (unknown), (unknown), Byunggook Na, Sungroh Yoon	2
15	Gradient Masking of Label Smoothing in Adversarial Robustness 2020 ·IEEE Access ·(unknown), Ho Bae, Sungroh Yoon	20
16	Sequence-specific prediction of the efficiencies of adenine and cytosine base editors 2020 ·Nature Biotechnology ·(unknown), Hui Kwon Kim, Sungtae Lee, Younggwang Kim, (unknown), Jinman Park, Jae Woo Choi, (unknown), (unknown), Seonwoo Min, Zhejiu Quan, Ji Hun Kim, Hoon‐Chul Kang, Sungroh Yoon, Seokjoong Kim	81
17	Pediatric Sleep Stage Classification Using Multi-Domain Hybrid Neural Networks 2019 ·IEEE Access ·(unknown), Siwon Kim, Hyun-Soo Choi, Yoon Gi Chung, Sun Ah Choi, Hunmin Kim, Sungroh Yoon, Hee Hwang, Ki Joong Kim	20
18	Learning-Based Instantaneous Drowsiness Detection Using Wired and Wireless Electroencephalography 2019 ·IEEE Access ·Hyun-Soo Choi, Seonwoo Min, Siwon Kim, Ho Bae, (unknown), (unknown), (unknown), Chang‐Ho Yun, Sungroh Yoon	18
19	Comprehensive ensemble in QSAR prediction for drug discovery 2019 ·BMC Bioinformatics ·Sunyoung Kwon, Ho Bae, (unknown), Sungroh Yoon	156
20	RNA design rules from a massive open laboratory 2014 ·Proceedings of the National Academy of Sciences ·Jeehyung Lee, Wipapat Kladwang, Min Jae Lee, (unknown), Martin Azizyan, Hanjoo Kim, Alex Limpaecher, Snehal Gaikwad, Sungroh Yoon, Adrien Treuille, Rhiju Das, (unknown)	182

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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