Sungchul Kim

Data Scientist

San Jose

Sungchul is a data scientist at the Systems Technology Lab of Adobe Research. I received my Ph.D. in Computer Science and Engineering at Pohang University of Science and Technology (POSTECH) in summer 2015 under the supervision of Prof. Hwanjo Yu. My thesis was on constructing mutation profiles for top-k patient search and stratification of cancer subtypes.

My research interests focus on user behavior modeling and visitor stitching and include representing and analyzing data by using data-mining techniques including regression, ranking, and dimensionality reduction, and also I have been working on recommender system, online advertisement and named entity recognition.


On Proximity and Structural Role-based Embeddings in Networks: Misconceptions, Techniques, and Applications

Rossi, R., Jin, D., Kim, S., Ahmed, N., Koutra, D., Lee, J., Rossi, R. (Jun. 1, 2020)

Transactions on Knowledge Discovery from Data (TKDD)

A Structural Graph Representation Learning Framework

Rossi, R., Ahmed, N., Koh, E., Kim, S., Rao, A., Abbasi-Yadkori, Y. (Feb. 4, 2020)

Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM)

Graph Convolutional Networks with Motif-based Attention

Lee, J., Rossi, R., Kong, X., Kim, S., Koh, E., Rao, A. (Nov. 3, 2019)

CIKM, 2019

Heterogeneous Network Motifs

Rossi, R., Ahmed, N., Carranza, A., Arbour, D., Rao, A., Kim, S., Koh, E. (Aug. 5, 2019)


Latent Network Summarization: Bridging Network Embedding and Summarization

Jin, D., Rossi, R., Koutra, D., Koh, E., Kim, S., Rao, A. (Aug. 4, 2019)

KDD '19 Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Domain Switch-Aware Holistic Recurrent Neural Network for Modeling Multi-Domain User Behavior

Kim, D., Kim, S., Zhao, H., Li, S., Rossi, R., Koh, E. (Feb. 11, 2019)

WSDM '19 Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining

Visualizing Uncertainty and Alternatives in Event Sequence Predictions

Guo, S., Du, F., Malik, S., Koh, E., Kim, S., Liu, L., Kim, D., Zha, H., Cao, N. (Jan. 4, 2019)

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2019)

Dynamic Network Embeddings: From Random Walks to Temporal Random Walks

Nguyen, G., Lee, J., Rossi, R., Ahmed, N., Koh, E., Kim, S. (Dec. 10, 2018)

2018 IEEE International Conference on Big Data (Big Data)

Conversion Prediction from Clickstream: Modeling Market Prediction and Customer Predictability

Yeo, J., Hwang, S., Kim, S., Koh, E., Lipka, N. (Nov. 30, 2018)

IEEE Transactions on Knowledge and Data Engineering

Predictive Analysis by Leveraging Temporal User Behavior

Chen, C., Kim, S., Bui, H., Rossi, R., Kveton, B., Koh, E., Bunescu, R. (Oct. 22, 2018)


Perceptual Similarity Ranking of Temporal Heatmaps Using Convolutional Neural Networks

Malik, S., Kim, S., Koh, E. (Oct. 22, 2018)

Proceedings of the Workshop on Understanding Subjective Attributes of Data, with the Focus on Evoked Emotions (EE-USAD 2018)

Attention Models in Graphs: A Survey

Lee, J., Rossi, R., Kim, S., Ahmed, N., Koh, E. (Jul. 20, 2018)

Transactions on Knowledge Discovery from Data (TKDD)

Continuous-Time Dynamic Network Embeddings

Nguyen, G., Lee, J., Rossi, R., Ahmed, N., Koh, E., Kim, S. (Apr. 27, 2018)

Proceedings of the 3rd International Workshop on Learning Representations for Big Networks (WWW BigNet)

Continuous-Time Dynamic Network Embeddings

Nguyen, G., Lee, J., Rossi, R., Ahmed, N., Koh, E., Kim, S. (Apr. 23, 2018)

WWW BigNet, 2018

Probabilistic Visitor Stitching on Cross-device Web Logs

Kim, S., Kini, N., Pujara, J., Getoor, L., Koh, E. (Apr. 3, 2017)


Predicting Online Purchase Conversion for Retargeting

Yeo, J., Kim, S., Koh, E., Hwang, S., Lipa, N. (Feb. 6, 2017)