NEWS: Our lab team won 2nd place award in CVPR 2022 LOng-form VidEo Understanding (LOVEU) challenge track3 (2nd in Recall@1 and 1st in Recall@3) [tech report]. Congratulations Hyeonyu, Jongeun and Jeonghun!


NEWS: Starting from Aug. 2021, I joined Artificial Intelligence Graduate School and Department of Computer Science and Engineering at Ulsan National Institute of Science and Technology (UNIST) as an assistant professor. Currently I am looking for self-motivated and curiosity-driven graduate students and undergraduate interns to join my group. If you are interested, please send me an email with your CV and transcript.



Currently, I am
an assistant professor in Artificial Intelligence Graduate School and Department of Computer Science and Engineering at Ulsan National Institute of Science and Technology (UNIST). Previously, I was an applied scientist at Amazon Alexa AI and a lead research scientist at a start-up company, ObEN. Before then, I was a postdoctoral scholar in the Computing and Mathematical Sciences department at the California Institute of Technology working with Prof. Yisong Yue. I completed my PhD in 2016 at Toyota Technological Institute at Chicago, a philanthropically endowed academic computer science institute located on the University of Chicago campus, and my advisor was Prof. Karen Livescu. I did my master in Computer Science at USC and bachelor in Computer Science & Engineering and Mathematics at POSTECH.

My main research interests span various problems related to the fields of Machine Learning and applications to Computer Vision and Language Processing. Specifically, I am interested in Deep Learning, Generative Models, Multimodal Learning, Transfer Learning, and Spatial-Temporal Data Analysis.

Students

· PhD students

Jaeyeon Bae

Seonghee Han

Hyunmin Song

· Master's students

Dahye Jang

Jeonghun Kang

Seok-Un Kang

Chaeri Kim

Hyeonyu kim

Jongeun Kim

Taegyeong Lee

Trinh Ngo

Wonjin Yang


· Undergraduate interns

Seokhoon Jeong

Geonho Kim

Chanbin Lee




Teaching

· CSE221 Data Structure, Fall 2022, UNIST

· AI517 Deep Learning for Natural Language Processing and Understanding, Spring 2022, UNIST

· AI503 AI Toolkits, Fall 2021, UNIST

· CS159 Advanced Topics in Machine Learning: Structured Prediction, Spring 2017, Caltech



Selected Peer Reviewed Publications

(for the complete list of the publications, please see my Google scholar page)


· Hyeshin Chu, Joohee Kim, Seongouk Kim, Hongkyu Lim, Hyunwook Lee, Seungmin Jin, Jongeun Lee, Taehwan Kim and Sungahn Ko, An Empirical Study on How People Perceive AI-generated Music, ACM Conference on Information and Knowledge Management (CIKM), 2022 (To Appear)


· Seyed Hamidreza Mohammadi and Taehwan Kim, One-shot voice conversion with disentangled representations by leveraging phonetic posteriorgrams, Interspeech, 2019 [pdf]


· Chao Yang, Taehwan Kim, Ruizhe Wang, Hao Peng and C.-C. Jay Kuo, Show, attend and translate: Unsupervised image translation with self-regularization and attention, IEEE Transactions on Image Processing 28 (10), 4845-4856 (2019) [pdf]


· Chao Yang, Taehwan Kim, Ruizhe Wang, Hao Peng and C.-C. Jay Kuo, ESTHER: Extremely Simple Image Translation Through Self-Regularization, British Machine Vision Conference (BMVC), 2018 [pdf]


· Seyed Hamidreza Mohammadi and Taehwan Kim, Investigation of Using Disentangled and Interpretable Representations for One-shot Cross-lingual Voice Conversion, Interspeech, 2018 [pdf]


· Taehwan Kim, Jonathan Keane, Weiran Wang, Hao Tang, Jason Riggle, Gregory Shakhnarovich, Diane Brentari and Karen Livescu, Lexicon-Free Fingerspelling Recognition from Video: Data, Models, and Signer Adaptation, Computer Speech and Language, 2017 [pdf]

· Sarah Taylor, Taehwan Kim, Yisong Yue, James Krahe, Anastasio Garcia Rodriguez, Jessica Hodgins, Moshe Mahler, Iain Matthews, A Deep Learning Approach for Generalized Speech Animation, ACM Conference on Computer Graphics (SIGGRAPH), 2017 [pdf][supplementary][demo video]

· Taehwan Kim, Weiran Wang, Hao Tang and Karen Livescu, Signer-independent Fingerspelling Recognition with Deep Neural Network Adaptation, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016 (Best Student Paper of Speech and Language Processing) [pdf]

· Taehwan Kim, Yisong Yue, Sarah Taylor and Iain Matthews, A Decision Tree Framework for Spatiotemporal Sequence Prediction, ACM Conference on Knowledge Discovery and Data Mining (KDD), 2015 [pdf]

· Taehwan Kim, Greg Shakhnarovich and Karen Livescu, Fingerspelling Recognition with semi-Markov Conditional Random Fields, IEEE International Conference on Computer Vision (ICCV), 2013 [pdf]

· Taehwan Kim, Karen Livescu and Greg Shakhnarovich, American Sign Language Fingerspelling Recognition With Phonological Feature-based Tandem Models, IEEE Workshop on Spoken Language Technology (SLT), 2012 [pdf]

· Taehwan Kim, Greg Shakhnarovich and Raquel Urtasun, Sparse Coding for Learning Interpretable Spatio-temporal Primitives, Neural Information Processing Systems (NIPS), 2010 [pdf]

· Jihie Kim, Erin Shaw, Saul Wyner, Taehwan Kim and Jia Li, Discerning Affect in Student Discussions, Annual Meeting of the Cognitive Science Society (CogSci), 2010

· Jihie Kim, Jia Li and Taehwan Kim: Identifying student online discussions with unanswered questions, K-CAP, 2009

· Jihie Kim, Taehwan Kim and Jia Li, Identifying unresolved issues in online students discussions: A multi-phase dialogue classification approach, Proc. of the AI in Education Conference (AIED), 2009