Our Faculty

Sung-Hyuk Cha


Seidenberg School of CSIS

Computer Science NY

  • @New York City
    163 William Street 228
Office Hours
New York City

Spring 2022

Wed, Thu 3:50pm-5:50pm

Tue 4:30pm-5:30pm

Office Hours

Spring 2022

Office Hours

Spring 2022


PhD, State University of New York at Buffalo, 2001
Computer Science

MS, Rutgers University, 1996
Computer Science

BS, Rutgers University, 1994
Computer Science

Awards and Honors

Center for Community Outreach, - Faculty Leadership Award
Pace University, December 5, 2019 - Provosts Open Educational Resource Grant 2019 ∼ 2020


Biometric Distinctiveness of Brain Signals Based on EEG
Li, S., Cha, S. & Tappert, C. (2018, October).

Minimising Branch Crossings in Phylogenetic Trees
Cha, S. (2016, June). International Journal of Applied Pattern Recognition. Vol 3 (Issue 1) , pages 22-37. http://www.inderscienceonline.com/doi/abs/10.1504/IJAPR.2016.076982

Graphs whose vertices are forests with bounded degree: Open Problems
Cha, S., Ducasse, E., Kravette, K. J., Quintas, L. V. & Shor, J. P. (2015, December). International Journal Graph Theory and Its Applications. Vol 1 (Issue 2) , pages 123-129. http://www.mililink.com/upload/article/903485702IJGTA%20v1i2%20123-129.pdf


Cha, S. (2019, December 6). Machine Intelligence Day. Topics in Dichotomy Transformation Model for Biometric Systems. Pace University Seidenberg school, New York NY.

Cha, S. (2019, May 2). 7th International Workshop on Biometrics and Forensics. Feature Extraction based on High Order Statistics measures and Entropy for EEG biometrics. IEEE, Cancun, Mexico.

Cha, S. (2019, February). 3rd International Conference on Machine Vision and Information Technology. Feature Extraction Method for EEG based Biometrics. Guangzhou, China.

Cha, S. (2018, October 22). 29th IEEE International Conference on Biometrics: Theory, Applications, and Systems. Biometric Distinctiveness of Brain Signal Based on EEG. IEEE, Los Angeles, California.

Cha, S. (2017, May 15). 30th International FLAIRS Conference. On ROC Curve Analysis of Artificial Neural Network Classifiers. AAAI, Marco Island, Florida.


Document Analysis; Pattern Recognition & Machine Intelligence & Data Mining; Distance Measures & Pattern Matching Algorithm;


AAAI (Assoc. for the Advancement of Artificial Intelligence)[Member]


IEEE, Computer Society[Member]



Korean PACS Society[Member]

Pattern Recognition Society[Member]


Korean-American Scientist and Engineer Association[Council member]


  • Machine Intelligence Day 2019[Committee Chair]
    Desc: Organized the Machine Intelligence Day 2019 and edited the Proceedings.
    Committee's Key Accomplishments: Organized the Machine Intelligence Day 2019 and edited the Proceedings.
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