Gissella Bejarano

Assistant Professor of Computer Science

Bio

Professor Bejarano earned her doctoral degree from the State University of New York at Binghamton, where she also pursued a Master's in Computer Science thanks to a Fulbright Scholarship. She has lectured at Universidad Peruana Cayetano Heredia and Pontificia Universidad Católica del Perú. After her doctoral studies, she worked as a Postdoctoral Researcher at Baylor University in Texas. Her research has focused on machine learning for sequential data, such as sign language processing and forecasting in smart city problems. She has been awarded the AI2050 Early Career Fellowship from Schmidt Futures to explore iconicity in sign language and gestures through artificial intelligence methods. She has experience in the financial and insurance industries, as well as serving in the Peruvian Government in topics related to Artificial Intelligence. Bejarano is a member of the LatinxInAI community and the Research Experience for Peruvian Undergrad program (REPU).

Education

PhD, Computer Science, Binghamton University (SUNY), 2021
MS, Computer Science, Binghamton University (SUNY), 2017
BS, Informatics Engineering, Pontificia Universidad Católica del Perú, 2009
 

Research Interests / Areas of Focus

Sign Language Processing
Smart Cities
Data Science and Artificial Intelligence

Selected Publications

Bejarano, G., Huamani-Malca, J., Cerna-Herrera, F., Alva-Manchego, F., & Rivas, P. (2022, June). PeruSIL: A Framework to Build a Continuous Peruvian Sign Language Interpretation Dataset. In Proceedings of the LREC2022 10th Workshop on the Representation and Processing of Sign Languages: Multilingual Sign Language Resources (pp. 1-8).

Jui, T. D., Bejarano, G. M., & Rivas, P. (2022, June). A machine learning-based segmentation approach for measuring similarity between sign languages. In sign-lang@ LREC 2022 (pp. 94-101). European Language Resources Association (ELRA).

Bejarano, G., DeFazio, D., & Ramesh, A. (2019). Deep Latent Generative Models for Energy Disaggregation. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 850-857. https://doi.org/10.1609/aaai.v33i01.3301850

Bejarano, G., Kulkarni, A., Raushan, R., Seetharam, A., & Ramesh, A. (2019, November). Swap: Probabilistic graphical and deep learning models for water consumption prediction. In Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (pp. 233-242).

Bejarano, G., Jain, M., Ramesh, A., Seetharam, A., & Mishra, A. (2018, June). Predictive analytics for smart water management in developing regions. In 2018 IEEE International Conference on Smart Computing (SMARTCOMP) (pp. 464-469). IEEE.
 

Creative Work

First Peruvian Sign Language – Spanish Dictionary: www.dvlsp.link

Awards and Honors

AI2050 Early Career Fellow. Schmidt Futures, 2022

Teaching Assistant Award. Department of Computer Science, SUNY Binghamton 2021 

Google Anita Borg Scholarship for Grace Hopper Conference (GHC). Orlando, USA 2017 

Google Travel Scholarship for Lisbon Machine Learning Summer School (LxMLS). Portugal 2017 

Fulbright Scholarship from Peru for master program at SUNY Binghamton. USA 2015-2017 

Media Links

https://www.linkedin.com/in/gissemari/

Image of Gissella Bejarano.

Contact Information

Academic School

School of Computer Science and Mathematics

Office

Hancock 3008

Email

gissella.bejarano@marist.edu

Phone

(845) 575-3000 ext. 2623