Berk Atıl

Berk Atıl

PhD Student at Penn State University

Bio

Berk Atıl is a PhD student working on Natural Language Processing and Teaching Assistant at Penn State University. If you are interested in the NLP community at Penn State, feel free to check our website.

His interests are Machine Learning, Natural Language Processing and Chemical Language Processing. He got his BSc in Computer Engineering from Bogazici University.

News

  • [May 2024] :rocket: I am starting my internship at Comcast AI!
  • [Mar 2024] :tada: Our work VerAs got accepted to AIED 2024!
  • [Nov 2022] :tada: Our work DebiasedDTA got accepted to RECOMB 2023!
  • [Nov 2022] :tada: Our work Look back, look around: A systematic analysis of effective predictors for new outlinks in focused Web crawling (LBLA) got accepted to Knowledge Based Systems!
  • [Aug 2022] Started PhD at Penn State University in Computer Science and Engineering!
  • [Feb 2022] Graduated from Bogazici University Computer Engineering with high honors!

Education

Pennsylvania State University, State College, PA, The USA
PhD. in Computer Science and Engineering 2022 - Present
Advisor: Prof. Rebecca Jane Passonneau


Bogazici University, Istanbul, Turkey
BSc. in Computer Engineering 2016 - 2022
Advisor: Prof. Arzucan Ozgur
GPA: 3.61/4.0 Thesis: DebiasedDTA: Debiasing Approach for Drug-Target Affinity Prediction

University of Twente, Enschede, The Netherlands
Erasmus Student in Technical Computer Science 2020 - 2020

Publications

  • Atil, B., Sheikhi Karizaki, M., & J. Passonneau, R. (2024, July). VerAs: Verify Then Assess STEM Lab Reports. In International Conference on Artificial Intelligence in Education (pp. 133-148). Cham: Springer Nature Switzerland. [paper]
  • Özçelik, R., Bağ, A., Atil, B., Barsbey, M., Özgür, A., & Ozkirimli, E. (2023). A Framework for Improving the Generalizability of Drug–Target Affinity Prediction Models. In Research in Computational Molecular Biology: 27th Annual International Conference, RECOMB 2023, Istanbul, Turkey, April 16–19, 2023, Proceedings (Vol. 13976, p. 262). Springer Nature. [paper]
  • Barsbey, M., Özçelik, R., Bağ, A., Atil, B., Özgür, A., & Ozkirimli, E. (2023). A Computational Software for Training Robust Drug–Target Affinity Prediction Models: pydebiaseddta. Journal of Computational Biology, 30(11), 1240-1245. [paper]
  • Dang, T. K. N., Bucur, D., Atil, B., Pitel, G., Ruis, F., Kadkhodaei, H., & Litvak, N. (2022). Look back, look around: A systematic analysis of effective predictors for new outlinks in focused Web crawling. Knowledge-Based Systems, 110126. [paper]