Professors Mohammad Hossein Manshaei and Anita Raja won the grants for a project on a multimodal intrusion-detection tool leveraging generative AI. PhD. student Mahdi Ara Loodaricheh will be the student lead on the project. https://www.gc.cuny.edu/news/announcing-cuny-winners-2025-google-cybersecurity-grants

Congratulations to DAIR Ph.D. students Nan Jia and Mahdi Arab Loodaricheh who jointly won first palce for their posters for their posters titled “Handling Uncertainty in Health Data using Generative Algorithms” and ” ReLess: A Framework for Assessing Safety in Deep Learning Systems”. DAIR Masters student Kat Desai won secodn place for her poster titled “Predicting Green Gentrification in New York City.” Great work!!

Jeffrey successfully defended his Masters thesis titled” Intuiting Interaction: Meta-Reasoning and Meta-Learning as Foundations for Intelligent User Interfaces” Congrats Jeffrey!

Raffi Khatchadourian, Tatiana Castro Vélez, Mehdi Bagherzadeh, Nan Jia,  and Anita Raja. Hybridize functions: A tool for automatically refactoring imperative Deep Learning programs to graph execution. In Fundamental Approaches to Software Engineering, FASE ’25. ETAPS, May 2025. To appear. (11/31; 35% acceptance rate). Distinguished Paper Award 

The paper is titled “Handling Uncertainty in Health Data using Generative Algorithms,” co-authored by “M. A. Loodaricheh, N. Majmudar, A. Raja, and A. Salleb-Aouissi,

Dylan successfully defended his Masters thesis titled “Dynamic Approaches to Missing Data in Healthcare: Evaluating Ensemble Models, Feature Selection and Meta-Features”. Congrats Dylan on your degree!

Article on DAIR lab research in CUNY Research in Focus Vol 1, Issue 3 “The Year of Artificial Intelligence at CUNY“.

Y. C. Lin, D. Mallia, A. O. Clark-Sevilla, A. Catto, A. Leshchenko*, Q. Yan, D. M. Haas, R. Wapner, I. Pe’er, A. Raja, A. Salleb-Aouissi. “A comprehensive and bias-free machine learning approach for risk prediction of preeclampsia with severe features in a nulliparous study cohort. BMC Pregnancy Childbirth 24, 853 (2024). https://doi.org/10.1186/s12884-024-06988-w”

IJCAI 2024 DC Program https://ijcai24.org/doctoral-consortium-track/

N. Jia, A. Raja, R. Khatchadourian, “ReLESS: A Framework for Assessing Safety in Deep Learning Systems“, Workshop on AI Safety at The International Joint Conference in Artificial Intelligence  (IJCAI 2024), Jeju, S. Korea, August 2024. (Nominated for Best Workshop Paper award)