Learning Reduced Latent Representations of Protein Structure Data. - Fardina Fathmiul Alam; Taseef Rahman; Amarda Shehu (BCB, 2019)

Variational Autoencoders for Protein Structure Prediction. - Fardina Fathmiul Alam; Amarda Shehu (BCB, 2020)

Towards more equitable question answering systems: How much more data do you need? - Arnab Debnath; Navid Rajabi; Fardina Fathmiul Alam; Antonios Anastasopoulos (ACL/IJCNLP (2), 2021)

Generating Physically-Realistic Tertiary Protein Structures with Deep Latent Variable Models Learning Over Experimentally-available Structures. - Fardina Fathmiul Alam; Amarda Shehu (BIBM, 2021)

Deep Latent-Variable Models for Controllable Molecule Generation. - Yuanqi Du; Yinkai Wang; Fardina Fathmiul Alam; Yuanjie Lu; Xiaojie Guo 002; Liang Zhao 002; Amarda Shehu (BIBM, 2021)

Unsupervised multi-instance learning for protein structure determination. - Fardina Fathmiul Alam; Amarda Shehu (J. Bioinform. Comput. Biol., 2021)

Equivariant Encoding based GVAE (EqEn-GVAE) for Protein Tertiary Structure Generation. - Taseef Rahman; Fardina Fathmiul Alam; Amarda Shehu (BIBM, 2022)

RAGent: A Self-Learning RAG Agent for Adaptive Data Science Education. - Mariia Vetluzhskikh; Fardina Fathmiul Alam (ICPEC, 2025)