activity
20222026
most citedDistraction is All You Need for Fairness

2 citations · 7 across the 9 of their papers we have counts for

collaborators

12 papers

cs.LG2026

Geometric Relevance Is Not Sufficient: Evaluating Focused Post-Training Supervision in Diffusion Docking

Michael Brown, Maryam Rahimimovassagh, Mehdi Yazdani-Jahromi +2

Diffusion-based molecular docking requires learning a corrective score field across a broad corruption distribution, yet individual pose errors can differ substantially in their st…

q-bio.QM2026

MIRAGE: Measuring Interpolation and Redundancy in Affinity GEneralization

Mehdi Yazdani-Jahromi, Sanjay Padhi, Ivan Garibay

Deep learning now underpins structure-based drug design, from complex and affinity prediction to ligand ranking and pose generation. Recent co-folding models reportedly approach fr…

cs.LG2025

FairContrast: Enhancing Fairness through Contrastive learning and Customized Augmenting Methods on Tabular Data

Aida Tayebi, Ali Khodabandeh Yalabadi, Mehdi Yazdani-Jahromi +1

As AI systems become more embedded in everyday life, the development of fair and unbiased models becomes more critical. Considering the social impact of AI systems is not merely a…

q-bio.QM2025

Equi-mRNA: Protein Translation Equivariant Encoding for mRNA Language Models

Mehdi Yazdani-Jahromi, Ali Khodabandeh Yalabadi, Ozlem Ozmen Garibay

The growing importance of mRNA therapeutics and synthetic biology highlights the need for models that capture the latent structure of synonymous codon (different triplets encoding…

q-bio.BM2025★ 1 cited

BoKDiff: Best-of-K Diffusion Alignment for Target-Specific 3D Molecule Generation

Ali Khodabandeh Yalabadi, Mehdi Yazdani-Jahromi, Ozlem Ozmen Garibay

Structure-based drug design (SBDD) leverages the 3D structure of biomolecular targets to guide the creation of new therapeutic agents. Recent advances in generative models, includi…

cs.LG2024

Fair Bilevel Neural Network (FairBiNN): On Balancing fairness and accuracy via Stackelberg Equilibrium

Mehdi Yazdani-Jahromi, Ali Khodabandeh Yalabadi, AmirArsalan Rajabi +3

The persistent challenge of bias in machine learning models necessitates robust solutions to ensure parity and equal treatment across diverse groups, particularly in classification…

cs.LG2024★ 2 cited

HELM: Hierarchical Encoding for mRNA Language Modeling

Mehdi Yazdani-Jahromi, Mangal Prakash, Tommaso Mansi +2

Messenger RNA (mRNA) plays a crucial role in protein synthesis, with its codon structure directly impacting biological properties. While Language Models (LMs) have shown promise in…

cs.MA2024

Agent-Based Modeling of C. Difficile Spread in Hospitals: Assessing Contribution of High-Touch vs. Low-Touch Surfaces and Inoculations' Containment Impact

Sina Abdidizaji, Ali Khodabandeh Yalabadi, Mehdi Yazdani-Jahromi +2

Health issues and pandemics remain paramount concerns in the contemporary era. Clostridioides Difficile Infection (CDI) stands out as a critical healthcare-associated infection wit…

cs.MA2024★ 1 cited

Controlling the Misinformation Diffusion in Social Media by the Effect of Different Classes of Agents

Ali Khodabandeh Yalabadi, Mehdi Yazdani-Jahromi, Sina Abdidizaji +2

The rapid and widespread dissemination of misinformation through social networks is a growing concern in today's digital age. This study focused on modeling fake news diffusion, di…

cs.LG2023

FragXsiteDTI: Revealing Responsible Segments in Drug-Target Interaction with Transformer-Driven Interpretation

Ali Khodabandeh Yalabadi, Mehdi Yazdani-Jahromi, Niloofar Yousefi +3

Drug-Target Interaction (DTI) prediction is vital for drug discovery, yet challenges persist in achieving model interpretability and optimizing performance. We propose a novel tran…

cs.CV2022★ 1 cited

Through a fair looking-glass: mitigating bias in image datasets

Amirarsalan Rajabi, Mehdi Yazdani-Jahromi, Ozlem Ozmen Garibay +1

With the recent growth in computer vision applications, the question of how fair and unbiased they are has yet to be explored. There is abundant evidence that the bias present in t…

cs.LG2022★ 2 cited

Distraction is All You Need for Fairness

Mehdi Yazdani-Jahromi, AmirArsalan Rajabi, Ali Khodabandeh Yalabadi +2

Bias in training datasets must be managed for various groups in classification tasks to ensure parity or equal treatment. With the recent growth in artificial intelligence models a…