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20212026
most citedDeep Generative Views to Mitigate Gender Classification Bias Across Gender-Race Groups

3 citations · 4 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2026

PVminerLLM2: Improving Structured Extraction of Patient Voice via Preference Optimization

Samah Fodeh, Linhai Ma, Ganesh Puthiaraju +7

Motivation: Patient-generated text contains critical information on patients' lived experiences, social context, and care engagement, but remains largely unstructured, limiting its…

cs.AI2026

EPPC-OASIS: Ontology-Aware Adaptation and Structured Inference Refinement for Electronic Patient-Provider Communication Mining in Secure Messages

Samah Fodeh, Sreeraj Ramachandran, Elyas Irankhah +7

Secure patient-provider messages contain clinically important communication behaviors that are difficult to characterize manually at scale. The Electronic Patient-Provider Communic…

cs.LG2026

STaR-DRO: Stateful Tsallis Reweighting for Group-Robust Structured Prediction

Samah Fodeh, Ganesh Puthiaraju, Elyas Irankhah +5

Structured prediction with large language models requires outputs that are label-accurate, ontology-constrained, structurally valid, and evidence-grounded under label imbalance and…

cs.CV2024★ 1 cited

A Self-Supervised Learning Pipeline for Demographically Fair Facial Attribute Classification

Sreeraj Ramachandran, Ajita Rattani

Published research highlights the presence of demographic bias in automated facial attribute classification. The proposed bias mitigation techniques are mostly based on supervised…

cs.CV2022★ 3 cited

Deep Generative Views to Mitigate Gender Classification Bias Across Gender-Race Groups

Sreeraj Ramachandran, Ajita Rattani

Published studies have suggested the bias of automated face-based gender classification algorithms across gender-race groups. Specifically, unequal accuracy rates were obtained for…

cs.CV2021

Harnessing Unlabeled Data to Improve Generalization of Biometric Gender and Age Classifiers

Aakash Varma Nadimpalli, Narsi Reddy, Sreeraj Ramachandran +1

With significant advances in deep learning, many computer vision applications have reached the inflection point. However, these deep learning models need large amount of labeled da…

cs.CV2021

An Experimental Evaluation on Deepfake Detection using Deep Face Recognition

Sreeraj Ramachandran, Aakash Varma Nadimpalli, Ajita Rattani

Significant advances in deep learning have obtained hallmark accuracy rates for various computer vision applications. However, advances in deep generative models have also led to t…