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I am a Machine Learning researcher with extensive experience developing evaluation frameworks for large language models, particularly in the assessment of radiology reports. My work also includes deep learning-based physics-informed data augmentation techniques for improving low-dose CT imaging. Over the years, I have broadened my academic research interests to include biometric identification, cross-modal super-resolution, and generative adversarial networks focused on face and iris recognition. I am passionate about applying advanced machine learning and data science methods at the intersection of medical imaging and AI to produce impactful outcomes. My career journey includes roles at the FDA and West Virginia University, where I developed innovative ML models and contributed to multiple peer-reviewed publications. I look forward to continuing to grow and contribute in high-impact roles that leverage my expertise in medical imaging and AI technologies.…I am a Machine Learning researcher with extensive experience developing evaluation frameworks for large language models, particularly in the assessment of radiology reports. My work also includes deep learning-based physics-informed data augmentation techniques for improving low-dose CT imaging. Over the years, I have broadened my academic research interests to include biometric identification, cross-modal super-resolution, and generative adversarial networks focused on face and iris recognition. I am passionate about applying advanced machine learning and data science methods at the intersection of medical imaging and AI to produce impactful outcomes. My career journey includes roles at the FDA and West Virginia University, where I developed innovative ML models and contributed to multiple peer-reviewed publications. I look forward to continuing to grow and contribute in high-impact roles that leverage my expertise in medical imaging and AI technologies.

Moktari Mostofa

Data Scientist, AI Engineer, Data Analyst, +1

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I am a Machine Learning researcher with extensive experience developing evaluation frameworks for large language models, particularly in the assessment of radiology reports. My work also includes deep learning-based physics-informed data augmentation techniques for improving low-dose CT imaging. Over the years, I have broadened my academic research interests to include biometric identification, cross-modal super-resolution, and generative adversarial networks focused on face and iris recognition. I am passionate about applying advanced machine learning and data science methods at the intersection of medical imaging and AI to produce impactful outcomes. My career journey includes roles at the FDA and West Virginia University, where I developed innovative ML models and contributed to multiple peer-reviewed publications. I look forward to continuing to grow and contribute in high-impact roles that leverage my expertise in medical imaging and AI technologies.…I am a Machine Learning researcher with extensive experience developing evaluation frameworks for large language models, particularly in the assessment of radiology reports. My work also includes deep learning-based physics-informed data augmentation techniques for improving low-dose CT imaging. Over the years, I have broadened my academic research interests to include biometric identification, cross-modal super-resolution, and generative adversarial networks focused on face and iris recognition. I am passionate about applying advanced machine learning and data science methods at the intersection of medical imaging and AI to produce impactful outcomes. My career journey includes roles at the FDA and West Virginia University, where I developed innovative ML models and contributed to multiple peer-reviewed publications. I look forward to continuing to grow and contribute in high-impact roles that leverage my expertise in medical imaging and AI technologies.

Available to hire

I am a Machine Learning researcher with extensive experience developing evaluation frameworks for large language models, particularly in the assessment of radiology reports. My work also includes deep learning-based physics-informed data augmentation techniques for improving low-dose CT imaging. Over the years, I have broadened my academic research interests to include biometric identification, cross-modal super-resolution, and generative adversarial networks focused on face and iris recognition.

I am passionate about applying advanced machine learning and data science methods at the intersection of medical imaging and AI to produce impactful outcomes. My career journey includes roles at the FDA and West Virginia University, where I developed innovative ML models and contributed to multiple peer-reviewed publications. I look forward to continuing to grow and contribute in high-impact roles that leverage my expertise in medical imaging and AI technologies.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Work Experience

Machine Learning Engineer - ORISE Fellow at Food and Drug Administration (FDA)

May 1, 2025 - August 6, 2025

Designed and implemented automated radiology report evaluation methods for large language models to improve consistency of assessments and explored the capability of LLMs as alternatives to human experts in evaluating radiology reports. Developed deep learning-based physics-informed data augmentation (PIDA) models to simulate low-dose CT scans from high-dose data, contributing to lung nodule detection advancements.

Machine Learning Researcher - Graduate Research Assistant at West Virginia University

May 1, 2023 - August 6, 2025

Worked on funded projects related to biometrics and computer vision, including face recognition at extreme poses using pose attention mechanisms, joint pose estimation and frontalization, benchmarking video super-resolution for face recognition, identity-aware face hallucination with GANs, and cross-spectral iris recognition using coupled conditional GANs. Also developed joint super-resolution and vehicle detection networks for aerial imagery and cross-modal image enhancement.

Machine Learning Engineer - ORISE Fellow at Food and Drug Administration (FDA)

May 1, 2025 - August 6, 2025

Designed and implemented automated evaluation methods for large language models (LLMs) to improve the consistency of radiology report assessments. Explored the potential of LLMs to act as alternatives to human experts in evaluating LLM-generated X-ray reports. Developed a deep learning-based physics-informed data augmentation model to synthesize low-dose noise characteristics from high-dose CT scans, improving lung nodule detection applications. Authored papers currently under review and released code on GitHub.

Machine Learning Researcher - Graduate Research Assistant at West Virginia University

May 1, 2023 - August 6, 2025

Led multiple research projects funded by intelligence and biometric research centers focusing on face recognition at extreme poses, joint pose estimation with face frontalization, benchmarking deep video super-resolution methods optimized for face recognition, and identity-aware face hallucination using GANs. Developed a coupled conditional GAN architecture for cross-spectral iris recognition, and designed novel networks for joint super-resolution and vehicle detection in aerial imagery, achieving superior cross-domain performance.