Rituraj

About

I am a Marie Skłodowska-Curie Postdoctoral Fellow at the Artificial Intelligence in Medicine Lab, University of Barcelona, working at the intersection of generative AI, computer vision, medical image analysis, and trustworthy clinical AI.

My current research focuses on trustworthy generative and multimodal AI for breast cancer imaging, including mammography, ultrasound, MRI/DBT-related imaging, cross-modal image synthesis, pseudo-3D reconstruction, anomaly detection, and digital breast twin representations.

My long-term research vision is to develop clinically reliable AI systems that can connect multiple breast imaging modalities and generate patient-specific visual representations for cancer detection, longitudinal monitoring, and decision support.

I completed my PhD in Computer Science and Engineering from IIT Indore, where my research focused on generative deep learning and video anomaly detection. I also worked at Samsung Research, Bangalore, where I gained experience in applied AI, computer vision, scalable experimentation, and research-to-engineering workflows.

Research interests:

• Generative AI for medical imaging

• Breast cancer AI and ultrasound AI

• Mammography, MRI, DBT, and multimodal imaging

• 2D-to-3D / pseudo-3D reconstruction

• Digital twins for healthcare

• Diffusion models, flow matching, GANs, and synthetic medical data

• Mamba/state-space models and efficient vision architectures

• Trustworthy AI, anomaly detection, robustness, privacy, and clinical validation

I am open to research collaborations, visiting researcher opportunities, postdoctoral/faculty positions, and research scientist roles in medical AI, generative AI, computer vision, and digital health.

Google Scholar: https://scholar.google.com/citations?user=hLYP314AAAAJ&hl=en

Email: [email protected]

Employment

• University of Barcelona MSCA Postdoc
  2025 - 2026
• Samsung (India) Lead Engineer
  2025 - 2025
• Institut de Biomedicina de la Universitat de Barcelona Visiting researcher
  2024 - 2024
• Samsung (India) PhD research intern
  2024 - 2024

Education

• Indian Institute of Technology Indore PhD
  2020 - 2024
• Indian Institute of Information Technology Vadodara MTech
  2018 - 2020

Projects & Funding

Projects & funding information is unavailable.

Publications (10)

• CUNIT-GAN: Constraining Latent Space for Unsupervised Multi-domain Image-to-Image Translation via Generative Adversarial Network
  Communications in Computer and Information Science 2026 DOI: 10.1007/978-3-031-93688-3_12
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• Enhancing Image Style Transfer with PAIN-GAN: A Dual-Stream Encoder Incorporating GAN
  Communications in Computer and Information Science 2025 DOI: 10.1007/978-981-96-6975-2_11
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• iMAppGAN: Integrated Motion Appearance Generative Adversarial Networks for Video Anomaly Detection
  Communications in Computer and Information Science 2025 DOI: 10.1007/978-981-96-6972-1_27
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• Attention-guided generator with dual discriminator GAN for real-time video anomaly detection
  Engineering Applications of Artificial Intelligence 2024 DOI: 10.1016/j.engappai.2023.107830
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• CVAD-GAN: Constrained video anomaly detection via generative adversarial network
  Image and Vision Computing 2024 DOI: 10.1016/j.imavis.2024.104950
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• MAAD-GAN: Memory-Augmented Attention-Based Discriminator GAN for Video Anomaly Detection
  Communications in Computer and Information Science 2024 DOI: 10.1007/978-3-031-58535-7_14
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• VALD-GAN: video anomaly detection using latent discriminator augmented GAN
  Signal Image and Video Processing 2024 DOI: 10.1007/s11760-023-02750-5
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• STemGAN: spatio-temporal generative adversarial network for video anomaly detection
  Applied Intelligence 2023 DOI: 10.1007/s10489-023-04940-7
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• Video Anomaly Latent Training GAN (VALT GAN): Enhancing Anomaly Detection Through Latent Space Mining
  2023 IEEE Symposium Series on Computational Intelligence Ssci 2023 2023 DOI: 10.1109/SSCI52147.2023.10371992
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• Efficient user assignment in crowd sourcing applications
  2016 International Conference on Advances in Computing Communications and Informatics Icacci 2016 2016 DOI: 10.1109/ICACCI.2016.7732208
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