PhD in Computer Science
University of Texas at Arlington
2021 – 2026
Hi, I'm Saurav, a Machine Learning Researcher at Luber Lab, where I recently completed my PhD under Dr. Jacob Luber. My research focuses on generative models in medical imaging. I'm working on AI models that use multimodal approaches to help improve cancer diagnostics and explore personalized treatment options, with applications in virtual staining, multiplexed imaging, and computational pathology. My work is published in NEJM AI, IEEE, and Springer venues.
Research Interests
Background
Education
B.Sc. in Computer Science
Shahjalal University of Science & Technology
2013 – 2018
Experience
Research Assistant
University of Texas at Arlington
2022 – Present
Software Engineer
pipilika.com
2017 – 2020
Recent News
May 2026
Our paper "UNIStainNet: Foundation-Model-Guided Virtual Staining of H&E to IHC" accepted at ACM-BCB 2026 (Calabria, Italy) 🎉
April 2026
Successfully defended my PhD dissertation, "Generative Imaging for Computational Pathology" 🎓
March 2026
New preprint: "UNIStainNet: Foundation-Model-Guided Virtual Staining of H&E to IHC" now available on arXiv
September 2025
Our paper "Cross-Domain Image Synthesis: Generating H&E from Multiplex Biomarker Imaging" accepted at MICAD 2025 (Springer LNCS)
October 2024
Our poster "Bridging mIF and H&E: A GAN-based Approach for Cross-Modality Image Translation in Digital Pathology" presented at APBJC 2024 (Okinawa, Japan)
May 2024
Our paper "Spatialvisvr: An Immersive, Multiplexed Medical Image Viewer" accepted at IEEE CIBCB 2024 (Natal, Brazil)
Show earlier news
April 2024
New work on "Peptide Sequencing Via Protein Language Models" to appear at ACM-BCB 2024 (Shenzhen, China)
April 2024
Happy to announce that I have passed my Comprehensive Exam and became a PhD Candidate! 🎉
April 2024
Paper "An Augmented Reality Multiplexed Pathology Image Viewer" accepted at IEEE ISBI 2024 (Athens, Greece)
April 2024
"Histopathology Slide Indexing and Search" selected for ACM BCB 2024 Highlights Track (Chapel Hill, USA)
August 2023
"A SSIM Guided cGAN Architecture" selected as a highlight paper by ACM SIGBio 🏆
July 2023
Published "B-NER: A Novel Bangla Named Entity Recognition Dataset" in IEEE Access
June 2023
Our work "Real-Time Diagnostic Integrity Meets Efficiency" accepted at IEEE ICASSP 2023 (Rhodes Island, Greece)
April 2023
Paper "A SSIM Guided cGAN Architecture for Clinically Driven Generative Image Synthesis of Multiplexed Spatial Proteomics Channels" accepted at IEEE CIBCB 2023 (Eindhoven, Netherlands)
April 2023
Paper "Clinically Relevant Latent Space Embedding" accepted at IEEE ISBI 2023 (Cartagena, Colombia)
Featured Publications
Cross-Domain Image Synthesis: Generating H&E from Multiplex Biomarker Imaging
A SSIM Guided cGAN Architecture for Clinically Driven Generative Image Synthesis of Multiplexed Spatial Proteomics Channels
Histopathology Slide Indexing and Search — Are We There Yet?
Clinically Relevant Latent Space Embedding of Cancer Histopathology Slides through Variational Autoencoder Based Image Compression
For a complete list of publications, visit my Google Scholar profile.
Skills
Languages: Python, Java, SQL
Deep Learning: PyTorch, TensorFlow, JAX, GANs, VAEs, Diffusion Models, Transformers
Computer Vision & Medical Imaging: Image Synthesis, Computational Pathology, Virtual Staining, Contrastive Learning
ML Tooling: scikit-learn, XGBoost, Weights & Biases, OpenCV, Pandas, NumPy
Systems & Infrastructure: Docker, Linux, Git, HPC Clusters, Embedded Inference (Jetson, ARM)
Data Engineering: Elasticsearch, Apache Solr, Django, MongoDB, PostgreSQL