Anuvind Pramod
Master’s Thesis Fellow · Jug Lab, Human Technopole, Milan
BS-MS (Interdisciplinary) · IISER Pune · Expected May 2026
I am a final-year student at IISER Pune, completing my Master’s thesis at the Jug Lab, Human Technopole, Milan, advised by Dr. Florian Jug. My thesis develops deep learning models for biological age estimation from screening mammography, using “mammographic age gap” as a novel imaging biomarker for personalized breast cancer risk stratification.
My interests span medical image analysis, self-supervised and transfer learning, and interpretable AI for clinical decision support — problems where computation can directly influence patient outcomes.
Seeking PhD positions in computational oncology, imaging biomarkers & clinical AI · Starting 2026
Research
Biological Age Estimation from Mammography for Breast Cancer Risk Stratification code ↗
Building an end-to-end deep learning framework for predicting biological age from screening mammograms — achieving a MAE of 3.2 years, showing competitive performance against existing benchmarks. The architecture combines distilled DINOv3 backbones with hierarchical multi-head attention. Investigating mammographic age gap (biological − chronological age) as a novel imaging biomarker for personalized cancer risk assessment. Trained on large-scale multi-institutional datasets using HPC / SLURM infrastructure.
Deep CNN for Histopathology Image Classification code ↗
Designed a custom CNN with stacked convolutional blocks, batch normalization, and progressive dropout for multi-class lung and colon cancer classification. Achieved 99.58% test accuracy and AUC 0.9999 on the LC25000 benchmark. Conducted ablation studies comparing architectural variants against ResNet baselines.
Single-Cell Transcriptomic Analysis of YAP/TAZ in Breast Cancer
Developed a reproducible Python/Scanpy scRNA-seq pipeline for the lab. Investigated co-expression and functional redundancy of YAP/TAZ transcriptional co-activators in breast cancer vs. normal mammary epithelial cells using dimensionality reduction, clustering, and differential expression analysis.
Spatial Protein Expression Analysis in Breast Tumor Microenvironment
Analyzed THBS1 expression across tumor cell types using multiplex immunofluorescence imaging (PanCK and CD3 markers). Performed quantitative spatial analysis using Halo and inForm software.
Computational Optimization for Sustainable Aviation Fuel Production
Led the Measurements division (statistical modeling via Design of Experiments) and the Wet Lab team. Outcome: Best Education Award, nominated for Best Climate Crisis Project, Top-10 global undergraduate ranking at iGEM Jamboree, Paris.
Publications & Talks
Poster · Conference
Deep Learning-Based Mammographic Age Estimation: Towards an Image-Based Biomarker for Cancer Risk Prediction
Cancer Research UK Data-Driven Cancer Research Conference
Edinburgh International Conference Centre, UK · February 24–26, 2026
Manuscript on mammographic biological age estimation in preparation.
Technical Skills
Machine Learning & AI
Programming & Computing
Medical Image Analysis
Bioinformatics & Data Science
Blog
Notes on medical imaging papers, AI in medicine, and research reflections — coming soon.