Anuvind Pramod

Anuvind Pramod

BS-MS Graduate, IISER Pune · Master’s Thesis, Jug Lab, Human Technopole, Milan

BS-MS (Interdisciplinary) · Graduated May 2026

I recently graduated from IISER Pune with a BS-MS (Interdisciplinary) degree, completing my Master’s thesis at the Jug Lab, Human Technopole, Milan, advised by Dr. Florian Jug. My thesis developed deep learning models for biological age estimation from screening mammography, using the “mammographic age gap” as a novel imaging biomarker for personalized breast cancer risk stratification.

My interests span medical image analysis, causal inference, self-supervised and transfer learning, and interpretable AI for clinical decision support — problems where computation can directly influence patient outcomes.

Seeking PhD positions in AI for medicine, causal inference & clinical AI · Available Fall/Winter 2026

/ / GitHub / CV (PDF)

Research

Master’s Thesis · Jug Lab, Human Technopole, Milan · Jul 2025 – Apr 2026

Biological Age Estimation from Mammography for Breast Cancer Risk Stratification code ↗

Developed an end-to-end deep learning framework for predicting biological age from screening mammograms — achieving a MAE of 3.13 years, demonstrating competitive performance against existing benchmarks. The architecture combines distilled DINOv3 backbones with hierarchical multi-head attention. Investigated 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.

Course Project · Medical Image Analysis, IISER Pune · Feb – Apr 2025

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.

Research Project · Tumor Microenvironment Lab & Leelavati Lab, IISER Pune · Aug 2024 – Jan 2025

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.

Research Project · Tumor Microenvironment Lab, IISER Pune · Jan – Aug 2024

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.

iGEM IISER Pune 2023 · Feb – Nov 2023

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.

Projects

Personal Project · Sep 2026 – Present

Private PhD Research Assistant

v0.1 · In development

Built a local-first, evidence-grounded RAG pipeline that collects AI/ML PhD advertisements from five curated Europe/UK sources, indexes page chunks with local embeddings, and answers questions with source citations. Structured extraction checks values against normalized source excerpts; unsupported values remain unknown rather than being guessed.

37 documents crawled 375 evidence chunks 28 unit tests passing 10/10 saved-answer consistency checks 2 opportunities with textual support

Snapshot: 4 September 2026. Includes an offline parser demo. Text matching and citation checks do not measure overall answer accuracy or confirm current availability.

Python Ollama Qwen3 LlamaIndex ChromaDB Firecrawl
View on GitHub ↗

Publications & Talks

Presented

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

Technical Skills

Machine Learning & AI

PyTorch scikit-learn ViT / DINOv3 / Swin CNNs Attention Mechanisms Transfer Learning Fine-tuning GradCAM SHAP Weights & Biases TensorBoard

Programming & Computing

Python C++ Bash HPC / SLURM Distributed Training Git Linux Docker uv

Medical Image Analysis

Mammography Histopathology Multiplex IF Halo / inForm DICOM preprocessing Whole-slide imaging

Bioinformatics & Data Science

scRNA-seq Scanpy Seurat Statistical Modeling Design of Experiments Matplotlib Seaborn AutoDock

Generative AI & LLM Systems

PEFT / LoRA QLoRA Local LLMs Ollama / Qwen3 LlamaIndex ChromaDB Firecrawl Embeddings & Vector Search AI Safety & Guardrails RAG Systems Evidence-Grounded Extraction Citation Validation LLM Evaluation

Relevant Coursework

Machine Learning Natural Language Processing Deep Learning Computer Vision Statistical Inference Linear Algebra Bayesian Approaches Computational Biology Cancer Biology Molecular Cell Biology Systems and Implementation of Algorithms

Honors & Awards

Leadership & Service

Blog

Paper Review · Jul 2026

Understanding the Causal Transformer (Melnychuk et al., ICML 2022)

How do transformers reason about counterfactual outcomes under time-varying treatments? This post unpacks the Causal Transformer — a method for estimating individual treatment effects over time using attention mechanisms adapted for causal inference, enabling more credible predictions of what would have happened under alternative treatment sequences.

Read more →