AI Researcher · Computer Vision · Medical Imaging

Aadya Arora

Final-year undergraduate at IIT Gandhinagar (Electrical Engineering, Minor in AI). My research sits at the intersection of vision-language models, medical imaging, and generative AI — with a focus on building efficient, interpretable systems for real-world healthcare deployment.

Incoming PhD · Johns Hopkins University (EECS) · Medical AI
Aadya Arora

About

I work on vision-language models, diffusion-based generative AI, and few-shot medical image classification. Through research stints at IISc Bangalore, University of Bath, IIIT Hyderabad, and an internship at Microsoft IDC, I've built expertise spanning diffusion transformers, attention-based image editing, document AI, and autonomous driving anomaly detection.

I care deeply about making AI systems that are not just accurate, but interpretable and robust enough for deployment at population scale — especially in healthcare settings where reliability directly impacts lives.

Beyond research, I serve as an IEEE reviewer, teach ML and probability courses, and lead career development initiatives at IITGN's Professional Development Council.


Research

Publications

MedFocusCLIP: Improving Few-Shot Classification in Medical Datasets using Pixel-Wise Attention
IEEE ICASSP 2025

A. Arora, V. Namboodiri

Integrated SAM-based pixel attention with CLIP for interpretable and robust few-shot medical image classification. Demonstrates improved performance through attention mechanism visualisation.

Flagship IEEE SPS Conference · CORE A · h5-index: 110

WavShadow: Wavelet-Based Shadow Segmentation and Removal
ICVGIP 2024

S. Jain*, A. Arora*, V. Vekaria, K. Gandhi, S. Raman  (*Equal Contribution)

Wavelet-enhanced pipeline for shadow detection and removal, achieving state-of-the-art performance by combining frequency-domain analysis with deep learning.

Premier Indian Conference in Computer Vision · h5-index: 18

TEMPEST: A Machine Learning Framework for Battery Thermal Prediction and Chemistry Selection
IEEE TIA 2026

A. Arora*, S. Patil*, P. Bhardwaj  (*Equal Contribution)

LSTM-based framework for predicting internal battery temperature and recommending optimal chemistry for EV and grid storage systems.

Q1 Journal · Impact Factor: 4.4 · h5-index: 78

Battery ETHOS: Electro-Thermal Model for State Estimation
Under Review · IEEE COMPEL 2026

S. Patil*, A. Arora*, P. Bhardwaj  (*Equal Contribution)

Electro-thermal modelling approach for accurate battery state estimation, extending the TEMPEST framework.

Q2 Journal · Impact Factor: 1.5 · h5-index: 25


Experience

Internships & Research

May – July 2024
Microsoft IDC

Data Scientist Intern (Received Full-Time PPO)

  • Worked with the Copilot team for PowerPoint; integrated AI to improve structured presentation creation.
  • Built datasets by extracting and structuring text & formatting info from slides in JSON format.
  • Developed data pipelines to generate diverse formatting examples; improved model performance through error analysis, leading to a Pre-Placement Offer.
Dec 2024 – Apr 2025
IISc Bangalore · VAL Lab

Research Intern — Diffusion Transformers

  • Layer-wise ablation of Diffusion Image Transformers (DiTs); studied how features evolve for structure vs. style.
  • Designed unified attention masks to reduce prompt leakage in multi-region text-to-image generation.
  • Ran LoRA and DreamBooth experiments to understand editing behaviour at different transformer depths.
May – July 2024
University of Bath

Research Intern — Vision-Language Models

  • Developed AdaptHIPIE: lightweight adapters into HIPIE for open-vocabulary referring segmentation.
  • Achieved 85.15 mIoU on RefCOCO, improving visual-text alignment with CLIP features.
  • Concurrently developed MedFocusCLIP, rethinking annotation-efficient methods for the medical domain.
Dec 2023 – Jan 2024
IIIT Hyderabad · CVIT Lab

Research Intern — Autonomous Driving

  • Analysed corner cases in Indian traffic datasets (IDD, CODA) for unstructured environments.
  • Used class-agnostic RPNs to capture anomalous instances beyond predefined categories.
  • Built a pipeline using semantic segmentation & common-class suppression to surface safety-critical anomalies.

Recognition

Achievements

PhD Offer
Johns Hopkins University

Fully funded PhD position in EECS to specialise in Medical AI (Ranked #24 globally, #1 for Medical AI).

Industry
Microsoft PPO — Data Scientist

Secured full-time Pre-Placement Offer at Microsoft IDC with highest compensation in a tech role from IITGN.

Publication
ICASSP 2025 · Cash Prize

Only B.Tech student in the batch to publish at IEEE's flagship SPS conference. Awarded ₹25k cash prize by IITGN.

Service
IEEE Reviewer

Official reviewer for IEEE Signal Processing Letters (2025–present). Completed 4 technical peer-reviews to date.

Invitation
Microsoft Research India Summit 2025

One of few students nationwide selected for India's premier annual AI academic summit.

Competition
Inter-IIT Tech Meet — Top 3

Ranked Top 3 for Research Paper Poster across all 23 IITs in EE and CSE domains.

Teaching
Teaching Assistant × 3 Courses

TA for Machine Learning (250+ students), Probability & Data Visualization (400+ students), and Principles of EE.

Outreach
Featured in Quill Magazine

Featured in the April 2026 edition; also served as Problem Statement Setter for IITGN's flagship HackRush '26.


Expertise

Skills

Languages

Python C++ C MATLAB

Deep Learning

CNNs Vision Transformers CLIP Diffusion Models SAM LSTMs

Frameworks

PyTorch TensorFlow OpenCV mmDetection Azure OpenAI

Domains

Computer Vision Medical Imaging Generative AI Document AI Autonomous Driving