member portrait Meghal Dani PhD Student International Max-Planck Research School for Intelligent Systems (IMPRS-IS)

Profile

Meghal Dani is a Ph.D. candidate in Computer Science at the International Max Planck Research School for Intelligent Systems (IMPRS-IS), supported by the Else Kröner-Fresenius Foundation (EKFS) through the ClinBrAIn doctoral fellowship. She is affiliated with the Explainable Machine Learning Lab EML and is jointly supervised by Prof. Dr. Zeynep Akata and Dr. rer. nat. Stefanie Liebe. Previously, she also worked with the MIDAS Lab underProf. Dr. Med. Sergios Gatidis, now at Stanford University.

Prior to her Ph.D., Meghal completed her M.Tech in Computational Biology at IIIT Delhi (2017–2019), where she focused on Deep Learning, AI for Science, and earned her bachelor’s degree in Computer Science Engineering from BIT Mesra (2012–2016). She worked as a full-time researcher (2019-2021) at Tata Research and Innovation Labs in the area of Deep Learning and AI under the supervision of Senior Scientist Dr. Lovekesh Vig and Ramya Hebbalaguppe. She particularly contributed to innovations in Medical image analysis and 3D Computer Vision, which led to multiple publications and patents.

Her doctoral research focuses on building safe, interpretable, and robust multimodal AI systems for healthcare applications. She develops methods that integrate clinical text, EEG signals, medical imaging, and video data for improved diagnostic support.

Publications

SemioLLM: Assessing Large Language Models for Semiological Analysis in Epilepsy Research
Meghal Dani, Muthu Jeyanthi Prakash, Zeynep Akata, and Stefanie Liebe
ICML AI4Science Workshop
Paper
Code coming up soon

 

DeViL: Decoding Vision features into Language
Meghal Dani, Isabel Rio-Torto, Stephan Alaniz, and Zeynep Akata
German Conference on Pattern Recognition, 2023 (Oral)
Paper
Code
This was also presented at the ICCV 2023 Workshop on Closing the Loop Between Vision and Language (CLVL).

 

An Efficient Anchor-Free Universal Lesion Detection in CT-Scans
Manu Sheoran, Meghal Dani, Monika Sharma, Lovekesh Vig
International Symposium on Biomedical Imaging (ISBI), 2022
Paper

 

DKMA-ULD: Domain Knowledge augmented Multi-head Attention based Robust Universal Lesion Detection
Manu Sheoran, *Meghal Dani**, Monika Sharma, Lovekesh Vig
The British Machine Vision Conference (BMVC), 2021
Paper

 

3DPoseLite: A Compact 3D Pose Estimation Using Node Embeddings
Meghal Dani, Karan Narain, Ramya Hebbalaguppe
Winter Conference on Applications of Computer Vision (WACV), 2021
Paper

 

PoseFromGraph: Compact 3-D Pose Estimation using Graphs
Meghal Dani, Additya Popli, Ramya Hebbalaguppe
SIGGRAPH Asia, 2020
Paper

 

Mid-air fingertip-based user interaction in mixed reality
Meghal Dani, Gaurav Garg, Ramakrishna Perla, Ramya Hebbalaguppe
ISMAR, 2018
Paper Link

 

For up-to-date information and patents, please also check: Google Scholar.

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