🔬 Machine Learning Engineer at Moffitt Cancer Center > Explore our work on [GitHub|Hugging Face]
- LinkedIn: linkedin.com/in/aakash-tripathi
- ResearchGate: researchgate.net/profile/Aakash-Tripathi-2
- GitHub: github.com/lab-rasool
- Hugging Face: huggingface.co/Lab-Rasool
- Website: Aakash-Tripathi.github.io
- IEEE Eta Kappa Nu (IEEE-HKN) Honors Society, Member since April 2024
- Institute of Electrical and Electronics Engineers (IEEE), Member since January 2019
| Degree | Institution | Dates |
|---|---|---|
| Ph.D. in Electrical Engineering | College of Engineering, University of South Florida | Aug 2022 – Aug 2025 |
| B.S. in Electrical and Computer Engineering | Henry M. Rowan College of Engineering, Rowan University | Sep 2018 – Jun 2022 |
Dissertation: Embedding-Based Deep Learning Frameworks for Multimodal Oncology Data Integration
📚 Publications || Google Scholar | ORCID ||
- Accelerate Cancer Research With AI-Driven Multimodal Data Integration NVIDIA GTC 2025 Presentation Session Page | Poster Page | Poster PDF
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HONeYBEE: Enabling Scalable Multimodal AI in Oncology Through Foundation Model-Driven Embeddings npj Digital Medicine 8(1), 622 (2025).
Aakash Tripathi, Asim Waqas, Matthew B. Schabath, Yasin Yilmaz, and Ghulam Rasool. DOI: 10.1038/s41746-025-02003-4 -
Robust Multimodal Fusion for Survival Prediction in Cancer Patients Cancer Informatics 24, 11769351251376192 (2025). Dominic Flack,
Aakash Tripathi, Asim Waqas, Ghulam Rasool, and Delil Dera. DOI: 10.1177/11769351251376192 -
Self-Normalizing Multi-Omics Neural Network for Pan-Cancer Prognostication International Journal of Molecular Sciences 26(15), 7358 (2025). Asim Waqas,
Aakash Tripathi, Sabeen Ahmed, Ashwin Mukund, Hamza Farooq, Joseph O. Johnson, Paul Stewart, Mia Naeini, Matthew B. Schabath, and Ghulam Rasool. DOI: 10.3390/ijms26157358 -
Transformers in Time-Series Analysis: A Tutorial Circuits, Systems, and Signal Processing 42(12), 7433–7466 (2023). Sabeen Ahmed, Ian E. Nielsen,
Aakash Tripathi, Shamoon Siddiqui, Ravi P. Ramachandran, and Ghulam Rasool. DOI: 10.1007/s00034-023-02454-8 -
Building Flexible, Scalable, and Machine Learning-Ready Multimodal Oncology Datasets Sensors 24(5), 1634 (2024).
Aakash Tripathi, Asim Waqas, Kavya Venkatesan, Yasin Yilmaz, and Ghulam Rasool. DOI: 10.3390/s24051634 -
A Comparison of Feature Selection Techniques for First-Day Mortality Prediction in the ICU In 2023 IEEE International Symposium on Circuits and Systems (ISCAS), 1–5 (2023). Jacob R. Epifano, Alison Silvestri, Alexander Yu, Ravi P. Ramachandran,
Aakash Tripathi, and Ghulam Rasool. DOI: 10.1109/ISCAS46773.2023.10182228 -
Multimodal Data Integration for Oncology in the Era of Deep Neural Networks: A Review Frontiers in Artificial Intelligence 7, 1408843 (2024). Asim Waqas,
Aakash Tripathi, Ravi P. Ramachandran, Paul Stewart, and Ghulam Rasool. DOI: 10.3389/frai.2024.1408843 -
Using consensus-based reasoning and large language models to extract structured data from surgical pathology reports Laboratory Investigation (2025): 104272.
Aakash Tripathi, Asim Waqas, Ehsan Ullah, Asma Khan, Farah Khalil, Zarifa Gahramanli Ozturk, Daryoush Saeed-Vafa, Wei-Shen Chen, Marilyn M. Bui, Matthew B. Schabath. DOI: 10.1016/j.labinv.2025.104272
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SeNMo: A Self-Normalizing Deep Learning Model for Enhanced Multi-Omics Data Analysis in Oncology Cancer Research 84(6_Supplement), 908–908 (2024). Asim Waqas,
Aakash Tripathi, Sabeen Ahmed, Ashwin Mukund, Hamza Farooq, Paul Stewart, Mia Naeini, and Ghulam Rasool. DOI: 10.1158/1538-7445.AM2024-908 -
Multimodal Transformer Model Improves Survival Prediction in Lung Cancer Compared to Unimodal Approaches Cancer Research 84(6_Supplement), 4905–4905 (2024).
Aakash Tripathi, Asim Waqas, Yasin Yilmaz, and Ghulam Rasool. DOI: 10.1158/1538-7445.AM2024-4905 -
BIO24-030: Unifying Multimodal Data, Time Series Analytics, and Contextual Medical Memory: Introducing MINDS as an Oncology-Centric Cloud-Based Platform Journal of the National Comprehensive Cancer Network 22(2.5) (2024).
Aakash Tripathi, Asim Waqas, and Ghulam Rasool. DOI: 10.6004/jnccn.2023.7305 -
PARADIGM: An Embeddings-Based Multimodal Learning Framework with Foundation Models and Graph Neural Networks Cancer Research 85(8_Supplement_1), 991–991 (2025). Asim Waqas,
Aakash Tripathi, Mia Naeini, Paul Stewart, Matthew B. Schabath, and Ghulam Rasool. DOI: 10.1158/1538-7445.AM2025-991 -
Predicting Treatment Outcomes Using Cross-Modality Correlations in Multimodal Oncology Data Cancer Research 85(8_Supplement_1), 3641–3641 (2025).
Aakash Tripathi, Asim Waqas, Yasin Yilmaz, Matthew B. Schabath, and Ghulam Rasool. DOI: 10.1158/1538-7445.AM2025-3641 -
1391 AI-Driven Extraction of Key Clinical Data from Pathology Reports to Enhance Cancer Registries Laboratory Investigation 105(3) (2025).
Aakash Tripathi, Asim Waqas, Kavya Venkatesan, Ehsan Ullah, Minh Bui, and Ghulam Rasool. DOI: 10.1016/j.labinv.2024.103629
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Embedding-Based Multimodal Learning on Pan-Squamous Cell Carcinomas for Improved Survival Outcomes arXiv preprint arXiv:2406.08521 (2024). Asim Waqas,
Aakash Tripathi, Paul Stewart, Mia Naeini, Matthew B. Schabath, and Ghulam Rasool. arXiv:2406.08521 -
TheBlueScrubs-v1: A Comprehensive Curated Medical Dataset Derived from the Internet arXiv preprint arXiv:2504.02874 (2025). Lucas Felipe, Carlos Garcia, Issam El Naqa, Michael Shotande,
Aakash Tripathi, Vineel Rudrapatna, and others. arXiv:2504.02874 -
EAGLE: Efficient Alignment of Generalized Latent Embeddings for Multimodal Survival Prediction with Interpretable Attribution Analysis arXiv preprint arXiv:2506.22446 (2025).
Aakash Tripathi, Asim Waqas, Matthew B. Schabath, Yasin Yilmaz, and Ghulam Rasool. arXiv:2506.22446 -
Trustworthy AI for Medicine: Continuous Hallucination Detection and Elimination with CHECK arXiv preprint arXiv:2506.11129 (2025). Carlos Garcia-Fernandez, Lucas Felipe, Michael Shotande, Marcus Zitu,
Aakash Tripathi, Ghulam Rasool, and Gilmer Valdes. arXiv:2506.11129 -
Explainable AI in Genomics: Transcription Factor Binding Site Prediction with Mixture of Experts arXiv preprint arXiv:2507 (2025).
Aakash Tripathi, Ian E. Nielsen, Muhammad Umer, Ravi P. Ramachandran, and Ghulam Rasool. arXiv:2507