Scholar
Pratinav Seth
Google Scholar ID: DwBn1fcAAAAJ
AryaXAI Alignment Lab, Arya.ai (An Aurionpro Company)
Citations & Impact
Citations
73
H-index
5
i10-index
2
Publications
20
Co-authors
17
list available
Publications
Resume (English only)
Academic Achievements
- Selected as AAAI Undergraduate Consortium Scholar in 2023
- Paper 'Interpretability-aware pruning for efficient medical image analysis' accepted at MICCAI Workshop 2025
- Paper 'SELF-PERCEPT: Mental Manipulation Detection' accepted at ACL 2025
- 'Alberta Wells Dataset' accepted at ICML 2025
- Paper 'Obscure to Observe: A Lesion-Aware MAE for Glaucoma Detection' accepted at MIDL 2025 (Short Paper Track)
- Paper 'DL-Backtrace' accepted at IJCNN 2025
- Program Committee member for AAAI 2026
- Reviewer for multiple venues: NeurIPS 2025 (RegML Workshop), ICML 2025 (Actionable Interpretability Workshop), ICCV 2025, IJCNN 2025, ICLR 2025 (Advances in Financial AI Workshop), CVPR 2025
Research Experience
- Research Scientist at AryaXAI Alignment Labs (Arya.ai, an Aurionpro Company) since July 2024
- Works on Explainable AI (XAI), AI alignment, and AI safety
- Enhanced DLBacktrace method and developed benchmarking frameworks for XAI evaluation
- Investigates alignment and optimization strategies across CNNs, BERT, and LLaMA
- Developing foundation models for tabular data with applications in risk modeling and financial safety
Education
- Bachelor’s (B.Tech) in Data Science from Manipal Institute of Technology
- Interned at Mila Quebec AI Institute under Dr. David Rolnick
- Interned at Bosch Research India with Dr. Amit Kale and Mr. Koustav Mullick
- Interned at KLIV Lab, IIT Kharagpur (PI: Dr. Debdoot Sheet)
- Conducted research with Mars Rover Manipal AI Research alongside Dr. Ujjwal Verma
- Active in Research Society MIT
- Mentored by Dr. Abhilash K. Pai
Background
- Aspiring AI researcher exploring computer vision, NLP, and deep learning
- Focuses on Explainable AI (XAI), AI alignment, and AI safety for high-stakes real-world applications
- Passionate about building responsible, transparent, and safe AI systems
- Strong interest in AI for Social Good, particularly in medical imagery and remote sensing
- Enthusiastic about healthcare, remote sensing, and resource-efficient models
