current work
Ongoing research and projects
Current Role
Applied Scientist II at Amazon (January 2026 - Present)
Working on agentic bot systems.
Under Review at ICML 2026
CalPro: Prior-Aware Evidential Conformal Prediction with Structure-Aware Sensitivity Bounds for Protein Structures (with Sanjeda Akter, Anuj Sharma)
arXiv:2601.07201
What Reward Structure Enables Efficient Sparse-Reward RL? A Proof-of-Concept with Policy-Aware Matrix Completion (with Sanjeda Akter, Anuj Sharma)
arXiv:2509.03790
Selective Risk Certification for LLM Outputs via Information-Lift Statistics: PAC-Bayes, Robustness, and Skeleton Design (with Sanjeda Akter, Anuj Sharma)
arXiv:2509.12527
CGRiC: Compositional Risk Certification for Structured LLM Outputs (with Sanjeda Akter, Anuj Sharma)
Certificate-Guided Pruning for Stochastic Lipschitz Optimization (with Sanjeda Akter, Anuj Sharma)
arXiv:2601.20231
Differentiable Range-Partition Entropy for Instance-Optimal Geometric Algorithms (with Sanjeda Akter, Anuj Sharma)
arXiv:2509.03733
Under Review at ACL ARR 2026 (January Submission)
Adaptive Constraint Propagation: Scaling Structured Inference for Large Language Models via Meta-Reinforcement Learning (with Sanjeda Akter, Anuj Sharma)
arXiv:2601.00095
Detecting Proxy Gaming in RL and LLM Alignment via Evaluator Stress Tests (with Sanjeda Akter, Anuj Sharma)
arXiv:2507.05619
Anytime-Valid Answer Sufficiency Certificates for LLM Generation via Sequential Information Lift (with Sanjeda Akter, Anuj Sharma)
arXiv:2510.06478
Beyond Variance: Knowledge-Aware LLM Compression via Fisher-Aligned Subspace Diagnostics (with Sanjeda Akter, Anuj Sharma)
arXiv:2601.07197
Causal Consistency Regularization: Training Verifiably Sensitive Reasoning in Large Language Models (with Sanjeda Akter, Anuj Sharma)
arXiv:2509.01544
Under Review at ECCV 2026
Enhancing Traffic Incident Response through Sub-Second Temporal Localization with HybridMamba
arXiv:2504.03235
Temporal Zoom Networks: Distance Regression and Continuous Depth for Efficient Action Localization
arXiv:2511.03943
Planning for NeurIPS 2026
Learning to Forget Attention: Memory Consolidation for Adaptive Compute Reduction (CRAM)
arXiv:2602.12204
On the Sparsifiability of Correlation Clustering: Approximation Guarantees under Edge Sampling
arXiv:2602.13684
Grassmannian Mixture-of-Experts: Concentration-Controlled Routing on Subspace Manifolds
arXiv:2602.17798
Under Review at ITSC 2026
A Unified Random Matrix Theory Diagnostic Framework for Crash Classification Models
arXiv:2602.19528
DEEP-SS: A Deep Reinforcement Learning Approach for Traffic Signal Synchronization
Precise and Robust Sidewalk Detection: Leveraging Ensemble Learning to Surpass LLM Limitations in Urban Environments
arXiv:2405.14876
Planning for ACL ARR 2026 (May Submission)
Calibrated Adaptation: Bayesian Stiefel Manifold Priors for Reliable Parameter-Efficient Fine-Tuning
arXiv:2602.17809
Under Review at IEEE ITS Transactions
Calibrated and Resource-Aware Super-Resolution for Reliable Driver Behavior Analysis
arXiv:2509.23535
Image Segmentation with Large Language Models: A Survey with Perspectives for Intelligent Transportation Systems (with Sanjeda Akter)
arXiv:2506.14096
Under Review at Journal of Safety Research
Unlocking Insights Addressing Alcohol Inference Mismatch through Database-Narrative Alignment (with Sudesh Bhagat, Raghupathi Kandiboina, Skylar Knickerbocker, Neal Hawkins, and Anuj Sharma)
arXiv:2506.19342
Preprints
Large Language Models for Crash Detection in Video: A Survey of Methods, Datasets, and Challenges (with Sanjeda Akter)
arXiv:2507.02074
Open to Collaborations
Actively seeking collaborations in:
- Computer Vision for safety-critical applications
- Large Language Models and novel architectures
- Reinforcement Learning theory and practice
- Quantum Machine Learning
- Transportation AI
| Contact: ishihab@iastate.edu |
Upcoming Presentations
- None