I build reproducible machine-learning systems for reinforcement learning, large language models, computer vision, vision-language systems, and applied data science.
I am a Computer Science PhD candidate at the University of Dayton, with research experience spanning Safe Reinforcement Learning, Vision-Language Models, AI Safety, Human-AI Systems, and industry experience at Walmart and Padagis LLC.
🌐 Personal Website: https://www.shrutisinghphd.com/
- 🧠 LLM-guided Safe Reinforcement Learning
- 🤖 Adversarial robustness in RL environments
- 👁️ Vision-Language Models for construction safety
- 🏗️ AI systems for construction safety analysis
- 📊 Applied data science and statistical modeling
- 🔍 Human-AI collaboration and explainability
Entropy-driven feature selection for adversarial robustness; 94–95% accuracy across Gym (LunarLander, BipedalWalker), outperforming KL-divergence and joint-entropy baselines. Published at KSE 2024.
🔗 Repository: adversarial-rl-resilience
Modular, glass-box vision-language pipeline for automated construction-safety hazard detection — captioning, hazard proposal, multimodal reasoning, hybrid visual grounding, and rule-based reconciliation into an auditable safety report.
🔗 Repository: sitecortex-construction-safety-vlm
Classical search (DFS, BFS, UCS, A*) and reinforcement-learning planning (value iteration, policy iteration, Q-learning) with trajectory and policy visualizations.
🔗 Repository: gridworld-search-strategies
Deep learning for time-series prediction with advanced preprocessing, hyperparameter tuning, learning-rate scheduling, and early stopping — benchmarked against MLP, CNN, and CNN-LSTM (LSTM achieves the lowest error).
🔗 Repository: lstm-time-series-forecasting
PPO agent that allocates a multi-asset ETF portfolio using a differential-Sharpe reward, benchmarked out-of-sample against equal-weight, mean-variance, and buy-and-hold with leakage-free backtesting.
🔗 Repository: drl-portfolio-optimization
Gradient-boosted default prediction on 30k accounts with imbalance-aware metrics, probability calibration, and SHAP explanations for auditable, per-applicant credit decisions.
🔗 Repository: credit-risk-default-prediction
Access here ASME JESBC 2025
Systematic review of AI technologies and their impact on construction safety research.
Access here CISS 2025
Segmentation of brain cells in fluorescence microscopy using deep learning methods.
Access here CISS 2025
Real-time pose estimation and feedback system for guided virtual yoga instruction.
Access here KSE 2024
Entropy-driven feature selection approach for adversarial robustness in reinforcement learning environments.
Predicting an Optimal Medication/Prescription Regimen for Patient Discordant Chronic Comorbidities Using Multi-Output Models
Access here Information, 2024
Multi-output modeling approach for personalized medication recommendations in patients with comorbidities.
Access here CISS 2023
Benchmark suite and multi-output methods for career trajectory prediction.
Python · R · SQL · NoSQL
PyTorch · TensorFlow · Keras · scikit-learn · Hugging Face
DDQN · OpenAI Gym · LunarLander · BipedalWalker
OpenCV · BLIP-2 · GroundingDINO
Pandas · NumPy · Matplotlib · Statistical Analysis · Time-Series Modeling
BigQuery · ETL Pipelines
PhD in Computer Science
Focus:
- Safe Reinforcement Learning
- Machine Learning
- Human-AI Systems
MS in Computer Science
Graduated with 4.00 GPA
📧 shruti.singh97.phd@gmail.com
💼 LinkedIn
https://www.linkedin.com/in/shruti-singh97/
🎓 Google Scholar
https://scholar.google.com/citations?user=t2OTFtkAAAAJ&hl=en
🌐 Website
https://www.shrutisinghphd.com/