ParallelLLC/FREDML
Updated
AI & ML interests
Natural Language Processing & LLM Safety • Legislative text summarization & classification • Multilingual policy translation • Adversarial red-teaming & bias audits Reinforcement Learning for Autonomous Systems • Agentic data-pipeline self-tuning • RL-based trading-strategy optimization • Simulation-driven policy iteration Time-Series Forecasting & Sensor Fusion • Predictive maintenance on 1,200+ IoT sensors • High-frequency market-trend prediction • Hybrid statistical-deep models Financial Modeling & Algorithmic Trading • Multi-asset risk analytics • Serverless muni-bond data APIs • Synthetic-scenario stress testing Multimodal Computer Vision • Radar-camera fusion object detection • Edge situational-awareness for defense & law enforcement • Real-time CV pipelines Recommendation Systems & Personalization • Netflix-style media profiling • B2B influencer-matching engine • Graph-based news ranking Graph Machine Learning • Policy-influence knowledge graphs • Supply-chain risk propagation analysis • Graph neural networks with PyG Generative Modeling & Synthetic Data • Synthetic time-series & text generation • Data augmentation cutting training time 40 % • Text-to-code assistants Privacy-Preserving & Federated ML • Static-analysis–driven privacy compliance • Edge federated learning on distributed sensors • Differential-privacy safeguards MLOps & Cloud-Native Pipelines • Spark/Airflow/dbt CI/CD automation • AWS EKS + Lambda cost optimization (-35 %) • Auto-retrain & model monitoring Causal Inference & Policy Analytics • Tariff price-elasticity modeling • Workforce-layoff impact assessment • Experiment-driven decision support AI Governance & Ethics • Model-risk management frameworks • Explainability & FAIR compliance • DoD & financial-sector audit readiness