•
•
"Optimizing the intersection of high-dimensional data and actionable intelligence."
I am a Machine Learning Engineer and Researcher focused on the transition of state-of-the-art models from academic environments into low-latency, scalable production architectures. My core competencies lie in Bayesian Optimization, Edge AI Deployment, and LLM Orchestration.
Currently, I am architecting intelligent systems that solve non-trivial problems in:
Financial Modeling(Stochastic Calculus & Time-Series)Industrial Automation(Computer Vision on the Edge)Enterprise Decision Support(RAG & Semantic Search)
|
|
|
A Bayesian Optimization engine for cointegration-based statistical arbitrage. Uses Gaussian Processes to dynamically traverse hyperparameter spaces, optimizing entry/exit thresholds to minimize drawdown in non-stationary markets.
|
Real-time object detection pipeline using YOLO architectures optimized for edge deployment (Raspberry Pi). Achieved <15ms inference latency and 80.1% mAP for automated industrial sorting.
|
|
Hybrid NLP system combining Rasa's intent classification with OpenAI's GPT models via LangChain. The architecture manages context retention and fallback mechanisms for robust automated support.
|
Phase-shift optimization simulation for Reconfigurable Intelligent Surfaces (RIS). Implemented control logic to maximize Signal-to-Noise Ratio (SNR) in wireless communication environments.
|
def research_roadmap():
return [
"Multi-Modal Transformers",
"Reinforcement Learning (RLHF)",
"Neuromorphic Computing"
]