PhD Computer Science • Statistical Consulting • Machine Learning Systems
I am a Computer Science PhD student passionate about the science of computation and the engineering of intelligent systems. My interests span algorithm design and analysis, database architectures, machine learning, artificial intelligence, cryptography, high-performance computing, and statistical modeling. I enjoy transforming rigorous mathematical ideas into scalable, practical solutions.
Design and analysis of efficient computational systems.
Machine learning, deep learning, and intelligent systems.
Architecture, query optimization, and distributed systems.
Parallel processing, distributed computing
Secure systems and encryption protocols.
Scalable architecture and system design.
Discrete math, linear algebra, probability, and optimization.
Supervised Learning - Regression, classification, and predictive modeling systems.
Unsupervised Learning - Clustering, dimensionality reduction, and pattern discovery.
Reinforcement Learning - Agent-based decision systems using reward optimization.
Neural Networks
Convolutional Neural Networks (CNNs)
Recurrent Neural Networks (RNNs)
Language understanding, parsing, and generation systems
Image recognition, segmentation, and visual reasoning
Attention-based architectures for sequence modeling
Generative models for image and data synthesis
Foundation models for reasoning and text generation
Visual and spatial feature extraction systems
equential and temporal modeling systems
Open to academic collaboration, statistical consulting, and machine learning system development.