https://github.com/callmequant/callmequant

https://github.com/callmequant/callmequant

Last synced: 5 months ago
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• Host: GitHub
• URL: https://github.com/callmequant/callmequant
• Owner: CallmeQuant
• Created: 2023-04-27T20:34:54.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2023-09-13T14:36:55.000Z (over 2 years ago)
• Last Synced: 2023-09-14T04:51:10.640Z (over 2 years ago)
• Size: 9.77 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
## Hello 👋

I am an independent researcher working across **mathematical statistics**, **machine learning**, and **time-series analysis**.

My work focuses on developing and analyzing methods that blend **rigorous statistical theory** with **modern computational modeling**, particularly for high-dimensional or structured data.

I am interested in collaborations involving **theoretical analysis**, **modeling frameworks**, and **computational methodology** motivated by real-world complex data.

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## 🔬 Research Interests

### **Statistical Methodology**

* High-dimensional statistics

* Model selection and regularization

* Nonparametric and semiparametric inference

* Missing-data mechanisms (MAR/MNAR)

* Robustness and contamination models

### **Learning Theory & Generative Modeling**

* Empirical processes, concentration, and generalization

* Approximate inference: variational Bayes, MCMC, stochastic approximations

* Deep generative models: flows, diffusion models, energy-based models

### **Time-Series & Stochastic Systems**

* State-space models (linear, nonlinear, SSMs, SDEs)

* Diffusion-based forecasting

* Representation learning for sequential data

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## 🧰 Technical Stack

**Languages:**

![Python](https://img.shields.io/badge/-Python-333333?style=flat\&logo=python)

![R](https://img.shields.io/badge/-R-333333?style=flat\&logo=R)

![Julia](https://img.shields.io/badge/-Julia-333333?style=flat\&logo=julia)

**Computational Frameworks:**

![PyTorch](https://img.shields.io/badge/-PyTorch-333333?style=flat\&logo=pytorch)

![JAX](https://img.shields.io/badge/-JAX-333333?style=flat\&logo=jax)

![Scikit-Learn](https://img.shields.io/badge/-Sklearn-333333?style=flat\&logo=scikit-learn)

**Probabilistic Programming:** NumPyro - Pyro - PyMC3

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## 📘 Research Perspective

My work aims to build connections between:

* **Statistical theory** (empirical processes, concentration, asymptotics)

* **Modeling and computation** (variational inference, SDEs, diffusion-based models)

* **Applications** where structure and uncertainty play a central role (biostatistics, forecasting, high-dimensional regimes)

I am particularly motivated by methodologies that offer **both statistical guarantees and practical applicability**, and I enjoy collaborations where theory, computation, and application inform each other.

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## 📫 Contact

[![Linkedin](https://img.shields.io/badge/linkedin-black?logo=Linkedin\&logoColor=white)](https://www.linkedin.com/in/binh-ho-899390193/)

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