springnuance Goto Github PK

followers: 26.0 following: 11.0 repos: 128.0 gists: 0.0

Name: Nguyen Xuan Binh

Type: User

Company: Aalto University

Bio: 🛩️ Feasibility, simplicity and scalability are my top priorities in solving problems

Location: Espoo, Finland

Blog: https://www.linkedin.com/in/xuanbinh/

Hello visiting scientists. I'm Xuan Binh a.k.a Spring Nuance

⚡ I am specialized in applied machine learning models for solving mechanical/material engineering problems
⚡ The engineering softwares that I use frequently include Abaqus, DAMASK, Matlab, Finnish CSC HPC service and CAD softwares

💼 Skills

💡 These are currently under my command: Python, R, Scala, C++, Stan, Julia, C, Javascript, SQL and Bash

More Skills

My university courses

MECHANICAL ENGINEERING	THEORETICAL DATA SCIENCE	COMPUTER SCIENCE	APPLIED DATA SCIENCE
Statics and Dynamics	Statistical Inference	Data Structures And Algorithms	SQLite/PostgresSQL Databases
Solid Mechanics	Linear Algebra	Algorithmic Techniques Principles	MYSQL for Data Analytics
Fluid Mechanics	Mathematical Optimization	C/C++ Object-oriented Programming	Business Anlytics I Basic
Material Science in Engineering	Machine Learning	Theory Of Computation	Business Analytics II Advanced
Thermodynamics and Heat Transfer	Time Series Analysis	Assembly Programming	Business Intelligence
Finite Element Methods	Multivariate Statistical Analysis	Operating Systems	Business Simulation
Continuum Mechanics	Deep Learning	Concurrent Programming	Speech Processing
Computer-aided Tools in Engineering	Supervised ML methods	Parallel Programming	Statistical Signal Processing
Numerical methods in Engineering	Artificial Intelligence	Computer Graphics	Speech Recognition
Numerical Analysis	Bayesian Data Analysis	Computer Networks	Statistical Natural Language Prcoessing
Fracture Mechanics	Gaussian Processes	Web Software Development	Speech Processing Project
Computational Engineering Project	Computer Vision	Information Security	Human-in-the-loop RL Molecular Design
Crystal Plasticity Thesis	Advanced Probabilistic Methods	Declarative Programming	Computational Genomics
Selection of Engineering Materials	Large Scale Data Analysis	Computational Social Science	High-throughput Bioinformatics
Materials Safety	Methods Of Data Mining	High Performance Computing	Modeling Biological Networks
Machine Design	Reinforcement Learning	Software Project I-II	Stats Genetics & Personalised Medicine
Finite Element Analysis	Stochastic Processes	Cloud Software and System	Information Visualization

📔 My publications

Check out my published paper

📌 Pinned Repositories

📈 My statistics

📣 A quote before you go

The universe is full of magical things patiently waiting for our wits to grow sharper.

EDEN PHILLPOTTS

Nguyen Xuan Binh's Projects

abaqus-fortran-subroutine

Resources collected from various sources for subroutine documentations

abaqus-macromechanics-literature

abaqus-subroutine-references

This repository contains the subroutine source code of Emilion Martinez on various physical problems. This is his website https://www.empaneda.com/codes/

This course covers Bayesian statistics and steps of the Bayesian modeling process, statistical models, and formulation of the models in various situations. Example: Bayesian probability theory and bayesian inference. Bayesian models and their analysis. Computational methods, Markov-Chain Monte Carlo.

bayesian-data-analysis-project

beginner-python-for-engineer

big-data-platforms

Mirror the materials of the Big Data Platforms course in Aalto

business-analytics-i

This course focuses on optimization models used in business applications. The student can (i) recognize the types of real-life business decision problems where use of these models brings added value, (ii) interpret results of these models to derive defensible decision recommendations, and (iii) build and solve these models using relevant software

business-analytics-ii

This course covers simulation, decision trees, value of information, expected utility theory, risk attitudes, stochastic dominance, risk measures, multi-attribute utility/value theory, modelling uncertainty and multiple objectives in optimization problems.

business-intelligence

This course covers the key building blocks of BI, such as data management, data warehousing, analytic tools, data mining, and reporting. The course provides both a hands-on practical and a theoretical approach to learning about data driven decision-making and analytical problem solving.

chat_application_command-line-version

chat_application_gui-version

Chat application supporting IPv4 and IPv6 network with an integrated GUI Tkinter

computational-social-science

computer-aided-tools-in-engineering

computer-graphics

computer-networks

computer-vision

concurrent-programming

convex-optimization

cryptography

deep-learning

This course covers the general principles of deep learning, and the central deep learning methods discussed in the course, such as MLP, Recommender System, RNN, Transformers, GAN, autoencoders, diffusion generative model, autoregressive model and fewshot classification