Welcome to this Personal Website

Hey, I am Jie Ding, a 5G/6G researcher and data analyst. This page recordes some of my portfolios in data analysis and selected publications in wireless communications. The most common technical tools I used for research and data analysis include Matlab, Python, SQL, Databricks, and Tableau.

Analyzing and Visualizing Historical Stock/Revenue Data Using Webscraping

Extracting and Webscraping Stock&Revenue Data of Tesla and GameStop using libraries such as yfinance, requests, bs4 (BeautifulSoup), and Visualizing the data using Plotly.

Business Churn EDA & Prediction

Using Python to perform EDA and prediction for the data from Telco-Customer-Churn.csv, where Matplotlob, Seaborn, and Plotly are used for data visualisation. For prediction (classification), different methods are used, such as KNN, Random Forest, Logistic Regression, DNN, and Adaboost. The principles of these methods are also highlighted and explained.

Supermarket Data Analysis

A portfolio of supermarket EDA that utilises Python to perform data import, data analysis, and visualisation. Some interesting observations based on data visualisation are provided.

USA Aviation Accident Analysis

A portfolio for USA aviation accident analysis that utilises Jupyter to perform data import, data cleaning/prepping, and visual analysis. Some interesting observations based on data visualisation are provided.

Association Rules Analysis

A portfolio that applies association rules for retail data. MLXTEND library is used in Python.

Cohert Analysis

A portfolio for customer classification that utilises Python/SQL for data prepping/cleaning and Tableau for visualisations.

Bechdel Test Analysis

A portfolio for Bechdel test analysis that utilises Python for data prepping/cleaning and Tableau for visualisations.

Prepping Data Challenge -- Call Center Agent Metrics

Utilising Python and SQL respectively to complete the Preppin' Data Challenge -- Call Center Agent Metrics. This challenge is from Tableau weekly Preppin' Data blog.

Prepping Data Challenge -- Pokemon Evolution Stats

Utilising Python and SQL respectively to complete the Preppin' Data Challenge -- Pokemon Evolution Stats. This challenge is from Tableau weekly Preppin' Data blog.

My Research Interests

My current research interests include wireless communications, Internet of Things (IoT), and machine-type communications. I have authored over 40 peer-reviewed publications in the area of wireless communications and IoT. The majority of my papers have appeared in JCR Q1 journals, such as IEEE TWC, IEEE TCOM, IEEE WCM, and IEEE IoT-J, and were presented at IEEE top-tier conferences, such as IEEE Globecom, IEEE ICC, IEEE CCNC, and IEEE WCNC. Some selected publications can be found below.

Enabling Grant-Free URLLC: An Overview of Principle and Enhancements by Massive MIMO

First and Corresponding Author

IEEE Internet of Things Journal

IoT Connectivity Technologies and Applications: A Survey

First and Corresponding Author

IEEE Access

Grant-Free Random Access in Machine-Type Communication: Approaches and Challenges

Corresponding Author

IEEE Wireless Communications

Success Probability of Grant-Free Random Access With Massive MIMO

First Author

IEEE Internet of Things Journal

Virtual Carrier Sensing-Based Random Access in Massive MIMO Systems

First Author

IEEE Transactions on Wireless Communications

Machine Learning Enabled Preamble Collision Resolution in Distributed Massive MIMO

First Author

IEEE Transactions on Communications

Dynamic Preamble-Resource Partitioning for Critical MTC in Massive MIMO Systems

First and Corresponding Author

IEEE Internet of Things Journal

Triangular Non-Orthogonal Random Access in mMIMO Systems

First and Corresponding Author

IEEE Transactions on Communications

Analysis of Non-Orthogonal Sequences for Grant-Free RA With Massive MIMO

First Author

IEEE Transactions on Communications

Multiple Preambles for High Success Rate of Grant-Free Random Access With Massive MIMO

IEEE Transactions on Wireless Communications

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