Read our students' stories that start from the CUHK and go further beyond.

Experience Sharing: 

In late October, I attended the 2022 Technology Hackathon held by Natixis. The event was promoted by CUHK, and the task given was to detect fraudulent Ethereum addresses by applying machine learning models to Ethereum transactions.  

I’ve picked up quite many data science skills during the 4 years of undergraduate study, so when I found out the challenge was closely related to my major and interest, I registered for this hackathon as a trial. The result was kind of “unexpected” for me, because the major goal for me was only to gain more real-life task exposure. 

The whole process of the challenge combined both the business perspective (e.g., how to build meaningful features, how to present the model) and the technology one (e.g., how to build the model, how to interpret the data distribution). As a result, the task was a good practice for those who would like to gain familiarity with the real-life production process. In terms of the dataset, participants were given a dataset of normal and fraudulent addresses, along with their account activities - such as the number of sent transactions, received transactions, transferred ETHs, etc. 

As I was more familiar with supervised learning tasks, I treated this problem as a traditional classification task (using algorithms like Boosting Classifier, Logistic Regression Classifier), and constructed features of statistical meaning for each account using transaction history. 

The result is more than a big encouragement for me to continue my path in the field of data science and fintech. I am glad to have the chance to practice, and to explore model and visualization techniques out of my original knowledge scope. 

Encouragement Words: 

When I decided to pursue my future path in data science 3 years ago, I did not even know what data science was exactly. As such, I began my long way of exploration in this field. What drives me continuously was the abstruse interpretation in the world of data, the process to continuously learn new knowledge about machine learning and many specific areas.  

I believe that with proper use of the tools we have, life could be made better. And data science is just one way to connect the dots of technology and our daily lives, in fields of finance, healthcare, human language interpretation, and more. 

I started my first prediction project on my data mining course 2 years ago. Since then, I’ve been actively participating in different projects. I am glad to see my skillsets built up gradually, but I know there are still a long way for me to go. I would like to hereby convey my appreciation to all my friends and professors who always encourage me. 

Lastly, I would like to share with you one sentence that has been inspiring me since high school. That is, “with every deed you are sowing a seed, though the harvest you may not see.” I hope we all can one day see the harvest.