Liwei Wu...

always curious about the world around me

Liwei's Homepage~

Or Liwei's home, Liwei's page, whatever you call it ;)

My name is Liwei Wu. I am studying Statistics and Computer Science at University of California-Davis. As a third-year PhD candidate, my research focus is on designing and implementing novel machine learning algorithms for recommender systems that can handle massive datasets. I am jointly advised by Professor Cho-Jui Hsieh and Professor James Sharpnack. Before moving to Davis, I received a BSc (First Class Honors) in Computing Mathematics from City University of Hong Kong in 2014. I did my undergraduate thesis on Extreme Value Thoery under supversion of Professor Xiang Zhou.


Research/Teaching/Working et al...

To know more about my research and teaching experience, one can refer to the sections research and teaching in the homepage I made from scratch.

As to my working experience, I am currently working at AT&T labs as an intern on cloud services (AT&T Integrated Clouds) team during 2017 summer. I am doing text mining on log data, which is stored in noSQL database and can be queried using Elasticsearch. The data is generated in the process of building and operating AT&T's private cloud which uses openstack framework. My goal of the summer intern is to build internal tools to help quantify the cloud's current state using KPI (Key Performance Indicator), diagnose existing issues and predict potential issues in the AT&T Integrated Clouds.

The job requires not only data engineering skills and in-depth data mining/machine learning knowledge, but also the ability of writing production codes. My role is like a combination of data engineer, data scienctist and machine learning engineer.

For the first two weeks, I have built an internal tool (a python module) to efficiently and precisely extract useful information specified by the user in parallel. This can be used for alerting tenants when the cloud services go down.

Another project I am working on is to build a tool to detect discrepancy between Vertica database and ElasticSearch database in real-time. Since data for those two databases are related but come from two different channels, sometimes discrepancy can happen. This project was handed over to me since the full time employee reposibile for this is leaving the company. The other project I am also working on is to analyze the sequence data and hope to detect patterns that are useful for prediction.

As to my programming skills, I can write production codes in Python and C++. I use Julia mainly for research in machine learning/optimization and am very proficient in Julia. I can make websites with knowledge of front end (html, CSS, javascript) and backend (php, relational(SQL)/NoSQL databases) knowledge. I also have a good knowledge of other languages such as R/matlab and various machine learning libraries, including Tensorflow and XGBoost. I can read Java codes and write simple Java as well as simple Shell Scripts. I feel I can easily pick up any language within a short time. Anyway, all the languages mentioned are connected and similar to each other to some extent. For me, I think the knowledge base itself is not as important as the curiosity for new things and the willingness and ability to pick up something new quickly.

Recent News

I am travelling to Halifax, Nova Scotia - Canada to give an oral presentation at KDD 2017 during Aug 13-17, 2017.

I am currently working at AT&T labs as an intern on cloud services (AT&T Integrated Clouds) team during 2017 summer

I am actively looking for researach/industry internship opportunies during 2018 summer.

Promotional Video for my paper on Collaborative Ranking

My Greatest Achievement

The one thing I am proudest of in my life is that I lost over 80 pounds of weight and finished a couple of full marathons, as one can easily tell the difference from the photos below. The first one was me back in 2013. The second and third ones is me at Big Sur during 2017 Spring Break.

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