What a Professor and PhD Learned in 3 Months at AT&T Labs
AT&T casts a wide net when looking for interns. It was apparent when Professor Zhenming Liu took a break from teaching computer science at the College of William and Mary to intern at AT&T Labs this summer.
He worked with the Statistics Research Department building models and tools to help us solve ways to boost interactions with customers. He looked at methods used in machine learning and statistics.
Following his 3 month stint, we sat down with Professor Zhenming to hear about his experience. Here are the 3 key lessons he’s taking back to his classroom.
- Real problems are priceless. “The questions we asked in the Statistics Research group inspired me to present case studies and assignments in my data science and machine learning courses. Students are best motivated when they can apply classroom learning to real problems. I’m developing examples that resemble real problems at AT&T. And I’m interested to see how my students approach these issues.”
- Collaboration is key. “I spent most of my time on technical issues – coming up with theory or large-scale machine learning. I met weekly with other Lab scientists. We all worked on the customer care dataset, but all had different backgrounds. So we assessed the same problems differently. Our collaborative work gave a strong foundation for the theories and practical solutions I developed as a part of the team.”
- Progressive leadership drives innovation. “AT&T’s researchers know how to balance short-term deliverables and long-term planning. They apply expertise and great skills to problem-solving, are good with building large-scale distributed algorithms and quickly grasp statistical concepts that are often quite subtle.”
While we don’t usually have professors intern at AT&T, it was a privilege to have someone of Professor Zhenming’s caliber work with and offer his expertise. His team members also learned a lot during these few months.
You can read more about intern opportunities at AT&T Labs here.
Wenling Hsu - Big Data research scientist working on applying machine learning to customer care.