Academics

Data analytics student presents research at international summer school

MALVERN, Pa. — Any opportunity graduate students have to receive feedback on their research is exciting for them. When that coincides with attending a selective summer school session and presenting to industry leaders, it’s an even more prestigious honor.

Anchal Gupta, a data analytics graduate student at Penn State Great Valley, attended the inaugural Artificial Intelligence for Engineering Summer School, where she presented her master's thesis research to a panel of industry leaders. The two-week event, held at the Autodesk AI research center in Toronto, sought to educate the attendees on the importance and future of AI in engineering.

Gupta’s résumé was impressive enough to earn her a spot at the event; she was one of 32 students from across the world chosen to attend, and she also received a fellowship.

Lectures highlighted the first week of the session, and the following week, Gupta had the opportunity to present her master’s thesis research during an industry mixer event. Autodesk’s director of AI and representatives from a variety of other research labs were present.

“It was amazing,” Gupta said of presenting her research. “That was my first poster presentation. My most important thing is my master’s thesis and presenting it in front of so many talented people was a really great experience. Not just presenting — getting their feedback was really helpful. They told me something like, ‘In the future, you can extend this work.’”

Gupta has worked with her thesis supervisor, Youakim Badr, associate professor of data analytics; Ashkan Negahban, assistant professor of engineering management; and Robin Qiu, professor of information science, to research temperature control in smart buildings.

The impetus for Gupta’s research came from the buildings at Penn State at the Navy Yard. For more than a decade, the Navy Yard, with support from the U.S. Department of Energy and the Commonwealth of Pennsylvania, has focused on building energy efficiency and efficient energy management.

“Basically, we have rule-based or regular thermostats these days, but buildings are converting into smart buildings, so we have automated that process,” Gupta said. “For example, you want the office indoor temperature to be 70 degrees Fahrenheit. The thermostat automatically adjusts the temperature according to your requirement. It is able to maintain the user comfort as well as save energy costs. It outperforms the thermostats that are plugged into buildings now.”

Attending the summer school session also gave Gupta the opportunity to learn about new topics, particularly machine learning and deep learning, which she believes will be useful in her future career.

Gupta isn’t sure what the next step is after she finishes her master’s degree — she might pursue a doctorate, or she might work in the artificial intelligence industry. Regardless, she knows she wants to do something with reinforcement learning.

“I think the work I have done involves the latest technology,” Gupta said. “People are still experimenting with and applying reinforcement learning … mostly in gaming or robotics. Applying it to the field of energy and buildings was really challenging and I think it will help me in my further studies or in my job.”

Last Updated December 17, 2020