News featuring Nurendra Choudhary

Sanghani Center Student Spotlight: Nurendra Choudhary

Graphic is from the paper 
“Self-Supervised Hyperboloid Representations Logical Queries over Knowledge Graphs”

Nurendra Choudhary was an applied science intern with the Amazon Search Team in Palo Alto, California, last summer where he worked on representation learning of products by leveraging the heterogeneous relations between them.

At The Web Conference 2021 last week, Choudhary, a Ph.D. student in computer science at the Sanghani Center, presented “Self-Supervised Hyperboloid Representations Logical Queries over Knowledge Graphs,” his research with data scientists at Amazon and his advisor Chandan Reddy.

It was Reddy’s research on deep learning methods in information retrieval that drew Choudhary to Virginia Tech. “It aligned well with my previous work in social media analytics and I felt that the Sanghani Center would be a great place to develop my expertise in a broader area,” he said.

Choudhary said that he was right. “I have benefited from being able to discuss my own research with a very diverse set of students working on many different problems and getting multiple diverse perspectives and possible solutions to my problems,” he said.

Choudhary’s primary research interest is representation learning with a focus on natural language processing and E-commerce.

Representation learning forms the foundation of most deep learning architectures, he said, and given the potential of change that an improvement in this area could bring, he was extremely interested in contributing to it.

“We notice a lot of E-commerce platforms being spammed by fake reviews,” said Choudhary. “An important pattern in these reviews is a lack of product detail and relevance. With better product and review representations, we can identify the spammers and provide a better customer experience.”

Choudhary has a bachelor’s degree in computer science and master’s degree in computational linguistics, both from the International Institute of Information Technology, Hyderabad, India.

Projected to graduate in 2023, he would like to pursue a career in industry research.


DAC students working virtually at summer internships across the country

DAC Ph.D. student Chidubem Arachie is working remotely as an intern at Google Research.

A national pandemic that forced the closing of physical offices has not stopped graduate students at the Discovery Analytics Center from working remote internships at companies, research laboratories, and other institutions across the country. For many students, summer internships help further their own research as they gain real world experience.

Following is a list of DAC students and the work they are doing for the next few months:

Chidubem Arachiea Ph.D. student in computer science, is a research intern at Google Research in Mountain View California. He is working on generative modeling for 3D shapes. His advisor is Bert Huang.

John Aromando, a Ph.D. student in computer science, is an intern at Graf Research in Blacksburg, working on utilizing natural language processing to support the software verification process. His advisor is Edward Fox.

Hongjie Chen, a Ph.D. student in computer science, is a data science research intern at Adobe in San Jose, California. He is on the Cloud Technology Team, researching cloud resource allocation strategy. His advisor is Hoda Eldardiry.

Nurendra Choudhary, a Ph.D. student in computer science, is an applied science intern with the Amazon Search Team in Palo Alto, California. He is working on representation learning of products by leveraging the heterogeneous relations between them. His advisor is Chandan Reddy.

Joshua Detwiler, a Ph.D. student in computer science, is an intern for the Navy in Dahlgren, Virginia, where he is working on a distributed application for network analysis. His advisor is Layne Watson.

Chen Gao, a Ph.D. student in electrical and computer engineering, is a research intern at Google in Mountain View, California. He is working on improvements to the portrait mode on the Google Pixel phone. His advisor is Jia-Bin Huang.

Akshita Jha, a Ph.D. student in computer science, is a research intern in the Interdigital AI Lab in Palo Alto, California. Her work involves building interpretable natural language processing models. Her advisor is Chandan Reddy.

Prerna Juneja, a Ph.D. student in computer science, is an intern at the Information Science Institute at the University of Southern California with Emilio Ferrara, assistant research professor and associate director of Applied Data Science in the Department of Computer Science. She is investigating the spread of COVID-19 related conspiracy theories on Twitter. Her advisor is Tanushree Mitra.

You Lu, a Ph.D. student in computer science, is a research intern at NEC Labs America in Princeton, New Jersey, working on sequence labeling for signals in fibers. His advisor is Bert Huang.

Shruti Phadke, a Ph.D. student in computer science, is doing a research internship with James Pennebaker, a professor in the Department of Psychology at the University of Texas at Austin. She is studying online communities, their social processes, and behaviors. Her advisor is Tanushree Mitra.

Aarathi Raghuraman, a master’s degree student in computer science, is an intern at GlaxoSmithKline (GSK), working with the Digital, Data, and Analytics team to maximize process yield in upstream biopharm manufacturing. She is advised by Lenwood Heath.

Esther Robb, a master’s degree student in electrical and computer engineering, is a research intern at Google working with a team in San Francisco on reinforcement learning. Her advisor is Jia-Bin Huang.

Mandar Sharma, a master’s student in computer science, is working as a machine learning intern with Toyota Motors North America, specifically the Toyota Racing Development (TRD) branch, to help NASCAR drivers make better decisions when they are racing. His advisor is Naren Ramakrishnan.

Aarohi Sumant, a master’s student in computer science, is an intern at Amazon. She is working with the Kindle Marketing Team to develop machine learning techniques for book recommendations based on cross user activities as well as single-user activities on different Amazon platforms. Her advisor is Edward Fox.

Afrina Tabassum, a Ph.D. student in computer science is a data science intern in the Data Science for The Public Good (DSPG) program at the Biocomplexity Institute’s Social and Decision Analytics Division (SDAD) at the University of Virginia. She is working on projects that address state, federal, and local government challenges around critical social issues relevant in the world today. Her advisor is Hoda Eldardiry.

Mia Taylor, a senior undergrad in computer science, is interning at Amazon Web Services in the Route 53 (DNS) service. Her advisor is Hoda Eldardiry.

Sirui Yao, a Ph.D. student in computer science, is an intern at Google, working on tag prediction for recommender systems through learning items and tags embeddings. Her advisor is Bert Huang.

Shengzhe Xu, a Ph.D. student in computer science, is interning at Facebook Ads Core ML, working on attention-based time sequential embedding aggregation. Xu’s advisor is Naren Ramakrishnan.

Ming Zhu, a Ph.D. student in computer science, is interning at Amazon. She is an applied scientist intern for Amazon Alexa AI, working on conversational query representation learning. Zhu’s advisor is Chandan Reddy.

Yuliang Zou, a Ph.D. student in electrical and computer engineering, is working on learning with less/weaker annotations at Google. His advisor is Jia-Bin Huang.