Professional summer internships provide valuable real-world experience for Sanghani Center graduate students

Graduate students at the Sanghani Center often embark on summer internships to gain real-world experience and in some instances, enable them to also advance their own research interests and projects. Summer 2022 is no exception. While some companies and research labs are continuing to operate remotely, a number of students have returned to working on-site.

Following is a list of Sanghani Center interns, where they are working, and what they are doing:

Sikiru Adewale, a Ph.D. student in computer science, is a graduate technical research intern at Intel Corporation, working remotely. He is using machine learning to analyze the workloads dataset. His advisor is Ismini Lourentzou.

Jie Bu, a Ph.D student in computer science, is a machine learning research intern for an Apple Maps Team in Cupertino, California, working on-site. He is helping to optimize user experience and map services using deep learning methods. His advisor is Anuj Karpatne.

Satvik Chekuri, a Ph.D. student in computer science, is an natural language processing intern with the Deloitte Audit and Assurance Data Science team in New York City, working remotely on the entity extraction and entity linking problem for unstructured data in the financial domain. His advisor is Edward Fox.

Nurendra Choudhary, a Ph.D. student in computer science, is an applied science intern at Amazon A9 in Palo Alto, California, working on-site on use case of graph and language representation in the context of e-commerce platforms. His advisor is Chandan Reddy.

Elizabeth Christman, a master’s degree student in computer science, is a software engineering intern at Splunk in Blacksburg, Virginia, working remotely on automating the build process for Stream, a Splunk add-on for deep packet inspection. Her advisor is Chris North.

Arka Daw, a Ph.D. student in computer science, is a research intern at IBM T.J. Watson Research Center in New York, working on-site. He is developing physics-informed AI methods to solve inverse problems involving partial differential equations. His advisor is Anuj Karpatne.

Mohannad Elhamod, a Ph.D student in computer science, is an intern at NASA Langley Research Center in Hampton, Virginia, working remotely on applying machine learning in material engineering. His advisor is Anuj Karpatne.

Jiaying Gong, a Ph.D. student in computer science, is a research scientist intern at Rakuten in Boston, Massachusetts, working remotely on multi-label few-shot learning in natural language processing. Her advisor is Hoda Eldardiry.

Naveen Gupta, a master’s degree student in computer science, is a software engineering intern at Kentik in San Francisco, California, working remotely in the web development domain and using React, Node JS, and Express JS in building SAAS products. His advisor is Anuj Karpatne. 

Huimin Han, a master’s degree student in computer science, is a machine learning engineer intern at LinkedIn in Sunnyvale, California, working on-site. She is exploring machine learning techniques to build the most accurate occupational taxonomy for every Linkedin member. Her advisor is Chris North.

Jianfeng He, a Ph.D. student in computer science, is an applied scientist intern on the AWS AI team at Amazon in Seattle, Washington, working on-site. He is doing research related to audio, text, and semantic understanding. His advisor is Chang-Tien Lu.

Meghana Holla, a master’s degree student in computer science, is a machine learning intern on the Data Technologies team at Bloomberg LP in New York, working on-site. She is researching and optimizing entity extraction methodologies on financial documents with emphasis on low inference times. Her advisor is Ismini Lourentzou.

Aneesh Jain, a master’s degree student in computer science, is a machine learning engineering intern at Cadence Solutions, working remotely on applications of language models in the healthcare domain. His advisor is Chandan Reddy.

Gaurang Karwande, a master’s degree student in the Bradley Department of Electrical and Computer Engineering, is a machine learning intern at VideaHealth, Inc., in Boston, Massachusetts, working on-site in the field of medical imaging and developing AI-powered solutions in dentistry. His advisor is Ismini Lourentzou. 

Yoonjin Kim, a Ph. D. student in computer science, is a graduate software research intern at Intel IP and Competitive Analysis in Santa Clara, California, working an on-site/virtual hybrid. She is gaining industry exposure to the latest trend in workloads and workload-related research. Her advisor is Lenwood Heath. 

M. Maruf, a Ph.D. student in computer science, is an applied scientist intern at Amazon.com in Seattle, Washington, working on-site to solve an image referencing problem with a goal of improving Amazon delivery experiences. His advisor is Anuj Karpatne.

Amarachi Blessing Mbakwe, a Ph.D. student in computer science, is an AI research associate at JPMorgan Chase & Co in New York City, working on-site. She is conducting research on natural language processing-related problems. Her advisor is Ismini Lourentzou.

Makanjuola Ogunleye, a Ph.D student in computer science, is a data scientist intern at Intuit, working remotely with the AI Capital team in Mountain View, California. The team is building a natural language processing and AI framework to improve the company’s risk assessment strategy and policy that will be added as a reusable service to the Intuit AI core capital group. His advisor is Ismini Lourentzou.

Medha Sawhney, a master’s degree student in computer science, is a machine learning engineering intern at Twitter in San Francisco, California, working remotely with the Health ML Team. Her advisor is Anuj Karpatne. 

Avi Seth, a master’s degree student in computer science, is a data scientist intern at Gastrograph AI in New York City, working remotely on generalizing the preference prediction model for flavor profiles across different demographics. His advisor is Ismini Lourentzou. 

Afrina Tabassum, a Ph.D. student in computer science, is an intern at Los Alamos National Laboratory (LANL) in New Mexico, working remotely. She is exploring machine learning techniques under varying data quality. Her advisor is Hoda Eldardiry.

Mia Taylor, a master’s degree student in computer science, is a graduate research engineer intern at Graf Research in Blacksburg, Virginia, working on-site. She is conducting applied machine learning research in a hardware context. Her advisor is Chris North.

Muntasir Wahed, a Ph.D. student in computer science, is a research intern at IBM Research – Almaden in San Jose, California, working on-site with the Intelligence Augmentation Group on set expansion techniques to build lexicons for natural language processing tasks. His advisor is Ismini Lourentzou.

Sijia Wang, a Ph.D. student in computer science, is an applied science intern at Amazon Web Services in New York City, working on-site on information extraction, entity linking, and related natural language processing tasks. Her advisor is Lifu Huang. 

Xinyue Wang, a Ph.D. student in computer science, is a research intern on the Media Science Team at Yahoo, in San Jose, California, working on-site on a project related to trending user search queries and term refinement. His advisor is Edward Fox.

Zhiyang Xu, a Ph.D. student in computer science, is an applied scientist intern at Amazon Alexa AI in Sunnyvale, California, working on-site to detect the inconsistency of facts in dialog systems and improve the interpretability of the detecting process. His advisor is Lifu Huang.

Yi Zeng, a Ph.D. student in computer engineering, is an AI research intern at SONY Corporation of America in New York City, working remotely on developing a meta-learning-based method against general training data corruptions from a security perspective. His co-advisor is Ruoxi Jia.