An increasing number of tech companies, corporations, and research labs across the country are employing interns who can help them improve their products and services as well as their efficiency. 

“It’s a win-win situation,” said Naren Ramakrishnan, director of the  Sanghani Center for Artificial Intelligence and Data Analytics, “because they benefit from our students’ expertise and the students have an opportunity to contribute to solving real-world problems, which is the very essence of our center. And in many instances, what they learn in these internship positions often enhances own research interests.”

Students this summer are engaging in research that runs the gamut of artificial intelligence (AI), data analytics, and machine learning (ML). This includes work in Large Language Models (LLMs).

Following is a list of Sanghani Center interns –- where they are working and the kind of work they are doing:

Aafiya Hussain is a master’s degree student in computer science advised by Chris Thomas. An industrial metaverse intern at Nokia Bell Labs in Murray Hill, New Jersey, she is working on improving the quality of Gaussian splat models and building a robust 3D scene understanding with natural language interaction.

Ahmed Abdelhady is an undergraduate student in computer science advised by Hoda Eldardiry. He is a machine learning engineer intern at LiteraSeed in State College, Pennsylvania. He is working on building an LLM-focused script to extract clinical insights from maternal patient records to identify concerning health conditions and classify their severity. The goal is to expedite quality care for patients with pregnancy-related complications.

Alvi Ishmam is a Ph.D. student in computer science advised by Chris Thomas. He is a research intern at Futurewei Research in Framingham, Massachusetts, where he is working on self-evolving advance storage systems for Retrieval Augmented Generation (RAG) to mitigate hallucinations of LLMs.

Duo Cheng is a Ph.D. student in computer science advised by Bo Ji. He is interning as a machine learning engineer intern at DoorDash, Inc., in Sunnyvale, California, where he is working on advertising allocation.

Fausto German is a Ph.D. student in computer science advised by Chris North. A research scientist intern at Adobe in San Jose, California, he is working on a project in the vision-language domain for album and photo intelligence, using state-of-the-art deep learning techniques to learn novel alignments between text and images.

Gaurav Srivastava is a master’s degree student in computer science advised by Xuan Wang. He is an AI research intern at Dell Technologies in Austin, Texas. As part of Dell's Global Office of the Chief Technology Officer, he is working on agentic AI research with a focus on developing autonomous agents to solve critical business problems.

Kazi Hasan Ibn Arif is a Ph.D. student in computer science advised by Bo Ji. He is interning as an AI researcher at Kaliber Labs in San Francisco, California. He is working on a conversational pipeline for CareMate, Kaliber’s AI software for home-care assistant robots being designed to support patients recovering from surgery, managing chronic conditions, or navigating the challenges of aging at home.

Kazi Sajeed Mehrab is a Ph.D. student in computer science advised by Anuj Karpatne. As a Ph.D. artificial intelligence/machine learning intern at LinkedIn in Mountain View, California, he is working on research and development of LLM reasoning solutions using LinkedIn data.

Kiymet Akdemir is a Ph.D. student in computer science advised by Pinar Yanardag. She is a machine learning engineer intern at Adobe, in Seattle, Washington, where she is working on a generative multimodal foundation model pipeline that combines a multimodel LLM with diffusion renderers to produce high-fidelity images. It supports semantic understanding, multi-turn dialogue, and interactive editing, enabling tasks from initial concept design to detailed, high-fidelity image refinement.

Longfeng Wu is a Ph.D. student in computer science advised by Dawei Zhou.  She is an applied scientist intern at Amazon in Sunnyvale, California. She is focusing on developing large-scale generative recommendation models based on semantic identifiers (IDs), aiming to fundamentally transform how recommendations are generated and delivered.

Linhan Wang is a Ph.D. student in computer science advised by Chang-Tien Lu. He is a computer vision intern at XMotors.ai Inc. in Santa Clara, California, where he is working on the company’s Driving World Models with predictive power that bring more possibilities to self-driving systems.

Min Zhang is a Ph.D. student in computer science advised by Chang-Tien Lu. She is interning as an applied scientist at Amazon in Santa Clara, California, where she is working on trustworthiness of LLMs by improving the reliability and privacy preservation of LLM reasoning with multi-agent collaboration.

Najibul Haque Sarker is a master’s degree student in computer science advised by Chris Thomas. He is an AI intern at AMD Inc. in San Jose, California. He is working with the company’s Efficient GenAI team, specifically on LLMs.

Osama Bajaber is a Ph.D. student in computer science advised by Bo Ji. He is a software engineer intern at Meta in Menlo Park, California, where he is working with the Malware Analysis Team to detect malicious files across Meta's social media platforms.

Parshin Shojaee is a Ph.D. student in computer science advised by Chandan Reddy. She is a research intern at Apple in Seattle, Washington, where she is working on a project focused on better understanding and improving reasoning capabilities in large language models. Her work has contributed to a recent paper from Apple, “Illusion of Thinking,” well received by the research community and media.  

Pin-Jie Lin is a Ph.D. student in computer science advised by Tu Vu. He is an applied scientist intern at Amazon Artificial General Intelligence (AGI) in Seattle, Washington. Lin is exploring multi-modal foundation model training, designing methods to jointly model text and speech for improved cross-modal understanding.

Quyet Do is a Ph.D. student in computer science advised by Tu Vu. He is a research scientist intern at Adobe in San Jose, California, working on automatic evaluation for vision-language models.

Sha Li is a Ph.D. student in computer science advised by Naren Ramakrishnan. She is a research scientist intern at Adobe in San Jose, California, where she is developing LLM-based AI assistants for creative content generation. 

Shailik Sarkar is a Ph.D. student in computer science advised by Chang-Tien Lu. He is a ML/AI intern at the Washington Post in Washington, D.C. His team is working to improve retrieval-augmented generation (RAG)  solutions for News Chatbot that rely solely on organizational news data to help answer readers' questions about news, current affairs, and historical events with more reliable, hallucination-free, trustworthy AI responses.

Shengkun Wang is a Ph.D. student in computer science advised by Chang-Tien Lu. He is a quantitative research intern at Quantlab in Houston, Texas, where he is working on a finance market forecasting project.

Tahmina Sultana Priya is a Ph.D. student in computer science advised by Danfeng (Daphne) Yao. As a research intern in bioinformatics at the Mayo Clinic in Rochester, Minnesota, she is working on projects that apply artificial intelligence (AI) to leverage digital health, with a particular focus on improving the accuracy and effectiveness of precision medicine. Her research primarily centers on complex diseases -- such as type 2 diabetes, obesity, and Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) -- through the integration of phenotypic and genotypic data.

Tuna Meral is a Ph.D. student in computer science advised by Pinar Yanardag. He is an applied scientist intern at Amazon AGI Foundations in San Francisco, California. As part of the video generation team, Meral’s internship focuses on developing autoregressive models for creating both images and video.

Umid Suleymanov is a Ph.D. student in computer science advised by Murat Kantarcioglu. He is a data science intern at Amazon in Austin, Texas, where he is working with the Amazon Web Services (AWS) security testing team. 

Wei Fan is a Ph.D. student in computer science advised by Bo Ji. She is interning as a software engineer at Google in Seattle, Washington, working on two main projects: accelerating Tensor Processing Unit (TPU) training by implementing ZeRO-One Sharding with Gradient Accumulation in distributed system; and developing an autonomous RAG-based LLM agent to migrate Huggingface models -- from PyTorch to JAX-based Maxtext -- in a self-correcting loop that is continuously validated by an integrated unit testing agent.

Wei Liu is a Ph.D. student in computer science advised by Chris North. She is a data science intern at Verisk in Boston, Massachusetts, where she is working on data analysis related to weather and geospatial data.

Wilson Chang is a master’s degree student in computer science advised by Chang-Tien Lu. He is an AI research and development intern at TSMC, where his work centers on deploying LLMs on high-performance GPUs and developing agentic AI systems for data parsing, anomaly detection, and retrieval-augmented knowledge solutions in semiconductor manufacturing. 

Yoonjin Kim is a Ph.D. student in computer science advised by Lenwood Heath. He is a graduate software intern, working on Interactive Principal Component Analysis (ICPA) at Intel in Santa Clara, California.

Yusuf Dalva is a Ph.D. student in computer science advised by Pinar Yanardag. He is a research intern at Snapchat, Snap Inc., in Palo Alto, California, working on a project that enables users to visually target subjects to be edited and associate them with editing concepts -- adding a specific object to a certain location, for example.

Zaber Ibn Abdul Hakim is a master's degree student in computer science advised by Chris Thomas. He is an AI research intern at Comcast in Washington, D.C., where he is working on improving the company’s existing customer support assistance system.