Amir Hussein (he/him) is a fourth-year Electrical and Computer Engineering Ph.D. student. He is advised by Sanjeev Khudanpur, and expected to graduate in 2027. His past research includes various projects in the field of cross-lingual and conversational speech processing, addressing challenges of spontaneous speech and code-switching. Amir’s current research focuses on advancing conversational speech translation systems that can process conversational long-form speech in real time. He is also exploring multimodal representation learning to overcome the challenge of limited data. Amir earned his Master’s degree in Engineering from American University of Beirut, and his Bachelor’s degree in Engineering from University of Khartoum. He is originally from Rivne in Ukraine, and in his spare time enjoys traveling, hiking, and kayaking.

Drew Prinster (he/him) is a fourth-year Computer Science PhD student at Johns Hopkins University. He is advised by Professor Suchi Saria and Professor Anqi Liu, and he is expected to graduate in 2026. His research aim is to improve the reliability and regulatability of AI and machine learning systems for high-stakes settings such as healthcare. Specifically, he primarily focuses on developing statistical tools for black-box AI systems, to ultimately communicate to end users whether individual predictions can be trusted and to help monitor post-deployment risks. Prior to Hopkins, Drew received his B.S. in Computer Science and Mathematics from Yale University in 2021, and he grew up in Boulder, Colorado. In his free time, he enjoys playing soccer, climbing, hiking, and playing board games with friends, as well as reading and drawing.

Yiqing Shen (he/him) is a third-year Computer Science PhD student at Johns Hopkins University, advised by John C. Malone Associate Professor Mathias Unberath. He is expected to graduate in 2027, and his research focuses on developing visual foundation models, that can tackle real-world challenges. These models aim to understand and interpret visual information in ways that can be applied to various fields, such as healthcare. Prior to his doctoral studies, Yiqing earned his bachelor’s degree in mathematics and applied mathematics from Shanghai Jiao Tong University in 2018. He is from Shanghai and enjoys various kinds of sports during his spare time.

Yunjuan Wang (she/her) is a sixth-year PhD student in the Computer Science Department. She is advised by Raman Arora, PhD, and is expected to graduate in Spring 2025. Yunjuan’s research focuses on trustworthy AI, deep learning theory, transfer learning, and theoretical machine learning in general, with a specific focus on theoretical understanding of robust adversarial learning and building robust models against various attacks. She has a Bachelor’s degree in Computer Science from Xi’an Jiaotong University, China, and a Master’s degree in Computer Science from Johns Hopkins University. Hailing from Tianjin, China, Yunjuan likes to spend spare time cooking, reading, and traveling.