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Team HokieTokie

We are committed to advancing AI by developing code-generating LLMs that balance innovation, security, and reliability. Our goal is to create a system that adapts to emerging challenges while maintaining strong functionality, demonstrating that safety and utility can work together to drive responsible technology development for the benefit of society.

By Virginia Tech
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Yi Zeng - Team leader

Yi Zeng is a Ph.D. candidate in Computer Engineering at Virginia Tech under the supervision of Prof. Ruoxi Jia. His research focuses on AI safety and responsibility. Zeng has an extensive publication history in leading security and responsible AI venues, including USENIX Security, ACM CCS, NeurIPS, ICML, ICLR, ICCV, ACL, AsiaCCS, IJCAI, and TMLR. He obtained his Masters from UC San Diego and Bachelors from Xidian University. Zeng has industry experience interning at Meta and Sony AI, where he worked on techniques for responsible AI and security. His research has been featured in high-profile media outlets such as the New York Times, PCmag, the Register, and VentureBeat. Zeng's honors include the Best Social Impact Award from the ACL 2024, the Amazon Research Fellowship, and the Best Paper award at ICA3PP 2020.

Mahavir Dabas

Mahavir Dabas is a Masters student in Computer Engineering at Virginia Tech under Prof. Ruoxi Jia. He obtained his Bachelor's from the Indian Institute of Information Technology. Dabas has worked at ZS Associates as an NLP intern and at IIT Mandi as a Research Intern, focusing on combining reinforcement learning with cognitive science. He has also served as a Graduate Teaching Assistant in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. Currently, he works as a Graduate Research Assistant at the Responsible Data Science Laboratory at VT, focusing on the safety of large language models.

Adam Nguyen

Adam Nguyen is a third-year undergraduate student in Computer Science at Virginia Tech working under Prof. Ruoxi Jia's supervision. His research focuses on improving Large Language Model capabilities and reliability. He previously interned at Raytheon Technologies as a software engineer, developing enterprise software solutions. Currently, he is an Undergraduate Research Assistant in the Responsible Data Science Laboratory, contributing to research projects and building automated pipelines for experiments.

Tran Huynh

Tran Huynh is a first-year Ph.D. student in Computer Engineering at Virginia Tech, working under the supervision of Prof. Ruoxi Jia. She earned her Bachelor's degree in Computer Science from Vietnam National University. Huynh's research centers on AI safety, with her works published in venues including ECCV, AAAI, and EMNLP. She is currently a Research Assistant in the Responsible Data Science Laboratory at Virginia Tech, focusing on enhancing the safety alignment of large language models.

Sanchit Kabra

Sanchit is a first year Masters of Science in Computer Science student working under supervision of Prof. Rouxi Jia and Prof Chandan Reddy. He earned his Bachelors in CS from BITS Pilani, India. Kabra’s research centers around Responsible AI with a focus on evaluation and robustness. He has previously interned at Aalto University focusing on extreme classification. Currently, he is a Graduate Research Assistant at CS department working on concept alignment in multimodal models and code tasks on semi structured data.

Nikhil Reddy Billa

Nikhil is a first year Masters student in Computer Engineering at Virginia Tech working under Prof. Ruoxi Jia. He earned his Bachelors from National Institute of Technology Rourkela. Nikhil has worked as Software Engineer at NCR Corporation and ML Research Assistant at IIIT Hyderabad, focusing on Autonomous navigation in unstructured traffic and Adversarial Weather. Currently he is Graduate Research Assistant at Responsible Data Science Lab at VT, focusing on privacy in LLMs.

Bhuvishi Bansal

Bhuvishi Bansal is a Computer Science freshman at Virginia Tech, specializing in natural language processing (NLP) and the empirical evaluation of large language models. Her research explores bias detection, robustness analysis, and parameter-driven performance assessment, with a strong focus on enhancing the safety, fairness, and reliability of LLMs in real-world applications.

Rohan Praveen Chavan

Rohan Chavan is first year Masters of Science in Computer Engineering student. He has earned his Bachelors in IT from K.J. Somaiya College of Engineering, India. He has previously worked as a Intern at Colgate Palmolive Global Business Services, as an Robotic Process Automation developer where he helped the team to develop their inhouse LLM and also facilitated the integration of this LLM into their chatbot ecosystem. He is currently working for the Responsible Data Science Lab under guidance of Professor Ruxoi Jia on AI safety and safer, robust code generation by Large Language Models.

Ruoxi Jia - Faculty advisor

Ruoxi Jia is an assistant professor in the the Bradley Department of Electrical and Computer Engineering at Virginia Tech. She earned her PhD in the EECS Department from UC Berkeley and a B.S. from Peking University. Jia's recent work focuses on data-centric and trustworthy machine learning. Jia is the recipient of the NSF CAREER Award, the Dean's Award for Outstanding New Assistant Professor, the Chiang Fellowship for Graduate Scholars in Manufacturing and Engineering, the 8108 Alumni Fellowship, and the Okamatsu Fellowship, Cisco Research Awards, Amazon-VT Initiative Research Awards, and the Best Social Impact Paper Award at ACL 2024. She was selected for the Rising Stars in EECS in 2017. Jia’s work has been featured in multiple media outlets such as MIT Technology Review, New York Times, IEEE Spectrum, and Wired. Her work has been adopted in the financial sector and tech companies.

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