About Me

• [Bio] Jun Zhuang is an Assistant Professor of Computer Science at Boise State University. Prior to joining Boise State, he earned a Ph.D. degree in Computer Science at Purdue University in Indianapolis (previous IUPUI) in 2023, advised by Prof. Mohammad Al Hasan, and obtained an M.S. degree in Computer Science from University at Buffalo (UB) (UB) in 2018, advised by Prof. Mingchen Gao. Besides, he received an M.S. degree in Finance from the Rochester Institute of Technology (RIT) in 2013 and was awarded a B.E. degree in Safety Engineering from South China University of Technology (SCUT) in 2011.
• [Research Interests] He aims to investigate trustworthy and robust machine learning algorithms (or deep learning models) in multiple domains, such as quantum information, medical imaging, graphs, etc. Feel free to check out his Google Scholar profile for more details.

Team

Join Trustworthy and Robust AI Lab (TRAIL)

• He is looking for highly self-motivated Ph.D. students generally interested in his research topics.
• Please send him an email with the title “Ph.D. Application (Fall24) - {Name} - {Research Interests}” and the following information.
  1. Introduce your education, technical, and research background in your CV;
  2. Introduce your motivation (why do you want to pursue a Ph.D. degree?), your past research experience (what are the connections between both research interests?), your future research interests (how Jun’s research can help you; please feel free to propose any idea that you would like to work with Jun), and your future career plan (what’s your plan after graduation?).
• Prospective students are expected to be passionate about research. Strong programming skills and a solid foundation in statistics will be a big plus. Students with other STEM majors are welcome.
• How Jun helps his Ph.D. students?
  1. Provide weekly hands-on instructions on their research projects;
  2. Collaborate with students on top-tier conference (or journal) papers;
  3. Help students build strong professional profiles for future careers.

Current Students

• Ph.D. Student(s): Maqsudur Rahman.
• M.S. Student(s): Chia-Ying Wu, Shipra Kumari.

Alumni

• M.S. Student(s): Jack Cunningham.

Teaching and Mentoring

Instructor

• CS434 Applied Deep Learning (Sp24)
• CS533 Introduction to Data Science (Fa23, Fa24)
• CS597 Deep Learning (Sp25)
• CS695 Capstone Course (Sp25)

Mentor

• DS REU: Data Science of Risk and Human Activity (Su19)
• Blockchain REU: Embracing Blockchain for a Secure and Trustworthy Tomorrow (Su24)

Services

Internal Services

• Served on the CS graduate committee. (Fa23 - now)
• Served on the PhD admission committee. (Sp24 - now)
• Served on the AI faculty search committee. (Fa24)

External Services

• Reviewer(s): NeurIPS, AAAI, KDD, CIKM, AISTATS, TKDE, TNNLS, etc.
• Panelist(s): NSF’24, DOE’24.
• Session chair(s): CIKM’24.
• Workshop(s): Trustworthy and Responsible AI @ CIKM’24.

Professional Experience [LinkedIn]

• Assistant Professor, Boise State University, ID (Jul23 - present)
• Ph.D. Software Engineer Intern, Uber Technologies, Inc., CA (Su22)
• Algorithms and Advanced Analytics Intern, Roche Diabetes Care, Inc., IN (Su21)
• Research Intern, The University of Tennessee, Knoxville, TN (Su20)
• Foreign Exchange Trading Specialist, China Merchants Bank Co., Ltd., China (Jan14 - Jul16)

Contact

• Email: junzhuang [AT] boisestate [DOT] edu
• Office: CCP 354
• Address: 777 W Main St., Boise, ID 83702

News

• 2025-01: One survey paper “Investigating and Mitigating Barren Plateaus in Variational Quantum Circuits: A Survey” has been accepted for publishing in the Quantum Information Processing (QIP) journal.
• 2024-10: Jun attended a QED-C annual meeting in Seattle.
• 2024-10: Jun co-organized a TRAI workshop and served as a session chair at CIKM’24 in Boise.
• 2024-08: One paper “Blockchain for large language model security and safety: A holistic survey” has been accepted for publishing in the SIGKDD Explorations journal.
• 2024-08: One paper “Understanding Survey Paper Taxonomy about Large Language Models via Graph Representation Learning” is presented in the ACL’24 SDP workshop.
• 2024-05: One paper “Robust Data-centric Graph Structure Learning for Text Classification” is presented in the WWW’24 DCAI workshop.
• 2024-02: Jun attended CRA’s Career Mentoring Workshops in DC.
• 2023-08: Jun attended a QSim conference in Telluride, CO.
• 2023-07: Jun joined the computer science department at Boise State University as an assistant professor.
• 2023-06: Jun defended his dissertation.
• 2022-08: Jun is awarded SIGIR Student Travel Grant for CIKM 2022 conference.
• 2022-08: One paper “Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label Propagation” is accepted for CIKM 2022 Conference.
• 2022-02: One paper “How Does Bayesian Noisy Self-Supervision Defend Graph Convolutional Networks?” is published in Neural Process Lett Journal.
• 2021-12: One paper “Deperturbation of Online Social Networks via Bayesian Label Transition” is accepted for SIAM SDM 2022 Conference.
• 2021-12: One paper “Defending Graph Convolutional Networks against Dynamic Graph Perturbations via Bayesian Self-supervision” is accepted for AAAI 2022 Conference.
• 2021-06: One paper “Non-exhaustive Learning Using Gaussian Mixture Generative Adversarial Networks” is accepted for ECML-PKDD 2021 Conference.
• 2021-02: One paper “Geometrically Matched Multi-source Microscopic Image Synthesis Using Bidirectional Adversarial Networks” is accepted for MICAD 2021 conference.
• 2019-10: One paper “Into the Reverie: Exploration of the Dream Market” is accepted for IEEE BigData 2019 conference.
• 2019-10: One paper “Lighter U-Net for Segmenting White Matter Hyperintensities in MR Images” is accepted for MobiQuitous 2019 conference.