cv
General Information
Full Name | Kaijian Wang |
kaijianwang2003 [at] gmail.com, wangkaijian [at] ustc.edu.cn |
Education
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2021 - 2025 B.S. in Information Security
University of Science and Technology of China, Anhui, China
Experience
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2024 - Now Research Intern
UC San Diego, USA - LLM Server System
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2023 - 2024 Research Intern
WMGroup, USTC, China - Adivisors Prof. Weiming Zhang, Prof. Kejiang Chen
- Robust Image Watermark
- Proposed a watermark recovery module based on image hiding, designed to restore information-embedded images subjected to cropping and spatial manipulation.
- Completed experiments on the reproduction of related research and developed the code for the module framework as proposed by coworker.
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2023 - 2024 Research Intern
- Adivisors Prof. Weiming Zhang, Postdoc. Zehua Ma
- Review on Diffusion Model Watermarking
- Learned the principles of diffusion model in depth, and explored works involved in embedding watermarks on images generated by diffusion models.
- Tried to design a guiding map to use the probability distribution information in the diffusion process of the Diffusion Model to optimize subsequent watermark embedding.
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2022 - Now CTF Player
USTC-NEBULA, USTC, China - Member of USTC-NEBULA
- Our team ranks 16th/1655(~0.97%) in China in the CTFTime rating during 2023-2024!
- Mainly focus on Misc (Steganograpy and Forensics)
Projects
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2024 Tiny-C Compiler
- Developed a simplified C compiler in C, implementing lexical analysis, syntax analysis, and Intermediate Representation (IR) generation for the Tiny-C language.
- Supported key C language features in Tiny-C, including assignment, arithmetic operations, while loops, and if-else statements.
- Github repo Tiny-C Compiler
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2024 Semantic Guidance for Diffusion Model
- Conducted a detailed investigation into the semantic guidance of diffusion models, focusing on understanding both the theoretical underpinnings and experimental outcomes.
- Identified existing issues within the semantic guidance provided by diffusion models, particularly emphasizing the loss of positional information.
- Developed a straightforward method to address the loss of positional information in the semantic guidance of diffusion models, enhancing model accuracy and interpretability.
- Blog post Semantic Guidance for Diffusion Model
Selected CTF Awards
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2024 - 3rd prize(~20%) in D^3CTF
- Top 9th(~1%) in L3HCTF
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2023 - Top 3rd(~1%) in TPCTF
- 3rd prize(~20%) in D^3CTF
- 3rd prize(~10%) in Hackergame2023
Honors and Awards
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2024 - DAS Scholarship(Top 10 in the department)
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2023 - Outstanding Student Scholarship(Bronze)
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2022 - Zhang Zongzhi Scholarship
Teaching Assistant
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2024 Information Security Design and Practice
USTC, China - Information hiding in multimedia and file analysis
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2023 Data Structure and Algorithm
USTC, China
Other Interests
- Anime: Mushoku Tensei, Oshinoko, etc.