Ruizhe Song 宋睿哲

Short Bio

Master’s student of COSEC research group at Nanjing University, currently a concurrent enrollment student of UC Berkeley through the BISP program. My research background focuses on multimedia security and related AI topics. 

Education

• UC Berkeley — Concurrent Enrollment, in progress, 2025~now

• Nanjing University — M.S. (Software Institute), in progress (second year)2025~now

• Nanjing University — B.S. (Computer Science Department), 2020~2024

Research Interests

• Multimedia security, Generative AI, Deep learning, Computer vision, Network
  
  

Selected Publications

• First-author, Robust Steganographic System Against Multi-scale Scaling Attacks, IEEE GLOBECOM (accepted 2025).

Projects (Selected)

• Project: Robust Steganographic System Against Multi-scale Scaling Attacks (Master’s research, published at IEEE GLOBECOM)

 Role & Contribution: Proposed the core idea of an anti-scaling image steganography method; independently implemented the code, conducted experiments, and drafted the manuscript (with advisor’s guidance and revisions).

Duration: About 1 semester (part-time alongside coursework).

Origin: Research direction suggested by my advisor, method design and execution primarily led by me.

• Project: LLM-assisted AI Agent (Course Project)

Role & Contribution: Designed and implemented an AI agent framework that leverages large language models to build an arXiv search assistant and a course enrollment assistant, which covered RAG, AI agent and prompt engineering.
Duration: About 1 semester.
Origin: Proposed as a collaborative course project. I contributed mainly to system design and coding.

• Project: 3D Material Reconstruction System (Undergraduate Innovation Project)

Role & Contribution: Participated as the 3rd out of 9 members. Focused on learning and improving the reconstruction techniques, preparing demonstrations.

Duration: About 1 semester (joined from mid-phase of the project).

Origin: Project led by faculty from Nanjing Univ. VR & Graphics group.

Outcome: Awarded Provincial First Prize; valuable teamwork experience in a large-scale collaboration.

• Project: Adversarial Examples on Radar-Sensed Objects (Team research)

Role & Contribution: Supported a senior student’s project by running experiments, applying adversarial sample attacks on radar-detected objects, and validating results.

Duration: Several months.

Origin: Idea proposed by a PhD student in my lab; I mainly contributed to the experimental work.

Outcome: Contributed as a co-author (4th) in the ongoing paper draft.

• Project: Smart Elevator Maintenance Planning (Applied AI project, undergraduate)

Role & Contribution: Assisted in data preprocessing, clustering analysis, and location optimization for new elevator inspection centers in Nanjing.

Duration: Several months (under the guidance of a senior graduate student).

Origin: Industry collaboration with Nanjing Special Equipment Inspection Institute.

Outcome: Supported project delivery to the client; gained practical experience in applied AI and teamwork.

• Project : NEMU (Computer Architecture Emulator, Nanjing Univ.)

Role & Contribution: Built a full emulator framework (within provided skeleton) simulating CPU components, registers, floating-point units, and OS-level program execution. Debugged and developed modules independently, eventually enabling the emulator to load small operating systems and run simple games.

Duration: ~1 semester (weekly lab assignments 2–5 hrs each).

Origin: Lab for CS systems class, executed individually.

Outcome: Achieved a functioning emulator capable of running simple operating systems and games.

• Kaggle 

My kaggle account: Rachael Song | Kaggle

Awards & Honors

• Special Scholarship for Fundamental Subjects — Grand Prize (Top Award), Nanjing University (2022~2023)

Links

• CV (PDF):  View CV
  
  

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