Portfolio
Renwei Meng
I build systems that translate curiosity into usable tools — from papers to production.
Renwei Meng
Research output
Research spanning trustworthy generative AI, reliable language models, neurocognitive intelligence, and multimodal detection.
Renwei Meng*, Yansen Han*, Tao Lin
Co-first authors; equal contribution
International Conference on Learning Representations (ICLR), 2027
Renwei Meng
AAAI Conference on Artificial Intelligence (AAAI), 2027
Renwei Meng, Bowen Zhang, Jian Wang, et al.
International Conference on Neural Information Processing (ICONIP), 2026
View paperRenwei Meng, Hongyi Zhang
23rd Pacific Rim International Conference on Artificial Intelligence (PRICAI), 2026
Renwei Meng
International Conference on Artificial Neural Networks (ICANN), 2026
View paperJingming Wang*, Renwei Meng*, Yunjie Si*
Co-first authors; equal contribution
28th ACM International Conference on Multimodal Interaction (ICMI), 2026
View paperRenwei Meng
arXiv preprint, 2026
View paperRenwei Meng
18th Asian Conference on Machine Learning (ACML), 2026
Renwei Meng*, Haoyi Wu*, Jingming Wang*
Co-first authors; equal contribution
18th Asian Conference on Machine Learning (ACML), 2026
View paperA snapshot of my academic path and undergraduate journey.
Across frontend, backend, APIs, deployment, and performance tuning.
Turning raw data into actionable insights via modeling and visualization.
Focused on machine learning, deep learning, LLMs, computer vision, and intelligent systems, spanning data processing, training, and inference deployment.
I work across four research tracks from method exploration to system delivery.
Computer Vision
LLM
Brain-Computer Interface
Deep Learning & Machine Learning
Musician
Code + Music
I am a drummer, and I also play guitar and piano. I compose music as well.
My Gears
Music and software both reward rhythm, structure, and deliberate practice.
Music Component
Tap the vinyl to play
Music Tags
An Agent-RAG framework that organizes knowledge as method nodes with dual-tree indexing, strategy-guided synthesis, and verification-based pruning, enabling explainable and controllable innovation.
A group-aware EEG emotion recognition framework that combines individual neural dynamics, learnable group prototypes, and multi-subject resonance modeling to improve cross-subject generalization.
A layered multi-agent workflow for repository-level bug and vulnerability detection: risk triage → context expansion → specialist agents → selective verification → evidence fusion, aiming for higher recall, fewer false positives, and better interpretability.
Featured ResearchCORTEX / CORTEX-LOOP
Watch an autonomous cognition experiment: single-participant EEG, live tasks and explainable neural metrics. Explore RELAY and human–AI learning loops.
An AI-native product built around pet vocalization understanding, multimodal behavior analysis, and data flywheel design, covering an internal annotation platform, a consumer-facing app, agent workflows, RAG pipelines, and monetization strategy.
An interactive computer graphics lab for rasterization algorithms, covering DDA, Bresenham, circles, scanline polygons, region filling, fonts, and OpenGL primitive modes.
A latest hands-on tutorial for AI-assisted mathematical modeling, covering agents, workflow automation, and competition-oriented methodology.
Research does not magically become a product. The real transformation happens when technical novelty is translated into user value, engineering reliability, and a repeatable business model.
About
I enjoy turning complex problems into clean interfaces and reliable systems. My work sits at the intersection of AI, data, and product.
About