Associate Professor and Doctoral Supervisor at the National Engineering Laboratory for Big Data, Shenzhen University (a recipient of the "Hundred Talents Program").
Background:
2012-2016: Admitted to Peking University's Department of Mathematics through an undergraduate mathematics competition.
2016-2021: Pursued a PhD in Computer Science at Peking University, receiving the Apple PhD Scholarship (only one recipient in mainland China).
Graduated with awards including Outstanding Graduate of Beijing, Outstanding Graduate of Peking University, Huawei Genius Youth, and Tencent Technical Expert.
Received honors from ACM SIGSAC and the China Electronics Education Society.
Recruitment: Research topics and directions will be customized based on students' individual interests. Academically, the focus is on publishing papers in Nature sub-journals and CCF A-level papers. In terms of application, students are encouraged to explore new commercial product forms in the era of large-scale models, and assistance will be provided in connecting students with relevant corporate resources for implementation.
1. We are continuously recruiting undergraduate students/students applying for postgraduate studies/those preparing for postgraduate entrance exams who are interested in my research direction. Undergraduate students are encouraged to join our group for internships during their sophomore summer, with an internship period of no less than 6 months.
2. We have abundant computing resources, with over 20 local 4090 computing power servers and sufficient H2O cloud computing power.
We welcome students who are interested in (1) exploring cutting-edge model alignment technologies and (2) building entirely new AI-native commercial products in the AGI era to join our research group! Please send your [CV + research plan + supporting materials, etc.] in a package to wubingzheagent@gmail.com & wubingzhe@szu.edu.cn.
I encourage students to intern at leading domestic companies. If you meet our group's requirements (one first-author CCF A paper), I will recommend you for internships in core departments of companies like ByteDance and Tencent, which we collaborate with. Currently, three visiting students and students from our university have already secured internships in core departments related to large-scale model application algorithms at ByteDance and Tencent through this pathway. Research Directions
1. Large Model Alignment and Security
1) Constructing secure long-inference and slow-thinking models and applying them to robotics, finance, and other scenarios.
2) Constructing trusted tool invocation and RAG systems; researching security attack and defense methods.
2. Applications
1) Finance: Constructing a multi-agent risk early warning system for the financial market and applying it to downstream financial risk control, secondary market risk monitoring, and other fields.
2) Biomedicine: Designing out-of-distribution optimization methods to address model reliability issues in downstream applications such as two-photon imaging, pathological images, and genomics.
3) Robotics: Constructing corresponding alignment technologies for edge-side trusted embodied intelligent models.
4) Other related fields: such as AI supercomputing cluster operation and maintenance, architectural design, etc.
Basic Requirements for Students:
1. Proficiency in various AI tools, including Cursor, Coze, and LangChain.
2. Solid foundation in machine learning and mathematics.
3. Strong programming skills and system optimization ability are a plus.
4. Self-motivated and willing to explore cutting-edge technologies and products in the upcoming AGI industry cycle.
Personal Profile
Bachelor's and PhD degrees are from Peking University, under the supervision of Professor Sun Guangyu. Research has long focused on AI security and trustworthy AI, with over 40 papers published in top international journals and academic conferences, including:
(1) 20 CCF (China Computer Federation) Class A conference or journal papers;
(2) In the past five years, the applicant has published 13 CCF-A conference or journal papers as the first author or corresponding author, including 1 ICML oral paper (acceptance rate 2.3%) and 2 NeurIPS spotlight papers (acceptance rate 5%);
(3) According to Google Scholar, the total number of citations for the past five years is over 1900. (4) Has received the ACM SIGSAC Excellent Doctoral Dissertation Award and the China Electronic Education Society Excellent Doctoral Dissertation Award.
In addition, the applicant has extensive experience in the industrial transformation of academic achievements. The applicant is committed to applying the above-mentioned series of achievements in trustworthy AI to different interdisciplinary fields: (1) Open Domain Risk Governance: Based on the basic model, a more intelligent risk governance agent is built for a series of scenarios including content review, financial risk control, and text-to-image bias governance. Some of the above research results have been applied to the Tencent Charity risk control scenario to combat black and gray industries, and have won the Tencent Sustainable Social Value Award. (2) Life Sciences: A series of out-of-distribution robust optimization algorithms are applied to drug discovery, pathological analysis, omics analysis and other scenarios. A cross-disciplinary collaborative paper was published in Nature Methods, with an impact factor of 58.
