Yang Yang
副教授
Builds agentic AI systems that learn, collaborate and act, drawing on statistical physics of complex networks and large-scale industrial AI.
Yang Yang's lab at SJTU works on learning theory & optimization and human-AI collaboration & trust. Applications close .
At a glance
- papers, 2023–2026
- —
- at T1 venues
- —
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by year2023–2026
- 0 papers2026 · T1 0 · collecting
- 0 papers2025 · T1 0
- 0 papers2024 · T1 0
- 0 papers2023 · T1 0
T1 venuesOther
Paper list
No papers from 2023–2026 are listed for this lab.
Where alumni went
Alumni are not listed on the lab homepage.
Apply to SJTUFall 2027
Computer Science PhD (international applicants)
- Round
- Self-funded
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
Similar labsnearest by research summary
- GBImperial
Matthew Wicker
- Trustworthy & safe ML
- GBImperial
Eleonora Giunchiglia
- Reasoning & neuro-symbolic AI
- USMIT
Sendhil Mullainathan
- Human-AI collaboration & trust
- USUIUC
Huan Zhang
- Trustworthy & safe ML
- USMIT
Dylan Hadfield-Menell
- Trustworthy & safe ML
- USNYU
Jaume Vives-i-Bastida
- Reasoning & neuro-symbolic AI
Your notes
Save this lab to keep notes.
Data
Some numbers could not be verified:
- The member list could not be found on the lab site.
- The alumni list could not be found on the lab site.
- No publication list could be matched on the lab site or in DBLP.
- Collected
- Verified
- Papers
- Not collected
- Members
- Not collected
- Alumni
- Not collected
Tiers are venue classifications, not lab rankings.
SJTUcloses