Ruslan Salakhutdinov
UPMC Professor of Computer Science
Studies deep learning, reinforcement learning and multimodal agents.
Ruslan Salakhutdinov's lab at CMU works on reinforcement learning, vision-language & multimodal and multimodal & grounded language. 23 papers since 2023, 21 at top venues, mostly ICLR and NeurIPS. 8 PhD students. 27 alumni, most often to Google and Apple. Applications close .
At a glance
- papers, 2023–2026
- 6/ year
- at T1 venues
- 91%
- PhD students
- 8
- MS students
- 0
- alumni listed
- 27
Papers by yearfrom the lab homepage, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 0 papers2025 · T1 0
- 8 papers2024 · T1 8
- 15 papers2023 · T1 13
T1 venuesOtherVenues: ICLR, NeurIPS, ICML, ACL, CoRL
Research focuspaper titles that use each topic's words
- Vision-language & multimodal8 papers
- Multimodal & grounded language8 papers
- Reinforcement learning6 papers
- agents1 paper
- studies deep0 papers
Paper list
From the lab homepage.
20248 papers
- ICLR (T1)Confronting Reward Model Overoptimization with Constrained RLHF (opens in a new tab)
- ICLR (T1)Contrastive Difference Predictive Coding (opens in a new tab)
- ICLR (T1)Effective Data Augmentation With Diffusion Models (opens in a new tab)
- ICLR (T1)Manifold Preserving Guided Diffusion (opens in a new tab)
- ICLR (T1)Multimodal Learning Without Labeled Multimodal Data: Guarantees and Applications (opens in a new tab)
- ICLR (T1)Plan-Seq-Learn: Language Model Guided RL for Solving Long Horizon Robotics Tasks (opens in a new tab)
- ICLR (T1)Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data (opens in a new tab)
- ACL (T1)VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks (opens in a new tab)
202315 papers
- ICML (T1)A Connection between One-Step RL and Critic Regularization in Reinforcement Learning (opens in a new tab)
- ICLR (T1)A Simple Approach for Visual Rearrangement: 3D Mapping and Semantic Search (opens in a new tab)
- Learning for Dynamics and Control ConferenceContrastive Example-Based Control (opens in a new tab)
- ACL (T1)Cross-modal Attention Congruence Regularization for Vision-Language Relation Alignment (opens in a new tab)
- NeurIPS (T1)Factorized Contrastive Learning: Going Beyond Multi-view Redundancy (opens in a new tab)
- NeurIPS (T1)Generating Images with Multimodal Language Models (opens in a new tab)
- ICML (T1)Graph Generative Model for Benchmarking Graph Neural Networks (opens in a new tab)
- ICML (T1)Grounding Language Models to Images for Multimodal Inputs and Outputs (opens in a new tab)
- CoRL (T1)Imitating Task and Motion Planning with Visuomotor Transformers (opens in a new tab)
- ICMIMultimodal Fusion Interactions: A Study of Human and Automatic Quantification (opens in a new tab)
- ICLR (T1)MultiViz: An Analysis Benchmark for Visualizing and Understanding Multimodal Models (opens in a new tab)
- NeurIPS (T1)Quantifying & Modeling Feature Interactions: An Information Decomposition Framework (opens in a new tab)
Where alumni went27 listed, 65% to industry
Industry 15Academia 8
Most often to
- Apple
- Meta
Also to
- Duke University
- NYU
- Peking University
Apply to CMUFall 2027
CMU SCS Computer Science PhD
- Round
- Single round
- Opens
- GRE
- See program page
- English
- TOEFL / IELTS / Duolingo (F-1/J-1 non-native speakers)
- Fee
- USD 100 (USD 80 by early deadline)
Confirmed on the program page.
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