Baharan Mirzasoleiman
Associate Professor
Leads the BigML group on data-efficient and robust machine learning through data selection and coreset methods.
Baharan Mirzasoleiman's lab at UCLA works on trustworthy & safe ML and efficient training & inference. 38 papers since 2023, 32 at top venues, mostly ICML and ICLR. 7 PhD students and 2 master's students. 2 alumni, most often to Google and OpenAI. Applications close .
At a glance
- papers, 2023–2026
- 10/ year
- at T1 venues
- 84%
- PhD students
- 7
- MS students
- 2
- alumni listed
- 2
Papers by yearfrom the lab homepage, 2023–2026
- 9 papers2026 · T1 7 · collecting
- 6 papers2025 · T1 5
- 12 papers2024 · T1 12
- 11 papers2023 · T1 8
T1 venuesOtherVenues: ICML, ICLR, NeurIPS, AISTATS, TMLR
Research focuspaper titles that use each topic's words
- Efficient training & inference16 papers
- data selection3 papers
- data-efficient3 papers
- Trustworthy & safe ML2 papers
- robust machine0 papers
Paper list
From the lab homepage.
20269 papers
- ICML (T1)Data Selection for Fine-tuning Vision Language Models via Cross Modal Alignment Trajectories
- ICLR (T1)Do We Need All the Synthetic Data? Targeted Synthetic Image Augmentation via Diffusion Models
- COLMHow Transformers Learn to Plan via Multi-Token Prediction
- COLMLearning as Reasoning Unfolds: Progressive Rollout Allocation for Efficient Reinforcement Learning
- ICML (T1)Reasoning Quality Emerges Early: Data Curation for Reasoning Models
- ICML (T1)Theoretical Perspectives on Data Quality and Synergistic Effects in Pre-and Post-Training Reasoning Models
- ICML (T1)Tuning the Implicit Regularizer of Masked Diffusion Language Models: Enhancing Generalization via Insights from k-Parity
- ICLR (T1)Understanding the Role of Training Data in Test-Time Scaling
- TMLR (T1)Verify when Uncertain: Beyond Self-Consistency in Black Box Hallucination Detection
20256 papers
- ICLR (T1)Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-Training of Deep Networks
- ICLR (T1)Mini-batch Coresets for Memory-efficient Language Model Training on Data Mixtures
- DMLRMM-GEN: Enhancing Task Performance Through Targeted Multimodal Data Curation
- TMLR (T1)Occam’s Razor for SSL: Memory-Efficient Parametric Instance Discrimination
- ICML (T1)Representations Shape Weak-to-Strong Generalization: Theoretical Insights and Empirical Predictions
- ICML (T1)Synthetic Text Generation for Training Large Language Models via Gradient Matching
202412 papers
- ICML (T1)Better Safe than Sorry: Pre-training CLIP against Targeted Data Poisoning and Backdoor Attacks
- NeurIPS (T1)Changing the Training Data Distribution to Reduce Simplicity Bias Improves In-distribution Generalization
- ICLR (T1)Data Distillation Can Be Like Vodka: Distilling More Times For Better Quality
- AISTATS (T1)Data-Efficient Contrastive Language-Image Pretraining: Prioritizing Data Quality over Quantity
- ICML (T1)Few-shot Adaption to Distribution Shifts By Mixing Source and Target Embeddings
- UAI (T1)Graph Contrastive Learning under Heterophily via Graph Filters
- AISTATS (T1)Identifying Spurious Biases Early in Training through the Lens of Simplicity Bias
- ICLR (T1)Investigating the Benefits of Projection Head for Representation Learning
- UAI (T1)Investigating the Impact of Model Width and Density on Generalization in Presence of Label Noise
- ICML (T1)NeWRF: A Deep Learning Framework for Wireless Radiation Field Reconstruction and Channel Prediction
- NeurIPS (T1)SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models
- ICLR (T1)Understanding the Robustness of Multi-modal Contrastive Learning to Distribution Shift
202311 papers
- ICDHA Self-supervised Framework for Improved Data-Driven Monitoring of Stress via Multi-modal Passive Sensing
- ICML (T1)Data-Efficient Contrastive Self-supervised Learning: Most Beneficial Examples for Supervised Learning Contribute the Least
- AISTATS (T1)High Probability Bounds for Stochastic Continuous Submodular Maximization
- ICML (T1)Mitigating Spurious Correlations in Multi-modal Models during Fine-tuning
- HotStorageNeSSA: Near-Storage Data Selection for Accelerated Machine Learning Training
- TKDE (T1)On the fairness of time-critical influence maximization in social networks
- NeurIPS (T1)Robust Contrastive Language-Image Pre-training against Data Poisoning and Backdoor Attacks
- NeurIPS (T1)Robust Learning with Progressive Data Expansion Against Spurious Correlation
- Journal of Affective DisordersSleep, Brain Systems, and Persistent Stress in Early Adolescents During COVID-19: Insights from the ABCD Study
- ICML (T1)Towards Sustainable Learning: Coresets for Data-efficient Deep Learning
- ICML (T1)Which Features are Learned by Contrastive Learning? On the Role of Simplicity Bias in Class Collapse and Feature Suppression
Where alumni went2 listed, 100% to industry
Industry 2Academia 0
Most often to
- OpenAI
Apply to UCLAFall 2027
Computer Science PhD
- Round
- Single round (Dec 15)
- Opens
- —
- GRE
- optional
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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