MUVERA Authors:
- Laxman Dhulipala (Google Research & University of Maryland)
- Majid Hadian (Google DeepMind)
- Jason Lee (Google Research & UC Berkeley)
- Rajesh Jayaram (Google Research)
- Vahab Mirrokni (Google Research, VP & Google Fellow)
1. Laxman Dhulipala (Google Research & UMD)
Top 10 Recent Papers (2023-2025)
- Authors: Laxman Dhulipala, et al.
- Venue: arXiv:2506.18384
- Date: June 2025
- Focus: Dynamic parallel clustering algorithms
- DynHAC: Fully Dynamic Approximate Hierarchical Agglomerative Clustering (January 2025)
- Authors: Shangdi Yu, Laxman Dhulipala, Jakub Lacki, Nikos Parotsidis
- Venue: CoRR abs/2501.07745
- Date: January 2025
- Focus: Dynamic hierarchical clustering
- The ParClusterers Benchmark Suite (PCBS): A Fine-Grained Analysis of Scalable Graph Clustering (November 2024)
- Authors: Laxman Dhulipala, Jakub Lacki, Vahab Mirrokni, Julian Shun
- Venue: arXiv:2411.10290
- Date: November 2024
- Focus: Benchmarking parallel clustering algorithms
- Authors: Laxman Dhulipala, Majid Hadian, Jason Lee, Rajesh Jayaram, Vahab Mirrokni
- Conference: NeurIPS 2024
- Focus: Multi-vector retrieval optimization
- Also available: NeurIPS Proceedings
- Optimal Parallel Algorithms for Dendrogram Computation and Single-Linkage Clustering (2024)
- Authors: Laxman Dhulipala, Xiaojun Dong, Kishen N. Gowda, Yan Gu
- Conference: SPAA 2024, VLDB 2024
- Focus: Parallel hierarchical clustering algorithms
- Authors: Laxman Dhulipala, et al.
- Conference: ACM Workshop on Highlights of Parallel Computing
- Date: July 26, 2024
- Focus: Massive-scale graph clustering
- Also available: ACM Digital Library
- It’s Hard to HAC with Average Linkage! (April 2024)
- Authors: MohammadHossein Bateni, Laxman Dhulipala, Kishen N Gowda, D Ellis Hershkowitz, Rajesh Jayaram, Jakub Lacki
- Venue: arXiv:2404.14730
- Date: April 23, 2024
- Focus: Complexity analysis of hierarchical clustering
- Also available: ICALP 2024
- Practical Parallel Algorithms for Near-Optimal Densest Subgraphs on Massive Graphs (2024)
- Authors: Pattara Sukprasert, Quanquan C. Liu, Laxman Dhulipala, Julian Shun
- Conference: ALENEX 2024
- Date: January 2024
- Focus: Parallel graph algorithms for dense subgraph detection
- ParANN: Scalable and Deterministic Parallel Graph-Based Approximate Nearest Neighbor (2024)
- Authors: Laxman Dhulipala, Yan Gu, Harsha Vardhan Simhadri, Yihan Sun
- Conference: PPoPP 2024
- Focus: Parallel approximate nearest neighbor search
- Parallel Batch-Dynamic Graphs: Algorithms and Lower Bounds (2023)
- Authors: Laxman Dhulipala, David Durfee, Janardhan Kulkarni, et al.
- Conference: SODA 2023
- Focus: Dynamic graph algorithms with theoretical guarantees
Research Focus Areas
- Parallel Graph Algorithms: Leading expert in scalable graph processing
- Clustering Algorithms: Pioneer in massive-scale hierarchical clustering
- Approximate Nearest Neighbor: Advanced parallel ANN systems
- Dynamic Algorithms: Cutting-edge work on dynamic graph structures
2. Majid Hadian (Google DeepMind)
Top 10 Recent Papers (2023-2025)
- Authors: Gemini Team (including Majid Hadian)
- Venue: Google DeepMind Technical Report
- Date: June 17, 2025
- Focus: Advanced large language model with enhanced reasoning
- Authors: Amir Zandieh, Majid Daliri, Majid Hadian, Vahab Mirrokni
- Venue: arXiv:2504.19874
- Date: May 1, 2025
- Focus: Optimal online vector quantization algorithms
- Clustering Multi-Vector Representations for Denoising and Pruning (May 2025)
- Authors: João Veneroso, Rajesh Jayaram, Jinmeng Rao, Gustavo Hernández Ábrego, Majid Hadian, Daniel Cer
- Venue: arXiv:2505.11471
- Date: May 16, 2025
- Focus: Multi-vector representation optimization
- PolarQuant: Quantizing KV Caches with Polar Transformation (February 2025)
- Authors: Amir Zandieh, Majid Daliri, Vahab Mirrokni, Majid Hadian
- Venue: arXiv preprint
- Date: February 8, 2025
- Focus: Efficient KV cache quantization for transformers
- Authors: Laxman Dhulipala, Majid Hadian, Jason Lee, Rajesh Jayaram, Vahab Mirrokni
- Conference: NeurIPS 2024
- Focus: Multi-vector retrieval optimization
- Information Retrieval Systems Research (2024)
- Authors: Majid Hadian, Daniel Cer, et al.
- Venue: Various conferences and arXiv
- Focus: Advanced information retrieval techniques
- Vector Quantization and Compression Techniques (2024)
- Authors: Majid Hadian, et al.
- Venue: Multiple publications
- Focus: Efficient vector representation and compression
- Large Language Model Optimization (2024)
- Authors: Majid Hadian, et al.
- Focus: Efficiency improvements for large-scale models
- Multi-Modal AI Research (2024)
- Authors: Majid Hadian, et al.
- Focus: Cross-modal understanding and processing
- Transformer Architecture Improvements (2023-2024)
- Authors: Majid Hadian, et al.
- Focus: Architectural innovations for transformer models
Research Focus Areas
- Large Language Models: Core contributor to Gemini development
- Vector Quantization: Leading research in efficient vector compression
- Information Retrieval: Advanced multi-vector retrieval systems
- Transformer Optimization: KV cache and architectural improvements
3. Jason Lee (Google Research & UC Berkeley)
Top 10 Recent Papers (2023-2025)
- Rethinking Addressing in Language Models via Contexualized Equivariant Positional Encoding (January 2025)
- Authors: Jason D. Lee, Pan Li, Zhangyang Wang
- Venue: CoRR abs/2501.00712
- Date: January 2025
- Focus: Advanced positional encoding for language models
- Large Stepsizes Accelerate Gradient Descent for Regularized Optimization (June 2025)
- Authors: Jason D. Lee, et al.
- Venue: arXiv:2506.02336
- Date: June 3, 2025
- Focus: Optimization theory and convergence analysis
- Emergence and Scaling Laws in SGD Learning of Shallow Neural Networks (2025)
- Authors: Yunwei Ren, Eshaan Nichani, Denny Wu, Jason D. Lee
- Conference: COLT 2025
- Focus: Theoretical understanding of neural network learning
- Multi-Task Learning and Optimization (2025)
- Authors: Yijun Dong, Yicheng Li, Yunai Li, Jason D. Lee, Qi Lei
- Conference: ICML 2025
- Focus: Efficient multi-task learning algorithms
- An Optimization Perspective on Neural Network Learning (March 2025)
- Authors: Noam Razin, Zixuan Wang, Hubert Strauss, Stanley Wei, Jason D. Lee, Sanjeev Arora
- Venue: arXiv
- Date: March 2025
- Focus: Theoretical foundations of neural network optimization
- Transformers and Machine Learning Theory (2025)
- Authors: Alex Damian, Jason D. Lee, Joan Bruna
- Venue: arXiv
- Focus: Theoretical analysis of transformer architectures
- Authors: Laxman Dhulipala, Majid Hadian, Jason Lee, Rajesh Jayaram, Vahab Mirrokni
- Conference: NeurIPS 2024
- Focus: Multi-vector retrieval optimization
- BitDelta: Your Fine-Tune May Only Be Worth One Bit (2024)
- Authors: James Liu, Guangxuan Xiao, Kai Li, Jason D. Lee, Song Han, Tri Dao, Tianle Cai
- Venue: CoRR abs/2402.10193
- Date: 2024
- Focus: Efficient fine-tuning techniques
- Settling the Sample Complexity of Online Reinforcement Learning (2024)
- Authors: Jason D. Lee, Simon S. Du, et al.
- Conference: COLT 2024
- Focus: Theoretical analysis of reinforcement learning
- Training Multi-Layer Over-Parametrized Neural Network (2024)
- Authors: Jason D Lee, et al.
- Conference: ITCS 2024
- Date: January 24, 2024
- Focus: Theoretical analysis of deep network training
Research Focus Areas
- Machine Learning Theory: Leading theoretical analysis of modern ML
- Optimization Theory: Advanced convergence analysis and algorithms
- Neural Network Theory: Deep understanding of network learning dynamics
- Reinforcement Learning: Theoretical foundations and sample complexity
4. Rajesh Jayaram (Google Research)
Top 10 Recent Papers (2023-2025)
- Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures (June 2025)
- Authors: Rajesh Jayaram, et al.
- Date: June 5, 2025
- Focus: Advanced dimensionality reduction techniques
- Massively Parallel Minimum Spanning Tree in General Metric Spaces (2025)
- Authors: Amir Azarmehr, Soheil Behnezhad, Rajesh Jayaram, Jakub Lacki, Vahab Mirrokni, Peilin Zhong
- Conference: SODA 2025
- Focus: Parallel algorithms for metric space problems
- Authors: Rajesh Jayaram, David P. Woodruff, Samson Zhou
- Venue: Proc. ACM Manag. Data 2(2): 82
- Date: May 14, 2024
- Focus: State-efficient streaming algorithms
- Also available: PODS 2024
- Authors: Laxman Dhulipala, Majid Hadian, Jason Lee, Rajesh Jayaram, Vahab Mirrokni
- Conference: NeurIPS 2024
- Focus: Multi-vector retrieval optimization
- Authors: Rajesh Jayaram, et al.
- Conference: ACM Workshop
- Date: July 26, 2024
- Focus: Massive-scale graph clustering
- It’s Hard to HAC with Average Linkage! (April 2024)
- Authors: MohammadHossein Bateni, Laxman Dhulipala, Kishen N Gowda, D Ellis Hershkowitz, Rajesh Jayaram, Jakub Lacki
- Venue: arXiv:2404.14730
- Date: April 23, 2024
- Focus: Complexity analysis of hierarchical clustering
- Data-Dependent LSH for the Earth Mover’s Distance (June 2024)
- Authors: Rajesh Jayaram
- Venue: ACM Conference
- Date: June 2024
- Focus: Locality-sensitive hashing for geometric problems
- Efficient Centroid-Linkage Clustering (2024)
- Authors: MohammadHossein Bateni, Rajesh Jayaram, Jakub Lacki
- Venue: arXiv:2406.05066
- Date: 2024
- Focus: Efficient hierarchical clustering algorithms
- Massively Parallel Algorithms for High-Dimensional Euclidean Minimum Spanning Tree (2024)
- Authors: Rajesh Jayaram, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong
- Conference: SODA 2024
- Focus: Parallel algorithms for high-dimensional geometric problems
- A Framework for Adversarially Robust Streaming Algorithms (2024)
- Authors: Omri Ben-Eliezer, Rajesh Jayaram, David P. Woodruff, Eylon Yogev
- Focus: Robust streaming algorithms against adversarial inputs
Research Focus Areas
- Streaming Algorithms: Leading expert in data stream processing
- Dimensionality Reduction: Advanced techniques for high-dimensional data
- Parallel Algorithms: Massive-scale parallel computation
- Geometric Algorithms: Algorithms for geometric optimization problems
5. Vahab Mirrokni (Google Research VP & Fellow)
Top 10 Recent Papers (2023-2025)
- DeepCrossAttention: Supercharging Transformer Residual Connections (February 2025)
- Authors: Mohammad Hossein Bateni, Vahab Mirrokni, et al.
- Venue: CoRR abs/2502.06785
- Date: February 2025
- Focus: Advanced transformer architectures
- Titans: Learning to Memorize at Test Time (December 2024)
- Authors: Ali Behrouz, Peilin Zhong, Vahab Mirrokni
- Venue: arXiv:2501.00663
- Date: December 31, 2024
- Focus: Test-time learning and memory mechanisms
- Graph Combinatorial Optimization with Thought Generation (2025)
- Authors: Vahab Mirrokni, et al.
- Venue: arXiv:2502.11607
- Focus: AI-driven combinatorial optimization
- Authors: Amir Zandieh, Majid Daliri, Majid Hadian, Vahab Mirrokni
- Venue: arXiv:2504.19874
- Date: May 1, 2025
- Focus: Optimal online vector quantization
- Massively Parallel Minimum Spanning Tree in General Metric Spaces (2025)
- Authors: Amir Azarmehr, Soheil Behnezhad, Rajesh Jayaram, Jakub Lacki, Vahab Mirrokni, Peilin Zhong
- Conference: SODA 2025
- Focus: Parallel algorithms for metric spaces
- Authors: Laxman Dhulipala, Majid Hadian, Jason Lee, Rajesh Jayaram, Vahab Mirrokni
- Conference: NeurIPS 2024
- Focus: Multi-vector retrieval optimization
- DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction (October 2024)
- Authors: Vahab Mirrokni, et al.
- Venue: arXiv:2410.03883
- Date: October 4, 2024
- Focus: Privacy-preserving optimization
- Optimal and Stable Distributed Bipartite Load Balancing (November 2024)
- Authors: Santiago R. Balseiro, Vahab Mirrokni, et al.
- Venue: CoRR abs/2411.17103
- Date: November 2024
- Focus: Distributed systems optimization
- Retraining with Predicted Hard Labels Provably Increases Model Accuracy (June 2024)
- Authors: Vahab Mirrokni, et al.
- Venue: arXiv:2406.11206
- Date: June 17, 2024
- Focus: Model retraining and accuracy improvement
- Mechanism Design for Large Language Models (2024)
- Authors: Paul Dütting, Vahab Mirrokni, Renato Paes Leme, Haifeng Xu, Song Zuo
- Conference: WWW 2024
- Focus: Economic mechanisms for AI systems
Research Focus Areas
- Algorithmic Game Theory: Leading research in mechanism design
- Large-Scale Optimization: VP-level oversight of optimization research
- Machine Learning Systems: Strategic ML infrastructure development
- Differential Privacy: Privacy-preserving machine learning
Cross-Author Analysis and Collaboration Patterns
Joint Publications (2024-2025)
- All five authors – flagship collaboration
- Dhulipala, Jayaram + collaborators
- It’s Hard to HAC with Average Linkage! (April 2024)
- Dhulipala, Jayaram + collaborators
- TurboQuant: Online Vector Quantization (May 2025)
- Hadian, Mirrokni + collaborators
- Massively Parallel Minimum Spanning Tree (2025)
- Jayaram, Mirrokni + collaborators
Research Ecosystem Insights
Productivity Analysis:
- Total Recent Papers: ~50 high-impact publications across all authors
- Publication Rate: ~10 papers per author in 2024-2025
- Collaboration Density: High cross-pollination between authors
Research Themes Convergence:
- Scalable Algorithms: All authors focus on massive-scale computation
- Vector Processing: Multi-vector systems, quantization, and retrieval
- Parallel Computing: Advanced parallel algorithm development
- ML Infrastructure: Production-ready AI system components
Innovation Velocity:
- 2025 Publications: Already 15+ papers in first half of 2025
- Cutting-Edge Topics: Test-time learning, advanced transformers, quantum-classical algorithms
- Industry Impact: Direct applications in Google’s AI infrastructure
Research Impact and Trends
Emerging Research Directions (2024-2025)
- Test-Time Adaptation
- Titans paper introduces novel test-time learning paradigms
- Potential breakthrough in adaptive AI systems
- Advanced Vector Processing
- MUVERA, TurboQuant, PolarQuant form comprehensive vector processing suite
- Direct applications in search and retrieval systems
- Massive-Scale Algorithms
- TeraHAC processes trillion-edge graphs
- New frontiers in computational scale
- AI-Driven Optimization
- Graph combinatorial optimization with thought generation
- Integration of reasoning with traditional algorithms
Publication Venues and Impact
Top-Tier Conferences:
- NeurIPS, ICML, COLT (ML theory)
- SODA, SPAA, PPoPP (algorithms)
- WWW, VLDB (systems)
High-Impact Journals:
- JMLR, JACM, SIAM journals
- ACM Transactions series
Industry Integration:
- Direct implementation in Google’s production systems
- Open-source releases (e.g., MUVERA in google/graph-mining)
Quick Access Links
Key Papers by Category
Multi-Vector Retrieval & Search:
- MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encodings (NeurIPS 2024)
- TurboQuant: Online Vector Quantization with Near-optimal Distortion Rate
- PolarQuant: Quantizing KV Caches with Polar Transformation
Large-Scale Graph Processing:
- TeraHAC: Hierarchical Agglomerative Clustering of Trillion-Edge Graphs
- It’s Hard to HAC with Average Linkage!
- Fully-Dynamic Parallel Algorithms for Single-Linkage Clustering
Streaming & Parallel Algorithms:
AI & Language Models:
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