Local Navigation and Docking of an Autonomous Robot Mower Using Reinforcement Learning and Computer Vision. - Ali Taghibakhshi; Nathan Ogden; Matthew West 001 (ICCAE, 2021)

Optimization-Based Algebraic Multigrid Coarsening Using Reinforcement Learning. - Ali Taghibakhshi; Scott P. MacLachlan; Luke N. Olson; Matthew West 001 (NeurIPS, 2021)

Learning Interface Conditions in Domain Decomposition Solvers. - Ali Taghibakhshi; Nicolas Nytko; Tareq Uz Zaman; Scott P. MacLachlan; Luke N. Olson; Matthew West 001 (NeurIPS, 2022)

Optimized Sparse Matrix Operations for Reverse Mode Automatic Differentiation. - Nicolas Nytko; Ali Taghibakhshi; Tareq-Uz-Zaman; Scott P. MacLachlan; Luke N. Olson; Matt West 001 (CoRR, 2022)

Hierarchical Graph Neural Network with Cross-Attention for Cross-Device User Matching. - Ali Taghibakhshi; Mingyuan Ma; Ashwath Aithal; Onur Yilmaz; Haggai Maron; Matthew West 001 (DaWaK, 2023)

MG-GNN: Multigrid Graph Neural Networks for Learning Multilevel Domain Decomposition Methods. - Ali Taghibakhshi; Nicolas Nytko; Tareq Uz Zaman; Scott P. MacLachlan; Luke N. Olson; Matthew West 001 (ICML, 2023)

NeMo-Aligner: Scalable Toolkit for Efficient Model Alignment. - Gerald Shen; Zhilin Wang; Olivier Delalleau; Jiaqi Zeng; Yi Dong; Daniel Egert; Shengyang Sun; Jimmy J. Zhang; Sahil Jain; Ali Taghibakhshi; Markel Sanz Ausin; Ashwath Aithal; et al. (CoRR, 2024)

Generalizing Lloyd's Algorithm for Graph Clustering. - Tareq Uz Zaman; Nicolas Nytko; Ali Taghibakhshi; Scott P. MacLachlan; Luke N. Olson; Matthew West 001 (SIAM J. Sci. Comput., 2024)

Generalizing reduction-based algebraic multigrid. - Tareq Uz Zaman; Nicolas Nytko; Ali Taghibakhshi; Scott P. MacLachlan; Luke N. Olson; Matthew West 001 (Numer. Linear Algebra Appl., 2024)

Elucidating Optimal Reward-Diversity Tradeoffs in Text-to-Image Diffusion Models. - Rohit Jena; Ali Taghibakhshi; Sahil Jain; Gerald Shen; Nima Tajbakhsh; Arash Vahdat (WACV, 2025)

Systems and Algorithms for Convolutional Multi-Hybrid Language Models at Scale. - Jerome Ku; Eric Nguyen; David W. Romero; Garyk Brixi; Brandon Yang; Anton Vorontsov; Ali Taghibakhshi; Amy X. Lu; Dave P. Burke; Greg Brockman; Stefano Massaroli; Christopher Ré; et al. (CoRR, 2025)

Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models. - Aaron Blakeman; Aarti Basant; Abhinav Khattar; Adithya Renduchintala; Akhiad Bercovich; Aleksander Ficek; Alexis Bjorlin; Ali Taghibakhshi; Amala Sanjay Deshmukh; Ameya Sunil Mahabaleshwarkar; Andrew Tao; Anna Shors; et al. (CoRR, 2025)

Efficient Hybrid Language Model Compression through Group-Aware SSM Pruning. - Ali Taghibakhshi; Sharath Turuvekere Sreenivas; Saurav Muralidharan; Marcin Chochowski; Yashaswi Karnati; Raviraj Joshi; Ameya Sunil Mahabaleshwarkar; Zijia Chen; Yoshi Suhara; Oluwatobi Olabiyi; Daniel Korzekwa; Mostofa Patwary; et al. (CoRR, 2025)

NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model. - Aarti Basant; Abhijit Khairnar; Abhijit Paithankar; Abhinav Khattar; Adithya Renduchintala; Aditya Malte; Akhiad Bercovich; Akshay Hazare; Alejandra Rico; Aleksander Ficek; Alex Kondratenko; Alex Shaposhnikov; et al. (CoRR, 2025)