publications | Sanketh Vedula

2025

ICML

Inverse problems with experiment-guided AlphaFold

Advaith Maddipatla, Nadav Bojan Sellam, Meital Bojan, and 4 more authors

In Proc. International Conference on Machine Learning (ICML), 2025

@inproceedings{maddipatla2025inverse,
  title = {Inverse problems with experiment-guided AlphaFold},
  author = {Maddipatla, Advaith and Sellam, Nadav Bojan and Bojan, Meital and Vedula, Sanketh and Schanda, Paul and Marx, Ailie and Bronstein, Alex M},
  booktitle = {Proc. International Conference on Machine Learning (ICML)},
  year = {2025}
}

ICMI

From Lab to Wrist: Bridging Metabolic Monitoring and Consumer Wearables for Heart Rate and Oxygen Consumption Modeling

Barak Gahtan, Sanketh Vedula, Gil Samuelly Leichtag, and 2 more authors

In Proceedings of the 27th International Conference on Multimodal Interaction, 2025

Bib

@inproceedings{gahtan2025lab,
  title = {From Lab to Wrist: Bridging Metabolic Monitoring and Consumer Wearables for Heart Rate and Oxygen Consumption Modeling},
  author = {Gahtan, Barak and Vedula, Sanketh and {Samuelly Leichtag}, Gil and Kodesh, Einat and Bronstein, Alex},
  booktitle = {Proceedings of the 27th International Conference on Multimodal Interaction},
  pages = {60--77},
  year = {2025}
}

arXiv

Representing local protein environments with atomistic foundation models

Meital Bojan, Sanketh Vedula, Advaith Maddipatla, and 4 more authors

arXiv preprint arXiv:2505.23354, 2025

Bib

@article{bojan2025representing,
  title = {Representing local protein environments with atomistic foundation models},
  author = {Bojan, Meital and Vedula, Sanketh and Maddipatla, Advaith and Sellam, Nadav Bojan and Napoli, Federico and Schanda, Paul and Bronstein, Alex M},
  journal = {arXiv preprint arXiv:2505.23354},
  year = {2025}
}

CSBJ

Improving prediction accuracy in chimeric proteins with windowed multiple sequence alignment

Sanketh Vedula, Alex M Bronstein, and Ailie Marx

Computational and Structural Biotechnology Journal, 2025

Bib

@article{vedula2025improving,
  title = {Improving prediction accuracy in chimeric proteins with windowed multiple sequence alignment},
  author = {Vedula, Sanketh and Bronstein, Alex M and Marx, Ailie},
  journal = {Computational and Structural Biotechnology Journal},
  publisher = {Elsevier},
  year = {2025}
}

US Patent

Scalable Graph-Based Approach To Accelerating Recommendation Model Inference

Haojie Ye, Sanketh Vedula, Alex Bronstein, and 3 more authors

2025

US Patent App. 18/613,387

Bib

@misc{ye2025scalable,
  title = {Scalable Graph-Based Approach To Accelerating Recommendation Model Inference},
  author = {Ye, Haojie and Vedula, Sanketh and Bronstein, Alex and Dreslinski, Ronald and Mudge, Trevor and Talati, Nishil},
  note = {US Patent App. 18/613,387},
  year = {2025}
}

bioRxiv

Experiment-guided AlphaFold3 resolves accurate protein ensembles

Advaith Maddipatla, Nadav Bojan Sellam, Meital Bojan, and 5 more authors

bioRxiv, 2025

Bib

@article{maddipatla2025experiment,
  title = {Experiment-guided AlphaFold3 resolves accurate protein ensembles},
  author = {Maddipatla, Advaith and {Bojan Sellam}, Nadav and Bojan, Meital and Masalitin, Volodymyr and Vedula, Sanketh and Schanda, Paul M and Marx, Ailie and Bronstein, Alexander M},
  journal = {bioRxiv},
  pages = {2025--10},
  publisher = {Cold Spring Harbor Laboratory},
  year = {2025}
}

2024

ICML Workshop

Scalable unsupervised alignment of general metric and non-metric structures

S. Vedula, V. Maiorca, L. Basile, and 2 more authors

arXiv preprint arXiv:2406.13507 (AI for Science Workshop, ICML), 2024

Bib

@article{vedula2024scalable,
  title = {Scalable unsupervised alignment of general metric and non-metric structures},
  author = {Vedula, S. and Maiorca, V. and Basile, L. and Locatello, F. and Bronstein, A.},
  journal = {arXiv preprint arXiv:2406.13507 (AI for Science Workshop, ICML)},
  year = {2024},
}

bioRxiv

Seeing Double: Molecular dynamics simulations reveal the stability of certain alternate protein conformations in crystal structures

A. Rosenberg, S. Vedula, A. Bronstein, and 1 more author

bioRxiv, 2024

Abs

Proteins jiggle around, adopting ensembles of interchanging conformations. Here we show through a large-scale analysis of the Protein Data Bank and using molecular dynamics simulations, that segments of protein chains can also commonly adopt dual, transiently stable conformations which is not explained by direct interactions. Our analysis highlights how alternate conformations can be maintained as non-interchanging, separated states intrinsic to the protein chain, namely through steric barriers or the adoption of transient secondary structure elements. We further demonstrate that despite the commonality of the phenomenon, current structural ensemble prediction methods fail to capture these bimodal distributions of conformations.Competing Interest StatementThe authors have declared no competing interest.

AISTATS

Vector Quantile Regression on Manifolds

M. Pegoraro, S. Vedula, A. Rosenberg, and 3 more authors

In Proc. International Conference on Artificial Intelligence and Statistics (AISTATS), 2024

Bib

@inproceedings{pegoraro2023vector,
  title = {Vector Quantile Regression on Manifolds},
  author = {Pegoraro, M. and Vedula, S. and Rosenberg, A. and Tallini, I. and Rodola, E. and Bronstein, A.},
  booktitle = {Proc. International Conference on Artificial Intelligence and Statistics (AISTATS)},
  year = {2024},
}

US Patent

Method and system for training a machine learning procedure to analyze a radar signal

A. Bronstein, T. Weiss, N. Peretz, and 2 more authors

2024

US Patent App. 18/376,465

Bib

@misc{bronstein2024method,
  title = {Method and system for training a machine learning procedure to analyze a radar signal},
  author = {Bronstein, A. and Weiss, T. and Peretz, N. and Vedula, S. and Feuer, A.},
  year = {2024},
  note = {US Patent App. 18/376,465}
}

VLDB

Demystifying graph sparsification algorithms in graph properties preservation

Y. Chen, H. Ye, S. Vedula, and 4 more authors

Proceedings of the International Conference on Very Large Databses (VLDB), 2024

Bib

@article{chen2023demystifying,
  title = {Demystifying graph sparsification algorithms in graph properties preservation},
  author = {Chen, Y. and Ye, H. and Vedula, S. and Bronstein, A. and Dreslinski, R. and Mudge, T. and Talati, N.},
  journal = {Proceedings of the International Conference on Very Large Databses (VLDB)},
  volume = {17},
  number = {3},
  pages = {427--440},
  year = {2024},
  publisher = {VLDB Endowment},
}

VLDB

Everest: GPU-Accelerated System For Mining Temporal Motifs

Y. Yuan, H. Ye, S. Vedula, and 2 more authors

Proceedings of the International Conference on Very Large Databses (VLDB), 2024

Bib

@article{yuan2023everest,
  title = {Everest: GPU-Accelerated System For Mining Temporal Motifs},
  author = {Yuan, Y. and Ye, H. and Vedula, S. and Kaza, W. and Talati, N.},
  year = {2024},
  journal = {Proceedings of the International Conference on Very Large Databses (VLDB)},
  publisher = {VLDB Endowment},
}

NeurIPS W

Generative modeling of protein ensembles guided by crystallographic electron densities

Sai Advaith Maddipatla, Nadav Bojan Sellam, Sanketh Vedula, and 2 more authors

In Machine Learning for Structural Biology Workshop, NeurIPS, 2024

Bib

@inproceedings{maddipatla2024generative,
  title = {Generative modeling of protein ensembles guided by crystallographic electron densities},
  author = {Maddipatla, Sai Advaith and Sellam, Nadav Bojan and Vedula, Sanketh and Marx, Ailie and Bronstein, Alex},
  booktitle = {Machine Learning for Structural Biology Workshop, NeurIPS},
  year = {2024}
}

2023

ICML Workshop

Continuous Vector Quantile Regression

S. Vedula, I. Tallini, A. Rosenberg, and 4 more authors

In ICML Workshop on New Frontiers in Learning, Control, and Dynamical Systems, 2023

Bib

@inproceedings{vedula2023continuous,
  title = {Continuous Vector Quantile Regression},
  author = {Vedula, S. and Tallini, I. and Rosenberg, A. and Pegoraro, M. and Rodola, E. and Romano, Y. and Bronstein, A.},
  booktitle = {ICML Workshop on New Frontiers in Learning, Control, and Dynamical Systems},
  year = {2023},
}

ICLR

Fast Nonlinear Vector Quantile Regression

A. Rosenberg, S. Vedula, Y. Romano, and 1 more author

In Proc. International Conference on Learning Representations (ICLR), 2023

Bib HTML

@inproceedings{rosenberg2023fast,
  title = {Fast Nonlinear Vector Quantile Regression},
  author = {Rosenberg, A. and Vedula, S. and Romano, Y. and Bronstein, A.},
  booktitle = {Proc. International Conference on Learning Representations (ICLR)},
  year = {2023},
}

ASPLOS

GRACE: A Scalable Graph-Based Approach To Accelerating Recommendation Model Inference

H. Ye, S. Vedula, Y. Chen, and 5 more authors

In 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2023

Bib

@inproceedings{ye2023grace,
  title = {GRACE: A Scalable Graph-Based Approach To Accelerating Recommendation Model Inference},
  author = {Ye, H. and Vedula, S. and Chen, Y. and Yeng, Y. and Bronstein, A. and Dreslinski, R. and Mudge, T. and Talati, N.},
  booktitle = {28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS)},
  year = {2023}
}

2022

MICRO

Mint: An Accelerator For Mining Temporal Motifs

N. Talati, H. Ye, S. Vedula, and 8 more authors

In 55th IEEE/ACM International Symposium on Microarchitecture (MICRO), 2022

Bib

@inproceedings{talati2022mint,
  title = {Mint: An Accelerator For Mining Temporal Motifs},
  author = {Talati, N. and Ye, H. and Vedula, S. and Chen, K.Y. and Chen, Y. and Liu, D. and Yuan, Y. and Blaauw, D. and Bronstein, A. and Mudge, T. and Dreslinski, R.},
  booktitle = {55th IEEE/ACM International Symposium on Microarchitecture (MICRO)},
  pages = {1270--1287},
  year = {2022}
}

2021

MELBA

PILOT: Physics-informed learned optimal trajectories for accelerated MRI

T. Weiss, O. Senouf, S. Vedula, and 3 more authors

The Journal of Machine Learning for Biomedical Imaging, 2021

Bib HTML

@article{weiss2021pilot,
  title = {PILOT: Physics-informed learned optimal trajectories for accelerated MRI},
  author = {Weiss, T. and Senouf, O. and Vedula, S. and Michailovich, O. and Zibulevsky, M. and Bronstein, A.},
  journal = {The Journal of Machine Learning for Biomedical Imaging},
  volume = {1},
  issue = {April 2021 issue},
  year = {2021},
}

US Patent

Systems and methods for ultrasonic imaging

O. Senouf, S. Vedula, A. Bronstein, and 3 more authors

US Patent 11,158,052, 2021

Bib

@article{senouf2021systems,
  title = {Systems and methods for ultrasonic imaging},
  author = {Senouf, O. and Vedula, S. and Bronstein, A. and and Zibulevsky, M. and Zurakhov, G. and Michailovich, O.},
  journal = {US Patent 11,158,052},
  year = {2021}
}

MLSP

Joint optimization of system design and reconstruction in MIMO radar imaging

T. Weiss, N. Peretz, S. Vedula, and 2 more authors

In 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP), 2021

Bib

@inproceedings{weiss2021joint,
  title = {Joint optimization of system design and reconstruction in MIMO radar imaging},
  author = {Weiss, T. and Peretz, N. and Vedula, S. and Feuer, A. and Bronstein, A.},
  booktitle = {2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP)},
  pages = {1--6},
  year = {2021},
  organization = {IEEE}
}

MSML

Spectral Geometric Matrix Completion

A. Boyarski, S. Vedula, and A. Bronstein

In Proceedings of the Second Mathematical and Scientific Machine Learning Conference (MSML), 2021

Bib

@inproceedings{boyarski2021spectral,
  title = {Spectral Geometric Matrix Completion},
  author = {Boyarski, A. and Vedula, S. and Bronstein, A.},
  booktitle = {Proceedings of the Second Mathematical and Scientific Machine Learning Conference (MSML)},
  year = {2021},
}

2020

MICCAI-W

3D FLAT-Feasible Learned Acquisition Trajectories for Accelerated MRI

J. Alush-Aben, L. Ackerman, T. Weiss, and 3 more authors

In International Workshop on Machine Learning for Medical Image Reconstruction, MICCAI, 2020

Bib

@inproceedings{alush20203d,
  title = {3D FLAT-Feasible Learned Acquisition Trajectories for Accelerated MRI},
  author = {Alush-Aben, J. and Ackerman, L. and Weiss, T. and Vedula, S. and Senouf, O. and Bronstein, A.},
  booktitle = {International Workshop on Machine Learning for Medical Image Reconstruction, MICCAI},
  year = {2020}
}

CDMRI

Towards learned optimal q-space sampling in diffusion MRI

T. Weiss, S. Vedula, O. Senouf, and 2 more authors

In Computational Diffusion MRI, 2020

Bib

@inproceedings{weiss2020towards,
  title = {Towards learned optimal q-space sampling in diffusion MRI},
  author = {Weiss, T. and Vedula, S. and Senouf, O. and Michailovich, O. and Bronstein, A.},
  booktitle = {Computational Diffusion MRI},
  year = {2020},
  publisher = {Springer International Publishing},
  address = {Cham},
  pages = {13--28}
}

ICASSP

Joint learning of Cartesian undersampling and reconstruction for accelerated MRI

T. Weiss, S. Vedula, O. Senouf, and 3 more authors

In ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020

Bib

@inproceedings{weiss2019joint,
  title = {Joint learning of Cartesian undersampling and reconstruction for accelerated MRI},
  author = {Weiss, T. and Vedula, S. and Senouf, O. and Bronstein, A. and Michailovich, O. and Zibulevsky, M.},
  booktitle = {ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year = {2020}
}

Technion

Learning-based design of ultrasound imaging systems

S. Vedula, A. Bronstein, and M. Zibulevsky

M.Sc. Thesis, Computer Science Department, Technion, 2020

Bib

@article{vedula2020learning,
  title = {Learning-based design of ultrasound imaging systems},
  author = {Vedula, S. and Bronstein, A. and Zibulevsky, M.},
  year = {2020},
  journal = {M.Sc. Thesis, Computer Science Department, Technion}
}

2019

MIDL

Learning beamforming in ultrasound imaging

S. Vedula, O. Senouf, Grigoriy Zurakhov, and 3 more authors

In Proceedings of The 2nd International Conference on Medical Imaging with Deep Learning (MIDL), 2019

Bib PDF

@inproceedings{vedula2018learning,
  title = {Learning beamforming in ultrasound imaging},
  author = {Vedula, S. and Senouf, O. and Zurakhov, Grigoriy and Bronstein, A. and Michailovich, O. and Zibulevsky, M.},
  booktitle = {Proceedings of The 2nd International Conference on Medical Imaging with Deep Learning (MIDL)},
  pages = {493--511},
  year = {2019},
  editor = {Cardoso, M. Jorge and Feragen, Aasa and Glocker, Ben and Konukoglu, Ender and Oguz, Ipek and Unal, Gozde and Vercauteren, Tom},
  volume = {102},
  series = {Proceedings of Machine Learning Research},
  publisher = {PMLR},
  url = {https://proceedings.mlr.press/v102/vedula19a.html}
}

MICCAI-W

Self-supervised learning of inverse problem solvers in medical imaging

O. Senouf, S. Vedula, T. Weiss, and 3 more authors

In Domain adaptation and representation transfer and medical image learning with less labels and imperfect data, MICCAI, 2019

Bib

@inproceedings{senouf2019self,
  title = {Self-supervised learning of inverse problem solvers in medical imaging},
  author = {Senouf, O. and Vedula, S. and Weiss, T. and Bronstein, A. and Michailovich, O. and Zibulevsky, M.},
  booktitle = {Domain adaptation and representation transfer and medical image learning with less labels and imperfect data, MICCAI},
  pages = {111--119},
  year = {2019},
  publisher = {Springer, Cham}
}

2018

MICCAI

High frame-rate cardiac ultrasound imaging with deep learning

O. Senouf, S. Vedula, G. Zurakhov, and 5 more authors

In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2018

Bib

@inproceedings{senouf2018high,
  title = {High frame-rate cardiac ultrasound imaging with deep learning},
  author = {Senouf, O. and Vedula, S. and Zurakhov, G. and Bronstein, A. and Zibulevsky, M. and Michailovich, O. and Adam, Dan and Blondheim, David},
  booktitle = {International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)},
  pages = {126--134},
  year = {2018},
  organization = {Springer}
}

MICCAI-W

High quality ultrasonic multi-line transmission through deep learning

S. Vedula, O. Senouf, G. Zurakhov, and 5 more authors

In International Workshop on Machine Learning for Medical Image Reconstruction, MICCAI, 2018

Bib

@inproceedings{vedula2018high,
  title = {High quality ultrasonic multi-line transmission through deep learning},
  author = {Vedula, S. and Senouf, O. and Zurakhov, G. and Bronstein, A. and Zibulevsky, M. and Michailovich, O. and Adam, D. and Gaitini, D.},
  booktitle = {International Workshop on Machine Learning for Medical Image Reconstruction, MICCAI},
  pages = {147--155},
  year = {2018},
  organization = {Springer}
}

2017

arXiv

Towards CT-quality ultrasound imaging using deep learning

S. Vedula, O. Senouf, A. M Bronstein, and 2 more authors

arXiv preprint arXiv:1710.06304, 2017

Bib

@article{vedula2017towards,
  title = {Towards CT-quality ultrasound imaging using deep learning},
  author = {Vedula, S. and Senouf, O. and Bronstein, A. M and Michailovich, O. V and Zibulevsky, M.},
  journal = {arXiv preprint arXiv:1710.06304},
  year = {2017}
}