Intro

I am the CEO and co-founder of Genmo, a startup revolutionizing video generation. Our mission is to empower the next billion video creators to tell their stories by making it easy for anyone to create cinematic videos using simple text prompts. We envision a world where high-quality cinematic video content is as plentiful as water.

Prior to founding Genmo, I completed my Ph.D. at UC Berkeley, advised by Ion Stoica and Joseph Gonzalez. I was part of the RISE Lab, BAIR Lab and Berkeley Deep Drive Lab. My research focused on machine learning systems, particularly in areas that now drive our work at Genmo.

At Genmo, we're tackling the challenge of making video creation accessible to everyone. Despite the massive consumption of video content globally, the tools for video creation remain out of reach for most people. We're changing that by leveraging cutting-edge AI technology to transform simple text prompts into high-quality cinematic videos.

We're always looking for passionate, driven, and talented individuals to join our team and help us achieve our mission. If you're excited about democratizing video creation and want to be part of shaping the future of digital storytelling, we'd love to hear from you.

Research papers and publications


Skyplane: Optimizing Transfer Cost and Throughput Using Cloud-Aware Overlays
NSDI 2023 USENIX Symposium on Networked Systems Design and Implementation
Paras Jain, Sam Kumar, Sarah Wooders, Shishir G. Patil, Joseph E. Gonzalez, Ion Stoica
Skyplane accelerates wide-area transfers in the cloud by 5x via overlay routing and parallelism. Our open-source project moves TBs of data reliably and efficiently (>20Gbps) at up to 4x lower costs.
POET: Training Neural Networks on Tiny Devices with Integrated Rematerialization and Paging
ICML 2022 International Conference on Machine Learning
Shishir Patil, Paras Jain, Prabal Dutta, Ion Stoica, Joseph Gonzalez
We present POET, an algorithm to enable training large neural networks (like BERT) on memory-scarce battery-operated edge devices.
Learning to Design Accurate Deep Learning Accelerators with Inaccurate Multipliers
DATE 2021 Design, Automation and Test in Europe
Paras Jain, Safeen Huda, Martin Maas, Joseph E. Gonzalez, Ion Stoica, Azalia Mirhoseini
We improve the power-efficiency of the TPU by 4-6% by synthesizing a novel low-power approximate version using learning-augmented search.
Contrastive Code Representation Learning
EMNLP 2021 Empirical Methods in Natural Language Processing
Paras Jain*, Ajay Jain*, Tianjun Zhang, Pieter Abbeel, Joseph E. Gonzalez, Ion Stoica
Learning to represent software functionality for automated software engineering tasks like type inference, clone detection and summarization. Improving robustness of ML4Code.
Grounded Graph Decoding improves Compositional Generalization in Question Answering
EMNLP 2021 Empirical Methods in Natural Language Processing
Yu Gai*, Paras Jain*, Wendi Zhang, Joseph E. Gonzalez, Ion Stoica, Dawn Song
We propose Grounded Graph Decoding, a method to improve compositional generalization of language representations by grounding structured predictions with an attention mechanism.
Accelerating Quadratic Optimization with Reinforcement Learning
NeurIPS 2021 Neural Information Processing Systems
Jeffrey Ichnowski*, Paras Jain*, Bartolomeo Stellato, Goran Banjac, Michael Luo, Francesco Borrelli, Joseph E. Gonzalez, Ion Stoica, Ken Goldberg
We demonstrate reinforcement learning can significantly accelerate first-order optimization, outperforming state-of-the-art solvers by up to 3x.
Representing Long-Range Context for Graph Neural Networks with Global Attention
NeurIPS 2021 Neural Information Processing Systems
Zhanghao Wu*, Paras Jain*, Matthew Wright, Azalia Mirhoseini, Joseph E. Gonzalez, Ion Stoica
Transformers enable GNNs to achieve SOTA performance on graph classification tasks by enabling representations of long-range context.
Synthesizing Low-Power Approximate Hardware with Large-Scale Search
MLArchSys 2021 Workshop on Machine Learning in Architecture Systems as ISCA
Paras Jain, Safeen Huda, Martin Maas, Joseph E. Gonzalez, Ion Stoica, Azalia Mirhoseini
Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization
MLSys 2020 3rd Conference on Machine Learning and Systems
Paras Jain*, Ajay Jain*, Aniruddha Nrusimha, Amir Gholami, Pieter Abbeel, Kurt Keutzer, Ion Stoica, Joseph E. Gonzalez
Use up to 5x less memory when training DNNs by recomputing activations.
The Case for GPU Multitenancy: The OoO VLIW JIT Compiler for GPU Inference
arXiv 2019 arXiv:1910.02653, Jan 2019
Paras Jain, Xiangxi Mo, Ajay Jain, Alexey Tumanov, Joseph E. Gonzalez, Ion Stoica
Demonstrate 2.5x-4.9x speedups for deep learning inference workloads via GPU multitenancy.
Revec: Program Rejuvenation through Revectorization
CC 2019 International Conference on Compiler Construction
Ajay Jain, Charith Mendis, Paras Jain, Saman Amarasinghe
Achieve performance portability for hand-vectorized programs, with up to a 1.88x speedup.
Dynamic Space-Time Scheduling for GPU Inference
LearningSys 2018 LearningSys workshop at NeurIPS 2018
Paras Jain, Xiangxi Mo, Ajay Jain, Harikaran Subbaraj, Rehan Sohail Durrani, Alexey Tumanov, Joseph E. Gonzalez, Ion Stoica
Demonstrate 2.5x-4.9x speedups for deep learning inference workloads via GPU multitenancy.
DSCnet: Replicating Lidar Point Clouds with Deep Sensor Cloning
WAD 2018 Workshop on Autonomous Driving at CVPR
Paden Tomasello, Sammy Sidhu, Anting Shen, Matthew W. Moskewicz, Nobie Redmon, Gayatri Joshi, Romi Phadte, Paras Jain, Forrest Iandola
Generate high resolution LiDAR from ensembles of cheap sensors.
Scalable Architecture for Anomaly Detection and Visualization in Power Generating Assets
HPBDC 2017 HPBDC at IPDPS 2017
Paras Jain, Chirag Tailor, Sam Ford, Liexiao Ding, Michael Phillips, Fang Liu, Nagi Gebraeel, Duen Horng Chau
We present a scalable system for time-series anomaly detection that horizontally scales to sensor networks with >400k QPS.
Spotting Suspicious Reviews via (Quasi-)clique Extraction
S&P 2015 IEEE Security and Privacy (poster)
Paras Jain, Shang-Tse Chen, Mozhgan Azimpourkivi, Duen Horng Chau, Bogdan Carbunar
We uncover suspicious activity by well-organized reviewer rings sponsored by Yelp. Our work sheds light on Yelp's little-known paid review operations.

Full list of research papers

generated by bibbase.org
  2022 (2)
A Framework for Synthesizing Low-Power Approximate Inference Accelerators. Paras Jain; Safeen Huda; Martin Maas; Joseph E. Gonzalez; Ion Stoica; and Azalia Mirhoseini. In DATE 2022, 2022.
link   bibtex  
Systems and methods for training machine models with augmented data. Matthew John Cooper; Paras Jagdish Jain; and Harsimran Singh Sidhu. April 7 2022. US Patent App. 17/644,308
link   bibtex  
  2021 (7)
Multi-channel sensor simulation for autonomous control systems. Forrest Nelson Iandola; Donald Benton MacMillen; Anting Shen; Harsimran Singh Sidhu; Daniel Paden Tomasello; Rohan Nandkumar Phadte; and Paras Jagdish Jain. October 26 2021. US Patent 11,157,014
link   bibtex  
Systems and methods for training machine models with augmented data. Matthew John Cooper; Paras Jagdish Jain; and Harsimran Singh Sidhu. December 21 2021. US Patent 11,205,093
link   bibtex  
Contrastive Code Representation Learning. Paras Jain; Ajay Jain; Tianjun Zhang; Pieter Abbeel; Joseph E Gonzalez; and Ion Stoica. EMNLP 2021. 2021.
link   bibtex  
Accelerating Quadratic Optimization with Reinforcement Learning. Jeffrey Ichnowski; Paras Jain; Bartolomeo Stellato; Goran Banjac; Michael Luo; Francesco Borrelli; Joseph E Gonzalez; Ion Stoica; and Ken Goldberg. NeurIPS 2021. 2021.
link   bibtex  
Synthesizing Low-Power Approximate Hardware with Large-Scale Search. Paras Jain; Safeen Huda; Martin Maas; Joseph Gonzalez; Ion Stoica; and Azalia Mirhoseini. In MLArchSys at the International Symposium on Computer Architecture 2021, 2021.
link   bibtex  
Grounded Graph Decoding improves Compositional Generalization in Question Answering. Yu Gai; Paras Jain; Wendi Zhang; Joseph E. Gonzalez; Ion Stoica; and Dawn Song. In Findings of EMNLP 2021, 2021.
link   bibtex  
Representing Long-Range Context for Graph Neural Networks with Global Attention. Zhanghao Wu; Paras Jain; Matthew Wright; Azalia Mirhoseini; Joseph E. Gonzalez; and Ion Stoica. In NeurIPS 2021, 2021.
link   bibtex  
  2020 (3)
Data synthesis for autonomous control systems. Forrest Nelson Iandola; Donald Benton MacMillen; Anting Shen; Harsimran Singh Sidhu; and Paras Jagdish Jain. June 9 2020. US Patent 10,678,244
link   bibtex  
Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization. Paras Jain; Ajay Jain; Aniruddha Nrusimha; Amir Gholami; Pieter Abbeel; Kurt Keutzer; Ion Stoica; and Joseph E. Gonzalez. In Proceedings of Machine Learning and Systems 2020, pages 497–511, 2020.
link   bibtex  
Optimizing neural network structures for embedded systems. Harsimran Singh Sidhu; Paras Jagdish Jain; Daniel Paden Tomasello; and Forrest Nelson Iandola. January 30 2020. US Patent App. 16/522,411
link   bibtex  
  2019 (3)
DSCnet: Replicating lidar point clouds with deep sensor cloning. Paden Tomasello; Sammy Sidhu; Anting Shen; Matthew W Moskewicz; Nobie Redmon; Gayatri Joshi; Romi Phadte; Paras Jain; and Forrest Iandola. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pages 0–0, 2019.
link   bibtex  
The OoO VLIW JIT compiler for GPU inference. Paras Jain; Xiangxi Mo; Ajay Jain; Alexey Tumanov; Joseph E Gonzalez; and Ion Stoica. arXiv preprint arXiv:1901.10008. 2019.
link   bibtex  
Revec: program rejuvenation through revectorization. Charith Mendis; Ajay Jain; Paras Jain; and Saman Amarasinghe. In Proceedings of the 28th International Conference on Compiler Construction, pages 29–41, 2019.
link   bibtex  
  2018 (1)
Dynamic Space-Time Scheduling for GPU Inference. Paras Jain; Xiangxi Mo; Ajay Jain; Harikaran Subbaraj; Rehan Durrani; Alexey Tumanov; Joseph Gonzalez; and Ion Stoica. In LearningSys Workshop at Neural Information Processing Systems 2018, 2018.
link   bibtex  
  2017 (1)
Scalable Architecture for Anomaly Detection and Visualization in Power Generating Assets. Paras Jain; Chirag Tailor; Sam Ford; Liexiao Ding; Michael Phillips; Fang Liu; Nagi Gebraeel; and Duen Horng Chau. In 2017 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pages 1078–1082, 2017. IEEE
link   bibtex  
  2015 (1)
Spotting Suspicious Reviews via (Quasi-) clique Extraction. Paras Jain; Shang-Tse Chen; Mozhgan Azimpourkivi; Duen Horng Chau; and Bogdan Carbunar. In IEEE Security and Privacy 2015 extended abstract, 2015.
link   bibtex