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Engineering and Technology

D-Index
65
Citations
80528
World Ranking
1475
National Ranking
479

Overview

Vijay K. Vasudevan is a researcher affiliated with Google in the United States. Their work primarily focuses on engineering, with a significant concentration in mechanical engineering and materials chemistry. Additional subfields include ecological modeling, aerospace engineering, and mechanics of materials. Through these areas, Vasudevan has contributed to topics encompassing surface treatment and residual stress, erosion and abrasive machining, additive manufacturing materials and processes, metal and thin film mechanics, advanced welding techniques analysis, aluminum alloys composites properties, and high-temperature coating behaviors.

Vasudevan has coauthored research with several frequently collaborating scientists. These coauthors include Matthew A. Steiner, Jie Song, Seetha R. Mannava, Yalin Dong, and Chang Ye. Collaborative efforts are often published in venues that include arXiv (Cornell University), SSRN Electronic Journal, Advanced Engineering Materials, Scripta Materialia, and Metals. Among these, arXiv features the highest number of their publications.

Their recent research output encompasses works published between 2020 and 2022. Selected publications include:

  • "CoCa: Contrastive Captioners are Image-Text Foundation Models" (2022, arXiv (Cornell University))
  • "Scaling Autoregressive Models for Content-Rich Text-to-Image Generation" (2022, arXiv (Cornell University))
  • "Solid-state additive manufacturing of aluminum and copper using additive friction stir deposition: Process-microstructure linkages" (2020, Materialia)
  • "Effects of ultrasonic nanocrystal surface modification on the surface integrity, microstructure, and wear resistance of 300M martensitic ultra-high strength steel" (2020, Journal of Materials Processing Technology)
  • "Scene Transformer: A unified architecture for predicting multiple agent trajectories" (2021, arXiv (Cornell University))

Their research covers a diverse range of engineering challenges, notably in the development and analysis of materials and processes relevant to manufacturing and surface engineering. Topics such as additive manufacturing and surface integrity are frequently addressed, indicating an engagement with advanced production techniques and material properties.

Best Publications

  • TensorFlow: a system for large-scale machine learning

    Martín Abadi;Paul Barham;Jianmin Chen;Zhifeng Chen

  • TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

    Martín Abadi;Ashish Agarwal;Paul Barham;Eugene Brevdo

  • Learning Transferable Architectures for Scalable Image Recognition

    Barret Zoph;Vijay Vasudevan;Jonathon Shlens;Quoc V. Le

  • Searching for MobileNetV3

    Andrew Howard;Ruoming Pang;Hartwig Adam;Quoc Le

  • In-Datacenter Performance Analysis of a Tensor Processing Unit

    Norman P. Jouppi;Cliff Young;Nishant Patil;David Patterson

  • MnasNet: Platform-Aware Neural Architecture Search for Mobile

    Mingxing Tan;Bo Chen;Ruoming Pang;Vijay Vasudevan

  • Scalability in Perception for Autonomous Driving: Waymo Open Dataset

    Pei Sun;Henrik Kretzschmar;Xerxes Dotiwalla;Aurelien Chouard

  • AutoAugment: Learning Augmentation Strategies From Data

    Ekin D. Cubuk;Barret Zoph;Dandelion Mane;Vijay Vasudevan

  • In-Datacenter Performance Analysis of a Tensor Processing Unit

    Norman P. Jouppi;Cliff Young;Nishant Patil;David Patterson

  • AutoAugment: Learning Augmentation Policies from Data

    Ekin Dogus Cubuk;Barret Zoph;Dandelion Mane;Vijay Vasudevan

  • FAWN: a fast array of wimpy nodes

    David G. Andersen;Jason Franklin;Michael Kaminsky;Amar Phanishayee

  • Searching for MobileNetV3.

    Andrew Howard;Mark Sandler;Grace Chu;Liang-Chieh Chen

  • Safe and effective fine-grained TCP retransmissions for datacenter communication

    Vijay Vasudevan;Amar Phanishayee;Hiral Shah;Elie Krevat

  • Understanding and Simplifying One-Shot Architecture Search

    Gabriel M. Bender;Pieter-jan Kindermans;Barret Zoph;Vijay Vasudevan

  • PRECIPITATION REACTIONS AND STRENGTHENING BEHAVIOR IN 18 WT PCT NICKEL MARAGING STEELS

    Vijay K. Vasudevan;Sung J. Kim;C. Marvin Wayman

  • Large Scale Interactive Motion Forecasting for Autonomous Driving: The Waymo Open Motion Dataset

    Scott Ettinger;Shuyang Cheng;Benjamin Caine;Chenxi Liu

  • Measurement and analysis of TCP throughput collapse in cluster-based storage systems

    Amar Phanishayee;Elie Krevat;Vijay Vasudevan;David G. Andersen

  • Gradient nanostructure and residual stresses induced by Ultrasonic Nano-crystal Surface Modification in 304 austenitic stainless steel for high strength and high ductility

    Chang Ye;Abhishek Telang;Amrinder S. Gill;Sergey Suslov

  • Scalability in Perception for Autonomous Driving: Waymo Open Dataset

    Pei Sun;Henrik Kretzschmar;Xerxes Dotiwalla;Aurelien Chouard

  • Neural optimizer search with reinforcement learning

    Irwan Bello;Barret Zoph;Vijay Vasudevan;Quoc V. Le

  • Microstructure of Long-Term Aged IN617 Ni-Base Superalloy

    Quanyan Wu;Hyojin Song;Robert W. Swindeman;John P. Shingledecker

Frequent Co-Authors

Dong Qian
Dong Qian The University of Texas at Dallas
David G. Andersen
David G. Andersen Carnegie Mellon University
Jonathon Shlens
Jonathon Shlens Google (United States)
Tirumalai S. Srivatsan
Tirumalai S. Srivatsan University of Akron
Barret Zoph
Barret Zoph Google (United States)
Quoc V. Le
Quoc V. Le Google (United States)
Zhifeng Chen
Zhifeng Chen Google (United States)
Ruoming Pang
Ruoming Pang Google (United States)
Hamish L. Fraser
Hamish L. Fraser The Ohio State University

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