Gopinath Chennupati (గోపినాథ్ చెన్నుపాటి)

Gopinath Chennupati (గోపినాథ్ చెన్నుపాటి)

Machine Learning Scientist



Nath is an Applied Scientist at Amazon Alexa. His works include building automatic speech recoginition systems, federated learning. Prior to this, a machine learning scientist in the Information Sciences (CCS-3) group at LANL. His works on high performance computing (HPC), performance modeling, natural language processing, deep/machine learning and high perfomance linear algebra (matrix and tensor decompositions).

He worked on a couple of interesting projects in machine learning. One is nonnegative matrix and/or tensor factorizations with unspuervised learning and distributed computing. Next build parameterized software/hardware models for performance prediction while employing probabilistic learning. Another intersting project is NLP with deep learning for Cancer pathology reports.

I am driven to explore the unfamiliar terrains (both scientifically and personally). May be inspired by (or that’s how I am born!!!) “The Road Not Taken” – Robert Frost.


  • Automatic Speech Recognition,
  • High Performance Computing,
  • Nonnegative Matrix/Tensor Factorizations,
  • NLP, Deep/Machine Learning,
  • Performance Modeling,
  • Evolutionary Computing (EC)


  • PhD in Computer Science, 2015

    University of Limerick

  • MSc in Web Technologies, 2011

    National College of Ireland

  • BTech in Information Technology, 2010

    Jawaharlal Nehru Technological University



Applied Scientist


Jan 2021 – Present Sunnyvale, CAM

Computer Scientist

Los Alamos National Laboratory

May 2019 – Dec 2020 Los Alamos, NM

Postdoctoral Research Associate

Los Alamos National Laboratory

Jul 2016 – May 2019 Los Alamos, NM

Data Scientist


Jan 2016 – Aug 2016 Killarney, Ireland

Teaching Assistant

University of Limerick

Sep 2012 – Dec 2015 Limerick, Ireland

Production Engineer


Aug 2011 – Jan 2012 Dublin, Ireland

Recent Publications

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NVIDIA GPGPUs Instructions Energy Consumption

Semantic Nonnegative Matrix Factorization with Automatic Model Determination for Topic Modeling

Distributed Non-Negative Tensor Train Decomposition

An Out of Memory tSVD for Big-Data Factorization

Code Characterization With Graph Convolutions and Capsule Networks


Humies Silver Award

Humies Silver Award

For the paper Performance Optimization of Multi-core Grammatical Evolution Generated Parallel Recursive Programs at GECCO'15

ACM Student Travel Grant

Received to partially cover the expenses to attend GECCO'15

Evostar Student Accommodation Bursary

Received to cover the accommodation expenses to attend Evostar'15

ACM Student Travel Grant

Received to partially cover the expenses to attend GECCO'14

Best Graduate Student Contribution

For the paper Multi-core GE: Automatic Evolution of CPU Based Multi-core Parallel Programs in Student Workshop at GECCO'14


I have really enjoyed working with the follwoing students.

Name Institution Year Topic
Hector Alexis Carrillo Cabada UNM 2019 In-situ analysis of protein folding trajectories
Raviteja Vangara UNM 2018–2019 Charge regulation effects in electric double layers
Poornima Haridas NYU 2019 Applied Reinforcement Learning techniques to BlackBox Challenge
Miguel Hombrados Herrera UNM 2019 Bayesian tensor factorization
Nasrin Akhter GMU 2019, 2018 Decoy selection through machine learning
Yehia Arafa NMSU 2018 Performance prediction on GPUs
Atanu Barai NMSU 2018 Performance prediction on CPUs
Bhargava Kalla ASU 2017 Monte Carlo modeling for branch prediction