James Diffenderfer
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James Diffenderfer Email & Phone Number

Machine Learning Research Scientist | Applied Mathematics PhD | Python, PyTorch, C, C++ at Lawrence Livermore National Laboratory
Location: Sunnyvale, California, United States 11 work roles 4 schools
1 work email found @llnl.gov LinkedIn matched
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Role
Machine Learning Research Scientist | Applied Mathematics PhD | Python, PyTorch, C, C++
Location
Sunnyvale, California, United States
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James Diffenderfer is listed as Machine Learning Research Scientist | Applied Mathematics PhD | Python, PyTorch, C, C++ at Lawrence Livermore National Laboratory, a company with 6681 employees, based in Sunnyvale, California, United States. AeroLeads shows a work email signal at llnl.gov and a matched LinkedIn profile for James Diffenderfer.

James Diffenderfer previously worked as Machine Learning Research Staff at Lawrence Livermore National Laboratory and Approximate Computing and Machine Learning Postdoctoral Researcher at Lawrence Livermore National Laboratory. James Diffenderfer holds Doctor Of Philosophy - Phd, Applied Mathematics - Optimization, 4.0 from University Of Florida.

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{first_initial}{last}@llnl.gov
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Profile bio

About James Diffenderfer

Driven researcher with PhD in applied mathematics and 3+ years successfully researching neural network robustness and compression (pruning/quantization). Established problem solving track record in machine learning and numerical analysis with work in top venues (NeurIPS, ICLR, Supercomputing, SISC) and state-of-the-art results (RobustBench).

Listed skills include Neural Networks, Pandas, Mathematics Education, Git, and 44 others.

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Lawrence Livermore National Laboratory
Lawrence Livermore National Laboratory
Machine Learning Research Scientist | Applied Mathematics PhD | Python, PyTorch, C, C++
livermore, california, united states
Website
Employees
6681
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11 roles

James Diffenderfer work experience

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Machine Learning Research Staff

Current

Livermore, California, United States

  • Researching out-of-distribution and adversarial robustness, dynamic neural network adaptation for robustness (to out-of-distribution data) and compression, and catastrophic forgetting; Published at NeurIPS 2022
  • Designed neural network pruning and quantization experiments yielding 60× memory and 4× latency reduction on edge device (NVIDIA Jetson) while maintaining 95% of test performance compared to baseline
  • Proposed LDRD exploratory research project on gradient-free deep learning and secured funding for team of 4 researchers for 3 years (as Principal Investigator)
  • Managing project with team of 4 LLNL research staff, 2 university subcontracts, and 2 summer interns
  • Awarded LLNL Deputy Director Science and Technology (DDS&T) Publication Excellence Award
Jan 2022 - Present

Approximate Computing And Machine Learning Postdoctoral Researcher

Livermore, California, United States

  • Researched and developed neural network pruning and binarization methods and their effects on accuracy and out-of-distribution robustness; Published at ICLR 2021 and NeurIPS 2021
  • Investigated theoretical confidence in approximate computing methods through the use of error bound analysis and uncertainty quantification techniques; Implemented strategy on GPUs using CUDA
  • Proposed LDRD feasibility study research project on training scientific ML models and secured $150K in funding
  • Mentored LLNL Data Science Summer Institute (DSSI) and Approximate Computing summer interns
  • Awarded LLNL DDS&T Publication Excellence Award and Center for Applied and Scientific Computing SPOT Award
May 2020 - Jan 2022

Telecommuting Computation Student Worker

Livermore, CA

  • Investigating efficacy of methods for reducing bandwidth and storage costs in parallelizable algorithms being implemented on high-performance computing clusters
  • Collaborated on performing stability analysis for ZFP compression algorithm and for use of ZFP compression inline with parallelizable iterative methods which resulted in 2 research papers
  • Communicated results of analysis at the SIAM Conference on Computational Science and Engineering (CSE19) in Spokane, WA
Aug 2017 - May 2020

Computation Student Intern

Livermore, CA

  • Supported efforts of Variable Precision Computing group on 2 research projects and acquired experience working with high-performance computing systems
  • Conceptualized method for analyzing the stability of the ZFP compression/decompression algorithm
  • Implemented and tested mixed precision versions of the fixed point iterative solver KINSOL with Anderson acceleration in the SUNDIALS C++ software package that resulted in a reduction in the number of iterations in 25%.
May 2017 - Aug 2017

Graduate Research Assistant

Gainesville, Florida Area

  • Researched and developed a nonlinear program solver, NPASA, which resulted in 2 research papers and currently developing C implementation of nonlinear program solver NPASA
  • Contributed to the source code and data structure development for the C implementation of the polyhedral constrained optimization problem solver PASA
  • Developed makefiles and implemented Python and MATLAB interfaces for the optimization software suite SuiteOPT
Jan 2016 - May 2020

Graduate Teaching Assistant

Gainesville, Florida Area

  • Assisted with instruction and grading for 60 - 120 students 1 semester a year in Calculus 1, Calculus 3, or Differential Equations and received overall instructor rating of 4.76 / 5 from students
  • Introduced online student surveys, analyzed responses, and tailored instruction to the needs of each section
  • Administered examinations for 60 - 120 students, proofed examinations, and designed weekly assignments
Aug 2015 - May 2019

Visiting Instructor

Statesboro, GA

  • Instructed and developed course materials for 3 to 4 Calculus I, Survey of Calculus, Precalculus, Trigonometry, or College Algebra courses per semester
  • Personalized teaching techniques during office hours to accommodate learning styles of over 50 individuals
  • Volunteered on committee to organize and host the Annual Invitational Georgia Southern Mathematics Tournament and facilitated the grading and ranking of 800 - 1000 examinations
Aug 2013 - Jul 2015

Mathematics Gre Preparation Course Instructor

Statesboro, GA

  • Developed 16 hours of instructional materials for course reviewing math on the Graduate Records Examination (GRE)
  • Taught 6 separate month long courses to prepare students for the mathematics section of the GRE
Aug 2011 - May 2014

Student Employee In The Office Of Admissions

Statesboro, GA

  • Collaborated on preparation and organization of bulk mail projects with up to 3,000 letters and compiled visiting student information packets for the Office of Admissions
  • Communicated details about Georgia Southern University to over 30 prospective or current students in person and on the phone each week
Aug 2008 - May 2011

Soar (Summer Orientation, Advisement, And Registration) Leader

Statesboro, GA

  • Presented information about Georgia Southern University to groups of up to 300 incoming students and parents
  • Facilitated 14 different break out sessions for groups of 20 - 30 incoming students
  • Supervised 10 enrollment sessions of over 100 students and provided academic counseling to over 50 students
Jan 2008 - Aug 2008
Team & coworkers

Colleagues at Lawrence Livermore National Laboratory

Other employees you can reach at llnl.gov. View company contacts for 6681 employees →

4 education records

James Diffenderfer education

Doctor Of Philosophy - Phd, Applied Mathematics - Optimization, 4.0

Activities and Societies: Society for Industrial and Applied Mathematics (SIAM), Graduate Student Mentor

FAQ

Frequently asked questions about James Diffenderfer

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What company does James Diffenderfer work for?

James Diffenderfer works for Lawrence Livermore National Laboratory.

What is James Diffenderfer's role at Lawrence Livermore National Laboratory?

James Diffenderfer is listed as Machine Learning Research Scientist | Applied Mathematics PhD | Python, PyTorch, C, C++ at Lawrence Livermore National Laboratory.

What is James Diffenderfer's email address?

AeroLeads has found 1 work email signal at @llnl.gov for James Diffenderfer at Lawrence Livermore National Laboratory.

Where is James Diffenderfer based?

James Diffenderfer is based in Sunnyvale, California, United States while working with Lawrence Livermore National Laboratory.

What companies has James Diffenderfer worked for?

James Diffenderfer has worked for Lawrence Livermore National Laboratory, University Of Florida, and Georgia Southern University.

Who are James Diffenderfer's colleagues at Lawrence Livermore National Laboratory?

James Diffenderfer's colleagues at Lawrence Livermore National Laboratory include William Berry, Vercelli Donna, Larry Swick, Jeff Hillier, and Claudia Silveira.

How can I contact James Diffenderfer?

You can use AeroLeads to view verified contact signals for James Diffenderfer at Lawrence Livermore National Laboratory, including work email, phone, and LinkedIn data when available.

What schools did James Diffenderfer attend?

James Diffenderfer holds Doctor Of Philosophy - Phd, Applied Mathematics - Optimization, 4.0 from University Of Florida.

What skills is James Diffenderfer known for?

James Diffenderfer is listed with skills including Neural Networks, Pandas, Mathematics Education, Git, Deep Neural Networks, Public Speaking, Linux, and Data Science.

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