Karthik T. Narasimha

About Karthik T. Narasimha

Experienced engineer working on building smarter semiconductor tools using data analytics. Experience in delivering business impact using sensor data modeling in semiconductor industry. Well versed with various data science packages including Scientific Python stack (Pandas, SciPy, NumPy) Data Visualization tools (Bokeh, Plotly) Big data tools (PySpark, Dask) Machine learning packages (scikit learn, Spark ML) SQL and R/MATLAB Accomplished scientist with publications in top notch journals and invention disclosures. Team player comfortable with working in interdisciplinary, cross-functional organizations. PhD work in density functional theory modeling and experimental studies of nanocarbon materials

Experience

1. Staff Engineer, Equipment Intelligence

   Lam Research

   Feb 2017 — Present · Fremont, CA, US

   Staff Engineer: Oct 2019 - PresentSenior Engineer: Feb 2017 - Sept 2019I work on building smarter semiconductor tools using sensor data analytics. I develop equipment intelligence strategies and algorithms to solve tool productivity issues using sensor data. • Spear headed optical and mass based sensor deployments at customers as an engagement lead by developing sensor data-based use cases that generated over $2M in revenue. • Analyzed large datasets of sensor data using scientific python stack (pandas, numpy, scipy) and developed algorithms to implement self-correcting strategies that led to reduction in manufacturing variability • Developed many internal data analyses and viz tools (using bokeh & plotly) to monitor sensor health • Other work includes developing time-series based sensor algorithms for customer support

Education

• Indian Institute of Technology, Madras

  Bachelor and Master of Technology, Major: Mechanical Engineering, Minor: Theoretical Computer Science

  2003 — 2008

• Stanford University

  PhD, Materials Science and Engineering

  2008 — 2014

• Stanford University

  Master of Science (MS), Materials Science and Engineering

  2010 — 2011

Skills

• Simulations
• Design of Experiments
• Recommender Systems
• Statistics
• Scientific Writing
• Bootstrapping
• Data Wrangling
• Nanotechnology
• Machine Learning
• Scientific Computing
• Matlab
• Computational Materials Science
• Jmp
• Density Functional Theory
• Linear Regression
• Python
• Logistic Regression
• Neural Networks
• Classification
• Data Analysis
• Nanomaterials
• Sql
• Powder X-Ray Diffraction
• Characterization
• Principal Component Analysis
• Afm
• Decision Trees
• Predictive Analytics
• Physics
• Deep Learning
• Materials Science
• Numpy
• R
• Quantum Mechanics