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Krishna Chaitanya


Previous positions

  • Software Engineer – Calibration Tools at Bosch India


University of Colorado Boulder, Master of Science (MS), Computer Engineering




I wish to work in a challenging technical environment on Software Projects in the areas of Embedded Systems and/or Machine Learning. Technical Skills Languages: C/C++, Matlab scripts and mex, R, Python, PySpark, SQL Tools: vi editor, GDB, MS Visual Studio, Matlab – GUIDE, Apache Spark Miscellaneous: Data Structures, OOP, Multithreading (POSIX), RTOS, Linear and Logistic Regression


  • Software Engineer – Storage Device Drivers


    April 2014 – Present(5 years 6 months)Greater San Diego Area

    Create, automate and execute test plans for cell phone internal eMMC, UFS, external sdcard (SD 2.0 and 3.0) memory device drivers, and Modem File System. – Create Test Plan for Golden Copy feature of Modem File System – Develop unit tests in C for Modem File System – Create/maintain Perl and Shell scripts to automate the Level Based test plan – Automate eMMC and UFS Storage Memory chip validation tests – Create stability, regression, concurrency, low power mode and performance tests and automation for storage drivers and their interfaces with Modem subsystem

  • Software Engineer – Calibration Tools

    Bosch India

    June 2008 – November 2011(3 years 5 months)Bengaluru Area, India

    Develop object oriented programming (OOP) based software libraries in C++ and Matlab for parsing of Vehicle Calibration data in MDF format which was used by Calibration Engineers. – Design, Implement, Test the entire MDFLib library and end user APIs as per V-model – Use Agile (Scrum) methodology for SDLC and STLC – Create Test Plans with Testable Requirements and Requirement Traceability Matrix (RTM) – Automate Unit testing using MUnit in Matlab for Code Coverage and Decision Coverage – Use 5 Why and 3*5 Why for Root Cause Analysis – Document the code and the user manual, and conduct trainings for new joiners – On-site Co-ordinator for collection of requirements, analysis, customer feedback


  • University of Colorado Boulder

    Master of Science (MS), Computer Engineering

    2012 – 2013

    MS in Computer Engineering with focus on primary focus on Embedded Systems, and secondary focus on Machine Learning / Data Science

  • Vellore Institute of Technology

    Bachelor of Technology (B.Tech.), Computer Science

    2004 – 2008

    B.Tech Computer Science and Engineering


  • English

  • Hindi

  • Telugu


  • Hardware/Software partitioning algorithm for embedded systems with repeated functionalities



    We proposed a hardware software partitioning algorithm which would consider redundant functionalities/work-blocks in a embedded system and accordingly give an optimized hw/sw partition the system. Most of the research is done considering each block as unique, whereas in real life cases workflow of all systems has functionalities being re-used over and over again.

    Authors (3):
    • Krishna Chaitanya,
    • Krishna Chaitanya,
    • Sunny Sapra


  • Comparative beta diversity analysis of functional genomics in amphibian skin microbiomes

    February 2013 – May 2013

    Analyzed 16S RNA data from amphibians to enumerate host-microbe-pathogen relationships using the Quantitative Insights Into Microbial Ecology software package. Compared PCA and LLE dimensionality reduction techniques to visually determine the effect of pathogens on the immunity of amphibians.

    Team Members (2):
    • Krishna Chaitanya,
    • Narasimhan Madabusi
  • Time Lapse Video – Embedded Systems

    Implemented a USB image capturing system using Linux on a TI Beagleboard. The images were captured at every 1 sec interval in YUV format, sharpened, converted into PPM format, and stored on an SD card. And finally, ffmpeg was used to create time lapse video. – Producer/Consumer bounded buffer problem – Used semaphore and mutex locking on buffers between Image Capture (Producer) thread and Sharpening (Consumer) thread Resources/Technologies : C, Linux, TI Beagleboard

    Team Members (1):
    • Krishna Chaitanya
  • Speech Recogition

    This project was a subpart of a project to actuate a robotic arm to pick coloured balls and drop them in coloured bins upon receiving a speech stimulus. I incorporated the MFCC library to capture the feature vectors and implemented the k-means clustering to identify the spoken word is Red, Green or Blue. Technology : C

    Team Members (1):
    • Krishna Chaitanya
  • Music Categorization by Genre

    Retrieved features (MFCC) from songs, implemented Locally Linear Embedding (LLE) dimensionality reduction technique, and used SVM for classification of songs by genre. Resources/Technologies : Matlab, and LIBSVM toolboxes

    Team Members (3):
    • Krishna Chaitanya,
    • Krishna Chaitanya,
    • Sebin Gracy
  • ANOVA of Cache Coherency Protocols in Gem5

    Collected statistics of execution times of workloads in SPEC 2000 suite for different coherency protocols (MESI, MOESI) for a given cache configuration and performed Analysis of Variance and TukeyHSD to determine the better protocol. Resources/Technologies : R, Gem5, SPEC 2000 suite (integer workloads)

    Team Members (1):
    • Krishna Chaitanya
  • Click Through Rate Prediction

    Used OHE (One Hot Encoding) and Feature Hashing to produce feature vectors for the LogisticRegression to do Click Through Rate Prediction on data from Criteo Labs during KaggleCompetition. Technology : Apache Spark, PySpark, Logistic Regression, Sparse Vectors

    Team Members (1):
    • Krishna Chaitanya

Skills & Expertise

  • PL/SQL
  • Tortoise SVN
  • Linear Regression
  • Software Design
  • Core Java
  • JavaScript
  • XML
  • Perl
  • Unix
  • Multithreading
  • Automated Software Testing
  • Python
  • Software Testing Life Cycle (STLC)
  • Machine Learning
  • Web Services
  • Logistic Regression
  • Linux
  • Apache Spark
  • C
  • Requirements Analysis
  • Object-Oriented Programming (OOP)
  • C++
  • R
  • Java
  • Software Development
  • Oracle
  • SQL


  • R Programming

    Coursera, License

    March 2015

  • edX Verified Certificate for Scalable Machine Learning using Apache Spark

    edX, License
  • Statistical Inference

    Coursera Course Certificates, License 8XRDERPSRAGQ

    February 2016

  • Foundations of Programming: Data Structures

    LinkedIn, License

    November 2016


University of Colorado Boulder

  • Real Time Embedded Systems
  • High Dimension Datasets
  • Statistics in Computer Performance Modeling
  • BioStatistics

Vellore Institute of Technology

  • Data Structures

Independent Coursework

  • Machine Learning
  • R Programming

Volunteer Experience & Causes

  • Volunteer

    Association for Indias Development

    Social Services

    I have volunteered as a volunteer as part of the Association for India’s Development Boulder Colorado Chapter during organising Holi, Dandia celebrations to raise funds for Education, Housing, Health projects for people in Gujarat and Tamil Nadu in India. Also, volunteered for BolderBoulder Marathon. I have also taken part in the 2016 San Diego Heart & Stroke Walk organised by American Heart Association.