welcome to my website

Hello, I am Chandrashekhar Kalnad (Chad) currently based in the United States of America.

Summary

Chad is a Masters graduate from Clemson University. His technology-savvy attitude does not limit his ability to be innovative. He is passionate about futuristic technologies. Apart from being crazy about data techs he likes to play Racquetball, Badminton, Cricket, Board games and Video games. He also loves to hike and is very competitive in whatever he does. He belives that nothing is permanent except change and this belief makes him extremely adaptable. Every day he pushes himself to learn something new, and unrelentingly pursues his passion.


Email - ckalnad@g.clemson.edu
Mobile - 8646243224

My Skills

Python, C, MATLAB, VB, SQL, Tableau, PowerBI, AWS

Python 90%
MATLAB 80%
SQL 70%
Tableau 90%

Data Science

I like to use scientific methods, processes, algorithms and systems to extract knowledge and insights from many structural and unstructured data.


Data Analysis

I like to inspect, cleanse, transform and model data and discover useful information, inform conclusions and support decision-making.

Machine Learning

I like to develop computer systems that are able to learn and adapt without following explicit instructions, by using algorithms and statistical models to analyze and draw inferences from patterns in data.

Data Visualization

I like to represent data graphically and communicate relationships among the represented data to viewers of the images.


My Experiences

Machine Learning Researcher 2019 Sep - 2020 Sep

Clemson University

Reviewed/analyzed current Photovoltaic based IoT systems to improve scalability and efficiency.
Extracted data from Kaggle in XLS format and prepared data for exploratory analysis.
Modeled a Simulink solar water heater to predict energy output.
Performed cluster analysis for calculating variable correlations.
Applied regression models such as Linear regression, RidgeCV, Decision Tree regression, Support Vector regression, SGD, ADABoost, XGBoost for radiation prediction in Python and AWS Sagemaker.
Predicted future radiation values with fbprophet.

Data Scientist 2018 Jun - 2019 Apr

ZF transmissions

Projects
Measurement data automation
Automated the transfer of measurement results between production floor and lab, resulting in data traceability and process efficiency.
Implemented an alarm system to notify operators of data arrival.
Implemented LED system for final analysis display.
MetLab welding inspection and data validation
Created an efficient and automatic system for data entry, database generation and DMC (Data Matrix Code) creation resulting in automation and tracking.
Traceability
Troubleshooted and automated traceability process by creating PowerBI dashboards for flop 10 areas and parts.
This allowed the management to keep track of processes and its performance.
Cosmino connectivity loss warning and automated error detection system
Increased Python code efficiency and created a database comparator tool for Cosmino connectivity loss warning and error tracking.
Smart Glasses – Industry 4.0
Developed and tested applications such as training (implemented), automatic availability of data using QR and cycle-time reduction.
Was project lead and prime innovator.

Data Scientist 2016 Jun - 2017 Aug

Ramp Automation

AWS Cloud management and responsible for code build, release and configuration on Amazon EC2
Experience and good knowledge in AWS (Amazon Web Services) services like EC2, S3, EBS, EFS.
Performed AWS Cloud administration managing and ETL operations and SQL querying on EC2, S3 and Amazon RDS.
Participated in all phases of data extraction, data cleaning, data collection, developing models, validation, visualization.
Developed Python to collect data to implement business transformation rules to the data to enable analysis of theories to occur.
Analyzed, automated and visualized data and used ML techniques for classification and regression analysis.
Performed model tuning and selection by using cross-validation, parameters tuning to prevent over fitting.
Validated the machine learning classifiers using ROC Validated the machine learning classifiers using ROC curves
Performed Data Profiling to learn about behavior with various features such as traffic pattern, location, Date and Time etc.
Executed basic PLC programming (Ladder Logic) for machine automation

My Education

Master of Science 2017 Aug - 2019 Aug

Electrical Engineering - Intelligent systems, Clemson University

Bachelor of Engineering 2012 Jun - 2016 Jun

Electronics and Telecommunication Engineering, D.K.T.E.

Academic and Personal Projects

"The ones who are crazy enough to think they can change the world, are the ones that do."