Data Power Plant

NIKHIL KADLOOR

*** * ****** ****, ***.# ***, Tempe, AZ 85281 Cell # 480-***-**** Email- ********@***.*** LinkedIn- http://www.linkedin.com/in/nikhilkadloor

BACKGROUND

Industrial Engineer majoring in Statistics and Data-Science. Over 2 years’ experience in applying Data Science and Statistical concepts for the Energy Industry, leading industry-academia research projects and self-started projects

EDUCATION

Master of Science in Industrial Engineering (Statistics) Arizona State University May’17 (GPA:3.48)

Bachelor of Engineering, Mechanical Engineering, R.V College of Engineering, India May’15 (GPA:3.65)

TECHNICAL SKILLS

-Data extraction, pre-processing and Programming using R/python/SQL scripts

-Ability to execute complex SQL queries, knowledge of databases

-Using machine learning packages like Caret, Sci-Kit, MICE to run ML algorithms on large datasets.

-Statistical analysis like regression, hypothesis testing, Time-Series analysis using tools like JMP, Minitab, R. Data Mining using Clustering, Neural networks, SVM, Bayesian Rules

-Team player experienced in working with cross-functional research groups

WORK EXPERIENCE

Data Analyst, ASU-Photovoltaic Reliability Lab May’ 16- Present

Using unstructured Solar Photovoltaic data to derive insights that drive Research Projects

Developed a Solar Energy Forecasting technique and Performance data reporting and dashboards

Automated failure prediction in Solar modules using machine learning avoiding manual inspection

Using statistical modelling, Design of Experiments and quantitative analysis to design an Accelerated Test for Department of Energy funded projects

Working with a diverse team, communicating results with visualization and reports improving decision making

Continental Automotive AG, Bangalore, Karnataka, India June’14- Aug’14

Developed Tableau and BI dashboards to visualize Performance Indicators of the manufacturing line.

Stochastic modelling of the assembly line and decreased lead time by 5% for business intelligence group

Prepared a Value Stream Map for ECU assembly line and presented a lean line design using MS Visio.

Aeroto Boldrocchi Pvt Ltd, Milan, Italy June’13- July’13

Used SQL querying to pull production line data and automated data report creation

Presented a better shop layout, developed an Excel tool to automate job scheduling

PROJECTS

Master’s Thesis- Energy/Risk Forecasting of Solar Power Assets (Python, R, Tableau)

Time Series/Machine learning forecasting methods to predict energy production and impact of module degradation

Statistical Reliability approach developed has 98% long-term forecast accuracy

Use of Analytics to formulate dynamic pricing for Electricity Grid companies

Developed Python/R scripts for automating analytics and Data Visualization for each site

Master’s Thesis- Data Mining to Predict defects and risk of failure (R, Python, WEKA)

Using data mining/clustering algorithms (Decision Trees/random forests/Support Vectors) to predict failure and defects in Photovoltaic modules involving over 60,000 modules

Failure and lifetime prediction carried out helps manufacturers assess impact of defects on product lifetime

Predicts RPN(Risk Priority Number) a representation of risk of failure of a power plant

Distributed Energy Resource Prediction using Machine Learning (R, Python, Minitab)

• Used Machine Learning to predict Solar Irradiance for Distributed sources of Energy

• Time series, Support Vector Regression, Ensemble techniques used to train on historical meteorological data

ETL using SQL and Python, statistical inference testing carried out on the model

Accuracy of 90% in predicting short term energy generation forecasts, information useful to ensure grid stability

Decision Support System for Scheduling and Allocation of Resources at University (SQL, MS Access, VBA)

• Developed a detailed E-R and relational model for the database

• Designed and developed the database using MySQL workbench, MS Access

• Used SQL scripts, Functions and Stored Procedures to create reports

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