Post Job Free

Resume

Sign in

Assistant Professor

Location:
Lubbock, TX
Posted:
October 03, 2017

Contact this candidate

Resume:

EKARIT PANACHAROENSAWAD

**** **** **, *******, **, 79424 Cell: 918-***-**** ac2kvf@r.postjobfree.com Profile Summary: https://www.linkedin.com/in/ekarit-panacharoensawad-79634143/ Dr. Panacharoensawad is an assistant professor who is excellent at numerical method and programming in Python, C++ and Fortran. He has 10 years’ experience in analyzing engineering data and solving engineering problems including multiphase flow, heat transfer and flow assurance. Skills Highlights

Expert in numerical methods: PDEs, ODEs, non-linear optimization

Fluent in C++, Fortran, Python, VBA with Ubuntu + terminal / Windows OS Education

Ph.D., Petroleum Engineering (University of Tulsa, Tulsa, OK) 2012 M.S., Petrochemical Technology (Chulalongkorn University, Bangkok, Thailand) 2007 B.S., Physics, First Class Honors (Chulalongkorn University, Bangkok, Thailand) 2005 Certificates

• Introduction to Data Science in Python Coursera: 2017

• Applied Plotting Charting & Data representation in Python Coursera, 2017

• Applied Machine Learning in Python Coursera, 2017 Relevant Work Experience

Assistant Professor July 2014 – Present

Petroleum Engineering – Texas Tech University, TX

Taught Numerical Method with Python and C++, 3 credits hours graduate courses. The topic covered are regression, linear and non-linear system, ODE, PDE, optimization, etc.

Supervise a PhD student to solve hyperbolic two-phase flow problem with C++ Research Associate May 2012 – June 2014

Petroleum Engineering – University of Tulsa, Tulsa, OK

Replace the search algorithm with Levenberg-Marquart method. The program became 1000 times faster.

Built VBA user interface with user manual, linked with Fortran, for 7 oil and gas companies. Research Assistant August 2007 – May 2012

Petroleum Engineering – University of Tulsa, Tulsa, OK

Programmed 5000+ line of Fortran code for solving heat and mass transfer problems in wax deposition, with 20% relative error of the prediction

Analyze 454 MB data from sensors and laboratory analytical instruments (HTGC, DSC) Relevant Projects: https://github.com/epmmko

Github: Web-Traffic analysis (C++: data cleaning / exploratory data analysis), Titanic survival analysis

(Kaggle, python: machine learning), Boston housing analysis (Udacity, python: machine learning) Religion crime analysis (Coursera, data cleaning and visualization) My Python Course material https://goo.gl/zswEVN + lecture videos https://goo.gl/rMyj14 Recent Publications: *refers to the corresponding author Singh, A., Panacharoensawad, E.* and Sarica, C. (2017) A Mini Pilot-Scale Flow Loop Experimental Study of Turbulent Flow Wax Deposition by Using a Natural Gas Condensate, Energy and Fuels, 31 (3), pp 2457-2478. Impact Factor of 2.835. Peer-reviewed articles: 6 articles, totally Conference articles: 8 articles, totally Authorized to work in United State with a permanent resident card (green card)



Contact this candidate