Sébastien Celles is a professor of applied physics at Universite de Poitiers (working in the thermal science department). He has used Python for numerical simulations, data plotting, data predictions, and various other tasks since the early 2000s. He is a member of PyData and was granted commit rights to the pandas DataReader project. He is also involved in several open source projects in the scientific Python ecosystem.
Sebastien is also the author of some Python packages available on PyPi, which are as follows:
openweathermap_requests: This is a package used to fetch data from OpenWeatherMap.org using Requests and Requests-cache and to get pandas DataFrame with weather history
pandas_degreedays: This is a package used to calculate degree days (a measure of heating or cooling) from the pandas time series of temperature
pandas_confusion: This is a package used to manage confusion matrices, plot and binarize them, and calculate overall and class statistics
There are some other packages authored by him, such as pyade, pandas_datareaders_unofficial, and more
He also has a personal interest in data mining, machine learning techniques, forecasting, and so on. You can find more information about him at http://www.celles.net/wiki/Contact or https://www.linkedin.com/in/sebastiencelles.
Robert Dempsey is a leader and technology professional, specializing in delivering solutions and products to solve tough business challenges. His experience of forming and leading agile teams combined with more than 15 years of technology experience enables him to solve complex problems while always keeping the bottom line in mind.
Robert founded and built three start-ups in the tech and marketing fields, developed and sold two online applications, consulted for Fortune 500 and Inc. 500 companies, and has spoken nationally and internationally on software development and agile project management.
He's the founder of Data Wranglers DC, a group dedicated to improving the craft of data wrangling, as well as a board member of Data Community DC. He is currently the team leader of data operations at ARPC, an econometrics firm based in Washington, DC.
In addition to spending time with his growing family, Robert geeks out on Raspberry Pi's, Arduinos, and automating more of his life through hardware and software.
Maurice HT Ling has been programming in Python since 2003. Having completed his PhD in bioinformatics and BSc (Hons) in molecular and cell biology from The University of Melbourne, he is currently a research fellow at Nanyang Technological University, Singapore. He is also an honorary fellow of The University of Melbourne, Australia. Maurice is the chief editor of Computational and Mathematical Biology and coeditor of The Python Papers. Recently, he cofounded the first synthetic biology start-up in Singapore, called AdvanceSyn Pte. Ltd., as the director and chief technology officer. His research interests lie in life itself, such as biological life and artificial life, and artificial intelligence, which use computer science and statistics as tools to understand life and its numerous aspects. In his free time, Maurice likes to read, enjoy a cup of coffee, write his personal journal, or philosophize on various aspects of life. His website and LinkedIn profile are http://maurice.vodien.com and http://www.linkedin.com/in/mauriceling, respectively.
Ratanlal Mahanta is a senior quantitative analyst. He holds an MSc degree in computational finance and is currently working at GPSK Investment Group as a senior quantitative analyst. He has 4 years of experience in quantitative trading and strategy development for sell-side and risk consultation firms. He is an expert in high frequency and algorithmic trading.
He has expertise in the following areas:
Quantitative trading: This includes FX, equities, futures, options, and engineering on derivatives
Algorithms: This includes Partial Differential Equations, Stochastic Differential Equations, Finite Difference Method, Monte-Carlo, and Machine Learning
Code: This includes R Programming, C++, Python, MATLAB, HPC, and scientific computing
Data analysis: This includes big data analytics (EOD to TBT), Bloomberg, Quandl, and Quantopian
Strategies: This includes Vol Arbitrage, Vanilla and Exotic Options Modeling, trend following, Mean reversion, Co-integration, Monte-Carlo Simulations, ValueatRisk, Stress Testing, Buy side trading strategies with high Sharpe ratio, Credit Risk Modeling, and Credit Rating
He has already reviewed Mastering Scientific Computing with R, Mastering R for Quantitative Finance, and Machine Learning with R Cookbook, all by Packt Publishing.
You can find out more about him at https://twitter.com/mahantaratan.
Yingssu Tsai is a data scientist. She holds degrees from the University of California, Berkeley, and the University of California, Los Angeles.