I am a 5th year PhD candidate in the Department of Statistics at the Pennsylvania State University. Regularization methods specifically on High dimensional functional data sets are the heart of my research. Machine Learning, Big Data, Coding and Web-based apps are my interests.
PhD, Penn State University
Expected : Summer 2019
GPA : 3.92/4
I am working on several projects on Regularization methods under the advisorship of Dr. Matthew Reimherr. I am interested in conducting statistical inference on sample of functions. Please see my research projects at the Portfolio.
M.S, Sharif University of Tech
2011 – 2013
I mainly worked on Stochastic Analysis and my research topic was on Extending Supermartingales Hoeffding’s Inequality.
2006 – 2011
In department of Electrical Engineering and Communication, my research topic was on optimization in Information theory
Novartis, Cambridge, MA
Implementing multiple modularized R Shiny apps for analyzing and visualizing clinical and biomarker big data (around 1.5 million observations) in NIBR oncology center and consulting to other projects. Reading big data from the server and modularizing the apps were the two important challenges.
Raavi : Founder and Developer
2016 – now
Raavi is a Shiny web app (interactive website with back-end in R Statistical language) for visualization of high school and university grades data. It was a great experience for me on both UI/UX and Server part. Working with my own Shiny Server and linux system, modularizing shiny app, combining Shiny UI with WordPress styles, improving performance with Profvis package and combining many great visualization packages in R like ggplot, plotly, shinywidgets, rhandsontable, JS packages and many more empowered me to learn and deal with many challenges in writing a complicated shiny app.
Statistical Consulting I
Applications of statistical methods in the consulting environment with emphasis on written and oral communication skills.
Statistical Consulting II
Practical consulting and communication skills with focus on participating in the online discussion.
Latex , Overleaf , Onenote , Microsoft Team , Slack
Probability, statistics, and Calculus, Tehran Virtual University, Iran, 2008
Applied Statistics (STAT 500), PSU, FALL 2017,2016,2015, Summer 2016
Intermediate Applied Statistics (STAT 460), PSU, FALL 2017
Regression Methods (STAT 501), PSU, Summer 2017, Spring 2017
Elementary Statistics (STAT 200), PSU, Spring 2016
Introduction to Stochastic Models (STAT 416), PSU, Fall 2015
Applied Statistics in Science (STAT 319), PSU, Spring 2015
Probability & Mathematical Statistics (STAT 414), PSU, Fall 2014
Calculus I, Sharif University of Technology, Iran, 2011
Algebra I, K.N. Toosi University, Iran, 2010
Probability and Statistics, K.N.Toosi University, Iran, 2007
2017 – RAO
Best Poster Presentation Award
Best Poster Presentation Award, 2017 Rao Prize Conference, May 2017
2011 – NMC
Silver Medal, 35th Iranian National Mathematics Competition for university Students, 2011
Ranked 8th, among nearly 8,000 participants in the National University Entrance Exam for M.Sc. in Mathematics
Top ten, in Mathematics competition held among undergraduate university students who studied in Tehran By Iran University of Science and Technology.
Xiao Ni Group Head Biostatistics – NIBR
Energetic and highly professional are the phrases when I think of Ardalan. I’ve had the pleasure of collaborating with Ardalan during his summer internship with Novartis, as one of his mentors. I was impressed with his solid statistical training, deep knowledge and creativity in RShiny application development. His expertise and contributions in promoting Shiny modularization are highly valued. I think what made him exceptional is not only his technical competencies, but also a combination of passion, energy and pleasant personality. Ardalan would be a true asset for a statistician/biostatistician position. His skills in RShiny and machine learning would be a plus for a data science oriented quantitative organization. I highly recommend Ardalan without reservation. Read in LinkedIn