…a blog about Statistics and R Computing

About Me

I am a 3rd year graduate research assistant at Department of Statistics in Pennsylvania State University. Currently I am working on several exciting research topics under the advisorship of Dr. Lingzhou Xue. Before coming to Pennstate, I graduated with Masters in Engineering Physics from IIT Bombay.

My primary research interests include

  1. Statistical Machine Learning and Deep Neural networks
  2. Model based clustering in massive dynamic networks
  3. Bayesian Analysis and MCMC algorithms
  4. Statistical Computing
  5. Statistical Applications in Business Analytics, Recommendation Systems, and Engineering

My collaborative research interests include

  1. Data Mining applications to Geosciences
  2. Building Data Visualization tools using R Shiny


418, Thomas Building

Department of Statistics

The Pennsylvania State University

State College, PA 16802


“To see clearly is all!”



  • Graduate Research Assistant at Department of Statistics, The Pennsylvania State University, USA, 2014-Present
  • Teaching Assistant at Department of Physics, IIT Bombay, India, 2013-2014
  • Intern at Department of Power Mechanical Engineering, NTHU, Taiwan, Summer 2012.
  • Intern at Department of Physics, IMSc., India, Summer 2011.


  • Ph.D. Candidate in Statistics, The Pennsylvania State University
    Advisor: Dr. Lingzhou Xue
  • Masters of Technology in Engineering Physics, IIT Bombay, 2014
    Advisor: Dr. Anirban Sain
  • Bachelors of Technology in Engineering Physics, IIT Bombay, 2014
  • Minor in Statistics, IIT Bombay, 2014
    Advisor: Dr. Siuli Mukhopadhyay


  • Limca Certificate for National Record 2013 for most number of students solving Rubik’s Cube together within 30 minutes, 2012.
  • Yellow belt in Judo conducted by Judo Association of Bombay, 2011.
  • Best Volunteer Award in Group for Rural Activities under National Service Scheme of IIT Bombay, 2010.
  • Outstanding achievement award for being Central Board of Secondary Education (CBSE) topper in grade 12 in Institute for Plasma Research, Gandhinagar, 2008.
“To see clearly is all!”


  • Detecting the effects of coal mining, acid rain, and natural gas extraction in Appalachian basin streams in Pennsylvania (U.S.A.) through analysis of barium and sulfate concentrations
    Xianzeng Niu, Anna Wendt, Zhenhui Li, Amal Agarwal, Lingzhou Xue, and Susan L. Brantley.
    Environmental Geochemistry and Health Journal, 2017.
  • Asymmetric flows in the intercellular membrane during cytokinesis
    Vidya V. Menon, Soumya S S, Amal Agarwal, Sundar R. Naganathan, Mandar M. Inamdar, and Anirban Sain.
    Biophysical Journal, 2017 (Accepted).
  • Bayesian inversion and sequential Monte Carlo sampling techniques applied to nearfield acoustic sensor arrays
    MR Bai, A Agarwal, CC Chen, YC Wang.
    The Journal of the Acoustical Society of America 136 (4), 2084-2084, 2014.
  • Bayesian Approach of Nearfield Acoustic Reconstruction with Particle Filters
    Mingsian R. Bai, Amal Agarwal, Ching-Cheng Chen and Yen-Chih Wang
    Journal of the Acoustical Society of America, 2013 (pdf)


  • Discovery of Causal Time Intervals
    Zhenhui Li, Guanjie Zheng, Amal Agarwal and Lingzhou Xue
    SDM’17: the Seventeenth SIAM International Conference on Data Mining, 2017.


  •  Time-evolving Community Detection in Dynamic Networks 
    Amal Agarwal, Kevin Lee and Lingzhou Xue
  • Mixture of Exponential-Family Random Graph Models with Varying Network Parameters
    Kevin Lee, Amal Agarwal and Lingzhou Xue
“To see clearly is all!”

Temet Nosce

…a blog about Statistics and R Computing

“To see clearly is all!”

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