Instructional Assistant Professor
ConocoPhillips Faculty Fellow for 2021 and 2022
Program Director, For Students Initiatives for Texas A&M University Institute of Data Science (TAMIDS)
Here is my CV
Teaching Interest
I have created and revised 2 major senior undergraduate courses (STAT 335 and STAT 421) on Data science and Machine learning with Python, that are cross listed with the department of Computer Science. I have also taught graduate level courses on Statistical Data Analysis and revised Statistics for Biology. Courses I have taught from 2020 - 2022.
Spring 2022 : STAT 421: Machine Learning with Python. [Syllabus]
FALL 2021 : STAT 335: Principles of Data Science with Python. [Syllabus]
STAT 601: Statistical Data Analysis.
Spring 2021 : STAT 421: Machine Learning with Python.
STAT 312: Statistics for Biology with R . [Syllabus]
FALL 2020 : STAT 335: Principles of Data Science with Python.
STAT 312: Statistics for Biology with R.
Spring 2020 : STAT 335: Principles of Data Science with Python.
STAT 312: Statistics for Biology with R.
Contact
Research Interest
Department of Statistics, Texas A&M University
3143 TAMU
College Station, TX 77843-3143
Street Address: 155 Ireland Street
Office: 437 Blocker
Voice: (979) 845-3141
Fax: (979) 845-3144
Email: srahman@stat.tamu.edu
Clustering Algorithms; Unsupervised learning methods; High dimensional Inference.
During my postdoctoral work under Dr. Valen Johnson, we have developed one scalable clustering algorithm and one novel penalty criterion that has very low requirements on hyper-parameter specification and is very effective in detecting arbitrary shaped clusters automatically in high-dimensional data. I am currently working with one Masters and one Phd student to build deep embedded clusters for image and spatial data.
Software Published
RJCluster : R package at CRAN repository. A clustering algorithm for high dimensional data. Try it on your data !
Selected Awards and Honors
Refereed for Journals
1. Statistics and Probability Letters.
2. BMC Bioinformatics.
3. Statistics in Bioscience.