## Webpage of Arief Gusnanto

Department of Statistics, School of Mathematics, University of Leeds, Leeds LS2 9JT.
Phone: 0113 343 5135   Fax: 0113 343 5090   Email: a.gusnanto (at) leeds.ac.uk
Office: Room 10.14 Maths Satellite, EC Stoner Building (Level 10 between staircases 1 and 2)

Looking for R packages and datasets (including intro. to Tinn-R, a text editor for R)?
Click

### Teaching for 2023/2024 Academic Year

MATH1712 Probability and Statistics II [Module Description] [Timetable]

Check also the minerva for some more module material.
Introduction to R course

### Teaching for 2022/2023 Academic Year

MATH1712 Probability and Statistics II [Module Description] [Timetable]

### Teaching for 2021/2022 Academic Year

MATH1712 Probability and Statistics II [Module Description] [Timetable]
MATH5747 Learning through case studies [Module Description] [Timetable]

### Teaching for 2020/2021 Academic Year

MATH1712 Probability and Statistics II [Module Description] [Timetable]
MATH5835M Statistical Computing                           [Module Description] [Timetable]

(Please note that the main lecturer for MATH5835M Statistical Computing is Dr. Jochen Voss) I will be responsible for delivering teaching for some sessions in Semester 3, and all the material are available from his webpage to avoid confusion.

### Teaching for 2018/2019 Academic Year

MATH3880 Introduction to Statistics and DNA [Module Description] [Timetable]
MATH5880 Statistics and DNA                           [Module Description] [Timetable]

### Teaching for 2017/2018 Academic Year

MATH3880 Introduction to Statistics and DNA [Module Description] [Timetable]
MATH5880 Statistics and DNA                           [Module Description] [Timetable]

### Teaching for 2016/2017 Academic Year

MATH5745 Multivariate Methods                         [Module Description] [Timetable]
MATH3880 Introduction to Statistics and DNA [Module Description] [Timetable]
MATH5880 Statistics and DNA                           [Module Description] [Timetable]

### Current Research

1. Statistical methods and inference for genomic data
2. Penalised Partial Least Squares and its aplications
3. Machine learning methods for many applications
4. Sparse estimation of random effects in high-dimensional data