Contact

The students are encouraged to send me email at 

                     ayanbh(at)math(dot)iitb(dot)ac(dot)in

 concerning the course material, recommendations and any other academic purpose. 

For other purposes, I use following  email         

                                                                    ayanbhattacharya(dot)isi(at)gmail(dot)com

Mailing Address

Ayan Bhattacharya,

Department of Mathematics,

Indian Institute of Technology, Bombay,

Powai, Mumbai-400076,

Maharashtra, India.

For a letter of recommendation: 

I can't write a letter of recommendation in less than 14 working days before the deadline. If I am out of station, it may take more time. So please do not request in case the deadline is less than 14 working days.

Doing a project or a course with me does not ensure that I will write a letter of recommendation. 

For academic projects:

I do not offer projects once the semester starts.

I can ask for solutions to any problem of my choice from these books, depending on your interest. 

Usually, projects under my supervision require a good understanding of Analysis and Probability. If you are interested in a reading project with me on probability, you should have a good understanding of the following books: 

1.  Analysis I  by Terence Tao and Analysis II (up to Chapter 17) by Terence Tao

2.  Calculus Volume I and II by Richard Courant and Fritz John

3. Topology and modern analysis (Part I) by Simmons

4. Probability: An Introduction By Geoffrey Grimmett and Dominic Welsh 

5. Mathematics of Probability by D W Stroock

6. One Thousand Exercises in Probability by Geoffrey Grimmett, David Stirzaker.

7. Asymptopia by Joel H. Spencer, Laura Florescu

If you are interested in an advanced or hands-on project, then you need a good understanding of the following books:

1. A First Look at Rigorous Probability Theory By Jeffrey Seth Rosenthal

2. Chapter II in Adventures in Stochastic Processes by Sidney I. Resnick

3. Basic Stochastic Processes: A Course Through Exercises by Zdzislaw Brzezniak, Tomasz Zastawniak

4. Understanding Markov Chains: Examples and Applications by  Nicolas Privault

I offer some projects on Statistical Data Analysis, but that requires a good understanding of 

1. Introduction to Mathematical Statistics By Robert V. Hogg, Hogg, Joseph W. McKean, Allen T. Craig

2. Statistical inference by Lee Berger, Roger; Casella, George.

3. Mathematical Statistics: Basic Ideas and Selected Topics Volume I and Volume II by  Peter J. Bickel, Kjell A. Doksum

4. Linear Models in Statistics by Alvin C. Rencher, G. Bruce Schaalje

5. A Matrix Handbook for Statisticians by George A. F. Seber