Fractal Fern

Mihir Arjunwadkar

mihir AT scms dot unipune dot ac dot in


Mihir@SCMS   Mihir@arXiv   Mihir@Scholar   Mihir@ResearchGate   Mihir@LinkedIn   Mihir@ORCiD

I am an academic at the SCMS-SPPU. Here, I helped create academic programmes in modeling and simulation. A conference article about this curriculum design experiment is available here and here.



My broad research focus is on the development – or apt and meaningful use – of statistical and computational methodologies for data-intensive science. Predominantly, my focus has been astrostatistics (radio astronomy in particular). In the past, I have dabbled into computational biology – genomic sequence analysis in particular.

Many fields of knowledge – sciences in particular – have grown increasingly data-rich over the past few decades. The complexity of scientific questions being addressed has also increased rapidly. Indeed, 21st century science has been aptly described as "large data sets, complex questions" science by Bradley Efron.

The use of statistics is inevitable because of the inherent uncertainties in data, whereas computation is unavoidable because of data size, methodological intricacies, and model complexity. What often helps address complex problems is fresh ways of looking at the problem and the available data, coupled with apt use of statistical and computational methodologies.

My approach and outlook is imminently inter-/multi-disciplinary (where problems are domain-specific, and the methodologies are statistical and computational) and problem-centric (where methods are devised or adopted to suit the problem being addressed, and not vice versa).


Over the years, I have taught courses on probability theory, statistical inference, advanced data analysis, stochastic simulation / Monte Carlo methods, the R statistical computing / programming language, numerical computing, optimization and, of late, statistical learning and data visualization.

In my teaching, I try to illustrate mathematical concepts and results using computation as an aid and, at the same time, try to emphasize the necessity of formal methods of analysis.

As obvious as it may sound, in computing-heavy courses, I try to emphasize the importance of hands-on self-driven explorations. I also try to emphasize the ability to learn-unlearn-relearn in case of programming languages and computing platforms/paradigms.


On the occasion of the 2021 Indian National Science Day, this little book describes Neehar's chemistry explorations during the 2020 lockdown months.

Chemistry in the Time of Lockdown

Lecture slides for the course Stochastic Simulation at SCMS OpenCourseWare.

Leibnitz Quote: But when a rule is extremely complex, that which conforms to it passes for random.

Life After Death by R, a small pedagogic collection of programming problems solved using the R programming language. This is a self-learning book for those who like to solve problems via computing.

Life After Death by R

The original 2012 Transit of Venus Science Comic Book by Niruj Mohan (concept and text) & Reshma Barve (illustrations).

Transit of Venus: 6 June 2012 (English)

A working presentation (in Marathi) outlining personal outlook and a set of guiding principles for how the newly-mandated courses on indian knowledge systems may be designed.

IKS Programmes: Guiding Principles