Fractal Fern

Mihir Arjunwadkar

Professor

mihir AT scms dot unipune dot ac dot in

Curriculum vitae

List of publications

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

I am a professor at the SCMS-SPPU. Here's more about my research, teaching & outreach activities. Further information is available in my CV.

Here, I helped create academic programmes in modeling and simulation. The vision for these programmes is documented in detail here and has withstood the test of time. A conference article about this curriculum design experiment is available here.

As the very first faculty to join (2003) the Centre for Modeling & Simulation (now merged into SCMS-SPPU), I have a unique experiential persopective on building from scratch an academic department committed to academic rigour, critical inquiry, and excellence.


Research

My broad research focus has been 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. Of late, I was involved in research related to a Pune-specific minerology problem.

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).

Teaching

I have taught exclusively in the higher-education setting since 2004. Over the years, I have taught various courses to varied undergraduate, postgraduate, and research audiences consisting of engineers and scientists in various institutions in Pune. These include: 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/machine learning, and data visualization.

Over the years, my style of teaching has evolved from meticulously presenting content oneself to facilitating learning by understanding the audience (as well as possible, depending on its size). In my experience, students with some capability, sufficient interest and strong motivation will eventually overcome any handicaps in their prior background – with some push and help when required. As for strategies to help students engage with learning better, I have experimented with variety of formats and activities so as to nudge the students towards understanding, ability to put understanding into practice, self-reliance and excellence. As obvious as it may sound, in computing-focused 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.

Here is some pedagogic material which may be useful to teachers/instructors:

Outreach Highlights