Nabin K. Malakar, Ph.D.

I am a computational physicist working on societal applications of machine-learning techniques.

Research Links

My research interests span multi-disciplinary fields involving Societal applications of Machine Learning, Decision-theoretic approach to automated Experimental Design, Bayesian statistical data analysis and signal processing.


Interested about the picture? Autonomous experimental design allows us to answer the question of where to take the measurements. More about it is here...


I addition to the research, I also like to hike, bike, read and play with water color.

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Friday, June 18, 2010

Diffusive Nested Sampling: Brewer et. al.

Brendon et. al. has a newer version of nested sampling algorithm, they call it Diffusive Nested Sampling (DNS). As the name indicates, it principally differs from the "classic" nested sampling in presenting the hard constraint. It relaxes the hard evolving constraint and lets the samples to explore the mixture distribution of nested probability distributions, each successive distribution occupying e^-1 times the enclosed prior mass of the previously seen distributions. The mixture distribution is weighted at will (a hack :P) which is a clever trick of exploration. This reinforces the idea of "no peaks left behind" for multimodal problems.

On a test problem they claim that DNS "can achieve four times the accuracy of classic Nested Sampling, for the same computational effort; equivalent to a factor of 16 speedup".

I have not played with it yet. However, it seems worth trying. Just a note to myself.

What can grow out of side talks in a conference?
If you know the power of scrapping in the napkin paper, you would not be surprised.

The paper is available in arxiv:
The code is available at:; comes with handy instructions.

Thanks are due to Dr. Brewer for indicating typos in the draft and suggestions + allowing to use the figures.
 The original nested sampling code is available in the book by sivia and skilling: Data Analysis: A Bayesian Tutorial
Data Analysis: A Bayesian Tutorial 
Edit: Sep 5, 2013 An illustrative animation of Diffusive Nested Sampling ( sampling a multimodal posterior distribution. The size of the yellow circle indicates the importance weight. The method can travel between the modes because the target distribution includes the (uniform) prior as a mixture component.

Saturday, June 5, 2010

Human Body as an Ecosystem and advent of Green Medicine

This sounds fascinating concept; equally impressive to grasp!

In an article published in scientific american, Humans Carry More Bacterial Cells than Human Ones, scientists claim human body to contain more bacterial cell than the human cell itself. So if you have 100 trillion cells in your body,  about the same number of bacteria are are paying you homage. Nice host. Moreover, it has also been reported that they have also contributed to human genes ( Strangely, other species seem to have less  connections with bacteria; or may be it is yet to be discovered.

By definition, Ecosystem is a functional unit consisting of living things in a given area, non-living chemical and physical factors of their environment, linked together through nutrient cycle and energy flow. Since they help to maintain various body processes, this makes human as a host and the body as an ecosystem.

We had already learnt that some bacteria were friendly and some were not. Identification of pathogenic bacteria and use of  antibiotic treatment has been hailed as one of the great success in medical history. The side effects of antibiotics are not so unfamiliar and reasoned as  killing off pathogenic as well as friendly bacteria. However, once we are able to understand the ecosystem of human body, curing "infectious" diseases should be just a treat load of another identified bacteria! Shall we call it Green Medicine?