Sep 17, 2021
CombSGPO: A new algorithm to protect wildlife
Aravind Venugopal , Elizabeth Bondi , Harshavardhan Kamarthi , Keval Dholakia , Balaraman Ravindran , Milind Tambe
Poaching and illegal smuggling of wildlife have remained a cause of concern for wildlife authorities. As per the World Wide Fund for Nature (WWF), Wildlife trade poses the second-biggest direct threat to the survival of species after habitat destruction. As per the study conducted by TRAFFIC, a leading wildlife trade monitoring networking of the World Wide Fund for Nature (WWF), around 1,11,312 individual tortoises or freshwater turtles (11,000 a year) have been illegally traded across India since 2009.

3 min read

Jan 13, 2021
Ablation-CAM: Making AI trustworthy
Saurabh Desai , Harish G. Ramaswamy
As machine learning is set to change every aspect of our life, a key dilemma plagues the minds of researchers and its users- Can we trust machines to make key life decisions for us? Can we rely solely on the machine to drive us safely to the destination without knowing the basis of its function or shall we allow a machine to operate us instead of a doctor?

4 min read

Jan 13, 2021
Predicting Essential Genes through Network Approach: Deciphering basis of Life
A classic challenge in biology is to study the function of proteins. Of various functions, essential functions are very interesting, as they map to important indispensable genes in an organism. Experimentally identifying these genes is rather expensive and challenging. Computational predictions can help point in the right direction, to prioritise experiments. To date, experimental data are available for <100 organisms! On the other hand, sequencing data are available for 1000s of organisms, as also interactome (networks of interactions) data.

4 min read

Sep 5, 2020
Finding Influencers in Social Networks: Reinforcement Learning Shows the Way
Social Network Analysis has given us many tools to effectively manage information dissemination in a social group, study growth and dynamics in such groups, etc. But one of the key challenges when studying social groups of underprivileged or socially marginalized groups is the recovery of the underlying social network itself. This study proposes a machine learning approach for learning to effectively allocate a limited budget to discover the network.

5 min read