Anand Gopalakrishnan

Hi! I’m a PhD student with Prof. Jürgen Schmidhuber at The Swiss AI Lab (IDSIA). I’m broadly interested in the areas of unsupervised learning and deep learning. My long-term research goal is to design artificial agents that match the human-level capacity to build mental models composed of basic concepts such as objects, actions, space etc. which are learned from perceptual inputs. Learning such an idealized mental model in essence is to “invert” the generative process, that is to infer the underlying causal mechanisms given observations. These mental models could facilitate such agents to generalize beyond their direct experience through simulation of plausible yet unobserved outcomes (i.e. relevant interventions and counterfactuals). They also allow for reasoning about the world in terms of cause and effect in a more human-like manner. Towards this end, my current research is focussed on capturing meaningful discrete units (e.g. objects, skills, events etc.) within neural networks from perceptual inputs.

Before this, I received my Master’s degree in Electrical Engineering from Pennsylvania State University. My master’s thesis was on generative modelling of human motion, which I pursued with the guidance of Prof. C. Lee Giles. In my undergraduate days at National Insitute of Technology - Karnataka (NITK), I was interested in signal processing specifically on the domains of images and speech.