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I am currently working as an Associate in technology at Morgan Stanley, where I develop algorithms and infrastructure components that control the behavior of trading systems. At this stage, I deeply desire to study further in Computer Sciences, especially in the field of artificial intelligence and machine learning. Intelligent programs that automatically improve with experience have always fascinated me, along with the fundamental laws that govern all learning processes. These, I believe would become ubiquitous in the near future, and I wish to play my part in these exciting developments as an engineer and innovator. I also wish to have the satisfaction of gaining a thorough understanding of the subject that fascinates me, and contribute to the research in this field.
I am excited by the current research work on language acquisition (particularly on learning context dependent mappings from sentences). I find it interesting to explore the different approaches that can be taken for classification of text in the process of grounded language acquisition, and have studied the probabilistic generative model applied in this field to reduce the required supervision. I wish to work on such approaches and build upon traditional techniques (such as those that employ support vector machines and neural networks) to build a system that can draw meaningful semantic inferences from content matter with little or no supervision. I draw strong motivation from the applications that such a system could have – imagine if it could advise one against going for a football match the following day on grounds of bad weather, possible traffic congestion and disappointing injury to his/her favorite player, through real time analysis of content mined from the web.
I wish to pursue these interests through further studies and research at a graduate school - one that provides an excellent environment for the aspects of research that I wish to work on.
[Read more about my background, research interests]