When I think aboutadvancement of science and technology, one of the most futuristic is theprospect of machine super intelligence –machines matching humans in generalintelligence. For decades, simulating the human brain by computers has been religiously pursued, yet theresults are still not close to what nature has made . Researchers like PedroDomingos have proposed for the ultimate learning machine which derives allknowledge – past, present, and future from data by a single, universal learningalgorithm and rightly call the algorithms as – “ The Master Algorithm”. If such an algorithm is possible, inventingit would be one of the greatest scientific achievements of all time andsingularity is indeed near, as rightly argued by Ray Kurzweil in his book” Singularity is near”. This invention will have huge implications for world economy , it can revolutionize scientificresearch , invent everything else we need , discover patterns in nature provided enough of right kind of data is made available and by using advancedalgorithms for data mining and machinelearning, hidden trends and patterns may emerge that may advance our understandingof our world. I feel excitedabout this possibility of super-intelligence, where machine intelligencecompliments human intelligence to create an age of Artificial Intelligence .
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Iwant to contribute to that age of evolution. This motivates me to pursue M. S. degree in Computer Science (with emphasis on Machine Learning). My long andenjoyable interaction with computer science dates back to my school days, whereI was introduced to graphical user interfaces, operating systems and enjoyed drawinggraphical figures/recurring patterns, building miniature applicationssimulating real world systems using Java. My fascination for programming hassteered my career towards computer science . I have earned my undergraduatedegree in Computer Science at the CVSR College of Engineering, affiliated to Jawaharlal TechnologicalUniversity, Hyderabad.
Here, I studied electives such as web technologies, cloudcomputing, computer graphics, information retrieval systems. Having been exposed to the various facets of Computer Science, Ifound Theoretical Computer science most intellectually satisfying andsimulating , particularly courses like ” Design and Analysis of Algorithms”. Laboratory work provided deeper insight into various intricacies of computationand programming , this encouraged me tocontinuously learn and apply theoretical concepts and that is one of the reasons formaintaining high scores in oralexaminations , practical examinations and my final year project .
During my thirdyear , I was interested to do more of online courses for keeping myself updatedabout interesting advancements in technology . While I was searching for courses, I came across one with a weird title – “ Learning from data” . So, I wascurious enough to start the course. Initial lectures were quite invigoratingbecause they talked about using machine learning for predicting stock markets, recommendations for movies , predicting a movie’s success based on reviews andratings . But, I couldn’t complete the course because it was of advancedmaterial.
Further, during my final year project, Ihad the opportunity to build a web based simulation of an intelligent system whichdetects road accidents, notify them through vehicular networks, and estimatetheir severity based on the concept of data mining and knowledge inference. Itwas during the course of project work, while researching on intelligent system , I was fascinated by the breadth of applications of machine learning and thecapability of learning algorithms. Even after obtaining my Bachelor’s degree and during a demanding work schedule, I continued my study by reading bookssuch as “ Programming Collective Intelligence “ and through online courses suchas Machine Learning by Andrew Ng, which was a great introduction to ML withrigorous coursework, during which I have implemented neural network in octavefor digit recognition and Bayesian Statistics by Herbert Lee which provides mathematical intuitionbehind some of the learning algorithms.
Industrial exposure would present anopportunity to apply my knowledge to engineer real world systems, gain insightinto the best practices and an opportunity to interact and learn fromexperienced professionals’ . So, I have decided to join at Tata ConsultingServices Limited (TCS) after my graduation as an Assistant System Engineer. Iworked on developing enterprise web application for one of the largesthealthcare service providers based out in U. S. I was actively involved indeveloping and delivering nine users’cases across three modules . It was arich learning experience , I pushed my limits , rapidly prototyped capabilities, delivered use cases as per timelines and was appreciated by the client forthe same. I also worked on application level framework development, rule engineframeworks and gained insightful knowledge on design patterns, enterpriseintegration patterns, application level designing etc.
All these experienceshave made me a strong implementer familiar with software developmenttechnologies and frameworks like spring, ORM, Apache CXF, JBOSS Drools. Given the exposure and a desire to bepart of the next generation of machine learning researchers, I look forward topursuing a career inresearch and development by prototyping/building useful models, frameworks anddeveloping cutting edge software particularly in the field of machine learning. A Master’s degree would also present an opportunity to be part of prestigiousresidency programs like Google Brain , Facebook AI where, working on diverse projectswould be an unique learning experience . To achieve my research and careergoals, I hope to study in an environment filled with active learners andcreative ideas.
In addition , interacting with members of your research group will give me aninvaluable opportunity to broaden my horizons and later work in many researchareas that I cannot anticipate at the moment. Given my background, I believe Iam in a good position to make crucial contributions in such pursuits.