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Machine Learning and Optimization

Machine Learning algorithms and optimization techniques have become central to most applications of computing ranging from search, ads, data-mining, data-analytics in large databases, information retrieval and extraction, natural language processing including machine translation, speech, vision, gaming, user adaptation of computing systems, as well as security, privacy, and the broad topic of crowd-sourcing. Our goal is to conduct research in theoretical and practical aspects of Machine Learning and Optimization including:

  • Novel machine learning algorithms and paradigms
  • Foundational aspects of optimization techniques, including new algorithms and applications to machine learning
  • Theoretical analysis of machine learning and optimization algorithms
  • Performance analysis and enhancement of machine learning and optimization algorithms
  • Applications in search and IR, vision, NLP and other areas
  • Data mining and data analytics for very large data sets

Internship and Research Assistantship Opportunities

Internships: We are looking for interns to work on cutting edge research problems leading to publications in top tier conferences and journals. Students should send an email to in the format specified on the internship page. Click here to go to our internship page. Note that Indian undergraduate and masters students should apply through their respective campus placement programs rather than e-mailing us directly (we typically do not take Indian non-PhD students unless their institute has a campus placement tie-up with MSR and the students have applied through the program).

Research Assistantships: We are also looking for exceptional candidates who are fresh graduates (bachelors or masters in CS) to work with us for a period of 1+1 years on substantial research problems. The RA program is designed to give a flavor of research to those interested in pursuing a research career. RAs are exposed to cutting edge research and are expected to explore a problem in depth with their mentor and obtain multiple, high quality publications during this period. Previous Research Assistants have gone on to do a PhD from top CS schools or become successful entrepreneurs. Interested candidates with a strong track record in their undergraduate or master’s degree should send an e-mail to Manik Varma at along with their CVs and should mention their preferred starting date and the researchers they might be interested in working with.