Dr. Ritu Kapur Khosla

Senior Project Scientist,Β 

Non-Invasive Glucometer Project,

Indian Knowledge System and Mental Health Applications CentreΒ 

Indian Institute of Technology Mandi,Β 

Kamand, Mandi, Himachal Pradesh, India.

Education: I completed my Ph.D. (2016-20) in Computer Science and Engineering under the supervision of Prof. Balwinder Sodhi from the Indian Institute of Technology Ropar, Masters of Engineering (M.E.) (2013-15) in Computer Science and Engineering under the supervision of Prof. Maitreyee Dutta from the National Institute of Technical Teachers Training and Research (NITTTR) Chandigarh, and Bachelors of Engineering (B.E.) (2009-13) Β in Computer Science and Engineering from Chandigarh College of Engineering and Technology, both from Panjab University. I have also qualified for the Graduate Aptitude Test of Engineering (GATE) with All India Rank (AIR) 534 and the University Grants Commission (UGC) - National Eligibility Test (NET) in 2015.Β 

Research and Academic Experience:Β 

Broad Research interests: Software maintenance and evolution, Cyber-Physical Systems, Empirical software engineering, Data Science, Knowledge-based Engineering, Software Solutions for Health, and Gender Inequality in Software Engineering.

My research lies at the intersection of Software Engineering, Information retrieval, Data Mining, Natural Language Processing, Text Analysis, and Applied Machine Learning.Β 

So far, I have developed various Knowledge-based software artifacts such as Knowledge-warehouses and expert systems to automate different Software Development Life cycle (SDLC) tasks. Some of the prominent examples include estimating software development effort for a newly-envisioned software project, identifying source code defects and viable defect characteristics, and reviewing the source code.Β Β 

To develop these solutions, I have leveraged the information present on various open-source software portals (OSS), such as GitHub, Apache Bugzilla, StackOverflow, MavenCentral, and transformed it into structured datasets.

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