Laraib Abid Wins 120 Under 40 Award by Bill and Melinda Gates

Pakistan has got a lot of young people that are making a name for themselves and are making the country proud in the international arena. There are many accolades that these young people are winning which will also inspire other people as well in the future. Laraib Abid is one such individual that has been making everyone proud by her work and that she has already won the Bill and Melinda Gates award for the 120 under 40 family planning leader’s award. The award is given by the Bill and Melinda Gates Institute of Population and Reproductive Health to the people who are aged under 40 and working for the society.

Laraib Abid is the founder of Mashal, a non-profit organization that focuses on the health of women and how it can be improved in the future as well. This is not the first time that Laraib has won some award for her organization and her work as she has already won the Emerging Young Women Leader award that was given by the Institute of Peace and Diplomatic studies. Her organization Mashal focuses on sexual and reproductive health along with gender equality so that all stereotypes are cleared regarding specific gender.

Laraib’s work also got her funds from the US Department of International Research and Exchange Board which helped her to assist the transgender community and the minorities with their health. Different health programs were introduced for this purpose as well. Laraib’s mission is to end the inequality that is happening around her at all levels and advocates for the women due to this particular reason. Born and raised in Pakistan, Laraib has got her bachelor’s degree in social and cultural studies from the University of Punjab. During her leisure time, Laraib prefers to travel and do some volunteer work

Jennifer Mccarthy

Jennifer is Associate Professor (Ph.D) at Air University. Research Interests: Informatics; analysis of large-scale biological data sets (genomics, gene expression, proteolytic, networks); algorithms for integration of data from multiple data sources; visualization of biological data; machine learning methods in bio-informatics.

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