To strive for perfection in my working field by a continuous learning process & putting in the best of my efforts so as to achieve the desired results. ©

Dasturchi, jiddiy, kamgap, oddiy inson... ©

Graduated from Carleton College in June 2018 with a BA in Computer Science. I like writing useful stuff, especially with Python and JavaScript. I like data visualization and creating tools for data analytics. Folk guitarist, utilitarian cyclist, environmentalist. ©

Ever since from my school days exploring new technologies was my passion. I still remember going to my cousin house and sitting in front of intel power pc with windows loaded. Throughout my middle and high school, I got attracted to the world of the internet and started exploring software. I learned Java through books. This passion carried me through my education which after some time to do Masters in Computer Application. Here there are more resources available to me than I ever could have imagined as a kid. I studied new languages, algorithms, computer architecture, all with pretty much the same fascination that drove me as a kid. And it was here that I knew, truly how much there is yet to learn. So, now as I`m heading towards industries, this enthusiasm is increased in me. There`s certainly yet more to learn, yet more problems to solve, and yet more to build. And for this, I am very grateful. Specialities: Languages: , , ++, . Technologies: , , , . Academics: , with python ©

A student at Computer science department - facutly of engineering - Helwan university ©

a fresher in c/c++/python/JS/HTML/CSS/React Native/Node.js/ ©

To work in a competitive environment that effectively utilizes my analytical, interpersonal, leadership and organizational skills to conceive and achieve solutions. The solutions which help the organization in not only meeting its targets, but also allowing it to grow, thereby, enhancing my own skills as an individual and as a key player in the organization`s development. Profile ©

DPhil candidate in Sociology at Nuffield College, Oxford University. My research concerns the use of non-representative samples to obtain estimates of behaviour at the individual-level, and then project this to the area level. I draw heavily on the Bayesian Multilevel Regression and Post-Stratification (MRP) paradigm, with a digital twist; namely I attempt to leverage Digital Trace data from social media to obtain unobtrusive measures of preferences at the individual and areal level. The latest version of my paper with Raymond Duch on this topic is forthcoming in the International Journal of Forecasting. Other methodological innovations to the MRP literature include the introduction of machine learning methods, in particular random forests, instead of computationally costly multilevel regression, to predict individual-level behaviour and expand stratification frames to include political and socio-demographic variables. Substantive interests are in the field of human behaviour, especially but not exclusively political behaviour, and how to measure mass public opinion in the digital age. ©