Dr. Walid Magdy, of the University of Edinburgh, is giving a tutorial on possible directions to build a career in data science. The tutorial day consists of three lectures. The first two lectures give examples on domains of research in data science, namely: information retrieval and computational social science. The third lecture explores the possible career paths after graduation, where it includes some advices for those interested in different career paths, such as working in industry, working in research and academia (including graduate studies), and those who are interested in running their own business.
Al-Sawi Lecture Hall,
Facult of Engineering,
كلية الهندسة جامعة القاهرة, مدرج الساوي
Saturday, 16 December, 2017. 10am to 3:30pm.
Attendance is free, but you need to register you information here to be able to get into the Faculty of Engineering
This Tutorial consists of the following three lectures:
Social media is becoming a hub for most of internet users to communicate, share their thoughts, report news, and express themselves. Large amount of research started to utilize the huge amount of data from social media in many different applications. In this lecture, using social media for computational social science studies is presented to show how to learn about human behaviour, society’s trends, and political bias from the massive amount of online social data from social websites such as Twitter. Few examples are presented, such as:
Most of the work in this lecture was featured in news articles in popular press, such as BBC, CNN, Washington Post, the Independent, Aljazeera, the Daily Mail, and many others.
Information retrieval (IR) is mainly concerned with retrieving relevant documents to satisfy the information needs of users. Many IR tasks involving different genres and search scenarios have been studied for decades. Typically, researchers aim to improve retrieval effectiveness beyond the current “state-of-the-art”. However, revisiting the modelling of the IR task itself is often essential before seeking improvement of results. This includes reconsidering the assumed search scenario, the approach used to solve the problem, or even the conducted evaluation methodology. In this lecture, a quick introduction to IR is presented. Some well-known IR tasks are explored to demonstrate that beating the state-of-the-art baseline is not always sufficient. Novel modelling, understanding, or approach to IR tasks could lead to significant improvements in user satisfaction compared to just improving “objective” retrieval effectiveness. The lecture includes example IR tasks other than the famous web search task, such as printed document search, patent search, and social media search.
This might be the most important question in the mind of many undergraduates: What happens after graduation? Some dream about having a good position in an international company, others dream of pursuing their graduate studies by getting a masters and PhD degrees, and few think about running their own business. As a current academic in one of the top 20 universities in the world, who worked earlier for international companies such as IBM and Microsoft, and tried at some point of his career to make a startup, Dr. Walid will share his experience about the different routes that a successful engineer, data scientist can take for each of these different routes. He will be trying to answer some questions such as: What should I do to be able to secure a good position in an international company? What is the requirements that I need to work on to be able to join a top university for a PhD program? What are the possible routes after getting a PhD? I feel that I have entrepreneurship skills, how should I start to have my own successful business. This lecture will have some tips (not the most optimal, but based on personal experience) on the possible directions after graduations and the important preparation even before graduation. It is expected to have many QA in this session, so get ready to ask the questions that you think many of your friends might be thinking of.
Walid Magdy is an assistant professor at the school of Informatics, the University of Edinburgh (UoE) in UK. His main research interests include computational social science, information retrieval, and data mining. He received his PhD in 2012 from the School of Computing at Dublin City University (DCU) in Ireland. He received his MSc and BSc degrees from the Faculty of Engineering, Cairo Univeristy in 2005 and 2008 respectively. Before joining UoE, Walid worked for five years as a scientist at Qatar Computing Research Institute (QCRI). He also worked at his early career for IBM and Microsoft as a research engineer between 2005 and 2008.
Walid has over 60 peer-reviewed published articles in top tier conferences and journals. Some of his work was featured in popular press, such as CNN, BBC, Washington Post, the Independent, Daily Mail, and Mirror. He also has a set of 9 patents filed under his name.
More information could be found on his Homepage.