Events

We have an industry guest lecture coming up this term! This lecture will be given by Lars Lynne Hansen who is an AI Technical Expert and Khyla Kadeena-Miller who is a Data Scientist and they both work at AstraZeneca. AstraZeneca is one of our Capstone Project partners and Professor Milan Vojnović will be chairing this fantastic lecture!

Title: Data Science and AI in the pharmaceutical industry. 

Abstract: Data Science and AI are increasingly becoming an integrated part of the pharmaceutical industry. Applications cover widely - from discovery of new molecules and creating tools for better diagnosis of patients, all the way to running efficient commercial and manufacturing operations. We will give examples of how AI is used in the pharmaceutical industry, as well as the typical career opportunities within data science and AI in AstraZeneca. 

Register here

Are you an enthusiastic junior who would like to explore the field of Data Science? Or are you a more intermediate learner looking to upskill and try your first datathon? Or maybe you'd just like to learn something new and meet like-minded people?

LSESU Data Science Society is proud to announce its first flagship event: “Data Science Weekend - Navigating a Data-Centric World”.

Supported by the new LSE Data Science Institute, this 2-day event will include panel discussions by data scientists from the finance and consulting industries, beginner-friendly workshops and a 24-hour data science challenge open to all skill-levels.

Join us for a weekend of learning and professional growth you won't forget!

EXPLORE . PRACTICE. NETWORK.

Register via Eventbrite

We're delighted to announce that for our second industry guest lecture this term, we'll be joined by employees from Facebook. This lecture will be presented by Dima Karamshuk (Research Scientist) and Tiago Schmidt (University Recruiter). Facebook is one of our Capstone Project partners and Professor Milan Vojnović will be chairing.

Title: Popularity Prediction for Social Media 

Abstract: Predicting the popularity of social media content in real time requires approaches that efficiently operate at global scale. Popularity prediction is important for many applications, including detection of harmful viral content to enable timely content moderation. The prediction task is difficult because views result from interactions between content features, resharing, feed ranking, and network structure. In this talk we will discuss the problem of accurately predicting popularity both at any given prediction time since a content item's creation and for arbitrary time horizons into the future.

Register here

Course description: Graphs provide versatile abstraction for modelling, visualising and analysing rich and heterogeneous datasets. They offer a fundamental toolbox for modeling social, technological, biological systems and more. 

In this course, we will focus on the challenges and opportunities specific to the analysis of large graphs. The goals is to introduce students to the computational, algorithmic, and modeling foundations of the burgeoning area of machine learning ton graphs. We will study algorithms, programming frameworks and tools, and applications.

We will cover areas such as node and edge embeddings, representation learning and Graph Neural Networks; algorithms for the web, Knowledge Graphs, social network analysis, biological networks, and more.

Course lecturer: Moez Draief, Visiting Professor in Practice

Course content:

• Lecture 1 (16/03/21) - Challenges and Opportunities 
• Lecture 2 (23/03/21) - Shallow Graph Machine Learning
• Lecture 3 (30/03/21) - Deep Graph Machine Learning
• Seminar 1 (06/05/21) - Graph Machine Learning in Practice
• Seminar 2 (07/05/21) - Graph Machine Learning in Theory

Register for the three lectures here
Register for the two seminars here

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Hear from Statistics’ alumnae about their successes in the workplace, how they got to where they are today and any advice they might have for you in your job search.

This is an essential event for students interested in a career in statistics and data science. Panellists will discuss their own education, recruitment processes, their experiences, and more. 

There will be the opportunity to ask the panellists questions throughout the discussion, so bring your questions along with you!

The panel will be chaired by Sara Geneletti, Associate Professor in Statistics at LSE.

Panellists include:
Alyssa Staats, Economist at the Bureau of Labor Statistics (MSc Statistics, 2020)
Christine Yuen, Assistant Professorial Lecturer at the LSE Department of Statistics (PhD Statistics, 2021)
Malika Malik, Cloud Solution Architect at Microsoft (MSc Data Science, 2018)
Phoenix Feng, Divisional Strats at Deutsche Bank (PhD Statistics, 2018)
Sonal Shah, Education Actuary at the Institute and Faculty of Actuaries (BSc Actuarial Science)

This event is open to all and will be particularly useful if you:
     •  are interested in the work and responsibilities of jobs in different sectors,
     •  would like to hear about the experiences of women with statistics degrees,
     •  would like to get advice for your job search.

Register here

Speaker: John Burn-Murdoch is the Financial Times’ senior data visualisation journalist, and creator of the FT’s coronavirus trajectory tracker charts. He has been leading the FT’s data-driven coverage of the pandemic, exploring its impacts on health, the economy and wider society. When pandemics are not happening, he also uses data and graphics to tell stories on topics including politics, economics, climate change and sport, and is a visiting lecturer at the London School of Economics. 

Title: Tracking Covid-19 with the Financial Times.

Abstract: One of the most impactful ways that data science can change public policy and community is the building of tools that help people discover for themselves how the world works. In the midst of the confusion and muddled public messages by governments and international organisations at the onset of the covid-19 pandemic, the Financial Times created such a tool with their daily visualisations tracking the spread of the coronavirus around the world and providing one of the most reliable global view of the unfolding tragedy.

Joining us in session 2 of the CIVICA Data Science Seminar Series will be John Burn-Murdoch, the key architect behind the massively popular data visualisation tool by the Financial Times. John will share his and the FT team’s experience in data collection and presentation to the general public, the importance of good and evolving data visualisation in informing public discourse, and how he managed to capture the attention of millions and raised the global awareness on the seriousness of the ongoing pandemic.

This seminar is run jointly between the LSE Data Science Institute and the CIVICA network.

Find out more

Find out all about the events that we held in 2019/20 for our Undergraduate and MSc students!

Please join us for an IBM guest lecture on 30 November from 12pm - 1.30pm via Zoom!

Title: Using AI for Business Problems

Speaker: Loek Vredenberg who is the Chief Technology Officer of IBM Norge.

Abstract: This lecture positions Artificial Intelligence in context of how IBM use AI to solve business problems. It focuses on the different types of technologies IBM make available to clients and shows a small number of actual client cases. The event will benefit anyone interested in the use of AI, a career in technology, or careers at IBM. There will also be a Q&A session, so please bring any questions you may have.

Biography: Loek Vredenberg is the Chief Technology Officer of IBM Norge, with experience of technical leadership roles within IBM internationally and for deliveries of complex IT solutions. In recent years he has focused on artificial intelligence and IBMs cognitive technologies. He is currently working on cloud-based industry platforms for digital transformation. He has contributed to public debate around AI and given lectures and key notes on AI in many different settings.

To attend please register online with your name and LSE email address.

We are very excited to announce our first PLP this year! This online public event will take place on 17 September from 6pm with author and Economist Tim Harford on the day his new book, How to Make the World Add Up: Ten Rules for Thinking Differently About Numbers, is published! Chaired by our very own Professor Irini Moustaki, this looks to be a fantastic event and one not to be missed. You can register for the event from 10am on 3 September so set a reminder in your calendars!  

You can pre-order Tim's book How to Make the World Add Up: Ten Rules for Thinking Differently About Numbers. 

We invite our final year BSc and MSc students to join us for  celebratory Zoom events to mark the end of teaching and assessments in the Department of Statistics! We are so proud of all of our students and their achievements and we are even more impressed given the circumstances and we know that they should be very proud of their accomplishments!

Please note that this event has been postponed.

Our annual Risk and Stochastics event is taking place on 30th April at LSE and we havd seven fantastic speakers lined up! Please take a look at our conference webpage for more information. 

This event marks the inauguration of the MSc Data Science programme run by the Department of Statistics at the London School of Economics.

For more information on this event, please have a look here.