Machine Learning. Natural Language Processing.

Public Policy Innovation.

Health Implications of Climate Change.

About me

I am a professor of data science and public policy at the Hertie School of Governance in Berlin. At the Hertie School I am the director of the Data Science Lab - a new initiative to advance data science teaching and research at the School, and work with outside organisations to develop data science and artificial intelligence (AI) for common good.

Before joining the Hertie School faculty, I was a professor of public policy and data science at University of Essex, holding a joint appointment in the Institute for Analytics and Data Science and Department of Government. At Essex, I served as the Chief Scientific Adviser to Essex County Council, focusing on artificial intelligence and data science in public services. I also previously worked at University College London and London School of Economics.

I received a PhD in Political Science from Trinity College Dublin and a bachelor’s degree in Economics from Belarus State Economic University.

Selected invited talks

Lauching the Peace and Security Data Hub

October, 2021
UN World Data Forum Read more

Workshop on Computational Linguistics for Political Text Analysis

September, 2021
CPSS @ KONVENS 2021 Event page

Data Science for Data Driven Public Services

September 22, 2021
GIZ Future Forum - Data For Development Event page

Tracking the Connections Between Public Health and Climate Change

January 27, 2020
Applied Machine Learning Days at Swiss Federal Institute of Technology Lausanne, Lausanne, Switzerland Event page and recording

Complexity and Data Science: Cluster of Methods - pattern analysis, machine learning, causal inference

November 25, 2019
Helmholtz Incubator Information and Data Science Workshop, Berlin, Germany Slide deck

AI for SDG 16 on Peace, Justice, and Strong Institutions: Tracking Progress and Assessing Impact

August 11, 2019
Workshop on Artificial Intelligence and United Nations Sustainable Development Goals, IJCAI International Joint Conferences on Artificial Intelligence, Macao, China Slide deck

AI for Common Good

June 14, 2019
AI TRAPS: Automating Discrimination, Berlin, Germany Slide deck

NLP Applications in Political Science

December 12, 2018
Language and Computation Seminar Series, School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK Slide deck

Essex Centre for Data Analytics - a new vision for Essex

December 05, 2018
Innovation Series - Knowledge Gateway, Colchester, UK Slide deck

Data Science and AI for Public Good: Lessons from cross-sectoral collaboration

November 27, 2018
Bringing Data To Life For Policy and Practice: The BLGDRC Conference 2018, London, UK Slide deck

Transfer Topic Labeling with Domain-Specific Knowledge Base: An Analysis of UK House of Commons Speeches 1935-2014

November 08, 2018
Center for Comparative & International Studies, University of Zurich, Zurich, Switzerland Slide deck

Text Analysis and International Organizations - Tutorial

January 22, 2018
Empirical Research on International Organizations, Lorentz Workshop, Leiden University, Leiden, Netherlands Slide deck

Data science for the public sector

October 31, 2017
The growing ubiquity of algorithms in society: implications, impacts and innovations. The Royal Society Scientific Meeting, London, UK Slide deck

Slava Jankin

Leadership

Leadership roles and selected grants awarded

Data Lab

Hertie School Data Science Lab

I am the founding director of the Hertie School Data Science Lab – a trans-institutional initiative in artificial intelligence (AI) and data science (DS) with the mission to foster, advance and promote excellence in research, education, and applications to enable better decision making for the benefit of the individual, industry, government, and society at large. The research programme of the Lab is focusing on the applications of AI and DS methods such as computer vision, natural language processing, experimental survey methods, and causal inference to substantive problems in areas including political behaviour, climate change, decision making, and public policy. Research produced by the Lab has appeared in top scientific journals including The Lancet, PNAS, and Nature, and leading machine learning conferences such as NeurIPS and ICML. A new Master of Data Science for Public Policy has also recently been established through the Lab, with the aim to bring together passionate students, assist their learning and usage of modern data science tools, algorithmic decision-making process and machine learning methodology to tackle some of the most complex challenges of our time.

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Essex Centre for Data Analytics (ECDA)

At Essex my work focused on embedding artificial intelligence and data science in public service delivery. As Chief Scientific Adviser to Essex County Council I was the University lead on the Essex Innovates programme. The aims are to make Essex a place that is an exemplar for the integration of data across public bodies; to have the skill, capability and technology to undertake predictive analytics based on high ethical standards; to have a sustainable data infrastructure; and to have the best data science capabilities in the UK to benefit our people and communities. An outcome of the Essex Innovates is the creation of an office for data analytics - ECDA - an institutionalised, long-term collaborative effort to tackle public policy issues in Essex. ECDA will deliver on its aims through a data sharing platform, research and development platform, and an analytical hub pooling the capability across the partnership.

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CCAI

CATALYSE

Climate Action To Advance Healthy Societies in Europe

Role: Principal Investigator - working group lead on development of innovative health surveillance and forecasting tools that facilitate effective policy response to environmental health hazards caused by climate change.

  • Project goal: Despite clear signs that the impacts of climate change are escalating, the global response has been inadequate. Traditional scientific efforts have fallen short of providing knowledge and tools that have been broadly applied in decision-making, and innovative approaches to knowledge translation are needed. To catalyse climate action in Europe to protect public health, our overarching goal is to provide new knowledge, data, and tools on: i) the relationships between changes in environmental hazards caused by climate change, ecosystems, and human health; ii) the health co-benefits of climate action; iii) the role of health evidence in decision making; and iv) the societal implications of climate change for health systems.
  • Funder: Horizon Europe | European Commission
  • Total funding: €10.354 millions | Hertie allocation €975,000
  • Funding period: 01.07.22 → 30.06.27

SCRIPTS I

Contestations of the Liberal Script | Centre of Excellence - “Leader types and Liberal Narratives of the COVID-19 Pandemic”

Role: Principal Investigator

  • Project goal: This project compares decision-makers in the pandemic, with a focus on leaders, health and finance ministers. The role of these ministers is taken into account because much debate has revolved around the issues of life versus livelihoods. It considers the degree to which these persons are “experts” in the relevant policy area. It further investigates the extent to which leaders and ministers referred to scientific expertise and, when they did so, which particular disciplines they relied on.
  • Funder: German Research Council (DFG)
  • Total funding: €398,000
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SCRIPTS II

Contestations of the Liberal Script | Centre of Excellence - “Data and Methods Centre”

Role: Principal Investigator

  • Project goal: The Data and Methodology Center (DMC) contributes to a fruitful collaboration of scholars from a wide variety of disciplines, research traditions, and contexts. Its objective is to ensure and raise the standards of research by: 1) providing training and research consulting; 2) offering a forum for critical reflection about the concepts and methods underlying data collection; 3) discussing methodological innovations, especially those that connect quantitative and qualitative data; 4) assisting with data management and data accessibility; 5) establishing a central data portal to make the collected data available to other scholars (data archive and services) and thus contributing to a growing infrastructure of accessible social science data.
  • Funder: German Research Council (DFG)
  • Total funding: €740,000
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MiMac

Mixed methods for analysing what political parties promise to voters during election campaigns

Role: Co-Investigator

  • Project goal: For democracy to function effectively, political parties must offer meaningful choices to voters during election campaigns. However, as parties’ communication with voters is becoming increasingly fragmented, targeted and direct, it is becoming impossible for citizens to keep track of what different parties are promising. These new styles of campaigning are also challenging established methods for studying parties’ campaign promises. This project aims to develop innovative new methods that for the first time will enable researchers to examine the qualitative content of what parties promise in the large quantity of text and speech in election campaigns. The project includes leaders of the world’s largest research group devoted to the qualitative analysis of parties’ campaign promises. It also includes researchers who have developed new and widely used methods for the quantitative analysis of political texts, which detect patterns among words and ideas in large amounts of text. Progress in this field has been stifled by limited dialogue among the proponents of different qualitative and quantitative methods. This project will examine the strengths, limitations and theoretical implications of the full range of methods used in this field. The new methods that we will develop aim to combine they strengths of different approaches. These existing and new methods are highly relevant to the analysis of text and speech in a wide range of social science fields.
  • Funder: Bank of Sweden Tercentenary Foundation (Riksbanken Jubileumsfond):
  • Total funding: €1.1 million
  • Funding period: 1.01.20 → 31.12.22
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ESRC

ESRC Business and Local Government Data Research Centre

Role: Co-Investigator and Deputy Director

  • Project goal: Funded by the Economic and Social Research Council (ESRC), we aim to be the UK’s centre of choice for data research. We act as a hub of knowledge that reaches beyond Essex into a global network of experts, organisations and innovators. This ensures the far-reaching impact of our best practice models and concepts. Situated in the Knowledge Gateway of the University of Essex, we provide access to funding, training and world-leading expertise in data analytics.
  • Funder: ESRC
  • Total funding: £1.525 million (total funding including contribution from host institution £3 millions)
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Lancet Countdown

The Lancet Countdown Commission

Role: Working Group 5 Co-Investigator

  • Project goal: The Lancet Countdown on health and climate change is a collaboration involving over 120 leading experts including climate scientists, engineers, economists, political scientists, public health professionals, and doctors from 35 leading academic institutions and UN agencies across the world, including the World Health Organisation, World Meteorological Organisation, World Bank, European Centre for Disease Control and Prevention, and many of the world’s leading academic institutions. The work of The Lancet Countdown on health and climate change is supported by the Wellcome Trust.
  • Funder: The Wellcome Trust Foundation
  • Total funding: £5 millions
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Research

Selected publications from 2018 to present. Full publication listing can be found on my CV

  • All
  • Machine Learning & Natural Language Processing
  • Health Implications of Climate Change
  • Public Policy Innovation
Climate Change

Do Intergovernmental Organizations Have a Socialization Effect on Member State Preferences? Evidence from the UN General Debate

We adopt a novel approach to measuring state preferences and whether intergovernmental organizations (IGOs) have a socialization effect on them by applying text analytic methods to country statements in the annual United Nations General Debate (UNGD).

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Solar Panels

The 2021 report of the Lancet Countdown on health and climate change: code red for a healthy future

The Lancet Countdown is an international collaboration that independently monitors the health consequences of a changing climate. The 44 indicators of this report expose an unabated rise in the health impacts of climate change and the current health consequences of the delayed and inconsistent response of countries around the globe.

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Tracking progress on health and climate change in Europe

Left unabated, climate change will have catastrophic effects on the health of present and future generations. Responding to this need, the Lancet Countdown in Europe is established as a transdisciplinary research collaboration for monitoring progress on health and climate change in Europe.

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Corporate

The Challenges of Organizational Factors in Collaborative Artificial Intelligence Projects in the Public Sector

By using a case study that involves a large research university in England and two different county councils in a multi-year collaborative project around AI, we study the challenges that interorganizational collaborations face in adopting AI tools and implementing organizational routines to address them.

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Buildings

Transfer learning for topic labeling: Analysis of the UK House of Commons speeches 1935-2014

We present a transfer topic labeling method that seeks to remedy the issues stemming from the additional step of attaching meaningful labels to estimated topics in Natural Language Processing task, using domain-specific codebooks as the knowledge base to automatically label estimated topics

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Trucks

Engagement with health in national climate change commitments under the Paris Agreement: a global mixed-methods analysis of the nationally determined contributions

In this study, we aimed to examine how public health is incorporated in the nationally determined contributions outlined under the Paris Agreement, and how different patterns of engagement might be related to broader inequalities and tensions in global climate politics.

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Freights

Intergovernmental engagement on health impacts of climate change

We obtained the texts of countries’ annual statements in United Nations (UN) general debates to examine countries’ engagement with the health impacts of climate change in their formal statements to intergovernmental organizations, and the factors driving engagement.

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Energy

The 2020 report of The Lancet Countdown on health and climate change: responding to converging crises

The world has already warmed by more than 1.2C compared with preindustrial levels, resulting in profound, immediate, and rapidly worsening health effects, and moving dangerously close to the agreed limit of maintaining temperatures “well below 2C”. These health impacts are seen on every continent...

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Malthus

Improving public services by mining citizen feedback: An application of natural language processing

Digital technology has created new methods of collecting user feedback where service users post comments. As topic models can analyse large volumes of feedback, they have been proposed as a feasible approach to aggregating user opinions. This novel approach has been applied to process reviews of primary care practices in England.

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Freights

Managing artificial intelligence deployment in the public sector

There is a scarcity of empirical evidence surrounding the challenges and approaches to artificial intelligence deployment. Using data analytics, our study moves from speculation to gathering evidence. Our findings show that most challenges arise during implementation and relate to skills, culture, and resistance to share information driven by data challenges.

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Energy

Big data to the rescue? Challenges in analysing granular household electricity consumption in the United Kingdom

Rapid growth in smart meter installations has given rise to vast collections of data. However, to enable efficient policy interventions, we need to be able to appropriately segment the population of users. The aim of this paper is to consider challenges and opportunities associated with large highly-granular temporal datasets that describe residential electricity consumption.

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Malthus

Intra-cabinet politics and fiscal governance in times of austerity

Why are some governments more effective in controlling spending while others fall prey to excessive overspending by individual cabinet ministers? We approach this question by lifting the veil of collective cabinet responsibility and focusing on intra-cabinet decision-making around budgetary allocation.

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Freights

Power Plays and Balancing Acts: The Paradoxical Effects of Chinese Trade on African Foreign Policy Positions

This article examines whether trade with China leads African states to adopt more similar foreign policy preferences to China in the United Nations. We examine foreign policy similarity using voting patterns in the United Nations General Assembly and country statements in the United Nations General Debate.

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Energy

Big Data and AI–A transformational shift for government: So, what next for research?

This study offers an in-depth review of the Policy and Administration literature on the role of Big Data and advanced analytics in the public sector. It provides an overview of the key themes in the research field, namely the application and benefits of Big Data throughout the policy process, and challenges to its adoption and the resulting implications for the public sector.

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Malthus

The 2019 report of The Lancet Countdown on health and climate change: ensuring that the health of a child born today is not defined by a changing climate

The Lancet Countdown is an international, multidisciplinary collaboration, dedicated to monitoring the evolving health profile of climate change, and providing an independent assessment of the delivery of commitments made by governments worldwide under the Paris Agreement.

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Freights

Multiplex communities and the emergence of international conflict

Advances in community detection reveal new insights into multiplex and multilayer networks. Less work, however, investigates the relationship between these communities and outcomes in social systems. We leverage these advances to shed light on the relationship between the cooperative mesostructure of the international system and the onset of interstate conflict.

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Energy

AI for SDG-16 on Peace, Justice, and Strong Institutions: Tracking Progress and Assessing Impact

The transition from the Millennium Development Goals (MDGs) to the Sustainable Development Goals (SDGs) brought with it significant changes in the process of creating the goals and with the actual content of the SDGs. We argue that better use of machine learning techniques can help address the challenges of the SDG 16 inclusion.

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Malthus

Artificial intelligence for the public sector: opportunities and challenges of cross-sector collaboration

Public sector organizations are increasingly interested in using data science and artificial intelligence capabilities to deliver policy and generate efficiencies in high-uncertainty environments. The long-term success of data science and artificial intelligence (AI) in the public sector relies on effectively embedding it into delivery solutions for policy implementation.

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Policy Briefs

Published by the Centre for Digital Governance and the Data Science Lab

An essential part of the digital transformation in the public sector is the application of data science and artificial intelligence. These technologies will enable the public sector to become more efficient, responsive, prescient, sustainable as well as fairer by, for example, helping to detect and predict important trends, simulating and evaluating policy alternatives, and personalising or automating the implementation of policies. Yet governments are reticent about using these applications, in no small part because they lack in-house data science and AI capacities. To overcome their dependence on outside expertise and build up their own data science and AI capacities, governments are advised to:

  • Adapt recruitment practices and improve job attractivity for experts.
  • Build communities of practice and centres of excellence.
  • Collaborate with external experts and research institutions.
  • Strengthen interdisciplinary and intersectoral networks.
  • Hold government-sponsored competitions and hackathons.
  • Centralise capacities but continue to expand the base.
Read More
 

Teaching

Maths

Mathematics for Data Science

This course aims to deliver a compact and tailored introduction to the core mathematical concepts of data science, including linear algebra, probability theory, statistics, and optimisation.

AI in Government

Data Structures and Algorithms

This course begins with an introduction to fundamental programming concepts, presents basic ideas in data structures and algorithms and considers how to write efficient code using established software engineering practices and paradigms.

Machine learning

Machine Learning

The course covers topics in supervised and unsupervised learning, including the most common learning algorithms for regression, classification and clustering, such as random forests, neural networks, and dimensionality reduction techniques.

NLP with Deep Learning

Natural Language Processing with Deep Learning

This course provides an overview of modern data-driven models through deep learning towards richer structural representations of how words interact to create meaning.

AI in Government

Managing Digitalisation and Artificial Intelligence in Government

This course looks beyond the hype and focus on the real challenges and opportunities of practical applications of AI for government organisations.

AI for Decision Makers

AI for Decision Makers

This course aims to demystify the concepts of artificial intelligence, machine learning and data science, highlighting their direct business and societal benefits while also considering the challenges of their deployment.

Team

Hannah Bechara

Dr. Hannah Béchara

Postdoctoral researcher at the Hertie School

Olga Gasparyan

Olga Gasparyan, Ph.D

Postdoctoral researcher at the Hertie School

Paulina García Corral

Paulina García Corral

PhD researcher supervised under SCRIPTS

Alex Karras

Alex Karras

Faculty Assistant to Prof. Slava Jankin, Prof. Lion Hirth and Prof. Lynn Kaack

Krishnamoorthy

Krishnamoorthy Manohara

Research Assistant

Reed Garvin

Reed Garvin

Research Assistant

Ran Zhang

Ran Zhang

Research Assistant

Shuzhou Yuan

Shuzhou Yuan

Research Assistant

Contact

Get in touch

If you would like to contact me directly, please use the email address listed on my C.V. (linked above). I will do my best to get back to you as soon as possible, but often cannot respond to emails as quickly as I would like. Thank you!

Location:

Hertie School Data Science Lab

Friedrichstraße 180, 10117 Berlin

Email:

Faculty assistant:

karras@hertie-school.org