Masabah holds a Master's degree in Data Science from the School of Electrical Engineering and Computer Science (SEECS) at NUST, Islamabad. With a strong research focus on machine learning and big data analytics, she brings deep expertise in leveraging advanced technologies to address complex societal challenges. Masabah is skilled in building robust machine learning models, extracting actionable insights from large datasets, and employing cutting-edge techniques in data analysis. Developing a data driven solution across healthcare, environmental monitoring, and other industries - she is your go to expert.

Ayesha earned a Master's degree in Computer Science from GC University Faisalabad. Her research interests span the fields of artificial intelligence and applied machine learning, with a particular focus on advanced modeling techniques for data-driven insights. Her previous work included pioneering research in automated detection and analysis of lung nodules in CT scan images, utilizing state-of-the-art models to improve diagnostic accuracy and efficiency. She is the go-to expert for neural network architecture design. 

Belén holds a Bachelor's degree in Sociology from the University of Buenos Aires and a graduate diploma in Computer Science and Digital Humanities from the University of San Martin. She is currently pursuing a Master’s in Urban Social Policies at the University of Tres de Febrero. Her research focuses on public policy monitoring and evaluation. She is the go-to expert for merging data science with social impact studies.

Derya studied Economics at Lomonosov Moscow State University and is currently completing a Master’s in Data Science and Business Analytics at Bocconi University. Her research focuses on statistics, with a particular interest in interpretability in machine learning. She is currently working on her thesis on Bayesian networks and has built hands-on skills in market research as an analyst. Regarding causal inference and interpretability, Derya is the go-to expert.

Manpa is currently pursuing an MSc. in Information Technology (INFOTECH) at the Universität Stuttgart. Her current research focuses on enhancing cryptographic knowledge of Large Language Models (LLMs), computer vision and eye tracking. With a keen interest in these fields, she is dedicated to pushing the boundaries of technology and its applications. In her research, she worked on improving the natural understanding and mathematical reasoning skills of popular LLMs. For mathematical understanding in LLMs, design and analysis of eye tracking experiments, Manpa is the go-to expert. 

Anthony is a Ph.D. candidate in Survey and Data Science at the University of Maryland. He holds an M.A. in Experimental Psychology from Towson University and a B.A. in Psychology with a Minor in Philosophy from the University of Baltimore. In his research, he uses principles of survey methodology and data collection to improve machine learning and AI model training. Anthony is proficient in experimental design, questionnaire design, data analysis, statistical modeling, and large-scale survey research. For quantitative social science, Anthony is our go-to expert.

Patricio is a Sociology graduate from Universidad Nacional del Litoral and holds a diploma in Data Science, Machine Learning, and its Applications from Universidad Nacional de Córdoba. Over the past four years, he has worked as a data analyst on projects in the public and private sectors. His research focuses on integrating the theoretical and methodological foundations of sociology with the advanced capabilities of modern data collection, analysis, and prediction technologies. For integrating sociology with data science, Patricio is the go-to expert.

Jorge holds a Bachelor's degree in Public Policy from the Center for Research and Teaching in Economics (CIDE) and an M.Sc. in Data Science for Public Policy from the Hertie School. In his research, he has worked on survival analysis, geocodification, and web scraping. Jorge has worked extensively on the Decision Analysis Project in Uncertain Contexts (PADeCI), where he has developed quantitative and qualitative skills. Regarding data-driven insights for public policy challenges, Jorge is the go-to expert.

Jacob Beck holds a bachelor’s and master’s degree in Sociology and is a PhD Student at LMU Munich.

He interned at the Institute for Employment Research (IAB) in Nuremberg and participated at the “Data Science for Social Good” fellowship. For DSSGx he is in charge of the overall organisation and project management.

Clara Strasser Ceballos is a PhD Student at the Chair for Statistics and Data Science in Social Sciences and the Humanities (SoDa) at LMU Munich. She holds a Master's degree in Statistics and a Bachelor's degree in Economics from the University of Munich (LMU). 

Wiebke Weber is Scientific Manager at the Chair for Statistics and Data Science in Social Sciences and the Humanities (SoDa) at LMU Munich and Research Fellow at the Research and Expertise Centre for Survey Methodology (RECSM) of Pompeu Fabra University, Barcelona, Spain.

Julia has an academic background in social sciences and brings in a decade of experience in consulting and project management at the intersection of strategy, business, and IT. She likes to work in agile, fast-paced environments and has a strong emphasis on stakeholder engagement and diverse perspectives. In 2022, Julia enrolled in an International Master’s program in the field of IT and Learning at the University of Gothenburg and started collaborating with a digital health startup. As DSSG Project Manager she will be responsible for the project management in the fellow projects.

Julia is a Freelance AI Consultant offering services throughout the data project lifecycle. Inspired by her research interest in hybrid intelligence, Julia is passionate about injecting humane domain expertise when working on data solutions. In her spare time, Julia is a Lead Team Member at the non-profit organization Data Science for Social Good Berlin, where she evaluates, defines, and manages AI use cases.

For DSSGx Munich 2024, she is the Technical Mentor responsible for guiding the solution design, supporting the fellows in developing their solutions, and providing technical feedback.

Professor Frauke Kreuter holds the Chair of Statistics and Data Science at LMU Munich, Germany and at the University of Maryland, USA, she is Co-director of the Social Data Science Center (SoDa) and faculty member in the Joint Program in Survey Methodology (JPSM). Together with Bernd Bischl, she is the host of the DSSGx Munich Fellowship.

Bernd Bischl holds the chair of Statistical Learning and Data Science at the Department of Statistics at the Ludwig-Maximilians-University Munich and is a co-director of the Munich Center for Machine Learning (MCML), one of Germany’s national competence centers for ML. Together with Frauke Kreuter, he is the host of the DSSGx Munich Fellowship.