About

I am a DPhil Student at the University of Oxford and passionate about answering the question: How do we gather high-quality data and extract valuable information to answer important questions?

You can contact me here.

The longer version

I like to think of statistics as the honest interpretation of data, even when the honest interpretation is less catchy than the story we might want to tell. Whether we're fitting models to reality or trying to fit reality to our models is worth thinking about. The latter defeats the point, though it is often more marketable.

At Oxford, my work focuses on modeling the co-distribution of Malaria and Schistosomiasis. This involves a lot of time thinking about generalized additive "smooth" models and analyzing satellite imagery in various geometric configurations. I'm part of the SchistoTrack group, named after the ongoing cohort study in Uganda. I am supervised by Goylette Chami and Christl Donnelly.

Previously, under the supervision of Frauke Kreuter in Munich, I worked on the rather unfashionable problem of simply asking good questions. Understanding that people would rather click boxes than type thoughtful responses often matters more than any sophisticated model.

This led to several engineering projects to modernize data collection:

  • OASIS, an open-source platform for AI-powered conversational interviews. Self-hosted, research-first infrastructure for voice and text-based surveys.
  • Automated Telephone Surveys with 60 Decibels (20,000+ interviews and counting, now scaling in emerging markets) — case study
  • Adaptive Interviewers with LMU Munich to turn static surveys into conversational agents.
  • AVA, AI vaccination assistant for patients with mild cognitive impairment. Registered RCT, funded by BMBF. [Trial registry]

I'm always happy to discuss research ideas and look forward to new collaborations.

Profile

If something here sparks your curiosity, I'd love to hear from you.

Publications

+

2026

Schistosoma mansoni infections are associated with hepatosplenic organometry within the context of repeated praziquantel treatment and co-endemic infections of malaria, hepatitis B, and HIV: a population-based study in rural Uganda Seggelke, K.*, Lang, M. M.*, Nabatte, B., Anguajibi, V., Ntegeka, B., Mugume, T., Mpooya, S., Kabatereine, N. B., Smith, A. D., Chami, G. F. (*equal contribution)
OASIS: Open Agentic Survey Interview System Lang, M. M. [Zenodo]

2025

Shared risk factors for malaria and schistosomiasis co-infection: a systematic review and meta-analysis Lang, M. M., Lyne, B., Donnelly, C. A., Chami, G. F.
Non-linear age dynamics of malaria infection and fine-scale environmental exposure in rural Uganda Lang, M. M., Tuhaise, V., Kafuko, P., Nakato, A., Mohamed, A., Nabatte, B., Kabatereine, N. B., Donnelly, C. A., Chami, G. F.
hexsmoothR: Hexagonal Grid Smoothing for Satellite Data Lang, M. M. Presented at IDDConf 2025
Clinical outcomes associated with schistosome infection and alcohol use: a systematic scoping review Lyne, B., Lang, M. M., Lewington, S., Chami, G. F.
AVA – Study protocol for an AI-supported vaccination assistant Sanftenberg, L., Bader, F., Bundschuh, T., Lang, M. M., et al. Poster at 19th Vaccine Congress 2025
AVA (AI-supported vaccination assistant) - Shared decision-making to improve vaccination rates Bader, F., Sanftenberg, L., Bundschuh, T., Lang, M. M., et al. 59th Congress for General Medicine 2025
Telephone Surveys Meet Conversational AI: Evaluating a LLM-Based Telephone Survey System at Scale Lang, M. M., Eskenazi, S. Accepted at AAPOR 2025 — Case study

2024

AI Conversational Interviewing: Transforming Surveys with LLMs as Adaptive Interviewers Wuttke, A., Aßenmacher, M., Klamm, C., Lang, M. M., et al. Accepted at AAPOR 2025 & NAACL
Pytector Lang, M. M. A Python package for detecting prompt injection.
Financial Times Chart Doctor Visual Vocabulary in German Lang, M. M., & Smith

2023

Time Series Analysis of Climatological and Hydrological Low Water Drivers in Bavaria - Climex II Hobelsberger, C., Kleinlein, L., Lang, M. M., et al. Accepted at IWSM Dortmund 2023

Talks & Presentations

+

2026

Malaria-Schistosoma mansoni co-infection in Ugandan fishing communities Infectious Disease and Epidemiology Unit Symposium, Oxford, UK
Telephone Surveys Meet Conversational AI TADA Initiative Spring Speaker Series, online

2025

Fine-Scale Environmental Risk Mapping and Non-Linear Age Dynamics of Malaria Infection in rural Ugandan Communities Infectious Disease Dynamics Conference (IDDConf), Ambleside, UK
Using AI Phone Agents to conduct impact research on a large scale ID Insight

2024

Transforming Surveys with AI Conversational Interviewing University of Zurich, Digital Society Initiative
Using Chatbots as Interviewers SurvAI-Day, University of Maryland
Featured: IASS Webinar 42: Leveraging AI for Survey Research by Frauke Kreuter

2023

Analysis of Climatological Drivers of Low-Flow Events in Hydrological Bavaria Turing Institute ECR Connect 2023, Queen Elizabeth II Centre, London
Goodbye, Endless Feedback Forms. Hello, SurveyGPT! OxAI Conference, 2023

Projects

+

Malaria-Schistosomiasis co-distribution

Modeling disease co-infections in rural Uganda using satellite imagery and spatial statistics. DPhil project.

SchistoTrack Group →

OASIS – Open Agentic Survey Interview System

Open-source platform for AI-powered conversational interviews. Self-hosted, research-first. Voice agents, text chat, structured protocols.

Website → Repo → Org →

AVA – AI Vaccination Assistant

Voice agent for patients over 60 with mild cognitive impairment. Lead developer. Registered RCT, BMBF-funded.

Study page → Trial registry →

AI Telephone Surveys

Automating telephone surveys with conversational AI for 60 Decibels. 20,000+ interviews, scaling in emerging markets.

Paper → Case study →

hexsmoothR

R package for hexagonal grid smoothing of satellite data.

Documentation →

Pytector

LLM prompt injection detection Python package.

GitHub →

More on GitHub

RAG-nificent, cuda-gis-smoothing, timeglobe, and other open source projects.

View all projects →

Awards & Funding

+

My research is graciously funded by Oxford Population Health.

Teaching & Writing

+

Contact

Address

Max Melchior Lang
Big Data Institute
Old Road Campus
University of Oxford
Oxford OX3 7LF, United Kingdom

Email & Identifiers

max.lang@stx.ox.ac.uk
ORCID: 0009-0004-6815-5321

Elsewhere

Legal

Privacy Policy

This website does not collect any personal data from its visitors. It is hosted on GitHub Pages, which may collect some technical information such as IP addresses, browser types, and access times as part of its standard operation. This information is not used by the website owner.

GitHub may collect technical information as described in their Privacy Statement.

This website does not use cookies or any form of tracking technology.

Impressum (Legal Notice)

Angaben gemäß § 5 TMG:

Max Melchior Lang
Big Data Institute
Old Road Campus, University of Oxford
Oxford OX3 7LF, United Kingdom

Kontakt:
E-Mail: max.lang@stx.ox.ac.uk

Verantwortlich für den Inhalt nach § 55 Abs. 2 RStV:
Max Melchior Lang
Big Data Institute
Old Road Campus, University of Oxford
Oxford OX3 7LF, United Kingdom

Haftungsausschluss (Disclaimer):

Haftung für Inhalte
Die Inhalte dieser Seiten wurden mit größter Sorgfalt erstellt. Für die Richtigkeit, Vollständigkeit und Aktualität der Inhalte kann ich jedoch keine Gewähr übernehmen.

Haftung für Links
Diese Webseite enthält Links zu externen Webseiten Dritter, auf deren Inhalte ich keinen Einfluss habe. Deshalb kann ich für diese fremden Inhalte auch keine Gewähr übernehmen. Für die Inhalte der verlinkten Seiten ist stets der jeweilige Anbieter oder Betreiber der Seiten verantwortlich.

Copyright Notice

© 2025 Max Melchior Lang. All rights reserved.

Disclaimer

The views and opinions expressed on this website are my own and do not necessarily reflect the official policy or position of any affiliated institution.