AI, Computing and Society

Research on Artificial Intelligence, Computing and Society at MPI-SWS tackles the pressing scientific, engineering and societal challenges posed by an increasingly AI-driven world. Recent research includes AI-based tutoring systems, computational models of language processing in the brain that also inform improvements to large language models, methods for enhancing the transparency and reliability of modern AI systems, frameworks that support compliance of AI systems with EU regulations such as the AI Act and the Digital Services Act, and automated decision-support systems in high-stakes domains.

News

Several recent achievements by current institute members and alumni

June 2026

MPI-SWS members and alumni have received a number of different awards in the first quarter of 2026.

MPI-SWS researchers receive a Best Paper Award at SIGCSE TS 2026

June 2026

MPI-SWS researchers have received the 2026 SIGCSE TS best paper award for their paper "Closing the Loop: An Instructor-in-the-Loop AI Assistance System for Supporting Student Help-Seeking in Programming Education."

Interview with Krishna Gummadi on the agency of artificial intelligence, AI agents, and potential societal impacts

May 2026

In this interview, MPI-SWS director Krishna Gummadi discusses the benefits AI agents offer people and the risks they pose to society.

MPI researcher receives Outstanding Paper Award at ICLR 2026

April 2026

MPI-SWS Max Planck Fellow Anthony W. Lin has received one of only two Outstanding Paper Awards at ICLR 2026, for his paper "Transformers are Inherently Succinct."

"Teaming for Excellence" Horizon Proposal funded with INESC-ID and DFKI Kaiserslautern

April 2026

MPI-SWS researchers (together with DFKI in Kaiserslautern and researchers at INESC-ID) have been funded under the competitive Horizon Europe "Teaming for Excellence" programme.

All News

Recent projects

Recent software

Disease control

Stochastic Optimal Control of Epidemic Processes in Networks

Fair classification

This repository provides a logistic regression implementation in python for the fair classification mechanisms introduced in Zafar et al., 2017

HDHP

Hierarchical Dirichlet-Hawkes process: generative model and inference algorithm

Memorize

An Algorithm to Enhance Human Learning via Spaced Repetition Optimization

NeVAE

A Deep Generative Model for Molecular Graphs

RedQueen

An Online Algorithm for Smart Broadcasting on Social Networks

TPP-RL

Deep Reinforcement Learning of Marked Temporal Point Processes

Papers

Closing the Loop: An Instructor-in-the-Loop AI Assistance System for Supporting Student Help-Seeking in Programming Education.

Tung Phung, Heeryung Choi, Mengyan Wu, Christopher Brooks, Sumit Gulwani, Adish Singla.
SIGCSE 2026.

Text-Diffusion Red-Teaming of Large Language Models: Unveiling Harmful Behaviors with Proximity Constraints.

Jonathan Nöther, Adish Singla, Goran Radanovic.
AAAI 2025.

HALoGEN: Fantastic LLM Hallucinations and Where to Find Them.

Abhilasha Ravichander, Shrusti Ghela, David Wadden, Yejin Choi.
ACL 2025.

Program Synthesis Benchmark for Visual Programming in XLogoOnline Environment.

Chao Wen, Jacqueline Staub, Adish Singla.
ACL 2025.

Plan More, Debug Less: Applying Metacognitive Theory to AI-Assisted Programming Education.

Tung Phung, Heeryung Choi, Mengyan Wu, Adish Singla, Christopher Brooks.
AIED 2025.

All papers

People

Faculty

Peter Druschel

Manuel Gomez Rodriguez

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