29.5% Efficient Perovskite-Silicon Tandem Solar Cell with Enhanced Stability
Lars Eriksson, Nina Hoffmann, Christophe Ballif
Science2024
Journal Article
178I lead the Sustainable Energy Systems Lab at ETH Zurich, where our team of 15 researchers works on the science and engineering of tomorrow's energy infrastructure.
Our research spans three areas: perovskite-silicon tandem solar cells, solid-state battery electrolytes, and AI-driven optimization of power grids. We are particularly interested in translating laboratory breakthroughs into scalable, commercially viable technologies.
We collaborate with industry partners including ABB, Siemens Energy, and Meyer Burger. I hold an ERC Consolidator Grant and was named to the MIT Technology Review Innovators Under 35 Europe list in 2021.
PhD in Photovoltaics
KTH Royal Institute of Technology, Applied Physics
2012 - 2016
Stockholm, Sweden
Thesis: Nanostructured Interfaces for High-Efficiency Solar Energy Conversion
Research Group Leader in Computer Science
ETH Zurich, Mechanical and Process Engineering
2019 - Present
Zurich, Switzerland
Postdoctoral Researcher
EPFL, Materials Science
2016 - 2019
Lausanne, Switzerland
Lars Eriksson, Nina Hoffmann, Christophe Ballif
Nina Hoffmann, Lars Eriksson
Lars Eriksson, Marco Rossi, Sophia Weber
Lars Eriksson, Nina Hoffmann
Foundations of Faithful Reasoning in Language Models
Developing training methods and evaluation frameworks for improving logical consistency in large language models.
Human-Aligned NLP Systems
Multi-institution project on building NLP systems that align with human values and intentions.
MIT Technology Review Innovators Under 35
Recognized for pioneering work on faithful reasoning in AI systems.
Best Paper Award
NSF CAREER Award
Early-career faculty award for research on interpretable language models.
Graduate seminar covering modern approaches to NLP including large language models, in-context learning, and alignment techniques.
Introduction to machine learning concepts, supervised and unsupervised methods, with a focus on deep learning fundamentals.
Perovskite thin film deposition and characterization
AI-based grid optimization
Solid-state battery electrolyte interfaces
Perovskite-silicon integration
Battery cycling and lifetime modeling
Postdoc position on our DARPA-funded project on human-aligned NLP systems.
Requirements
PhD in NLP, ML, or related field. Publications in top venues.
Excited to share that our paper 'Scaling Faithful Reasoning in Large Language Models' has been accepted as an oral presentation at NeurIPS 2024!
Read moreI am recruiting 2 PhD students to start Fall 2025. Research areas: LLM reasoning, interpretability, and alignment. Please apply through the MIT EECS admissions portal.
Read moreMIT Technology Review
The Researchers Making AI Think More Clearly
Feature article on our group's work on faithful reasoning in language models.
Lex Fridman Podcast
AI Alignment: Where Are We Now?
Conversation about the current state of AI alignment research and practical approaches.
Department of Mechanical and Process Engineering
ETH Zurich