Driving Innovation Forward: Carlos Härtel on Deep Tech Solutions and Market Adoption

07/29/24 • 34 min

In this episode we host Carlos Härtel, an expert in innovation and strategy within the applied sciences. Carlos holds a Habilitation in Mechanical Engineering from ETH Zürich and a PhD in Chemical Engineering from the Technical University of Munich. Currently, he is a Venture Partner at Spacewalk VC, investing in deep tech startups, and a Senior Advisor at Carbon Removal Partners, focusing on carbon withdrawal technologies. He also chairs the Board at Science|Business, fostering collaboration between industry, research, and policy. Previously, Carlos served as CTO at Climeworks, a leader in carbon dioxide air capture technology, and held significant roles at General Electric, including CTO and Chief Innovation Officer for Europe. Additionally, he was a Non-Executive Director at Futurice, a digital consultancy, and Chairman at EUROGIA2020, promoting low-carbon energy technologies.

Carlos joins us in our Ecosystem category. We dive into CO2 capturing technologies and their role in climate innovation. Key takeaways include the cost-effectiveness of capturing CO2 at industrial sources, the advanced direct air capture methods Carlos developed at Climeworks, and the challenges of ocean-based CO2 capture. Drawing from his experience, Carlos furthermore discusses the critical factors for advancing hard technical innovations in climate and deep tech. He highlights how market demand drives innovation, addresses the chicken-and-egg dilemma of reliability versus adoption, and emphasizes the role of government policies in creating market demand. His insights reveal what’s needed to overcome barriers and implement complex solutions effectively.

Previous Episode

AI Meets Protein Science: Dr. Stanislav Mazurenko on the Impact of Machine Learning in Protein Engineering

In this episode, we are excited to host Dr. Stanislav Mazurenko, a leading expert in protein engineering and artificial intelligence. With a Ph.D. in applied mathematics and cybernetics from Lomonosov Moscow State University and extensive postdoctoral research at Loschmidt Laboratories, Stanislav now leads research at RECETOX. We delve into molecular dynamics simulations, statistical models, and the application of machine learning to protein design. Key takeaways include the essential role of proteins, the complexities of simulating their dynamics, and the optimization benefits provided by machine learning. Stanislav highlights the synergy between automation and machine learning, and underscores the importance of learning from mistakes in scientific research.

Next Episode

Productizing Research Code: Martin Steinegger on how to create useful and reusable Software

Dr. Martin Steinegger is an expert in computational biology and bioinformatics, specializing in large-scale sequence data analysis. He earned his Ph.D. from the Technical University of Munich in collaboration with the Max Planck Institute for Biophysical Chemistry, focusing on methods to cluster and assemble metagenomic sequencing data. Currently an Associate Professor at Seoul National University, his research group develops novel computational methods to analyze microbial communities using machine learning and big data algorithms. Martin is the creator of MMseqs, a highly efficient software suite for protein sequence searches and co-author of AlphaFold2. His work in pathogen detection and metagenomics has made a significant impact on bioinformatics, with a strong commitment to open science and open-source tools.

Together with Martin we discuss the importance of productizing research code and the key factors for creating reusable software. He emphasizes the need for user-friendly interfaces, intuitive outputs, and software that doesn't crash. Martin talks about his background in software engineering and how it influenced his approach to developing tools in bioinformatics. Hence, he gives an overview about all the different tools he has developed over the years and for what they are used. Furthermore, he explains the significance of protein structure in understanding protein evolution and function, and highlights the role of his tools MMSeqs and AlphaFold in protein sequence and structure analysis. Martin shares his personal journey from starting in a lower-level school to pursuing higher education and research, driven by his passion for computers and learning.

00:00 - 01:32 Introduction

01:32 - 06:25 Productization of research code

06:25 - 08:20 Testing of software

08:20 - 12:28 Overview about the tools Martin has developed

12:28 - 15:40 The relevance of protein structure

15:40 - 18:00 Structural vs. Statistical approaches

18:00 - 21:00 AlphaFold collaboration and insights

21:00 - 31:10 Martin's personal journey and motivation

31:10 - 33:41 Machines and Molecules theme - 3rd M-Word

Season 2, episode 5 - Category Knowledge