If you want to get a better picture of how I think, my posts on opinions I changed (part I, part II, part III) or on Effective Altruism are a good start. You can leave anonymous feedback here.
Marius Hobbhahn
LinkedIn
Github
Twitter
Google Scholar
Research Interests
Education
International Max-Planck Research School Tübingen, Germany
PhD with Philipp Hennig, 2020-2023 (currently writing thesis)
Topic: Making Bayesian ML fast and scalable
University of Tübingen, Germany
M.Sc., Machine Learning, 2018-2020
Grade (1.5)
Member of the German scholarship foundation (Studienstiftung) since 2017
University of Tübingen, Germany
B.Sc., Computer Science, 2016-2019
Grade: 1.7 (3.3 GPA equivalent)
University of Tübingen, Germany
B.Sc., Cognitive Science, 2015-2018
Grade: 1.8 (3.2 GPA equivalent)
Willstätter Gymnasium Nürnberg, Germany
Abitur, 2007 - 2015
Grade: 1.4 (3.6 GPA equivalent)
Miscellaneous
AI safety/alignment
- Received funding for independent research on AI safety from the Long-Term Future Fund (2022)
- Participant in the AI safety camp 2022 (supervised by Beth Barnes)
- Contributer to the ML progress research group (now Epoch)
- Participant in the 2022 AGI fundamentals reading group
- Participant in the 2022 s-risks intro fellowship by CLR
- Paid reviewer for the OpenPhil world view investigations team
- Emergent Ventures grantee for "exploring the role of Bayesian ML for AI safety"
- Won the fourth prize at the Metaculus AI progress forecasting tournament
- Founded AI safety mentors and mentees
- Speaker on AI safety at EAGx Berlin 2022 and X-risk workshop 2022
- SERI MATS scholar (winter 2022 cohort)
- Mentor of 7 AI safety students for SPAR by UC Berkeley
Effective Altruism
- Co-founded the Tübingen EA chapter in 2016 (still co-organizing it)
- Co-founded the Tübingen AI safety reading group in 2020 (currently inactive)
- participated in 10+ EAGs, EAGxs and other EA conferences
- Posts on the EA Forum and LessWrong
University Debating
- Broke at 35+ tournaments, were in the top 10 speakers 20+ times and won 10+ of them.
- My most prestigious speaker achievements include: 3x breaking ESL at EUDC, Winning Tilbury 2019 and Doxbridge 2020 (Oxford final), Winning 2 Campus Debatten and the Southern German Championship, breaking as 3rd (2018), 2nd (2019) and 1st (2020) team at the German National Championships (DDM) and being best speaker and grand finalist at the DDM 2020
- Broke at 20+ tournaments as adjudicator and chaired 5+ finals. I chief-adjudicated 15+ tournaments.
- Organized 5+ tournaments and was (vice-)president of the debating club for two years.
Academia
- Participated at multiple ML Summer Schools and conferences including: PAISS2019, ICML2020, GPSS2020, ESANN2020, UAI2022
- Organized an ML master overview for 9 European Universities
- Lead-organizer of the ELLIS doctoral symposium in 2021
- Reviewer for ICML22 and NeurIPS22
Selected Publications
Compute Trends Across Three Eras of Machine Learning
Jaime Sevilla, Lennart Heim, Anson Ho, Tamay Besiroglu, Marius Hobbhahn, Pablo Villalobos (2022). IJCNN.
[arxiv]
[Our World in Data]
Laplace Matching for fast Approximate Inference in Generalized Linear Models
Hobbhahn, Marius and Hennig, Philipp. (2021).
[arxiv]
[code]
[blog]
Fast Predictive Uncertainty for Classification with Bayesian Deep Networks
Hobbhahn, Marius; Kristiadi, Agustinus and Hennig, Philipp. UAI 2022.
[arxiv]
[code]
[Blog post]
Other Publications
Reflection Mechanisms as an Alignment Target: A Survey
Hobbhahn, Marius, Eric Landgrebe and Elizabeth Barnes. NeurIPS ML Safety Workshop. 2022.
[paper]
Investigating Causal Understanding in LLMs
Hobbhahn, Marius, Tom Lieberum and David Seiler. NeurIPS Workshop on Causality for Real-world Impact. 2022.
[paper]
What are the Red Flags for Neural Network Suffering?
Hobbhahn, Marius and Jan Kirchner. Seeds of Science. 2022.
[paper]
Should Altruistic benchmarks be the norm in Machine Learning?
Hobbhahn, Marius; ICML2021 Workshop for Socially Responsible Machine Learning
[paper]
Sequence Classification using Ensembles of Recurrent Generative Expert Modules
Hobbhahn, Marius; Butz, Martin; Fabi, Sarah and Otte, Sebastian. ESANN (2020).
[ESANN2020 proceedings]
[code]
CS Experience
ML related
Successfully completed over 20 lectures related to ML, AI, NNs, RL, Stats, etc. at the University of Tübingen
Programming Experience
Programming Languages: Python (since 2016) > R > Java, Julia, JavaScript, C++, SQL
ML related: PyTorch (since 2018) > JAX > Tensorflow, Keras, Cuda
Teaching
Math Summer Course (2 weeks) 2016, 2017
Teaching assistant for Probablistic ML (2020, 2021) and Data Literacy (2021, 2022)
Supervised 3 Bachelor's theses and 1 Master thesis
Work Experience
June 2022 - now: research fellow for Epoch
Language
English (C2 = IELTS 8.0)
French (B2)
German (native)