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PhD Student

Alexander Pfefferle

Postal address

Institut für Informatik
Albert-Ludwigs-Universität Freiburg
Sekretariat Hutter/Maschinelles Lernen
Georges-Köhler-Allee 074
79110 Freiburg, Germany

Office

Building 074, Room 00-014
https://alexanderpfefferle.com
pfeffera@cs.uni-freiburg.de
Publications
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I am a PhD student at the AutoML Freiburg Lab, supervised by Frank Hutter.
My current research is about Tabular Foundation Models and how to extend them to the textual modality.

I finished my Masters at the University of Freiburg in 2024, during which I successfully participated in multiple machine learning competitions:

I’ve worked on nanoTabPFN, a smaller and simpler implementation of TabPFNv2, as well as the TFM-Playground, which includes nanoTabPFN and is supposed to become a fully open source Playground for Tabular Foundation Models.

I’ve also worked on/supervised students on extending TFMs to text, making the pretraining of TFMs faster and evaluating priors for TFMs.

More recently I have started working on foundation model for creating tabular predictive task embeddings.

Teaching:

Publications

2026

Purucker, Lennart; Tschalzev, Andrej; Erickson, Nick; Blayer, Gioia; Holzmüller, David; Arazi, Alan; Pfefferle, Alexander; Tajjar, Mustafa; Varoquaux, Gaël; Hutter, Frank

Beyond IID: How General Are Tabular Foundation Models, Really? Proceedings Article

In: Preprint, 2026.

Öztürk, Salih Bora; Pfefferle, Alexander; Hutter, Frank

Speedrunning Tabular Foundation Model Pretraining Proceedings Article

In: 2nd ICML Workshop on Foundation Models for Structured Data, 2026.

Nayak, Kartik Nagaraj; Solpure, Nitishkumar; Mitra, Niladri; Zehle, Tom; Pfefferle, Alexander; Swelam, Omar; Hutter, Frank

Towards Benchmarking Agentic Data Scientists Proceedings Article

In: AutoAI Meets Foundation Models, 2026.

Türkmen, Zeynep; Kaya, Kürşat; Pfefferle, Alexander; Hutter, Frank

Towards Evaluating Data Priors for Tabular Foundation Models Proceedings Article

In: 2nd ICML Workshop on Foundation Models for Structured Data, 2026.

Tajjar, Mustafa; Pfefferle, Alexander; Purucker, Lennart; Hutter, Frank

Towards Pretraining Text Encoders for TabPFN Proceedings Article

In: 2nd ICML Workshop on Foundation Models for Structured Data, 2026.

2025

Pfefferle, Alexander; Hog, Johannes; Purucker, Lennart; Hutter, Frank

nanoTabPFN: A Lightweight and Educational Reimplementation of TabPFN Proceedings Article

In: EurIPS 2025 Workshop: AI for Tabular Data, 2025.

Pfefferle, Alexander; Purucker, Lennart; Hutter, Frank

DAFT: Data-Aware Fine-Tuning of Foundation Models for Efficient and Effective Medical Image Segmentation Proceedings Article

In: Ma, Jun; Zhou, Yuyin; Wang, Bo (Ed.): Medical Image Segmentation Foundation Models. CVPR 2024 Challenge: Segment Anything in Medical Images on Laptop, pp. 15–38, Springer Nature Switzerland, Cham, 2025, ISBN: 978-3-031-81854-7.

Ndir, Tidiane Camaret; Pfefferle, Alexander; Schirrmeister, Robin Tibor

Dynamic Prompt Generation for Interactive 3D Medical Image Segmentation Proceedings Article

In: Submitted to CVPR 2025: Foundation Models for 3D Biomedical Image Segmentation, 2025, (under review).

2024

Ma, Jun; Li, Feifei; Kim, Sumin; Asakereh, Reza; Le, Bao-Hiep; Nguyen-Vu, Dang-Khoa; Pfefferle, Alexander; Wei, Muxin; Gao, Ruochen; Lyu, Donghang; Yang, Songxiao; Purucker, Lennart; Marinov, Zdravko; Staring, Marius; Lu, Haisheng; Dao, Thuy Thanh; Ye, Xincheng; Li, Zhi; Brugnara, Gianluca; Vollmuth, Philipp; Foltyn-Dumitru, Martha; Cho, Jaeyoung; Mahmutoglu, Mustafa Ahmed; Bendszus, Martin; Pflüger, Irada; Rastogi, Aditya; Ni, Dong; Yang, Xin; Zhou, Guang-Quan; Wang, Kaini; Heller, Nicholas; Papanikolopoulos, Nikolaos; Weight, Christopher; Tong, Yubing; Udupa, Jayaram K; Patrick, Cahill J.; Wang, Yaqi; Zhang, Yifan; Contijoch, Francisco; McVeigh, Elliot; Ye, Xin; He, Shucheng; Haase, Robert; Pinetz, Thomas; Radbruch, Alexander; Krause, Inga; Kobler, Erich; He, Jian; Tang, Yucheng; Yang, Haichun; Huo, Yuankai; Luo, Gongning; Kushibar, Kaisar; Amankulov, Jandos; Toleshbayev, Dias; Mukhamejan, Amangeldi; Egger, Jan; Pepe, Antonio; Gsaxner, Christina; Luijten, Gijs; Fujita, Shohei; Kikuchi, Tomohiro; Wiestler, Benedikt; Kirschke, Jan S.; Rosa, Ezequiel; Bolelli, Federico; Lumetti, Luca; Grana, Costantino; Xie, Kunpeng; Wu, Guomin; Puladi, Behrus; Martín-Isla, Carlos; Lekadir, Karim; Campello, Victor M.; Shao, Wei; Brisbane, Wayne; Jiang, Hongxu; Wei, Hao; Yuan, Wu; Li, Shuangle; Zhou, Yuyin; Wang, Bo

Efficient MedSAMs: Segment Anything in Medical Images on Laptop Proceedings

2024.

2022

Roberts, Nicholas; Guo, Samuel; Xu, Cong; Talwalkar, Ameet; Lander, David; Tao, Lvfang; Cai, Linhang; Niu, Shuaicheng; Heng, Jianyu; Qin, Hongyang; Deng, Minwen; Hog, Johannes; Pfefferle, Alexander; Shivakumar, Sushil Ammanaghatta; Krishnakumar, Arjun; Wang, Yubo; Sukthanker, Rhea; Hutter, Frank; Hasanaj, Euxhen; Le, Tien-Dung; Khodak, Mikhail; Nevmyvaka, Yuriy; Rasul, Kashif; Sala, Frederic; Schneider, Anderson; Shen, Junhong; Sparks, Evan

AutoML Decathlon: Diverse Tasks, Modern Methods, and Efficiency at Scale Proceedings Article

In: Ciccone, Marco; Stolovitzky, Gustavo; Albrecht, Jacob (Ed.): Proceedings of the NeurIPS 2022 Competitions Track, pp. 151–170, PMLR, 2022.