Archived News ⏵

• 09/2026: Ye-Chao Liu started an Associate Researcher position at Hainan University. Congratulations!
• 08/2026: Our paper “Convex mixed-integer optimization with Frank-Wolfe methods” (with Deborah Hendrych, Hannah Troppens, Mathieu Besançon, and Sebastian Pokutta) won the MPC “Outstanding Paper of the Year” Award 2025.
• 07/2026: Kirill Khoruzhii won the Distinguished Student Author Award at ISSAC 2026 for “Faster Algorithms for Structured Matrix Multiplication via Flip Graph Search” (with Patrick Gelß and Sebastian Pokutta).
• 05/2026: Together with G. K. Tjusila, A. Hoen, N.-C. Kempke, G. Mexi, T. Berthold, A. Gleixner, and T. Koch, we won the Land-Doing MIP Computational Competition 2026.
• 04/2026: Six papers papers accepted this month at ICML (including one spotlight!), ISSAC, and IJCAI. Congratulations everyone!
• 01/2026: Kartikey Sharma accepted an Assistant Professor position in the Mechanical Engineering Department at IIT Delhi. Congratulations!
• 10/2025: Our book on Conditional Gradients and Frank-Wolfe methods has been published in the MOS-SIAM Series on Optimization.
• Fall 2025: Sai Ganesh Nagarajan started a Tenure Track Assistant Professor Position at the Department of Mathematics and Computer Science (IMADA), Southern Denmark University, Odense, Denmark. Congratulations!
• Summer 2025: Sébastien Designolle started an Inria Starting Faculty Position in the QINFO group based at the École Normale Supérieure in Lyon. Congratulations!
• 06/2025: Together with Gioni Mexi, Deborah Hendrych, Sébastien Designolle, and Mathieu Besançon, we won the Land-Doing MIP Computational Competition 2025.
• 05/2025: Cluster of Excellence MATH+ got extended for another 7 years.
• 03/2025: Received Science Prize of the Association for Pediatric Orthopedics (VKO) for “Feature Engineering for the Prediction of Scoliosis in 5q-Spinal Muscular Atrophy”, T.-L. Vu-Han (lead author), V. Sunkara, R. Bermudez-Schettino, J. Schwechten, R. Runge, C. Perka, T. Winkler, S. Pokutta, C. Weiß, M. Pumberger.
• 10/2024: Elected Chair of the Cluster of Excellence MATH+ together with Claudia Schillings and Andrea Walther.
• Fall 2024: David Martínez-Rubio started a faculty position at Carlos III University of Madrid. Congratulations!
• Fall 2024: Zev Woodstock started a faculty position at James Madison University. Congratulations!
• 01/2024: The Zuse Institute Berlin (ZIB) is celebrating its 40th anniversary in 2024.
• Fall 2023: Mathieu Besançon started a faculty position at INRIA Grenoble. Congratulations!
• 05/2023: Received Gödel Prize together with Samuel Fiorini, Serge Massar, Hans Raj Tiwary, Ronald de Wolf, and Thomas Rothvoss.
• 05/2023: We are organizing the fifth conference on “Discrete Optimization and Machine Learning” in Aug 2023 at GRIPS in Tokyo.
• 02/2023: We are organizing a Thematic Einstein Semester on “Mathematical Optimization for Machine Learning” within the Math+ Cluster of Excellence. The semester consists of various activities throughout the semester with three workshops, a conference, and a summer school as some of the highlights. We are looking forward to seeing you in Berlin!
• Fall 2022: Francisco Criado started a faculty position at CUNEF University Madrid. Congratulations!
• 11/2022: We finished our monograph on Frank-Wolfe methods a.k.a. Conditional Gradients. arxiv webpage blog
• 06/2022: Symposium on Theory of Computing (STOC) Test of Time award (10 years) for “Linear vs. Semidefinite Extended Formulations: Exponential Separation and Strong Lower Bounds”, S. Fiorini, S. Massar, S. Pokutta, H.R. Tiwary, R. de Wolf from 2012.
• 06/2022: 6th RIKEN-IMI-ISM-ZIB-MODAL-NHR Workshop on Advances in Classical and Quantum Algorithms for Optimization and Machine Learning in Japan. link
• 06/2022: New ZIB videos available. youtube channel. (german only)
• 06/2022: Interview on using AI to combat and mitigate climate change (German) article magazine
• 10/2021: Math+ Cluster presentation at the Humboldt Forum “Mit Mathematik die Welt verbessern?” (German) video
• 10/2021: Our group received a Google Research Award to explore the learning of heuristic schedules in MIP solvers.
• 10/2021: One project funded by the Math+ Research Center.
• 11/2020: Our group received a Google Research Award to support our work on Integer Programming solvers.
• 10/2020: Four projects funded by the Math+ Research Center.
• 10/2020: HTW Berlin enters cooperation with Zuse Institute Berlin. ZIB Press Release, HTW Press Release (German)
• 05/2020: Our Special Priority Program (SPP) proposal ‘Theoretical Foundations of Deep Learning’ was funded by DFG. With an overall budget of EUR 8.5m, this program sets out to significantly boost our fundamental understanding of Deep Learning. The coordination team is Gitta Kutyniok (speaker), Martin Burger, Matthias Hein, Sebastian Pokutta, and Ingo Steinwart. DFG Press Release (German), TUB Press Release (German) SPP Homepage
• 04/2020: Research Campus MODAL enters second funding phase
• 03/2020: Preliminary COVID19 forecast model / version for Berlin
• 03/2020: The third conference on “Discrete Optimization and Machine Learning” is cancelled due to COVID-19.
• 09/2019: We are organizing the third conference on “Discrete Optimization and Machine Learning” in May 2020 at Kyoto University in Kyoto.
• 09/2019: TU Berlin and the Berlin School of Mathematics, with the support of MATH+, are organizing the “Combinatorial Optimization at Work (Co@Work) 2020” summer school on September 14 - 26, 2020 at ZIB in Berlin. Application deadline is: June 14, 2020. Intended audience: master/PhD students, Post-docs.
• 09/2019: Sanjeena Dang, Antoine Deza, Swati Gupta, Paul McNicholas, Masashi Sugiyama, and I are organizing a focus program on Data Science and Optimization in November 2019 at the Fields Institute in Toronto.
• 12/2018: Antoine Deza, Takanori Maehara, and I are editing a special issue on “Machine Learning and Discrete Optimization” in Discrete Optimization. Deadline for submission is May, 30th 2019.
• 04/2019: Shipra Agrawal, Adam Elmachtoub, and I are organizing a track on Industrial Engineering and Operations Research at “Machine Learning in Science and Engineering (MLSE)” in June 2019 at the Georgia Institute of Technology in Atlanta.
• 02/2019: Lew Roberts and I are organizing a “Conference on Emerging and Converging Technologies: The Future World” in June 2019 at the Gordon Institute of Business Science in Johannesburg, South Africa.
• 12/2018: We are organizing the second workshop on “Discrete Optimization and Machine Learning” in July 2019 at the Center for Advanced Intelligence in Tokyo.
• 08/2018: We released our Blended Conditional Gradients code on github.
• Summer 2018: We are organizing a workshop on “Discrete Optimization and Machine Learning” in July 2018 at the Center for Advanced Intelligence in Tokyo.
• Spring 2018: We are organizing the “1st Transatlantic-Transpacific Workshop on Machine Learning and Discrete Optimization” in March 2018.
• Spring 2018: Teaching a special topics course on Machine Learning and Discrete Decisions and a VIP project (with M. Bloch) on Machine Learning in Wireless Communication.
• 05/2017: Georgia Tech has now a Ph.D. Program in Machine Learning.
• 12/2016: Passed the first hurdle of the DARPA SC2 challenge [project page].
• 06/2016: Official launch of Machine Learning @ GT Interdisciplinary Research Center.
• 03/2016: David M. McKenney Family Early Career Professor appointment
• 07/2015: Saving Lives @ Birth 2015 Seed Grant Award Nominee “Low-cost Technology to Assess the Risk of Obstructed Labor in Ethiopia” together with B. Dixon and R. Gleason
• 04/2015: ISYE/George Family Foundation Seed Grant in Predictive Health “Non-invasive Pregnancy Diagnostics for Predicting Obstructed Labor” together with B. Dixon and R. Gleason
• 01/2015: CAREER Award, National Science Foundation, 2015

Archived Talks ⏵

• 09/2026: (technical) “Frank-Wolfe Beyond Polytopes: Convergence on Non-Polyhedral Sets”. Plenary at OR2026 - Annual Meeting of the German Operations Research Society (GOR) (Passau, Germany). [slides]
• 07/2026: (technical) “Frank-Wolfe on Curved Domains: Unconditional o(1/t) Convergence and Tight Lower Bounds”. Talk at 65th School of Engineering Special Lecture (Tokyo, Japan). [slides]
• 07/2026: (technical) “The Agentic Researcher: Accelerating Optimization and Learning Research with AI”. Talk at AI4Science seminar (Online (Zoom)). [slides]
• 07/2026: (technical) “The Agentic Researcher: Accelerating Optimization and Learning Research with AI”. Talk at HORIZONS 2026: Learning and Optimization for a Sustainable Future (Hanoi, Vietnam). [slides]
• 06/2026: (technical) “When Algorithms Learn: Discrete Optimization Meets Machine Learning”. Talk at Oberseminar Angewandte Mathematik (Magdeburg, Germany).
• 06/2026: (technical) “How Machines Explore, Conjecture, and Discover Mathematics”. Talk at Mathematics Colloquium / Structure, Methods, and Theory Center (Jena, Germany). [slides]
• 06/2026: (general) “The Cargo Cult Meets Large Language Models: Demystifying AI Sentiments?”. Talk at Lange Nacht der Wissenschaften (Berlin, Germany).
• 06/2026: (technical) “Efficient Quadratic Corrections for Frank-Wolfe Algorithms”. Talk at SIAM Conference on Optimization (OP26) (Edinburgh, Scotland). [slides]
• 05/2026: (technical) “When Algorithms Learn: Discrete Optimization Meets Machine Learning”. Talk at TRR 154 Abschlusstagung — Mathematical Modelling, Simulation and Optimization (Gas Networks) (Nürnberg, Germany). [slides]
• 05/2026: (technical) “When Algorithms Learn: Discrete Optimization Meets Machine Learning”. Plenary at ISCO 2026 - 9th International Symposium on Combinatorial Optimization (Kuşadası, Turkey). [slides]
• 05/2026: (technical) “How Machines Explore, Conjecture, and Discover Mathematics: Agentic AI in Mathematics”. Talk at 5. Rundgespräch Angewandte Mathematik (Online (Zoom)). [slides]
• 03/2026: (technical) “Efficient Quadratic Corrections for Frank-Wolfe Algorithms”. Talk at MLaftermath Workshop (Berlin, Germany). [slides]
• 02/2026: (technical) “How Machines Explore, Conjecture, and Discover Mathematics”. Talk at Munich AI Lecture (Munich, Germany). [slides]
• 02/2026: (technical) “Neural Discovery in Mathematics: Do Machines Dream of Colored Planes?”. Talk at HKBU Computer Science Seminar Series (Hong Kong). [slides]
• 02/2026: (technical) “Algorithmic and geometric aspects of alternating linear minimization”. Talk at PolyU Applied Mathematics Seminar Series (Hong Kong). [slides]
• 01/2026: (technical) “How Machines Explore, Conjecture, and Discover Mathematics”. Talk at NUS CQF Seminar (Singapore). [slides]
• 12/2025: (general) “Wie wird KI gemacht und wo stehen wir heute? (in German)”. Keynote at Wintertagung 2025 der Berlin-Brandenburgische Augenärztliche Gesellschaft (Berlin, Germany).
• 12/2025: (technical) “A gentle introduction to Frank-Wolfe Algorithms”. Talk at Humboldt-Universität zu Berlin Optimization Seminar Series (Berlin, Germany).
• 11/2025: (general) “Datenbasierte Schulentwicklung, Bildung, und KI (in German)”. Keynote at Fachtag: KI + Schule (Berlin, Germany).
• 09/2025: (technical) “Splitting Algorithms via Linear Optimization Oracles”. Talk at Discrete Optimization. A conference in honour of Robert Weismantel (Zurich, Switzerland). [slides]
• 06/2025: (technical) “Constrained Optimization via Frank-Wolfe Algorithms”. Plenary at 22nd Conference on Advances in Continuous Optimization (EUROPT) (Southampton, UK). [slides]
• 06/2025: (general) “Cargo-Kult trifft auf große Sprachmodelle: Entmystifizierung von KI? (in German)”. Talk at Lange Nacht der Wissenschaften (Berlin, Germany).
• 06/2025: (general) “From Abstract Math to Applied AI”. Keynote at New Mathematics for AI Innovation (Berlin, Germany).
• 05/2025: (technical) “The Pivoting Framework: Frank-Wolfe Algorithms with Active Set Size Control”. Talk at AISTATS 2025 (Phuket, Thailand). [slides]
• 03/2025: (technical) “The colorful world of Optimization”. Plenary at VIASM Spring School and Workshop on Variational Analysis and Optimization 2025 (Hanoi, Vietnam). [slides]
• 12/2024: (technical) “Exploring Mixed-Integer Convex Optimization with Conditional Gradients: Foundations and Applications”. Talk at MIP International Workshop (Mumbai, India). [slides]
• 12/2024: (technical) “AI x Algorithms x Applications”. Talk at NUS School of Computing Seminar (Singapore).
• 11/2024: (technical) “Extending the Continuum of Six-Colorings”. Talk at MFO Program: Combinatorial Optimization (Oberwolfach, Germany). [slides]
• 07/2024: (technical) “German <-> Japanese Supercomputing - a success story”. Keynote at 16th JHPCN symposium (Tokyo, Japan). [slides]
• 07/2024: (technical) “Extending the Continuum of Six-Colorings”. Talk at Conference on Discrete Optimization and Machine Learning (Tokyo, Japan). [slides]
• 06/2024: (general) “Cargo-Kult trifft auf große Sprachmodelle: Entmystifizierung von KI? (in German)”. Talk at Lange Nacht der Wissenschaften (Berlin, Germany).
• 03/2024: (general) “The Cargo Cult Meets Large Language Models: Demystifying AI Sentiments?”. Talk at Hong Kong Analytics Community Meeting (Hong Kong, China).
• 03/2024: (technical) “Alternating Linear Minimization: Revisiting von Neumann’s alternating projections”. Talk at CUHK-Shenzhen Seminar (Shenzhen, China). [slides]
• 03/2024: (technical) “Conditional Gradients in Machine Learning”. Plenary at International Workshop on Image Processing and Machine Learning (Beijing, China). [slides]
• 02/2024: (technical) “Conditional Gradients in Machine Learning”. Talk at NUS Math Seminar (Singapore). [slides]
• 11/2023: (technical) “Conditional Gradients in Machine Learning”. Keynote at Workshop on Geometry and Machine Learning (Leipzig, Germany). [slides]
• 09/2023: (technical) “The approximate Carathéodory problem and an application to quantum mechanics”. Plenary at 7th Workshop on Future Algorithms and Applications (Berlin, Germany).
• 08/2023: (technical) “Alternating Linear Minimization: Revisiting von Neumann’s alternating projections”. Talk at ICIAM 2023 (Tokyo, Japan). [slides]
• 08/2023: (technical) “Improved local models and new Bell inequalities via Frank-Wolfe algorithms”. Talk at Conference on Discrete Optimization and Machine Learning (Tokyo, Japan). [slides]
• 07/2023: (technical) “Alternating Linear Minimization: Revisiting von Neumann’s alternating projections”. Talk at Jon-Shmuel Halfway to Twelfty (Paris, France). [slides]
• 06/2023: (general) “Möglichkeiten und Grenzen künstlicher Intelligenz (in German)”. Talk at Lange Nacht der Wissenschaften (Berlin, Germany).
• 05/2023: (technical) “Alternating Linear Minimization: Revisiting von Neumann’s alternating projections”. Talk at University of Magdeburg MathCoRe Lecture (Magdeburg, Germany). [slides]
• 04/2023: (technical) “Conditional Gradients in Machine Learning”. Talk at Yale Statistics and Data Science Seminar Series (New Haven, CT). [slides]
• 03/2023: (technical) “Alternating Linear Minimization: Revisiting von Neumann’s alternating projections”. Talk at ICERM Workshop: Combinatorics and Optimization (Providence, RI). [slides] [video]
• 03/2023: (technical) “Structured ML Training via Conditional Gradients”. Talk at Columbia IEOR Seminar Series (New York, NY). [slides]
• 03/2023: (technical) “Conditional Gradients – an overview”. Keynote at 2nd Vienna Workshop on Computational Optimization (Vienna, Austria). [slides]
• 03/2023: (technical) “Alternating Linear Minimization: Revisiting von Neumann’s alternating projections”. Talk at ADA Lovelace Center: Workshop on Optimization and Machine Learning (Waischenfeld, Germany). [slides]
• 12/2022: (technical) “Alternating Linear Minimization: Revisiting von Neumann’s alternating projections”. Talk at Fields Workshop on Recent Advances in Optimization (Toronto, Canada). [slides]
• 09/2022: (technical) “Convex integer optimization with Frank-Wolfe methods”. Talk at Advances in Classical and Quantum Algorithms for Optimization and Machine Learning (Tokyo, Japan). [slides]
• 07/2022: (technical) “Structured ML Training via Conditional Gradients”. Plenary at Workshop on Algorithmic Optimization and Data Science (Trier, Germany). [slides]
• 04/2022: (technical) “Conditional Gradients in Machine Learning and Optimization”. Talk at IST ELLIS Seminar Series (Klosterneuburg, Austria). [slides]
• 11/2021: (technical) “Discrete Optimization in Machine Learning - an (informal) overview”. Talk at Oberwolfach Workshop on Combinatorial Optimization (Oberwolfach, Germany). [slides]
• 10/2021: (technical) “Fast algorithms for 1-fair packing (and its dual)”. Talk at HIM Workshop: Continuous approaches to discrete optimization (Bonn, Germany). [slides]
• 09/2021: (technical) “Conditional Gradients - a tour d’horizon”. Talk at AI Campus Berlin Tech Lunch Talk (online). [slides]
• 02/2021: (technical) “Structured ML Training via Conditional Gradients”. Talk at IPAM Deep Learning and Combinatorial Optimization Workshop (online). [slides] [video]
• 11/2020: (technical) “Conditional Gradients: Overview and Recent Advances”. Talk at RWTH Aachen Mathematical Colloquium (online). [slides]
• 11/2020: (general) “AI and-for-with-against Humanity?”. Keynote at Human-centric Artificial Intelligence: 2nd French-German-Japanese Symposium (online). [slides]
• 09/2020: (technical) “Restarting Algorithms: Sometimes there is Free Lunch”. Keynote at CPAIOR 2020 (online). [slides] [video]
• 09/2020: (technical) “Robust ML Training with Conditional Gradients”. Talk at CO@Work 2020 Summer School (online). [slides] [video]
• 05/2020: (technical) “Beyond Worst-case Rates: Data-dependent Rates in Learning and Optimization”. Keynote at MIP 2020 (online). [slides] [video]
• 03/2020: (general) “Künstliche Intelligence im Arbeitsalltag (in German)”. Keynote at Künstliche Intelligenz: verständlich @ TH Wildau (Wildau, Germany). [slides]
• 09/2019: (technical) “Smooth Constraint Convex Minimization via Conditional Gradients”. Plenary at 19th French-German-Swiss conference on Optimization (Nice, France). [slides]
• 09/2019: (technical) “Mirror Descent and related methods in Linear and Discrete Optimization”. Talk at Cargese Workshop on Combinatorial Optimization (Cargese, France). [slides]
• 07/2019: (technical) “Locally Accelerated Conditional Gradients”. Talk at Research Institute for Mathematical Sciences Seminar, Kyoto University (Kyoto, Japan). [slides]
• 01/2019: (technical) “Smooth Constraint Convex Minimization via Conditional Gradients”. Plenary at INFORMS Computing Society Conference (Knoxville, TN). [slides]

Archived Outreach ⏵

• 05/2026: Der Traum der Gurke – Ein literarisches KI-Experiment. Weizenbaum-Institut. (Panel Discussion (German))
• 04/2026: Mehr als die Summe der Teile — Multi-Agenten-Systeme: Wie KI-Systeme gemeinsam Probleme lösen. c't 10/2026, pp. 120–125 (Heise). (Magazine feature (German))
• 11/2024: El aprendizaje automático ayuda a atacar problemas matemáticos clásicos (Machine learning helps attack classical mathematical problems). El Pais: Café y teoremas. (Newspaper (Spanish))
• 11/2024: Zukunftsforum KI. IHK Berlin. (Panel Discussion (German))
• 10/2021: Improve the World with Maths?. Humboldt Forum: Discourse, Science and Humanities. (Talk + Discussion (German))
• 05/2021: Durch KI verhandene Ressourcen effizienter nutzen. Aufbruch Ausgabe 28. (Interview (German))
• 12/2020: Folge 7: „Trendsetter Internet? Angstmacher KI? Folgen der Digitalisierung“. Brain City Berlin. (Podcast (German))
• 09/2019: Drei Fragen an Sebastian Pokutta. Felix-Klein-Herbstworkshop »Discrete Optimization«. (Interview (German))

Archived Teaching ⏵

• SS/2026: Discrete Optimization and Machine Learning (seminar)
• WS/2025: Discrete Optimization and Machine Learning (seminar)
• SoSe/2025: Discrete Optimization and Machine Learning (seminar)
• WS/2024: Discrete Optimization and Machine Learning (seminar)
• WS/2023: Discrete Optimization and Machine Learning (seminar)
• SoSe/2023: Discrete Optimization and Machine Learning (seminar)
• WS/2022: Discrete Optimization and Machine Learning (seminar)
• SoSe/2022: Discrete Optimization and Machine Learning (seminar)
• WS/2021: Discrete Optimization and Machine Learning (seminar)
• SoSe/2021: Discrete Optimization and Machine Learning (seminar)
• WS/2020: Discrete Optimization and Machine Learning (seminar)
• SoSe/2020: Discrete Optimization and Machine Learning (seminar)
• WS/2019: Discrete Optimization and Machine Learning (seminar)
• Spring 2018: Machine Learning and Discrete Decisions (lecture)