Dates: February 2-3, 2027Location: Berlin, Germany

REGISTRATIONSUBMIT ABSTRACT

MACHINE LEARNING. REAL-WORLD PROGRESS.

ML FORWARDSUMMIT

Explore prediction, evaluation and deployment, from ML research to systems that stay useful in production.

WHEN
February 2-3, 2027
WHERE
Berlin, Germany
REGISTRATIONSUBMIT ABSTRACT
MACHINE LEARNING. REAL-WORLD PROGRESS.
February 2-3, 2027 / Berlin, Germany
DEEP LEARNING · LANGUAGE & VISION
MLOPS · RESPONSIBLE ML · ROBOTICS

CONFERENCE SPEAKERS

SPEAKERS

Meet the research, engineering, and community voices shaping machine learning.

Explore the summit’s speakers and their research.

VIEW ALL SPEAKERS
  • Applied Compute
  • Arcee AI
  • Braintrust
  • Encord
  • Giskard
  • Kled
  • Lightly
  • Prime Intellect
  • Snorkel AI
  • Trajectory

ML FORWARD SUMMIT

About ML Forward Summit 2027

ML Forward Summit 2027 is a hybrid machine learning conference connecting AI research with product development and business applications. It brings together founders, business and technology professionals, engineers, data scientists and researchers.

ML Forward Summit 2027 takes place on February 2 and 3, 2027, in Berlin, Germany, with in-person and online participation.

Explore 16 research areas covering learning methods, language and vision models, generative AI, MLOps and responsible AI. Examine what it takes to evaluate models, deploy them in production and scale reliable machine learning systems.

Exchange ideas across research and industry, compare approaches to shared challenges and meet potential collaborators. Gain practical perspectives to inform your research, guide product decisions and support AI adoption within your organisation. Learn more about the summit.

EXPLORE THE FORMATGOSEE WHO IT IS FOR

MACHINE LEARNING

TOPICS

Connecting ML research, model development, production systems, and responsible practice.

White dotted helix on a muted blue background01

ML FOUNDATIONS & LEARNING METHODS

Explore learning theory, deep learning, reinforcement learning, causal inference, probabilistic models, and optimisation.

White dotted wave and orbit forms on a muted beige background02

LANGUAGE, VISION & GENERATIVE MODELS

Connect natural language processing, large language models, computer vision, speech, generative AI, and multimodal learning.

Connected white dotted spheres on a muted slate background03

ML SYSTEMS, MLOPS & EDGE AI

Discuss data-centric ML, deployment, monitoring, efficient inference, edge AI, federated learning, and production reliability.

White dotted orbital forms on a muted brown background04

RESPONSIBLE & APPLIED MACHINE LEARNING

Examine evaluation, fairness, explainability, privacy, and applications in science, healthcare, climate, robotics, and decision-making.

RESEARCH AREAS

SESSIONS

Explore 16 topic areas, from ML foundations to deployed systems, across four programme themes.

SESSION AREA 01

LEARNING THEORY & OPTIMISATION

Generalisation, statistical learning, optimisation methods, uncertainty, and the mathematical foundations of reliable learning.

01
SESSION AREA 02

DEEP LEARNING & REPRESENTATION LEARNING

Neural architectures, self-supervised learning, transfer learning, feature representations, and training methods.

02
SESSION AREA 03

NLP & LARGE LANGUAGE MODELS

Language understanding, speech, retrieval-augmented generation, adaptation, reasoning, and language-model evaluation.

03
SESSION AREA 04

COMPUTER VISION & PERCEPTION

Image and video understanding, detection, segmentation, 3D vision, and visual learning across real-world environments.

04
SESSION AREA 05

GENERATIVE & MULTIMODAL LEARNING

Generative models, diffusion methods, cross-modal representations, and learning across text, images, audio, and video.

05
SESSION AREA 06

REINFORCEMENT LEARNING & DECISION-MAKING

Sequential decisions, offline and model-based reinforcement learning, planning, multi-agent learning, and policy evaluation.

06
SESSION AREA 07

GRAPH LEARNING & RECOMMENDER SYSTEMS

Graph neural networks, relational data, knowledge graphs, ranking, recommendations, and personalisation.

07
SESSION AREA 08

TIME SERIES & FORECASTING

Temporal validation, leakage prevention, forecasting with limited history, anomaly detection, and learning from changing demand.

08
EXPLORE ALL 16 SESSION TOPICS
CONTRIBUTE TO THE CONVERSATION.Explore research themes and contribution guidance.
CALL FOR PAPERSGO

EVENT LOCATION

VENUE

Berlin / Germany

Crowne Plaza Berlin City Centre Ku'damm

Room: Sektion II + III.

CONFERENCE INFORMATION

FAQs

ML Forward Summit 2027 is a hybrid machine learning conference connecting AI research with product development and business applications.

PARTNERSHIP OPTIONS

PARTNERS & SPONSORS

Build partnerships around genuine contribution, visibility, and meaningful connections with the conference community.

PARTNER WITH USGO
01FOUNDING PARTNERHelp shape the first edition
02KNOWLEDGE PARTNERBring evidence and expertise
03EXPERIENCE PARTNERCreate a moment people remember
04COMMUNITY PARTNERConnect the right people

ATTENDANCE

ATTEND THE SUMMIT

Bring your questions, share your research and connect with the people moving machine learning forward.

EXPLORE THE SUMMITGO

ML FORWARD SUMMIT

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