Call for Speakers for MLconf SF 2023

MLconf gathers machine learning & AI enthusiasts from a broad range of industries and academic backgrounds to share new tools, tricks, platforms, algorithms and methods with a broad audience of practitioners. Each presentation offers an educational component to be shared with the community, in which specific algorithms and techniques can be shared and new applications of such are inspired. Today, we are making a call for presentations for our MLconf San Francisco conference to be held on October 19, 2023 at the Hotel Nikko in SF. The conference will feature presentations from across the machine learning landscape. If you, your team, organization, or colleague has done something innovative related to ML algorithms, Tools and Platforms, or Building and Managing Teams to solve hard problems, let us help you share your story. In your abstract, we encourage you to mention where you feel your techniques will transfer over into other Machine Learning applications, showing where it's relevant to the MLconf audience. Prior submissions have included presentations related to: Algorithms that have graduated from an academic/theory state and have proven to be effective, robust and scalable in production within industry application; Machine Learning/AI examples of specific challenges faced within current industry and how teams have found success by applying new algorithms and techniques or by applying modifications to existing practices for optimal outcomes; New platforms, tools for machine learning; New business practices for managing and growing data science teams; and Expanding machine learning to new domains. Abstracts should be 150-500 words in length and should illustrate the level of technicality in the proposed presentation. At the time of the event, presentations will be generally limited to 25-30 minutes in length in order to allow you to provide depth while also allowing for presentations from colleagues and Q&A. Emphasis should be given to the technical challenges, benchmarks, innovations and motivation for the development of models, algorithms and statistical models to analyze and draw inferences from patterns in data. Your presentation should definitely not be a product or sales pitch. ABSTRACT DEADLINE: June 30, 2023 Topics we are looking for include but are not limited to: AI/ML Ops Natural Language Processing Deep Learning Reinforcement Learning Data Science for Social Good Kernel Methods Causality Embeddings Recommendation Systems Quantum Computing and AI/ML Chemistry & AI/ML Pandemic Data & ML Model Interpretability Fraud Detection DeepFake Detection Generative Teaching Networks Facial Recognition/Biometric Identification Genetics & ML Experimental Reproducibility Best Practices Model Uncertainty and Data Drift Generative Adversarial Networks Transfer Learning Adversarial Machine Learning IoT and edge computing applications Genetic Algorithms Tensor Algebra Probabilistic Programming and Logic Machine Learning for Music and Art Bayesian Methods Markov Logic Networks Synthetic Art, Biology Ethics in Machine Learning Data / Algorithm Ethics Sketching Randomized Algorithms AI Education Game Theory Diversity in AI Community Detection Time Series Image Analysis Structured Learning using Neural Networks Healthcare & ML (Clinical Decision Support Systems, Record Keeping, Medical Imaging, etc.) FinTech & ML (Algorithmic Trading, Predictive Analytics, Fraud Detection & Prevention, Payments, etc.) In the spirit of sharing knowledge, presentation slides are shared with attendees and photographs and/or video footage of presentations are shared as well.