SEMLA aims at bringing together leading researchers and practitioners in software engineering and machine learning to reflect on and discuss the challenges and implications of engineering complex data-intensive software systems. IVADO is very proud to support this important event.

While everyone agrees that the development of new machine learning algorithms will enhance the potential of data analytics, only their implementation in real-world systems will allow them to realize their full potential. From an engineering perspective, once an algorithm is implemented, it requires a solid architecture, model/data validation, proper monitoring for changes, dedicated release engineering strategies, judicious adoption of design patterns and security checks, and thorough user experience evaluation and adjustment. All these activities require a combined knowledge in software engineering, data science, and machine learning.

Hence, SEMLA invites all practitioners and researchers to get to know the results and opinions of world leaders in both machine learning and software engineering and to discuss their views on the above problems.

Upcoming webinars

June 17: Diego Oppenheimer, Algorithmia 
DevOps for Machine Learning and other Half-Truths: Processes and Tools for the ML Lifecycle
June 18: Christian Kästner, Carnegie Mellon School of Computer Science
Engineering AI-Enabled Systems with Interdisciplinary Teams
June 22: Samuel Deng et Achille C. Varzi, Columbia University 
Methodological Blind Spots in Machine Learning Fairness: Lessons from the Philosophy of Science and Computer Science
June 23: Grady Booch, IBM Research
Software Methodology and Lifecycle In AI
June 30: Mark Harman, Facebook 
A Hidden, Bot-only Platform to Learn About Trolls and Scammers (tentative title)

Learn more about our guest speakers >>