Grégory Mermoud

Principal Engineer at Cisco | Computer Scientist | Inventor

My mission as an engineer and researcher is to foster scientific, engineering, and operational excellence across multidisciplinary teams and organizations, especially when faced with challenges in the area of data science, machine learning, and data engineering.

My core expertise lies in the design, development, and management of high-performance software systems that use telemetry, sensory, or historical data to build internal representations and models in order to achieve complex tasks through machine intelligence and control theory.


Innovation and Research

I authored more than 200 patents (130+ already issued) in the area of machine learning and artificial intelligence. I also published many peer-reviewed papers and book chapters. My H-index is 20. Furthermore, I published two monograms in the Springer Tracts in Advanced Robotics series (STAR): my PhD thesis as a monograph (volume 93) and the proceedings of DARS2010 (volume 83).

Team Leadership

I built 3 engineering teams built from the ground up. This amounts to more than 50 engineers hired, coached, and managed across a broad range of geographies and disciplines (software engineering, machine learning, data science, cloud engineering, data visualization, front-end design).

I have a broad expertise in managing agile teams to deliver reliable software using continuous integration and delivery strategies, test automation, code reviews, pair programming, and cloud devops.

Industry Impact

I lead the design and development of 3 products at Cisco used by 1000+ enterprise customers, including many Fortune 500, from inception to customer delivery in production.

Technological Landscape

My 10-year tenure at Cisco allowed me to gain insights into a broad technological landscape, including cybersecurity, internet of things, wireless networks, internet architecture, endpoint classification, and cloud computing.

Technical Skills
  • Programming languages: Python, Golang, C++, SQL, Apache Spark
  • Software engineering: data engineering, distributed computing, database design, cloud computing, web development
  • Technologies: machine learning, robotics, statistical modeling, Git, Linux, Gitlab, Github


Principal Engineer

Cisco, Stealth Internal Startup

I lead the design, development, and industrialization of key innovations in the area of machine learning applied to large enterprise networks. I lead a startup/scaleup of nearly 30 engineers, working on the future of the Internet. We leverage Cisco's unparalleled visibility of the Internet to deliver predictive application-driven networking technologies.

January 2019 - Present

Head of Product Development

Cisco, Enterprise Networking Group

I was the Senior Technical Leader in charge of the machine learning group, as well as the infrastructure and product development of Cisco AI Network Analytics, a cloud-based machine learning platform that provides visibility and learns from enterprise networks across the world. I lead the R&D process from white-boarding to the completion of first customer shipment. Today, it is routinely used by 1000+ customers across the world, including some of the largest enterprises in the world.

My role was highly technical, with a mix of research, system architecture, algorithm design, software development, product, and engineering management. I have hired and managed a multidisciplinary team of 12 software engineers, machine learning specialists and data scientists.

July 2016 - December 2018

Head of Machine Learning

Cisco, Security Business Group

I was the Technical Leader in charge of the machine learning and software development group for Stealthwatch Learning Network (SLN), Cisco's next-generation cyber security platform, now known as Cisco Secure Network Analytics. This product turns every router and switch into a security agent capable of analyzing the behavior of every host and device on the network and triggering alerts in case of anomalies.

April 2014 – June 2016

Senior Software Engineer

Cisco, Internet of Things Group

Design and development of many machine learning algorithms, visualizations, and data analytics pipelines for Low-power Lossy Networks (LLNs).

  • Technical project lead, architect and main developer of the first service assurance prototype for the Internet of Things.
  • Lead developer of the very first prototype of Edge Computing at Cisco.
Jun 2012 – May 2014


École Polytechnique Fédérale de Lausanne (EPFL)

PhD in Computer Science

PhD thesis on intelligent distributed systems, with a strong emphasis on robotics and self-assembling systems; other achievements included:

  • Selected among the top 3 PhD robotics theses in Europe in 2012;
  • Author of 10 peer-reviewed papers in international conferences and journals, 1 patent, and 1 book chapter;
  • Supervision of more than 10 future engineers in various fields (computer science, systems of communication, mechanics, micro-engineering, physics);
  • Co-editor of the 10th International Symposium on Distributed Autonomous Robotics Systems (DARS2010).


École Polytechnique Fédérale de Lausanne (EPFL)

Master in Computer Science

Focus on compiler construction and optimization, formal methods, machine learning and distributed intelligence.



My teams have always thought that building software that meets both customer requirements (by solving a key problem) and deadlines is possible. We have been historically pretty successful in doing so, and we strive to improve even further. This post introduces the foundational ideas and principles that have helped us in the past, and that we are committed to live by in the future.

Why Automation Will Unlock The Power of AI in Networking (Part 1 | Part 2)
March 23, 2022

There is a subtle, yet fundamental reason why automation is a key ingredient in the success of AI in networking and many other areas: causality.

I wrote this guide based on my experience managing various remote teams at Cisco. It provides practical pieces of advice for engineering teams on how to communicate effectively, in particular on technical matters.