Francesca Lazzeri, Ph.D.

Francesca Lazzeri, Ph.D. Email and Phone Number

Principal Director, AI Engineering at Microsoft | Advisor at MIT | Previously Researcher at Harvard @ Microsoft
Redmond, WA
Francesca Lazzeri, Ph.D.'s Location
Boston, Massachusetts, United States, United States
Francesca Lazzeri, Ph.D.'s Contact Details

Francesca Lazzeri, Ph.D. work email

Francesca Lazzeri, Ph.D. personal email

Francesca Lazzeri, Ph.D. phone numbers

About Francesca Lazzeri, Ph.D.

Francesca Lazzeri, Ph.D. has over 16 years of experience in research, applied machine learning, AI product development and engineering team management. Francesca is Principal Director of Applied Data Science and AI Engineering at Microsoft, where she leads an organization of data scientists and machine learning scientists building AI applications on the Cloud, utilizing data and techniques spanning from generative AI, time series forecasting, experimentation, causal inference, computer vision, natural language processing, reinforcement learning. Before joining Microsoft, she was a Research Fellow at Harvard University in the Technology and Operations Management Unit, Technical Advisor at the Massachusetts Institute of Technology, and Adjunct Professor of Python for AI at Columbia University.Francesca is the author of a few books on applied machine learning and AI, such as:• Machine Learning Governance for Managers (2023, Springer Nature) • Impact of Artificial Intelligence in Business and Society (2023, Routledge) • Machine Learning for Time Series Forecasting with Python (2020, Wiley)• Many other publications, including technology journals (O’Reilly, InfoQ, DZone). You can find her on LinkedIn https://www.linkedin.com/in/francescalazzeri/ and Medium https://medium.com/@francescalazzeri.

Francesca Lazzeri, Ph.D.'s Current Company Details
Microsoft

Microsoft

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Principal Director, AI Engineering at Microsoft | Advisor at MIT | Previously Researcher at Harvard
Redmond, WA
Website:
microsoft.com
Employees:
10
Company phone:
0124 415 8000
Francesca Lazzeri, Ph.D. Work Experience Details
  • Microsoft
    Principal Director, Applied Data Science & Ai Engineering, Copilot Ai
    Microsoft Dec 2023 - Present
    Redmond, Washington, Us
    Leading an engineering organization of data scientists and machine learning scientists focusing on building Data Science products, LLMs applications and AI solutions for Business & Industry Copilots.
  • Microsoft
    Senior Director, Ai & Ml Engineering, Cloud + Ai
    Microsoft Sep 2021 - Dec 2023
    Redmond, Washington, Us
    I was the head of an engineering organization (8 teams) of data scientists and machine learning scientists at Microsoft with the goal of building end-to-end AI solutions to improve and optimize Microsoft customer experiences and growth on the Cloud.
  • Microsoft
    Director/Principal Data Scientist Manager, Cloud + Ai
    Microsoft Dec 2020 - Sep 2021
    Redmond, Washington, Us
    I led an organization of data scientists and machine learning scientists, and I worked on the full life cycle of machine learning model production including feature engineering, machine learning algorithms, model automation, deployment, operations, and machine learning governance.
  • Microsoft
    Senior Ml Engineer Manager, Cloud + Ai
    Microsoft Jul 2018 - Dec 2020
    Redmond, Washington, Us
    • Led multiple engineering teams of cloud developers and advocates managing a large portfolio of customers in the research, education and AI/ML sectors. I was responsible for building technical content and intelligent automated solutions on Azure, utilizing techniques spanning from IoT, time series forecasting, computer vision, natural language processing, reinforcement learning and open-source frameworks.• Languages/Frameworks/IDE: Python, SQL, Scala, Spark, R, Bash, Git, Visual Studio Code, Databricks, Power BI, Tableau, Scikit-learn, PyTorch, TensorFlow, Pandas, Matplotlib, Numpy.
  • Microsoft
    Data Scientist Ii, Ai Research
    Microsoft Oct 2014 - Jul 2018
    Redmond, Washington, Us
    • Built end-to-end operationalized machine learning solutions for external customers across various business verticals (energy, retail, predictive maintenance, finance, and health care) using Python, Azure, and open-source machine learning frameworks (TensorFlow and PyTorch). • Required to build and evaluate machine learning algorithms to gather insight or produce tools for data-driven insights and products. Visualizing results and building analytics applications for external Microsoft customers to improve products and processes.
  • Microsoft
    Data Scientist, Ai Research
    Microsoft Apr 2014 - Oct 2014
    Redmond, Washington, Us
    As a data scientist, I worked with a team of engineers and solution architects within the AI Research division of Microsoft. I was in charge of leveraging statistical modeling and machine learning techniques to build end-to-end solutions for external customers using the Cortana Intelligence Suite, with a special focus on IOT (Internet of Things), demand forecasting and retail related use cases. I also wrote applications to visualize results and generate analytics for Microsoft customers, with the final purpose of improving our products and processes.
  • Massachusetts Institute Of Technology
    Technical Advisor
    Massachusetts Institute Of Technology Apr 2024 - Present
    Cambridge, Ma, Us
    Technical advisor and guest lecturer for the Break Through Tech AI program at MIT Schwarzman College of Computing.
  • Columbia University In The City Of New York
    Adjunct Professor, Machine Learning
    Columbia University In The City Of New York Jan 2021 - Oct 2023
    New York, Ny, Us
    Professor of "Introduction to Artificial Intelligence with Python"(COMS0100) at Columbia University. I designed this course to provide an introduction to machine learning, datamining, and statistical pattern recognition. Topics include: - Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks).- Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning).- Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). The course also draws from numerous case studies and applications, so that students also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.
  • Columbia University In The City Of New York
    Advisory Board Member Of Committee On Instruction
    Columbia University In The City Of New York Sep 2021 - Sep 2023
    New York, Ny, Us
    Board member of the Committee on Instruction (COI) at Columbia University, where I provide expertise and guidance on assessing curricular and scientific excellence for students, researchers and educators. I am responsible for reviewing all the scientific curriculum, lab and publication proposals for technical accuracy.
  • Massachusetts Institute Of Technology
    Technical Advisor
    Massachusetts Institute Of Technology Jan 2015 - Jan 2021
    Cambridge, Ma, Us
    AI technical advisor for post doctoral courses at the MIT: https://pda.mit.edu/2021-mit-postdoctoral-association-mentoring-program/
  • Harvard Business School
    Research Fellow
    Harvard Business School May 2012 - Apr 2014
    Boston, Ma, Us
    I was in charge of performing data science and econometric analysis within the Technology and Operations Management Unit. I worked on multiple patent, publication and social network data-driven projects to investigate and measure the impact of external knowledge networks on companies’ competitiveness and innovation.
  • Scuola Superiore Sant'Anna
    Research Associate
    Scuola Superiore Sant'Anna Sep 2008 - May 2012
    Pisa, Pi, It
    I was in charge of performing data science, statistical and econometric analysis within the Technology Innovation unit to investigate the economic and managerial factors determining growth processes in spin-off and start-up companies.

Francesca Lazzeri, Ph.D. Skills

Statistics Research Analytics Data Analysis R Machine Learning Big Data Economics Market Research Stata Statistical Modeling R&d Innovation Spss Innovation Management Econometrics Data Science Marketing Strategy Patents Public Speaking Algorithms Sql Hadoop Cloud Computing Python Artificial Intelligence Deep Learning

Francesca Lazzeri, Ph.D. Education Details

  • Harvard University
    Harvard University
    Econometrics And Quantitative Economics
  • Scuola Superiore Sant'Anna
    Scuola Superiore Sant'Anna
    Economics And Technology Innovation
  • Luiss Guido Carli University
    Luiss Guido Carli University
    Economics And Institutional Studies

Frequently Asked Questions about Francesca Lazzeri, Ph.D.

What company does Francesca Lazzeri, Ph.D. work for?

Francesca Lazzeri, Ph.D. works for Microsoft

What is Francesca Lazzeri, Ph.D.'s role at the current company?

Francesca Lazzeri, Ph.D.'s current role is Principal Director, AI Engineering at Microsoft | Advisor at MIT | Previously Researcher at Harvard.

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What schools did Francesca Lazzeri, Ph.D. attend?

Francesca Lazzeri, Ph.D. attended Harvard University, Scuola Superiore Sant'anna, Luiss Guido Carli University.

What skills is Francesca Lazzeri, Ph.D. known for?

Francesca Lazzeri, Ph.D. has skills like Statistics, Research, Analytics, Data Analysis, R, Machine Learning, Big Data, Economics, Market Research, Stata, Statistical Modeling, R&d Innovation.

Who are Francesca Lazzeri, Ph.D.'s colleagues?

Francesca Lazzeri, Ph.D.'s colleagues are Monique G., Shmuel Berezin, Mohsen Davtalab, 聰鹿鹿, Chika Nzeh, Pankajj Pandit, Mohd Faiyazuddin Farooqi.

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