Mawulolo Ameko, Ph.D.

Critic
DISC Type : C

Applied Scientist at Microsoft

United States

Overview

Mawulolo Ameko is an Applied Scientist at Microsoft with a Ph. D. from the University of Virginia. He specializes in applying AI, reinforcement learning, and causal modeling to build large-scale solutions that drive business outcomes. His experience spans user modeling, recommender systems at Netflix, and logistics ML at DoorDash.

His academic research focused on creating AI-driven mobile health interventions. Specifically, he developed recommender algorithms to suggest emotion regulation strategies for individuals with social anxiety, using passively sensed data to deliver targeted, just-in-time mental health support.

Unique fact: He co-authored research on using contextual multi-armed bandits, a type of reinforcement learning, to create mobile recommender systems for mental health treatments.

Personality Overview

Information Seeker

Objective Thinker

ROI Driven

They like to do things independently and don’t look for support from others.  They choose to analyze logically and value facts to emotions. They don’t appreciate bells and whistles unless backed by data.

Topics They Care About

AI in Healthcare
His Ph. D. research and multiple publications focus on using AI and mobile health (mHealth) interventions to improve mental health outcomes, such as emotion regulation and affect recognition.
Reinforcement Learning
This is a core skill listed in his experience. He has published research on using multi-armed bandits, a form of reinforcement learning, for mobile health applications.
Recommender Systems
He worked on recommender systems as a Research Scientist at Netflix and has published academic papers on building recommender algorithms for therapeutic strategies.

Media Appearances

Mawulolo has no verified media appearances

Work History

10-2021 - 6-2025
Applied Scientist at Microsoft
6-2021 - 8-2021
Research Scientist at Netflix
3-2021 - 5-2021
Machine Learning Engineer at DoorDash
8-2016 - 3-2021
Machine Learning Researcher at University of Virginia

Education

2016 - 2021
Doctor of Philosophy - Ph.D. from University of Virginia
2015 - 2016
Master of Science (M.Sc.) Mathematical Sciences from African Institute for Mathematical Sciences, Sénégal

More Information

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Exp : 8 Location : United States Job Level : N/A Designation : Applied Scientist at Microsoft
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Insights For Selling To Mawulolo

During A Call Or A Meeting

DO's

  • Tell them what ROI they can expect
  • Use phrases like ‘expect X% improvement’, ‘data clearly shows’ etc.
  • Keep some extra margin while sharing pricing, they are likely to negotiate later

DONT's

  • Avoid pushing them too much to involve other stakeholders unless it is critical
  • Don’t try to give too many examples of other users, they like to make their own decisions
  • Do not use very emotional or colorful language

When Cold Calling

When Writing An Email

While Negotiating & Closing

    The secret to closing fast with Mawulolo is

  • Proven ROI, pricing and objective proof points are the factors that sway their decision.
  • Will you ever get a clear answer from Mawulolo

  • They are comfortable saying no if they are convinced that it is the correct decision.

Insights For Deal Planning

    How fast (or slow) will Mawulolo move?

  • They are neither the fastest nor the slowest decision makers, they are somewhere in the middle.
  • Can Mawulolo take some risk or not?

  • They can bear some risk if their analysis backs the decision.

You And Mawulolo

Personality Compatibility


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