Anousha M.

CTO

Seattle, Washington, United States19 yrs 11 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in multi-agent systems and robotics.
Proven experience in software engineering and testing.
Strong background in mobile application development.

Stackforce AI infers this person is a Robotics and Software Engineering expert with a focus on mobile development.

Contact

anousham@microsoft.com LinkedIn

Skills

Core Skills

Machine LearningRoboticsSoftware EngineeringTesting

Other Skills

Multi-agent SystemsSimultaneous Localization and MappingMonte-Carlo state estimationparticle filteringAPI DevelopmentWindows PhoneSoftware TestingC#JavaC++WindowsLaTeXLinuxHTMLProgramming

Experience

19 yrs 11 mos

Total Experience

4 yrs 1 mo

Average Tenure

14 yrs 1 mo

Current Experience

Microsoft

6 roles

Partner Group Engineering Manager

Promoted

Sep 2024 – Present · 1 yr 8 mos

Principal Software Engineer Manager

Sep 2018 – Present · 7 yrs 8 mos

Senior Software Engineer Manager

Promoted

Jan 2017 – Present · 9 yrs 4 mos

Software Engineer at PowerApps

Jan 2014 – Present · 12 yrs 4 mos

Software Engineer in Test at Windows Phone

Jul 2012 – Jan 2014 · 1 yr 6 mos

Software Engineer Intern

May 2011 – Aug 2011 · 3 mos · Redmond WA

Windows Phone 7.1 Test;
Designed, developed and deployed a reliable message passing API for communication between foreground and background applications on windows phone
Created detailed functional and design specification stating the requirements of the library and end-user scenarios
Created foreground and background application to test the communication and memory/CPU usage performance of the library

University of georgia

3 roles

Graduate Research Assistant

Jun 2009 – May 2012 · 2 yrs 11 mos

Worked on a grant funded by NSF/ CS department about Multi-agent Systems and Simultaneous Localization and Mapping with multiple robots.
Designed, developed and implemented a simulation scenario for multi - robot localization in a dynamic environment lacking GPS signals
Developed a set of autonomous intelligent robots that are able to localize themselves and track the opponents accurately in a highly dynamic environment
Implemented a Monte- Carlo state estimation approach using particle filtering for localization purposes

Multi-agent SystemsSimultaneous Localization and MappingMonte-Carlo state estimationparticle filteringMachine LearningRobotics