C/C
Hi, I’m
Peter Ngure
Product Manager
Bielefeld
Summary
Product management professional with track record of driving successful product initiatives and optimizing product performance. Adept at collaborating with cross-functional teams and focusing on achieving impactful results. Known for adaptability and reliability in dynamic environments, with skills in market research, strategic planning, and project management.
Overview
8
years of professional experience
6
years of post-secondary education
3
Languages
Work History
dSPACE
Product Manager - Data Driven Development and Autonomous Driving
11.2022 - Current
Job overview
- Automated Driving Software Solutions - Data Driven Development Toolchain
- Product Management for the RTMaps & RTAG software, which is indispensable for the entire DDD toolchain (Data Logging. Data Management, Data replay, SW development, and Software execution)
- Managed full product lifecycle, from ideation through post-launch support, ensuring consistent quality control measures were in place.
- Coordinated project planning and execution with team members and team leads.
- Managed stakeholder expectations effectively throughout the entire product development process.
- Communicated effectively with team members to deliver updates on project milestones and deadlines.
- Collaborated with sales, marketing, and support teams to launch products on time and within budget.
- Reviewed sales, customer concerns, and new opportunities to drive business strategy at weekly planning sessions.
Volkswagen AG
Master Thesis
04.2022 - 11.2022
Job overview
- Volkswagen Group Innovation - Deep Learning Research Master Thesis
- Lead in the Pressure Distribution analysis using machine learning to analyze and infer seat occupant activities
- Research current state of the art on pressure sensor technologies and their performance
- Research on existing ML techniques for Pressure distribution analysis and their performance
- Investigate deep learning technologies such as Yolov4, Resnet, and Faster RCNN and their effectiveness in our project
- Collecting data and defining the study parameters
- Training data analysis to investigate outliers and investigate the best possible ML approach
- Testing the models on a live demonstrator based on either webapps developed using Django or desktop apps using Tkinter
- Presenting results regularly to the team and getting feedback from the team
- Documentation of the Results
- Volkswagen Group Innovation - Deep Learning Research Master Thesis
Volkswagen Group Innovation
Deep Learning internship
02.2022 - 04.2022
Job overview
- Deep Learning internship
- Supported staff members in their daily tasks, reducing workload burden and allowing for increased focus on higher-priority assignments.
Lehrstuhl für TMDT
Research Assistant (Machine Learning Research, Computer vision)
05.2021 - 03.2022
Job overview
- Part of the team in charge with development of computer vision systems to detect train defects using images taken from cameras along railway trucks for DB cargo
- Distributed AI, deep learning and computer vision solutions
- Developed code for automatic downloading and cleaning data (Images) from the internet
- Developed a model using Resnet50 to classify delivery vehicles to be used at road intersections to track delivery trucks
- Used both Yolov4 object tracking and Resnet classification to track delivery cars at road intersection as a proof of concept available at: TMDT Demonstrator Showroom (uni-wuppertal.de)
- Part of the team in charge with development of computer vision systems to detect train defects using images taken from cameras along railway trucks for DB cargo
Bepro
Machine Learning Engineer (Research and Development)
02.2020 - 01.2022
Job overview
- In charge of the model development for the automatic sorting of over 3000 LEGO blocks and minifigures
- Collecting the Data and research on the best strategies for collecting the data
- Data analysis to lift underlying statistics and patterns
- Developing Data augmentation strategies to reduce the computational efforts of data collection and labelling
- Used Resnet and Efficient to develop models that could classify 200 classes of Lego
- Fine tuning the model to improve accuracy levels
- Retraining the model to incorporate new data
- Deploy the models into the prototype machine
- Research of the different possible approaches in the development of resource efficient models
KHS GmbH
Technical Sales Engineer /Line Design
02.2017 - 10.2019
Education
Bergische Universität Wuppertal
Master of Science from Computer Simulations in Science
04.2019 - 01.2022
University of NairobiNairobi
Bachelor of Science from Electrical and Electronics Engineering
04.2010 - 01.2014
Skills
Product Management
Software
Python
Matlab
ROS
RTMaps
MQTT
Languages
6,3,6
Interests
ADAS/AD
SW Developement
Machine Learning
Timeline
Product Manager - Data Driven Development and Autonomous Driving
dSPACE
11.2022 - Current
Master Thesis
Volkswagen AG
04.2022 - 11.2022
Deep Learning internship
Volkswagen Group Innovation
02.2022 - 04.2022
Research Assistant (Machine Learning Research, Computer vision)
Lehrstuhl für TMDT
05.2021 - 03.2022
Machine Learning Engineer (Research and Development)
Bepro
02.2020 - 01.2022
Bergische Universität Wuppertal
Master of Science from Computer Simulations in Science
04.2019 - 01.2022
Technical Sales Engineer /Line Design
KHS GmbH
02.2017 - 10.2019
University of Nairobi
Bachelor of Science from Electrical and Electronics Engineering
04.2010 - 01.2014
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