Kázmér Nagy-Betegh
Flexciton
Introduction
Purpose of The Website
I use this site to give you a quick overview of myself and some highlights from my project and work experiences.
Download my resumé.
Biography
I am from Cluj-Napoca Romania, born in a Hungarian family, I finished high school there.
Studies:
Moved to London for University, where I studied Electrical and Electronic Engineering at UCL with an emphasis on Internet of Things and Machine Learning. I graduated with First Class Honours and my Masters project focused on power efficient indoor localisation using Ultra-Wideband won best project within the department. It was published in 2021 as part of the ICL-GNSS 2021 conference.
After working as a Software Engineer for a year at Bosch I’ve returned to school to complete a masters in Management and Analytics at London Business School.
A brief overview of my work experience:
I have worked a month in San Sebastian, Spain at Elektra, an international Electrical solutions distribution and Automation company, where I researched industry 4.0 technologies which cover internet of things, machine learning and robotics. I have worked as Business Analyst at Humatica during the summer of 2019, working on growth strategies for a client in wealth management, in this role I performed research and financial modeling. Starting 2020 November I worked at Bosch Budapest, as a software engineer as part of the near range camera visualisation team developing solutions in C++ and Python.
Since 2022 November I have been working at Flexciton London. Flexciton is focused on delivering advanced scheduling solutions for semiconductor fabs. I work as a Customer Solutions Engineer.
Hobbies/Activities:
I have played water polo at national level for 10 years in Romania and 4 years at University at BUCS level.
My hobbies include: skiing, culinary experiences, diving, hiking, movies
Some of my favourite books:
- The Last Samurai by Helen Dewitt
- The Sun Also Rises by Ernest Hemingway
- Flowers for Algernon by Daniel Keyes
- Do androids dream of electric sheep? by Philip K. Dick
- Artificial Intelligence
- Internet of Things
- Information Retrieval
- Business Strategy
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MSc Masters in Analytics and Management, 2022
London Business School
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MEng Electrical and Electronic Engineering, 2020
University College London
Skills
Stats and Visualisation
ML, Visualisation, General
Experience
Responsibilities included:
- Working with customers to understand their needs and requirements
- Designing and implementing solutions to meet customer needs
- Working with the development team to implement new features
- Working with the sales team to create proposals and presentations
Responsibilities included:
- Implementing new features in C++ for the Parking Video Visualisation
- Code improvements and debugging
- Development Process Improvement
Responsabilities included:
- Developed a Micrososft Power Automate based tool for the company to track Product Returns
- Helped in definining the new fully digital process and the information flow between teams.
Responsibilities included:
- Modelled the size of the High Net-Worth wealth management market and segmented it into 20 dimensions for the client.
- Wrote a 5 and 10 year outlook report on the effects of Automation and AI on operating models across industries, providing a roadmap for sectors where management consulting might be needed.
- Presented the analyses techniques and data sources in the excel models, during 3 client meetings accompanying the partner and manager
Responsabilities included:
- Researched topics that fall under the umbrella term Industry 4.0, such as: predictive maintenance, AR assisted production lines, machine learning, collaborative robots.
- Wrote, recoded and edited one in-depth explanatory and one marketing video about the technologies enabling the next industrial revolution, both of are still in use at the company.
- Shadowed the head of the innovation lab at the company, to learn about their digitalisation efforts.
Projects
Bike Rental Data London
Some visualisation around London Bike Rentals; Page Still under construction, Futher insights and examplanations will be added
Linear Regression to Predict Interest Rate
This is a short intro to linear regression with exampls inspired by my Data Science for Business class at LBS.
Metropolitan Police Stop and Search Data
Here are some results from my workings with the the London metropolitan police data for a LBS school assignment and the visualisations I have come up with.
Apple Stock Price Deep Learning
Evaluating the performance of LSTM, RNN and CNN on predicting apple Stock Price based on historical price and volume data.
London House Prices
London House Price prediction using statistical machine learning techniques
Tidytuesday Astronauts Dataset Dashboard
Dashboard with insights from the Astronut dataset from Tidy Tuesday Challange
Face Categorisation using Python
This is an overview of one of my machine learning assignments that I have completed at UCL
2020 US Election Results vs Vaccination
Introduction The purpose of this exercise is to reproduce a plot using your dplyr and ggplot2 skills. Read the article The Racial Factor: There’s 77 Counties Which Are Deep Blue But Also Low-Vaxx.
