Daniel M. Email & Phone Number

Geldermalsen, Gelderland, Netherlands

Amsterdam, North Holland, Netherlands

. Developed custom CMS solutions using Sanity and Dato CMS. Utilized Next.js and TypeScript for efficient React componentdevelopment, aligning with strategic goals of the company.• Implemented TDD with Jest in Stellar project. Enhanced code security and quality using JFrog Xray and SonarLint.• Led creation of internal Sections Library; streamlined Stellar’s website code for cross-project component reuse, resulting in an internal npm package release.• Improved testing practices by integrating Jest into GitHub workflow, setting foundational testing standards for the team.

Remote

. Engineered for 5+ international clients, including a top industry firm (subject to a non-disclosure agreement; no furtherdetails available).• Built an English learning platform for a private contractor from scratch focusing on scalability and UX using Typescript, React, Redis and MongoDB, leading to a 35% engagement boost during COVID-19.• Implemented automation in development using GitHub Actions, Synk, and Docker, showcasing a hacker mindset and project ownership.• Led experimental digital art projects with P5.js and ML-centric methodology utilizing GANs, engaging over 30 attendees at local events.

Qazvin, Iran

Ordibehesht Studio started as a creative bunch of students in 2014 at Qazvin Azad University, starting with a small project and publishing its first game Zoobi in Iran's local mobile game market. Later on, 4Wheelers had been worked on by the team before I initially stepped in, which has been nominated for the 14th International Mobile Gaming Awards Global (IMGA GLOBAL). The IMGA is the longest-standing and highest regarded mobile games award program started in 2004. As Machine Learning Researcher I joined the team since my knowledge was used for the analysis of the user's experience data and extraction of semantics for engagement campaigns.Along the way, I found myself passionate about making 4Wheelers more competitive. I created an intelligent computer player which would adjust its accuracy based on the user's power and steering angle (two important core mechanics of the game). I used a regression model with an added bias to calculate users' advancement curve per game for every 3 turns each user took each round. This was implemented in the game on Unity game engine written in C# language using Linear Regression.I worked as a part of the data team, my responsibility was broken down into interpretation of data from our "data-pool" that was created before hands using a Python3 middleware that would extract parameters out of users' activity respecting their privacy for further calculations. My role in this process was based on feature extraction which later would be fed to a regression model that outputs users' parametric variance from the expected engagement slope for a high-quality engagement and experience.I leveraged Numpy, Pandas, scikit-learn, and other modern scientific libraries in Python3 to engage in various aspects of user engagement campaigns. To enhance the development procedure in terms of speed and agility, I conducted a few sessions for team planning and meetings hovering over this subject.

Qazvin, Iran

• Conducted advanced research in Standard Platform League (SPL) on NAO robots, focusing on pre-game planning, behavior analysis, and vision enhancement using Bayes’ theorem and Hough Transform in C++.• Analyzed robot data to refine gameplay strategies for the Iran Open international robotics competition, showcasing a data-driven approach.• Mentored junior researchers, fostering a culture of creativity and effective teamwork.• Engineered the codebase architecture, implementing a well-documented DRY approach in component design, optimizingsoftware development processes.

Bachelor Of Engineering - Be, Software Engineering, 3.75 / 4 Gpa

Activities and Societies: Relevant Coursework: Algorithms, Operating Systems, Data Structures, Introduction to Artificial Intelligence.

Summer School Bootcamp, Computer Science

Activities and Societies: Relevant Coursework: Backpropagation, Introduction to TensorFlow/Pytorch, Introduction to Convolutional Neural.