Rutwik Mudholkar - Aylesbury – United Kingdom
As a child he was always interested in Maths and Science. He used Lego
to build structures and power them with motors.
As he grew up, he started
doing personal projects in Python at school, everything from Calculators
and Chatbots. His dream is to make a positive impact on the world with what he has learnt, while pushing himself to the BEST he can be…!
He has considerable exposure to Data Science.
For a Particle Physics lab project studying matter-antimatter asymmetries in the LHC, he used advanced statistical methods, error correction and relativistic kinematics to isolate salient Meson decay data retrieved from CERN.
He then used Scipy and Matplotlib to generate folded Dalitz plots and histograms to identify CP-violating regions.
His BSc dissertation on Attention and Correlation in Convolutional Neural Networks expanded on this front, learning more about deep learning models and pipelines. In tandem, he performed basic image processing in Python with NumPy and Scikit-learn.
In a professional capacity worked at Autodesk for a year, improving subtractive toolpath generation in the manufacturing kernel for their CAD products. He wrote in C++, learning to optimize low-level architecture by implementing better mathematical models to create and manipulate complex 3D geometry.
One task required him to use a custom k-means clustering algorithm to detect regions for smooth toolpath curve start and endpoints.
CNC Machine for Subtractive Manufacturing
