Monika is a Teaching Fellow and Deputy Admissions Tutor for Undergraduate Programmes at the Department of Aeronautics. Her primary focus is on Machine Learning and Artificial Intelligence in applications to Aeronautics.
AERO97072/3 - Artificial Intelligence for Aerospace Engineers
This course introduces the most popular Machine Learning and AI algorithms used in the Aerospace research and industry. Building on basic knowledge of MATLAB and Python as well as Linear Algebra, students gain both theoretical and practical understanding of AI models such as Deep Neural Networks or Unsupervised Learning algorithms. Course assignments give students familiarity with programming in TensorFlow Keras and proficiency in designing, training and optimization of their own AI models.
AERO40004 - Engineering Practice 1: Professional Skills
Introductory course aimed at development of experimental skills, including lab report writing.
2020 - present: Teaching Fellow, Imperial College London
2019 - 2020: Lecturer, INTO City, University of London
2016 - 2019: Director of Curriculum, Reach Cambridge
2012 - 2016: PhD in Physics (Optoelectronics), University of Cambridge
2011 - 2012: MPhil in Physics (Optoelectronics), University of Cambridge
et al., 2016, Photon recycling in lead iodide perovskite solar cells, Science, Vol:351, ISSN:0036-8075, Pages:1430-1433
et al., 2014, Structure Influence on Charge Transport in Naphthalenediimide–Thiophene Copolymers, Chemistry of Materials, Vol:26, ISSN:0897-4756, Pages:6796-6804
et al., 2014, Near-edge X-ray absorption fine-structure spectroscopy of naphthalene diimide-thiophene co-polymers, The Journal of Chemical Physics, Vol:140, ISSN:0021-9606, Pages:164710-164710
et al., 2014, Two-Dimensional Carrier Distribution in Top-Gate Polymer Field-Effect Transistors: Correlation between Width of Density of Localized States and Urbach Energy, Advanced Materials, Vol:26, ISSN:0935-9648, Pages:728-733