My name is Andres Ross and I'm very excited about the AI revolution we are experiencing. I love using applied mathematics and machine learning to solve a variety of problems.

Having worked in multiple interdisciplinary projects I believe links between different fields to be key in 21st-century research. I have experience in a wide variety of fields such as mathematical engineering, biophysics, AI for medicine, and molecular simulations.

Outside of work I enjoy basketball, fantasy stories and sunshine.


MSc applied math (Dr. Ortner)

  • Researching the use of ML techniques for molecular simulation.
  • Specifically, the use of nonlinear regression models.
  • Experience with, neural networks, SD, LSQR, ADAMS, linesearch methods, pre-conditioning, and other numerical methods.
  • Taken classes on: stochastic differential equations, advanced machine learning, control theory, optimal transport, numerical analysis and dynamical systems.

Astrophysics Research (Dr. Cline)

  • Studied the maximal amount of dark matter allowed in neutron stars.
  • Treating dark matter as a mirror copy of the neutron and using the theory for degenerate Fermi gases.
  • Using Runge-Kutta we showed that for a polytropic equation of state neutron stars cannot contain more than 16% dark matter.
  • Honors Thesis (Dr. Nave, Dr. Navarra)

    "Finite Difference and Discrete Event Simulation Applied To Copper Smelter Dynamics"

    • The objective was precise quantitative modelling of a copper smelter.
    • Such a model is important since it reduces the risk when investing large capital into smelter equipment.
    • The main challenge was accounting for the interplay of discrete events in the factory, with continuous dynamics inside the furnaces.
    • Using Runge-Kutta methods and Newton iterations combined with discrete event siulation I modeled the smelter.
    • Worked as the bridge between engineering and applied mathematics, learning a lot about interdisciplinary collaboration.
    • My work was published in the proceedings of Philip Mackey Honorary Symposium as well as on an issue of Process Modeling in Pyrometallurgical Engineering.

    The Ottawa Hospital Research Institute

    "Adaptive margins with an early system for motion-tracking errors in liver SBRT"

  • Worked on real time prediction of errors during radiation treatment.
  • I successfully developed a machine learning algorithm from the ground up that predicts errors with 84% accuracy.
  • For this, I used a combination of support vector machines, clustering, time series analysis, and statistical features.
  • I also developed a real-time program for adaptive breathing control.
  • This program would be used by patients to ease treatment.
  • This research was published for the 61st American Association of Physicists in Medicine Annual Meeting.
  • Abstract

    Biophysics Research (Dr. François)

    "Exploring the use of Mutual Information as a Fitness Function for Parameter Reduction"

  • The aim of my project was understanding mutual information as a cost function for parameter reduction in an immune detection model.
  • Using eigendecomposition techniques I reduced the dimensionality of the system and analyzed its behavior.
  • I was able to show that the mutual information outperforms other cost functions.



  • Python (PyTorch, SkLearn, SciPy, Pandas)
  • Julia (development of ACE.jl)
  • Java
  • Matlab and HTML (basic knowledge)


  • Message Passing Neural networks
  • Automatic differentiation and Adjoints
  • Modeling Differential Equations (partial and stochastic)
  • Signal Analysis (DTW, Fourier Transform, Euclidean Distance, MJC, etc)
  • Statistical Analysis (Mutual Information, entropy, standard deviation, skewness, kurtosis, etc)
  • Machine Learning (SVM, K-Means Clustering, Confusion Matrix, ROC, PCA, Regression, Logistic Regression, Lasso Regression, Normalization, etc)
  • Numerical analysis (Runge-Kutta, Krylov subspace, spectral, Quasi-Newton and methods)
  • Molecular Simluation (Langevin dynamics, photon spectra and ML inter atomic potentials)
  • Discrete Event Simulation, future event list, and interplay with thresholds of continous variables.


  • Spanish (Native Language)
  • English (Proficient)
  • French (Working Proficient)



    Navarra, A.; Wilson, R.; Parra, R.; Toro, N.; Ross, A.; Nave, J.-C.; Mackey, P.J. Quantitative Methods to Support Data Acquisition Modernization within Copper Smelters. Processes 2020, 8, 1478.

    Quantitative Methods to Support Data Acquisition Modernization within Copper Smelters

    A. Navarra, A. Ross, N. Toro, F. Ayala and T. Marin, “Quantitative methods for copper smelter reengineering projects”, Peer-reviewed contribution to the proceedings of the Philip Mackey Honorary Symposium (Copper 2019).

    proceedings of Philip Mackey Honorary Symposium

    M. Liu, A. Ross, J. E. Cygler, and E. Vandervoort. " TH-A-SAN2-10: Adaptive Margins with An Early Warning System for Motion-Tracking Errors in Liver SBRT.” Med. Phys. 46(6), 499-500, 2019. Presented at 61st American Association of Physicists in Medicine Annual Meeting (San Antonio, TX)



  • International Tuition Award - Sep 2020 UBC
  • Faculty of Science Graduate Award - Aug 2020 UBC
  • Science Undergraduate Research Award (funding for research) - May 2017 McGill University
  • One-Year Undergraduate Entrance Scholarship McGill - Jun 2016 McGill University
  • Hugh Brock Renewable Scholarship McGill - Jun 2016 McGill University


  • First Class Honours in Mathematics and Physics class of 2020 McGill University


Cell: (438)-928-8712