Negar Safinianaini

Aalto University

Finland

Teaching Experiences

I have been a teaching assistant (TA) both during my Doctoral and Postdoctoral research periods. Currently, at Aalto, I am the lead TA for the master/doctoral level Machine Learning Advanced Probabilistic Methods course.

Supervision Experiences

I have taken the doctoral supervision course at Aalto 2024.

I have been supervising four students at Aalto, and a paper is in the process of submission as the new method on the multiomics improved the state-of-the-art methods.

 

Theoretical Knowledge

Information Theory

Information Geometry

Convex Optimization

Optimization Algorithms: gradient descent, coordinate descent, natural gradient, mirror descent, stochastic gradient descent, alternating direction method of multipliers, alternating projections method, Dykstra, etc.

 Machine Learning: causal inference, regression, Laplace approximation, expectation-maximization, variational message passing, coordinate ascent variational inference, natural gradient based variational inference, stochastic variational inference, black-box variational inference, deep neural networks, variational autoencoders, hierarchical variational autoencoders, diffusion models, etc.

 Probabilistic Graphical Models: Markov chains, Hidden Markov models, Markov random fields, mixture models, Gaussian mixture models, mixtures of hidden Markov models, factor models, phylogenetic tree model with branch lengths and a continuous-time Markov model, etc.

Computational Biology, Computational Oncology, Multiomics, Single-cell, Mutational Processes, Medical Image Analysis, Tumor Genetics, Disease Genetics