Name: Genomoci epidemiology of infectious disease
Goal: Reconstructing person-to-person transmission events using genomic and epidemiological data can be valuable in designing strategies to control and prevent the spread of infectious diseases.
My Role: Research Scientist
Project Description: Sequenced genetic data from strains in an outbreak for pathogens that evolve slowly, such as mycobacterium tuberculosis (due to low mutation rate), can be partially informative about who infected whom; however, it should be supported with epidemiological data (such as infection and sampling time) to understand the transmission network better. This proposal will apply Bayesian inference to incorporate four unobserved processes: mutation, between-host transmission (epidemiology), within-host evolution, and unsampled cases.
BC TB DATA
Name: Host factor transmissibility risk prediction for Tuberculous outbreak
Goal: Estimate the TB patient’s risk of onward transmission.
My Role: Mathematical modeling and Developing a Package
Project Description: In this project, epidemiological information (sampling times) and whole genome sequence data from almost 1800 culture-positive tuberculosis (TB) patients between 2005 and 2014 will be used to reconstruct transmission networks (via TransPhylo) and then estimate the pairwise transmission probabilities. In this work, metadata (such as age, type of disease, gender, etc.) will be used as feature space, and we will assign an overall transmission probability for each patient as a response variable to build our machine learning models.
R shinny app for BCCDC
Name: Covid-19 simulation app
Goal: Simulation of Covid-19 spread by manipulating the epidemiological parameter
My role: Developing app and Data analysis
Project Description: This model simulates the emergence of an infectious illness in a population by using a stochastic branching process that was inspired by Hellewell et al. (2020). In this simulation, there are variables that either increase illness development (such the importation of cases) or decrease disease growth (such as contact tracing and subsequent isolation). When a case is first created, disease and behavioral parameters are stochastically generated from a user-defined distribution. This includes characteristics like the timing of subsequent infections and the start of symptoms (serial intervals). When the case is constructed, illness milestones like symptom onset or secondary infections are effectively "pre-loaded," but they don't really happen in the simulation until the appropriate time-step since our simulation advances one time-step at a time. This provides snapshots of the simulation at each timestep and enables procedures to be time-dependent and/or reliant on the present status of other instances (for example, the effectiveness of contact tracing may rely on the quantity of active cases that need tracing).
Computer generated music
Name: Simulation of musical composition
Goal: Human computer interaction to generate musical piece
My role: Mathematical modelling and Programming
Status: Finished (needs to be commercialized)
Project Description: The idea is to generate music at random that satisfies both the statistical distribution of the composer's hypothetically selected unique musical notes and the laws of musical theory. Our software can make music or aid musicians has been in practice for quite some time.
English learning app
Goal: Android app for Persian speaker to learning English language
My role: Manager and Android developer
Project Description:Oriolingo is an English language learning application for Persian speakers. Developed in five volumes, the package is suitable for language learners from the basic to lower-intermediate levels, and each volume contains chapters classified by topic. Each chapter consists of three sections: ‘words’, ‘sentences’ and ‘conversations’, each of which is in turn made up of different sub-sections including ‘lesson’, ‘review’ and ‘exercises’. The variety of exercises included in this package allows the user to retain the words and sentences in their long-term memory. The exercises include meaning-based, grammatical, listening and spelling exercises and they aim to help the learner master the words and sentences covered in each of the chapters. This application is recommended for beginner English language learners who wish to learn the basic vocabulary and sentence structure of English in different topics of everyday life.