Neurodata Tutors

Abhijit is an electrical engineer by training, with a strong drive to understand the brain. He uses his quantitative skills in signal processing and machine learning to solve convoluted problems in cognitive computational neuroscience. He is currently a graduate student in the Department of Bioinformatics at UBC. Under the guidance of Dr. Todd Woodward, he is investigating the physiological and behavioral effects of transcranial alternating current stimulation (tACS). His work involves using brain imaging techniques like EEG, MEG, and fMRI and developing analysis workflows to process the data. These include preprocessing, dimensionality reduction of the imaging data, and prediction. He is also involved in designing psychophysical experiments and analyzing behavioral data. Although most of his coding experience is in MATLAB, he also has some experience with Python, C, and Java. Abhijit’s email

Pankaj is a graduate student in Neuroscience at UBC. He is interested in building computational and quantitative tools to understand Brain functions and novel interventions in neurological disorders. He did Bachelor’s in Computer Science and MSc. in Interactive Technologies and had worked in industry as a software developer as well as a research engineer in academia, prior to joining UBC. He has experience working with open-source tools (OpenCV, EEGLab, OpenGL) and has contributed to some, such as HOMER. He has experience working with programming languages (Python, Matlab, C#, C++, shell scripts) on Windows and Linux platforms. At UBC, he works with Dr. Timothy Murphy on a project aimed to study how to induce neuroplasticity in neo-cortex in mice. Calcium imaging is his primary tool to record neural activity but he has some experience with EEG and NIRS data as well. Apart from these, he is interested in working with and learning about other imaging techniques such as TMS, fMRI and ECoG. Pankaj’s email

Peter is a graduate student working in the Haas lab, his background is in cell and developmental biology. He uses Xenopus laevis tadpoles to study early neuronal development and dendritic arborization. Peter has a particular interest in bioimage informatics and image analysis. His experimental work makes use of in vivo two-photon imaging to collect structural data of single neurons during development. Additionally, he performs calcium imaging experiments of entire populations of neurons. As a primarily self-taught coder, he has experience using Python to create data analysis pipelines to help automate the processing of experimental data. These include novel ways to visualize microscope images and volumes, using libraries to extract regions of interest from microscope data, analysis of calcium imaging data, statistical analysis and figure creation. Additionally, he has some previous experience with R and is currently using Matlab to control his microscope hardware. Peter’s email

Adrian has a passion for the future of technology, in particular the future of our efforts to understand human intelligence, artificial intelligence and the interface between humans and machines. He has combined his mixed background in computer and animal science, and is currently pursuing a PhD in computational neuroscience under the guidance of Dr. Jeremy Seamans at the UBC DMCBH. His work involves developing computational models of the function of neural ensembles, their relation to behaviour, and applications of machine learning algorithms in neural encoding, computer vision, and other multi-data-stream analysis paradigms. In addition, he regularly works as a TA for the department of Computer Science, and has experience working in and teaching a variety of coding languages, including Python, MATLAB, Java, Javascript, C and C++. Adrian’s email

Nick is a neuroscience graduate student with a background in Biomedical Engineering. He currently uses in vivo wide-field imaging of mesoscale cortical calcium activity to investigate cortex-wide activity dynamics in the mouse brain during social interaction. His previous research incorporates analysis from multiple data acquisition modalities, including 2-photon imaging of neuronal calcium indicators, behavior video data, implanted electrode recordings, and human EEG recordings. His primary coding experience is in MATLAB, but he also has some experience with Python. Nick’s email

Kaitlin is a Neuroscience PhD candidate with a background in cognitive science. Her research is focussed on identifying precise molecules and cell types participating in fear memory encoding and retrieval. In particular, her work involves the use of single cell transcriptomic techniques such as single cell RNA sequencing (scRNA-seq) and multiplexed fluorescent in situ hybridization (mFISH). As such, she is experienced in using R for the integration, dimensionality reduction, clustering, and identification of differential gene expression in scRNA-seq datasets. She furthermore is well-versed in the open-sourced image analysis software FIJI’s macro language (a Java-like language) and has developed user-friendly computational tools for mFISH analysis on this platform. Kaitlin furthermore has experience developing R Shiny Apps for sharing of simple, code-free analysis. In addition to her work, Kaitlin assists in the teaching of an R workshop for CAPS students at UBC alongside the DBC Tutorial. While her main language is R, she also has familiarity with Python and Java.

Nikita is a PhD Candidate in the Medical Genetics program, co-supervised by Dr. Wendy Robinson at BC Children’s Hospital Research Institute and Dr. Wan Lam at BC Cancer Research Centre. Her project focuses on characterising small RNAs in the human placenta and its cell types, while investigating the biological, clinical, and technical variables driving variation. She earned her BSc in Biomedical Genetics (2017) from Newcastle University, and her MSc in Genetics of Human Disease (2018) from University College London (UCL). Self-teaching herself R programming, she actively seeks out collaboration projects which measure different genomic data types to build up her experience. As the Co-Chair of the BC Children’s Trainee ’Omics Group (TOG), she organizes and leads workshops and support sessions at this data analysis and bioinformatics support group. Ultimately, she’s interested in applying her knowledge in elucidating how ancestry and ethnicity drive the genetic differences that exist between populations, and how we can better assimilate those differences towards providing truly personalized and individualistic diagnoses and treatment. Check out her website and GitHub!

Will is a PhD candidate in UBC’s Bioinformatics Training Program, co-supervised by Dr. Sara Mostafavi and Dr. Jessica Dennis. He received a BS in Computational Biology at Carnegie Mellon University in 2017, pursuing research in phylogenetics under Dr. Russel Schwartz.  His research investigates the role of genetic and non-genetic factors in complex traits and disorders. In particular, he investigates how the genetic regulation of DNA methylation and gene expression is affected by sex and environmental exposures. This involves integrating a variety of techniques from statistics, genetic epidemiology and computer science in order to better understand the function of genetic loci that increase disease risk. As a co-chair and past study group leader with the Trainee Omics Group (TOG), he has helped to organize and conduct several tutorials regarding everything from introductory concepts in R, differential methylation analysis, and gene set enrichment analysis.

Hannah is part of the Data Champions tutor team from the University of Victoria. She is a PhD candidate in the lab of Dr. Brian Christie. Her thesis work is on prenatal cannabis exposure and its affects on the developing hippocampus. She uses microscopy, electrophysiology, and behaviour in a rat model to study these brain changes. In her spare time, she likes hanging out with Autumn, her cat, and playing Dungeons and Dragons.

Megan is a UBC graduate student in the Granville lab located at the International Collaboration on Repair Discoveries (ICORD). Her work focuses on granzyme B’s contribution to the severity of radiation dermatitis. Her works involves PCR, Western blot/ELISA, Immunofluorescence, and Immunohistochemistry analysis. She is also a part of the ICORD Trainee Committee as a workshop coordinator. She has organized many workshops for the trainees of ICORD including R/Rstudio statistical workshop, ImageJ, Open Science Framework, and DeepLabCut workshop.