Georgia Institute of Technology and Emory University, Atlanta, GA August 2020 – May 2025 (Expected)
Candidate for Ph.D. in Biomedical Engineering
Georgia Institute of Technology, Atlanta, GA August 2017 – August 2020
Candidate for Bachelor of Science in Biomedical Engineering
Skills
Programming: C++, Python, MATLAB Concepts: Data Analytics (Keras, Scikit-Learn), Circuits and Electronics, Digital Signal Processing, AWS, Computational Neuroscience, Systems Neuroscience, Medical Imaging Language: French (intermediate), English (native), German (native), Romanian (native) Extra- Curricular: Girls Who Code Club Facilitator, STEM Professional School Partnership, Women in Engineering, M&M Mentorship Program, BMES Research Committee, Brainhack ATL, Computational Neuroscience Training Program Recruitment and Outreach
Teaching
TA for Quantitative Engineering Physiology Lab 1
In charge of facilitating 4 teams during lab, a total of 24 students, through the process of designing and condition with own experiment
TA for Problem Solving in Biomedical Engineering
Facilitating a group of 8 students through 4 phases: defining the problem and design, conceptualizing and quantifying the model, building a proof-of-concept, and testing
Gave Signal and Processing Lecture to class of 250 Students for phase 3
Research
Group Research, Atlanta, Ga. September 2020 – Present MIND Lab and Jaeger Lab Dr. Keilholz co-advised by Dr. Jaeger Simultaneous optical imaging and fMRI of neural dynamics
Simultaneous optical imaging and fMRI of neural dynamics
Relationships between pupil diameter and spontaneous functional cortical activity
Changes in cortical dynamics during learning of sensorimotor task
Group Research, Atlanta, Ga. August 2020 – May 2021 Bio-MIB Lab Dr. Wang Precision staging and time series prediction using machine learning
Wrote python code to store and access large MIMIC-4 dataset
Implemented an LSTM Autoencoder in Keras for time series prediction
Trained an autoencoder to predict the progression of sepsis patients’ vital signs over the next 12 hours
Group Research, Atlanta, Ga January 2019 – May 2020 Haider Neuro Lab Dr. Haider Analyzing Local Field Potential and Spike data to determine the dominant responses in mice V1.
Wrote MATLAB code to store and access large data sets remotely as well as code for the analysis pipeline
Writing a pipeline to analyze spike data based on input stimuli
Characterize ON and OFF responses in excitatory versus inhibitory neurons across cortical layers
D.A.A.D RISE Research Scholarship, Aachen, Germany May 2019 – July 2019 Brain Imaging Facility in Neuro Phycology Dr. Mathiak Implementing convolutional neural networks for image classification in MRI T1 weighted images
Implemented a residual network (ResNet) to classify image quality based on random head motion artifacts
Trained a convolutional neural network (CNN) to detect the left and right side of the brain for quality assurance
Wrote code in python to evaluate the accuracy of trained CNN
Trained a CNN to distinguish between left and right-handed patients on UK BioBank data
Group Research, Tallahassee, FL May 2018 – July 2018 Scientific Computing Department FSU Dr. Amirhessam Tahmassebi • Graph signal analysis for characterizing dementia networks • Dynamical systems analysis for determining driver nodes in dementia evolution
Group Research, Atlanta, Ga August 2018 – December 2018 Prototype for a hand accelerometer that can be used to help clinicians detect OFF-periods in Parkinson’s Patients
Trained a math model (Perceptron) to distinguish between ON and OFF periods
Created a prototype with Arduino compatible devices and Tested our device on our model
Independent Research, Tallahassee, Fl June 2016 – December 2016 Using Graph Theory for the Detection of Alzheimer’s Disease
Used statistical analysis to find a correlation between the connectivity in nodes and Alzheimer’s Disease
Work published in an Extended Essay
Publications
Nan Xu, Theodore J. LaGrow, Nmachi Anumba, Azalea Lee,4, Xiaodi Zhang, Behnaz Yousefi, Yasmine Bassil, Gloria Perrin Clavijo, Vahid Khalilzad Sharghi, Eric Maltbie, Lisa Meyer-Baese, Maysam Nezafati, Wen-Ju Pan, Shella Keilholz (2021). Functional Connectivity of the Brain Across Rodents and Humans. arXiv
Williams B., Del Rosario J., Coletta S., Brichler E., Muzzu T., Speed A., Meyer-Baese L., Saleem A., Haider B (2021). Spatial Modulation of Dark Versus Bright Stimulus Responses in Mouse Visual System. Current Biology, 31(18). https://doi.org/10.1016/j.cub.2021.06.094
Presentations & Publications
Meyer-Baese L., Morrissette A., and Jaeger Dieter. “Spatiotemporal Patterns of Cortical Coupling to Pupil Fluctuations During Spontaneous Behavior”
Barrels 34th Annual Conference Short 10 min talk
Meyer-Baese L., Kashyap A., Zhang X., Pan WJ., and Keilholz S. “Generative Models Linking Neuronal Local Field Potentials with fMRI in Rat Somatosensory Cortex”
OHBM 2021 Poster Presentation
Meyer-Baese L., Roecher E., Moesch E., Bzdok D., and Mathiak K. “Convolution Neural Networks for the Classification of Brain Hemispheres: Handedness Application in MRI-T1 weighted Images”
SPIE Real-Time Image Processing and Deep Learning 2020
Roecher E., Moesch L., Thiele F., Meyer-Baese L., Eisner P., Zweerings J., Sarkheil P., Mathiak K. "Machine Learning Approaches for Real-Time Quality Assurance of MRI Images”
Real-time functional imaging and neurofeedback conference Poster
Meyer-Baese, L. and Tahmassebi A. “Graph Signal Processing in Application to Diagnosis of Dementia”
SPIE Real-Time Image Processing and Deep Learning 2020