Mike Schachter
Verified Expert in Engineering
Neuroscience Developer
Castro Valley, CA, United States
Toptal member since July 14, 2022
Mike has over 20 years of experience in machine learning, data science, and computational biology. His expertise includes signal and image processing, working with unstructured data such as images, video, audio, and text, and he is proficient in time series analysis. Extending from leveraging cloud platforms such as GCP and AWS to writing Python, R, C++, and Java code, Mike's technical experience resulted in significant contributions to the field of neuroscience.
Portfolio
Experience
- Python - 12 years
- Neuroscience - 12 years
- Web Development - 10 years
- Machine Learning - 10 years
- Time Series Analysis - 6 years
- Data Science - 6 years
- OpenCV - 3 years
- Bioinformatics - 1 year
Work Experience
Postdoctoral Fellow in Data Science
Parker Institute for Cancer Immunotherapy
- Performed the analysis of transcriptomic data obtained from hundreds of subjects and thousands of single cells. Currently focused on analyzing tumor-immune microenvironment in gliomas.
- Implemented spatial biology technologies by analyzing multiplex images of tumors.
- Worked with a team of academic collaborators to test hypotheses and aggregate clinical and molecular data.
Data Scientist
- Derived insights related to the Google Assistant search queries by performing unsupervised analysis using the BERT and clustering models.
- Oversaw establishing and maintaining the requirements of quantitative and qualitative metrics of Google Assistant for the release of Chromecast for Google TV.
- Worked with various software development teams for Google Assistant on Android TV to develop metrics for evaluating search quality.
Data Scientist
Inscopix
- Refined and automated video processing algorithms and pipelines using machine learning.
- Quantified brain activity in awake, behaving animals using time series analysis.
- Participated in collaborative efforts to develop neurodegenerative disease assays.
Doctoral Researcher
University of California, Berkeley
- Extracted complex acoustic features from audio signals using DSP and time-frequency analysis.
- Applied multivariate time series analysis to brain signals to extract their meaning, related to work in brain-machine interfaces.
- Taught classes in Machine Learning in Python and Statistics in R to graduate students.
- Researched deep networks and implemented basic neural network algorithms.
Project History
Study of Neuropsychiatric Diseases Using Machine Learning
https://www.frontiersin.org/articles/10.3389/fnins.2019.00176/fullAcoustic Features Decoding from Brain Activity
Single Neuron Activity Simulation
https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000899Education
PhD in Neuroscience
University of California, Berkeley - Berkeley, CA
Bachelor's Degree in Mathematics
Temple University - Philadelphia, PA
Certifications
Applied Bioinformatics
University of California San Diego
Skills
Libraries/APIs
Scikit-learn, PyTorch, TensorFlow, OpenCV
Tools
MATLAB
Languages
Python, R, C++
Industry Expertise
Bioinformatics
Platforms
Google Cloud Platform (GCP), Amazon Web Services (AWS)
Other
Neuroscience, Data Science, Time Series Analysis, Machine Learning, Web Development, Computational Biology, Mathematics, Computer Science, BERT, Big Data, Deep Learning, Computer Vision, Distributed Systems, Audio, Signal Analysis, Statistics, Probability Theory, Probabilistic Graphical Models, Information Theory, Time Series, Digital Signal Processing, Multivariate Statistical Modeling
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