Biomedical & Clinical Informatics Lab
- Designed and tested machine learning pipelines for automated diagnosis using healthcare data such as imaging and medical coding.
- Worked both independently and under supervision, providing weekly reports and recommendations for overcoming technical obstacles.
- Communicated technical results to a diverse team of managers, investors, clinicians, engineers, and students.
New York University
New York City College of Technology
John Jay College of Criminal Justice
- Designed & taught courses including Python for Engineering, Computer Programming and Problem Solving with Python, and Calculus I & II, and more.
The Graduate Center of the City University of New York
- Designed, implemented, and evaluated encryption-friendly adaptations of machine learing algorithms in C++
- Used object-oriented programming to create a homomorphic encryption library in C++.
The Graduate Center, CUNY
DePaul University
DePaul University
Python, git, SQL
sklearn, keras, tensorflow
Object-oriented programming
TeX, Matlab
Problem solving
Statistics, Machine learning
Big data, cloud computing, databases
Data cleaning, Data engineering
Algorithms
Fast learner
Collaboration, direct communicator
Proactive problem solving
Translating tech jargon
Eye for detail
AngioAid
AngioInsight / University of Michigan
Project lead. Designed, tested, and evaluated machine learning pipeline for real-time evaluation of severity of stenosis, or thinning, of the coronary arteries.
- Cleaned and pruned large, messy data from 5 sources to create a curated data set, discarding unusable or irrelevant data
- Built and maintained an accessible data pipeline with Python and SQL
- Engineered features to extract relevant and actionable information from data regarding the severity of stenosis
- Analyzed complex model results to discover actionable insights
- Increased model performance with a novel automated data cleaning pipeline
Polytrauma Decision Support System
University of Michigan
Project lead. Used machine learning and computer vision to design and develop real-time recommendation algorithms for clinical decision-making during time sensitive trauma treatment.
- Developed algorithms for automated segmentation of abdominal organs in CT volumes
- Trained cascading classifiers for categorization of CT volume slices based on visualized organs
- Coordinated a small group of talented graduate and undergraduate students
Cardiac Event Database
Toyota Research / University of Michigan
- Designed and populated a SQL database unifying 500,000+ health records from 6+ sources into one cohesive data repository.
- Coded a pre-processing pipeline in Python to extract relevant features from text files containing clinical notes and heterogeneous patient records.
Privacy-Preserving Machine Learning
The Graduate Center, CUNY
- Designed, implemented, and evaluated encryption-friendly adaptations of machine learing algorithms in C++
- Algorithms include privacy-preserving versions of naive Bayes, decision tree, and third-party search
- Used object-oriented programming to create a homomorphic encryption library in C++
- Wood, A., Najarian, K., & Kahrobaei, D. (2020). Homomorphic Encryption for Machine Learning in Medicine & Bioinformatics. Accepted to ACM Computing Surveys (CSUR).
- Wood, A., Shpilrain, V., Najarian, K., & Kahrobaei, D. (2019). Private Naive Bayes Classification of Personal Biomedical Data: Application in Cancer Data Analysis. Computers in Biology and Medicine, 105, 144-150. doi: 10.1016/j.compbiomed.2018.11.018.
- Wood, A., Soroushmehr, S.M.R., Farzaneh, N., Ward, K., Fessell, D., Gryak, J., & Najarian, K. (2018) Fully Automated Spleen Localization and Segmentation Using Machine Learning and 3D Active Contours. In Proceedings of the 40th IEEE Engineering in Medicine and Biology Society Conference (pp. 53-56). doi: 10.1109/EMBC.2018.8512182
- Wood, A. (2018). Private-Key Fully Homomorphic Encryption for Privacy-Preserving Classification of Medical Data. (Doctoral dissertation, The Graduate Center of the City University of New York, New York, NY, USA). Available from CUNY Academic Works (No. 2888).
- Wood, A., Shpilrain, V., Najarian, K., Mostashari, A., & Kahrobaei, D. (2018). Private-key fully homomorphic encryption for private classification. In International Congress on Mathematical Software - ICMS 2018 (pp. 475-481). doi: 10.1007/978-3-319-96418-8_56.
- Farzaneh, N., Soroushmehr, S.M.R., Patel, H., Wood, A., Gryak, J., Fessell, D., & Najarian, K. (2018). Automated Kidney Segmentation for Traumatic Injured Patients through Ensemble Learning and Active Contour Modeling. In Proceedings of the 40th IEEE Engineering in Medicine and Biology Society Conference (pp. 3418-3421). doi: 10.1109/EMBC.2018.8512967
- Li, Z., Derksen, H., Gryak, J., Hooshmand, M., Wood, A., Ghanbari, H., Gunaratne, P., Najarian, K. (2018). Supraventricular tachycardia detection via machine learning algorithms. In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 2419-2422). doi: 10.1109/BIBM.2018.8621164.
LGBTQ+ Postdoc Circle
- Co-organizer (2019-2020)
Student Cryptography Seminar
- Co-organizer (2014-2016)
Computer Science Students' Association
- Chairperson (2016)
- Elections Committee
- Curriculum Committee
- Executive Committee
Doctoral and Graduate Students' Council
- Computer Science representative (2014-2016)
- Student Technology Fee Committee (2015-2016)
- Curriculum Committee
- Executive Committee
Graduate Council
- Computer Science students' representative (2014-2016)
- Computer Science Fellowship
The Graduate Center, CUNY - Research Foundation Assistantship
The City University of New York - Graduate Assistantship
The Graduate Center, CUNY - Mathematics Fellowship
The Graduate Center, CUNY - Mathematics Fellowship
DePaul University - Presidential Scholarship
DePaul University - Shelby Endowed Scholarship
DePaul University - O'Malley-Liput Endowed Scholarship
DePaul University - Pry Memorial Scholarship
DePaul University - Frank & Frances Zeman Memorial Scholarship
DePaul University
Passed qualifying examinations and requirements as a graduate student in the following departments.
Department of Computer Science
- Algorithms & Theory
- Artificial Intelligence
- Systems and Computational Science
Department of Mathematics
- Abstract Algebra
- Algebraic Topology
Department of Mathematical Sciences
- Algebra
- Analysis
Designed and led courses as an adjunct lecturer at New York University, John Jay College of Criminal Justice, and New York City College of Technology. Utilized experiential and collaborative learning techniques. Mentored undergraduate students in a one-on-one capacity. Courses taught include:
Computer Programming and Problem Solving with Python
- Final presentation: Generic-case complexity in non-commutative cryptography (slides)
- Final presentation: MixCoin: Anonymity for BitCoin with Accountable Mixes (slides)
- Midterm: Behavior of Distance Metrics in High Dimensional Spaces (report)
- Final: Quantization & Statistical Analysis of Data Using a Bayes Decision Rule (report)
- Spring 2013. DePaul University (study guide)