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Ph.D. in Biomedical Data Science

• Advised by Prof. Serena Yeung
• Convex Optimization (EE364A), Deep Learning for Computer Vision (CS231n), Natural Language Processing with Deep Learning (CS224n), Applied Multivariate Statistics, Representations and Algorithms for Computational Molecular Biology, Statistical Inference, Data Science for Medicine

B.S. in Mathematics, Computer Science, and Physics

• Dean's List (GPA 3.95/4)
• Partial Differential Equations, Advanced Linear Algebra, Calculus of Several Variables, Topics in Artificial Intelligence, Advanced Data Structures and Algorithms, Graph Theory, Uncertainty and Error Analysis, Numerical and Computational Methods in Physics, Analytical Mechanics, Quantum Physics

Graduate Teaching Assistant

• TA for an advanced course in computational methods for molecular biology. Topics ranged from algorithms for biological sequence alignment, phylogenetic tree creation, hidden Markov models, protein structure prediction, protein energetics, chemoinformatics, pharmacogenomics, and applications of classical machine learning methods for biomolecular data.
• Held office hours and graded assignments for a class of over 100 students.

Recitation Instructor

• Instructed in course material ranging from topics in bit-wise operations, counting, combinatorics, probability, and set logic.
• Lead one-hour recitation sessions for approximately 10 students once per week.

Undergraduate Teaching Assistant

• TA for summer introductory course in NoSQL databases with topics ranging from writing queries for non-relational databases to exploring different types of database models like graphical (Neo4j) and document-based (MongoDB).
• Graded assignments for class of over 20 students.

Recitation Instructor

• Instructed and reinforced topics discussed in lecture and explained course material including implementations of various graph algorithms, algorithm runtime complexities, sorting and string-matching algorithms, tree representations, and various algorithm design paradigms.
• Lead one-hour recitation sessions for approximately 15 students twice per week.

Apple PhD Fellowship in AI/ML Nominee

William K. Bowes Jr. Fellow, Stanford Graduate Fellowship

University of Denver Distinction in Computer Science

Hornbeck Scholar

Academic Fellow

• Course in R programming language for statistical learning.
• Engaged in weekly journal clubs and workshops for navigating graduate school and research.

Treasurer

• Served as treasurer co-managing a budget of over 8000 USD for an organization dedicated to providing a space for discussions and workshops in topics relevant to the African-American community.
• Participated in financial officer meetings with representatives from other affinity groups to approve funding for various on-campus events and programs.

Peer Leader

• Served as a mentor and leader for the E-STEM program, advising and assisting a group of incoming 1st year college students from minority backgrounds and historically underrepresented groups in STEM fields.
• Helped plan and run orientation weeks for E-STEM participants.

Planning Committee Leader and Facilitator

• Facilitated group discussions with 10-15 high school students on topics ranging from black identity to financial responsibility, education, and leadership.
• Co-organized the 2018 and 2019 BMIS summits.

Board Member

• Engaged as a member on a panel of undergraduate and graduate students advising the faculty of the Daniel F. Ritchie School of Engineering and Computer Science on improvements to department curriculum.

Executive Board Member

• Presented to students with African heritage on Ethiopian culture and cuisine as a part of a series of presentations on the African continent.