Systems and Computer Science

B.S.
Howard University
2018

Computer Science (Artificial Intelligence, Computer Vision, and Human-Computer Interaction)

Ph.D.
Howard University
2021

Applied Artificial Intelligence

AI & ML in Healthcare

Natural Language Processing and Understanding

Computational Biometrics

Human-Computer Interaction

Artificial Inteliigence

Computer Vision

Intro to Machine Learning

This course introduces fundamental topics related to machine learning, including techniques for learning from data and applying these algorithms to application settings; other topics covered include Bayesian methods, linear classifiers such as the perceptron, regression, and non-parametric methods such as k-nearest neighbors. Specifically, we will study how computers can learn from data in this course. We will discuss fundamental concepts of machine learning and practice applying these concepts. The centerpiece of the course is a sequence of interactive learning labs that cover the concepts using real data. After taking this course, students will be familiar with some important approaches and algorithms, including linear models and neural networks for prediction and classification. Students will also learn some of the standard vocabularies of machine learning. The course is offered as a cross-listed course for graduate and undergraduate students. 

Computer Science III

Computer Science III teaches students advanced data structures and algorithmic programming. This course after taking or receiving credits for Computer Science II. While the course was initially taught in C/C++, this variant of the course was revamped and taught in Python. The course mostly focuses on CS majors and minors; however, all majors are welcome.

Computer Science II

Computer Science II teaches students basic data structures and object-oriented programming. This course after taking or receiving credits Computer Science I. While the course was initially taught in C/C++, this variant of the course was revamped and taught in Python. The course is mostly focused on CS majors and minors; however, all majors are welcome.

Computer Science I

Computer Science I teaches students advanced programming concepts. Most students usually take this course after taking or receiving credits for the intro course. While the course was initially taught in C/C++, this variant of the course was revamped and taught in Python. The course is mostly focused on CS majors and minors; however, all majors are welcome.

Grants, Honors, and Awards

2022 – Environmental Impact Data Collaborative/Bezos Earth Fund

2023 - Awarded $500,000 research gift, split into two $250,000 payouts, through Blocpower.io.

- Developing a distributed, realtime open source data platform with a personal ownership model.

- Piloting the developed platform with indoor air quality sensors in the DC-Baltimore area.

2022 – Amazon Sponsored Research Award

2023 - Awarded $80,000 research gift through Amazon to pursue research into healthcare and AI.

- Developing an AI model to understand and map clinical notes to the lab report.

- Detecting and predicting possible side effects from merging clinical notes and biomarkers.

2022 – NIH/AIM-AHEAD Course Development Mini Grant 

2023 - Awarded $20,000 mini-grant for course development through the NIH AIM-AHEAD initiative. 

- Developing a bridge course for social science and natural science majors to learn AI/ML.

- Course will be administered to address issues in diversity and equity in data science fields.

2022 – NVIDIA Jetson Nano Hardware Grant 

2023 - Awarded a grant of 20 Jetson Nano Developer Kits through a competitive application process.

- Designing a collaborative course structure on applying hardware to course content.

2020 – Vertically Integrated Project

2021 - Served as a faculty advisor to a mentorship and industry partnership program for 2 semesters.

- Awarded a grant of $30,000 for two semester: $22,000 funding students and $8000 towards 

   research and development.

2020 – Google Cloud Research Credit Grant

2021 - Awarded a grant to be used towards utilizing cloud computing resources from Google Cloud.

- The award totaled for about $5300 for a duration of one academic year.

2018 – Graduate Assistantship Award

2020 -Awarded ~ $58,000 annually to cover tuition and stipend expenses.

2020 National Security Agency Fund

- Awarded $16,000 toward tuition for dissertation research towards Biometric Identification.

2019 – Edmund & Maria Pioleau Award

2020 - Awarded $1,000 in scholarship from Howard University towards tuition and fees expenses.

2018 Magna Cum Laude Honors

- Graduated B.S. in Systems and Computer Science with honors and GPA > 3.6.

2014 – Founder’s Scholarship Award

2018                - Awarded by Howard University upon acceptance for 4 years of undergraduate study.

                        - Total award valued ~ $150,000 covering full tuition, room, board, and book stipend. 

Professional service and organizational memberships

2023 Program Committee Member, International conference on Innovations in Computing Research

2023 Reviewer, Workshop on the Social Impact of AI for Africa @ AAAI

2022 Program Committee Member, ACM Special Interest Group on Computer Science Education

2022 Session Chair, International Conference on Bioinformatics and Biomedical Science 

2022 – Editorial Board. American Journal of Artificial Intelligence

Present              

2022 – Review Board. American Journal of Medical Imaging

Present

2022 – InSTEM Mentor.  National Science and Technology Medals Foundation

Present

2021, Program Committee Member, IEEE International Conference On Healthcare Informatics

2022  

2020 – Professional Member, Association for Computing Machinery (ACM)

Present

2022 – Professional Member, Institute of Electrical and Electronics Engineers (IEEE)

Present

2014 – Student Member, National Society of Collegiate Scholars (NSCS)

2018

Research articles, conference papers, and abstracts

Aryal, S. K., Williams, C. F., Rosemond, K. J., Salaam, C., & Washington, G. (2020, November). Self-Efficacy 

Sydney: An EHWLT for Young Children with Chronic Illness. In Extended Abstracts of the 2020 Annual 

Symposium on Computer-Human Interaction in Play (pp. 178-181).

Washington, G., Mance G., Aryal, S.  and Kengni, M. (2021, February) ABL-MICRO: Opportunities for Affective 

AI Built Using a Multimodal Microaggression Dataset. In Proceedings of the 4th Workshop on Affective 

Content Analysis @ AAAI (AffCon2020).

Washington, G., Mejias, M., Aryal, S., Shurn, T., & Burge III, L. (2021). Opportunities for using HBCU culture to 

teach elementary data structures to computing students. Journal of Computing Sciences in Colleges, 37(3), 

63-73.

Aryal, S. K., Prioleau, H., & Burge, L. (2022). Acoustic-Linguistic Features for Modeling Neurological 

Task Score in Alzheimer’s. In PACIFIC SYMPOSIUM ON BIOCOMPUTING 2023: Kohala Coast, Hawaii, USA, 3–7 January 2023 (pp. 335-346).

Aryal, S.K., Barrett, T., Washington, G. (2022) “Comparative Analysis of Mask RCNN Variants for Ear Mask 

Segmentation” International Conference on Bioinformatics and Biomedical Science.

Aryal, S.K., Prioleau, H., Washington, G. (2022) “Sentiment Classification of Code-Switched Text 

using Semantic Similarity”. In Proceedings of the 8th International Conference on Natural Language Computing. 

Pokhrel, A.,  Subedi, N., Aryal, S.K., (2023). “Evaluating feature importance for COVID-19 

spread and mortality with decision trees” (Student Paper). AAAI . (in press)

Aryal, S., Ngueajia, M., Aryal, S.K., Washington, G., (2023). “Hey, Siri! Why are You Biased Against 

Women?” (Student Paper). AAAI. (in press) 

Aryal, S. K.,  Prioleau, H., and Aryal, S. Sentiment analysis across multiple african

languages: A current benchmark. In Social Impact of AI in Africa Workshop @ AAAI, 2023. (in press)

Aryal, S. K.,  Prioleau, H.,  (2023). Howard University Computer Science at SemEval-2023 Task 12: A 2-Step System Design for Multilingual Sentiment Classification with Language Identification. In Proceedings of the 17th International Workshop on Semantic Evaluation. (in press)

Shah, U., & Aryal, S. K. (2023). Experimenting with Multimodal AutoML: Detection and Evaluation of 

Alzheimer's Disease. ICLR 2023, Tiny Papers. (in press)

Aryal, S. K., & Adhikari, G. (2023). Evaluating Impact of Emoticons and Pre-processing on Sentiment 

Classification of Translated African Tweets. ICLR 2023, Tiny Papers. (in press)

Prioleau, H., & Aryal, S. K. (2023). Feature Importance Analysis for Mini Mental Status Score Prediction in 

Alzheimer’s Disease. ICLR 2023, Tiny Papers. (in press)

Aryal, S. K., Sapkota, H., & Prioleau, H. (2023). Zero-Shot Classification Reveals Potential Positive Sentiment 

Bias in African Languages Translations. ICLR 2023, Tiny Papers. (in press)

Aryal, S. K.  & Tiwari, S. (2023), Fast-Tracking Your Geospatial Queries with RTree-based Point-in-Polygon 

and Nearest Neighbor Search. Howard University Research Symposium., Washington, DC.

Aryal, S. K. & Acharya, S (2023). Unlocking the Road Ahead: Predicting Future Car Locations with Rank 

Learning. Howard University Research Symposium.

Aryal, S. K. & Abdus-Shakoor, A.  (2023), Bracing for Impact: Modeling Hypothetical Detonations with 

NukeMap and Python. Howard University Research Symposium.

Aryal, S. K. & Sankah, J. (2023), Addressing Datagaps in Ear Biometrics Research: Diverse Ear Dataset. 

Howard University Research Symposium.

Aryal, S. K. & Eshun, F. (2023), Evaluating the Robustness of Open-Source Face Verification Models. Poster 

Howard University Research Symposium.

Books and Chapters

Aryal, S., Okunji, P., Shara, N., Libin, A., Jackson, A. D., Laurence, B., Symonette Ferguson, E., Washington, G., & Burge, L. (2023). Bias in Data, Artificial Intelligence and Machine Learning: Community Case Studies. Beech, B. M., & Heitman, E. (Eds.), Race and Research: Perspectives on Minority Participation in Health Studies 2nd ed., Vol.2) American Public Health Association. (in press)

Conference and Poster Presentations

Aryal, S. K., Thomas, Shondace., Johan Greene, & Gloria Washington (2019). EmotiColl: Towards Understanding and Prediction of Harmful Acts by Depressed Students. Poster presented at the Howard University Research Symposium.

Aryal, S. K., Prioleau, H., & Burge, L. (2022). Acoustic-Linguistic Features for Modeling Neurological 

Task Score in Alzheimer’s. Poster presented at the PACIFIC SYMPOSIUM ON BIOCOMPUTING, Kohala Coast, Hawaii, USA, 3–7 January 2023.

Aryal, S., Aryal, S.K., Washington, G. (2023) Skin Tone Detection using K-means Clustering. Poster presented at the Howard University Research Symposium.

Shah, U., & Aryal, S. K. (2023). Experimenting with Multimodal AutoML: Detection and Evaluation of 

Alzheimer's Disease. Poster presented at the Howard University Research Symposium.

Aryal, S. K., & Adhikari, G. (2023). Evaluating Impact of Emoticons and Pre-processing on Sentiment 

Classification of Translated African Tweets. Poster presented at the Howard University Research Symposium.

Prioleau, H., & Aryal, S. K. (2023). Feature Importance Analysis for Mini Mental Status Score Prediction in 

Alzheimer’s Disease. Poster presented at the Howard University Research Symposium.

Aryal, S. K., Sapkota, H., & Prioleau, H. (2023). Zero-Shot Classification Reveals Potential Positive Sentiment 

Bias in African Languages Translations. Poster presented at the Howard University Research Symposium.

Aryal, S. K.  & Tiwari, S. (2023), Fast-Tracking Your Geospatial Queries with RTree-based Point-in-Polygon and Nearest Neighbor Search. Poster presented at the Howard University Research Symposium., Washington, DC.

Aryal, S. K. & Acharya, S (2023). Unlocking the Road Ahead: Predicting Future Car Locations with Rank Learning. Poster presented at the Howard University Research Symposium.

Aryal, S. K. & Sankah, J. (2023), Addressing Datagaps in Ear Biometrics Research: Diverse Ear Dataset. Poster presented at the Howard University Research Symposium.

Aryal, S. K. & Eshun, F. (2023), Evaluating the Robustness of Open-Source Face Verification Models. Poster presented at the Howard University Research Symposium.