I am a Postdoctoral Fellow at Northwestern University. I am ingenious and
resourceful Transportation Data Scientist with a proven track record of success
in research and hands-on experience developing cutting-edge database solutions,
statistical modeling, data products, and computer vision systems aimed at improving
transportation system management and operations. Has worked as an architect and
application developer on a variety of projects that required the use of data mining
and machine learning models to solve large-scale, complex, and difficult transportation problems.
I'm broadly interested in computer vision and machine learning.
My research involves visual reasoning, vision and language, image generation,
air taxis, naturalistic studies, and autonomous vehicles.
I received my PhD from University of Missouri-Columbia, advised by
[01/01/2023] Join Northwestern University as a Postdoctoral Student under the Supervision of Dr. Ulas Bagci
[12/17/2022] Graduated with a PhD from the University of Missouri-Columbia
[11/07/2022] Driver Maneuver Detection and Analysis using Time Series Segmentation and Classification was accepted for publication
[10/12/2022] Mobile Sensing for Multipurpose Applications in Transportation was accepted for publication
[06/20/2022] Oral presentation at CVPR: A Region-Based Deep Learning Approach to Automated Retail Checkout
Driver Maneuver Detection
Yaw Adu-Gyamfi et al.
Journal of Transportation Engineering Part A: Systems
Pavement Roughness Estimation
Advances in Data Science and Adaptive Analysis
Vehicle Anomaly Detection
Armstrong Aboah*, Maged Shoman*, Vishal Mandal, Yaw Adu-Gyamfi et al.
Automatic Retail Checkout
Maged Shoman*, Armstrong Aboah*, Yaw Adu-Gyamfi et al.
Bus Delay Prediction
Maged Shoman, Armstrong Aboah, Yaw Adu-Gyamfi
Journal of Big Data Analytics in Transportation
Pavement Condition Prediction
Ashkan Behzadian, Tanner Wambui Muturi, Amanda Mullins, Armstrong Aboah, Yaw Adu-Gyamfi et al.
Armstrong Aboah, Michael Boeding, Yaw Adu-Gyamfi
GC-GRU-N for Traffic Prediction using Loop Detector Data
Maged Shoman, Armstrong Aboah,Abdulateef Daud, Yaw Adu-Gyamfi
IEEE Transactions on Intelligent Transportation Systems
A simple NLP algorithm for recommending movies.
In this project I developed a simple movie recommendation
system, that returns the top 10 movies base on a given movie title.
The goal of this Project was to understand the driver's environment in a naturalistic settings.
This repository contains implementations of multiple deep learning models
(U-Net, FCN32 and SegNet) for multiclass semantic segmentation of the CamVid dataset.
This project involves a multiclass classification of the weather. Three main multi-classes were considered.
They are '[day,rainy]', '[night,clear]', and '[day,clear]'. The project utilizes image data sourced from smarphone camera.