Research Interests

• Computer Vision / Photography

• ML / Artificial Intelligence

• Autonomous Systems

Education

Relevant Coursework: [ PDF ]

1. University of Arizona, USA        Jan 2023 - Present

• Doctor of Philosophy in Optical Sciences

• Advisor: Dr. Florian Willomitzer

2. Northwestern University, USA        Sep 2020 - Dec 2021

• Master of Science in Computer Science, 2021

• Cumulative GPA: 3.95/4.00

• Advisors: Dr. Oliver Cossairt, Dr. Jack Tumblin, Dr. Florian Willomitzer, and Dr. Marc Walton

• Dissertation: "Quantitative Analysis of Holography Interpolation With NeRF"
  [ PDF ] [ Defense ]

3. University at Buffalo, The State University of New York, USA       Aug 2018 - May 2020

• Bachelor of Science in Computer Science With Distinction, 2020

• Magna Cum Laude

• Advisor: Dr. Nils Napp

• [ Commencement ] [ ALANA Celebration ]

4. Stony Brook University, The State University of New York, USA       Feb 2016 - Dec 2017

• Bachelor of Science in Computer Science and Applied Mathematics & Statistics (Double Major)

5. Reedley International School, Philippines       Class of 2016

• High School Secondary Education, Valedictorian

Research Experience

1. University of Arizona, USA       Jan 2023 - Present

• Research Assistant

• Working on photometric deflectometry and deep-learning based single-shot eye tracking deflectometry under the advisement of Dr. Florian Willomitzer from Computational 3D Imaging and Measurement Lab (3DIM).

2. Northwestern University, USA       Jul 2021 - Dec 2022

• Graduate Researcher

• Worked on 3D neural rendering/reconstruction of holography images under the advisement of Dr. Oliver Cossairt from Computational Photography Lab (CPL), and co-advisement of Dr. Jack Tumblin, Dr. Florian Willomitzer from Computational 3D Imaging and Measurement Lab (3DIM), and Dr. Marc Walton from Center for Scientific Studies in the Arts (NU-ACCESS).

3. DEEPNOID, Seoul, Korea       Jul 2021 - Aug 2021

• Research Intern

• Proposed a novel image windowing algorithm that enhances the input image quality through calculating the image pixel with the provided DICOM tag values.

• Developed multiple CNN-based machine learning models to classify whether the input spinal medical image should be analyzed for compression fracture or scoliosis calculations.

• Developed following classification machine learning models: - View Model: Anteroposterior (AP), Lateral (LAT), Oblique (OBL), Cone View - Posture Model: Plain, Bending - Exception Model: Assist, Gas, Gas Only, Spine

• As of Nov 2021, the proposed classification model is in an installation process to the multiple affiliated hospitals in nationwide (South Korea), including Seoul National University Hospital (SNUH).

• As of Dec 2022, the proposed DICOM file windowing algorithm and the classification model are adapted to the deep-learning-based algorithm that measures the compression ratio (CR) for compression fracture (CF) diagnosis in lateral X-rays. This work was presented at Radiological Society of North America (RSNA 2022).

4. Northwestern University, USA       Jan 2021 - Jun 2021

• Graduate Researcher

• Worked on multi-agent modeling environment with NetLogo at the Center for Connected Learning and Computer-Based Modeling Lab (CCL Lab), under Dr. Uri Wilensky. Built a NetLogo library of cartesian genetic programming, and multiple simulation environments with it.

5. University at Buffalo, The State University of New York, USA       Jan 2019 - May 2020

• Undergraduate Research Assistant

• Worked on robotic dry stacking with irregular stones, and autonomous modification of unstructured environments with in-situ materials in the Artificial Intelligence Lab, under Dr. Nils Napp.

Work Experience

1. QuickMD, USA        Sep 2022 - Jan 2024

• Data Engineer

• Data pipeline automations including ETL (Extract, Load, and Transform).

• Manage, analyze, and yield a meaningful information with ML, for QuickMD patient, revenue, and other telehealth data.

• Relocated from PwrdBy.

2. PwrdBy, USA        Mar 2021 - Sep 2022

• Data Scientist

• Manage, analyze, and yield a meaningful information with ML, for QuickMD and non-profit organizations including GivingTuesday and Catholic Leadership Institute.

• GivingTuesday Projects: 2020 annual report, social listening project, aggregating donor advised funds data, and optimize airflow SQL and sanity checks

• QuickMD Projects: patient wait time estimation, marketing revenue and advertisement spend analysis, recurring Suboxone patient analysis, patient data (180K patient records) migration from SnapMD (former platform), daily doctor and patient supply and demand analysis

3. Common Computer Inc.       Apr 2022 - Jun 2022

• Contract AI Developer

• Proposed an individual-driven ML project "Performance Comparison of Binary and Multi Class Text Classification Models" and published to Ainize platform, which gives an insight of multiple models with various metrics including: accuracy, RAM & CPU usage, training and prediction runtime, confusion matrix, and etc.

• Following models were trained to classify binary dataset (disaster Tweets) and the multiclass dataset (news article categorization):

  • scikit-learn Models: Logistic Regression, Naive Bayes, SVM (Support Vector Machine), Gradient Boosting (not included in the frontend demo, yet in full code)

  • TensorFlow Models: CNN (Convolutional Neural Network) Model, BERT Transformer Pre-Trained Model + CNN

• [ Medium Post ] [ Full Code ] [ Server on Ainize ] [ Frontend on Ainize ] [ YouTube Demo ] 

4. Gangdong-gu District Office, Seoul, Korea       Sep 2020 - Dec 2020

• Data Quality Management Intern

• Worked on managing the quality of the public data with SQL. It has dispatched by Korea National Information Society Agency, and supervised by Korea Ministry of the Interior and Safety.

Teaching Experience

1. Northwestern University, USA       Sep 2021 - Dec 2021

• Graduate Teaching Assistant

• Teaching assistant for Data Structures and Algorithms (CS 214), Fall 2021

• [ TA Evaluation ]

2. University at Buffalo, The State University of New York, USA       Jan 2019 - May 2020

• Undergraduate Teaching Assistant

• Teaching assistant for Software Quality in Practice (CSE 306), Spring 2020

• Teaching assistant for Introduction to Artificial Intelligence (CSE 368), Fall 2019

• Teaching assistant for Great Ideas in Computer Science (CSE 111), Spring 2019

Awards

1. Student Paper Award        Jul 2024

• Awarded by: 14th International Conference on Optics-photonics Design & Fabrication

• Paper: Jiwon Choi, Jiazhang Wang, Tianfu Wang, and Florian Willomitzer, "Accurate Eye-Tracking from Deflectometric Information using Deep Learning." in International Conference on Optics-photonics Design & Fabrication (ODF'24), 2024.

• Read more: [ Department News ]

2. Joseph W. Goodman Graduate Student Endowed Scholarship in Optical Sciences        Sep 2022

• Awarded by: University of Arizona, USA

• Read more: [ Department Scholarship Page ]

3. Peter and Adrienne Barris Outstanding Teaching Assistant Award        Dec 2021

• Awarded by: Northwestern University, USA

• "Jiwon went above and beyond in her work supporting MS students in Comp Sci 214. She made herself available to her students at all hours of the day and the night, and would routinely spend hours at a time working with them. Jiwon would consistently keep tabs on each of her students to make sure no one was falling behind. Her nominators attribute their success in the class in large part to Jiwon's heroic dedication and incredible patience."

• Read more: [ Department News ]

4. Student Academic Excellence Award        May 2020

• Awarded by: University at Buffalo, The State University of New York, USA

• Showcased e-portfolio at the celebration.

Grant

1. Graduate and Professional Student Council (GPSC) Basic Needs Microgrant (BNM) 2024-2025        Mar 2025

• Granted by: University of Arizona, USA

• Amount: $200

2. Graduate and Professional Student Council (GPSC) Basic Needs Microgrant (BNM) 2023-2024        Feb 2024

• Granted by: University of Arizona, USA

• Amount: $200