I’m a 5th year PhD student developing generalizable and robust models to ensure the deployment of safe and reliable AI systems.
I work in the ASU APG lab where I’m advised by Yezhou Yang. I recently interned at 
Microsoft Research, where I developed novel datasets, machine learning models, and benchmarks for forecasting and analyzing cybersecurity incident escalation, and 
Lawrence Livermore National Lab, where I developed a novel zero-shot deep learning architecture using image and natural language data sources. Prior to pursuing my Signal Processing/Machine Learning specialized Master’s degree in 2016, I also interned for two summers at 
Honeywell where I worked on web development, test automation scripts, electrical component diagrams, and hardware programming.
After receiving my Master’s degree, I worked full-time as a Senior Digital Signal Processing Engineering at 
General Dynamics where I designed algorithms for spectral decomposition, detection, characterization, and classification of communication and radar signals before pursing my PhD.
2023Our Misalignment in Object Detection work was accepted to WACV 2024.
2023I joined Microsoft Research as a Research Intern.
2022Our Covariate Shift Detection work was accepted into a NeurIPS 2022 Workshop as a spotlight presentation.
2022I joined Lawrence Livermore National Lab as a Computing Scholar Intern.
2021Our paper, SMURF, was accepted to ACL 2021 as a competitively selected oral presentation.
Aug. 2019 —May 2024Ph.D. in Computer Engineering w/ Machine Learning Specialization
May 2024Arizona State University, Tempe, AZ
Advisor:
Yezhou Yang
Aug. 2016 —May 2018M.S. in Computer Engineering w/ Machine Learning Specialization
May 2018Arizona State University, Tempe, AZ
GPA: 3.93/4.00
Aug. 2012 —May. 2016B.S. in Electrical Engineering
May. 2016Arizona State University, Tempe, AZ
Barrett, the Honors College Graduate
Electrical Engineering Student Mentor
GPA: 3.85/4.00
May 2023 —Aug. 2023Microsoft Research, Redmond, WA
Aug. 2023Research Intern, Augmented Learning and Reasoning
Mentor:
Jack (Jay) Stokes,
Scott Freitas
Developed novel datasets, machine learning models, and benchmarks for forecasting and analyzing cybersecurity incident escalation. Further explored potential implementation options and use cases to demonstrate feasibility and product impact, respectively.
May 2022 —Dec. 2022Lawrence Livermore National Lab, Livermore, CA
Dec. 2022Graduate Research Intern, Computing at LLNL
Mentor:
Jayaraman Thiagarajan,
Rushil Anirudh,
Jayram Thathachar
Developed a highly generalizable Zero-Shot Learning architecture with pre-trained vision pipelines, automated external knowledge retrieval from natural language sources, and model regularization techniques.
May 2018 —Dec. 2019General Dynamics Mission Systems, Scottsdale, AZ
Dec. 2019Senior Digital Signal Processing Engineer, Trusted Space Solutions
Created specifications for the standard operation and packet-level communication of devices in an edge computing framework. Developed algorithms for detecting communication and radar signals of interest and estimating their time and frequency characteristics for downstream decoding, classification, and localization tasks. Automated and optimized the creation of data compression pipelines for efficient communication channels and downstream data visualization tasks based on project requirements.
Jan. 2020 —PresentArizona State University, Tempe, AZ
PresentPhD Researcher, Active Perception Group
Mentor:
Yezhou Yang
Exploring concepts like knowledge representation/extraction, model generalization/robustness, and inference consistency/evaluation in Natural Language and Image Processing applications. First author of a novel information theory based evaluation of captions for semantics and fluency presented in ACL 2021, outlier detection/uncertainty estimation using domain interpolation based sensitivity analysis presented as a spotlight presentation in the NeurIPS 2022 INTERPOLATE workshop, and an object detection work which introduces and addresses upstream and downstream task misalignment by computing object importance scores using semantic modeling and graph signal processing to be presented at WACV 2024.
Jan. 2017 —Dec. 2017Arizona State University, Tempe, AZ
Dec. 2017Master's Research Assistant, Image, Video, and Usability (IVU) Lab
Mentor:
Lina Karam
Built software frameworks using C, Python, OpenCV, Ada, and Matlab on a Linux platform for data acquisition and signal processing on the Soli radar device. Developed biometric and gesture detection/estimation algorithms using machine learning, sensor fusion, feature point tracking, beamforming, spectral analysis and pattern recognition algorithms on Photoplethysmographic (PPG) and Frequency-Modulated Continuous-Wave (FMCW) signal information.
May 2016 —Aug. 2016Honeywell, Phoenix, AZ
Aug. 2016Intern, Test Services
Mentor:
Craig Stevens,
Bob Apodaca
Modified and updated PHP/HTML/CSS/JavaScript/Fusebox based web applications and tested any changes using a Debian VM. Created and restructured Perl scripts, Ladder Logic Programs (PLC), and other software programs used for Test Cell support. Implemented revisions to existing AutoCAD Electrical designs and developed a strain-gauge specimen box to fulfill the electrical and mechanical requirements of a work request from another department.
May 2015 —Aug. 2015Honeywell, Phoenix, AZ
Aug. 2015Intern, Test Services
Mentor:
Craig Stevens,
Bob Apodaca
Modified and updated PHP/HTML/CSS/JavaScript/Fusebox based web applications and tested any changes using a Debian VM. Created and restructured Perl scripts, Ladder Logic Programs (PLC), and other software programs used for Test Cell support. Implemented revisions to existing AutoCAD Electrical designs and developed a strain-gauge specimen box to fulfill the electrical and mechanical requirements of a work request from another department.
Towards Addressing the Misalignment of Object Proposal Evaluation for Vision-Language Tasks via Semantic Grounding
Joshua Feinglass,
Yezhou Yang
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 2024.
Project
BibTeX
Covariate Shift Detection via Domain Interpolation Sensitivity
Tejas Gokhale*,
Joshua Feinglass*,
Yezhou Yang
NeurIPS 2022 Workshop INTERPOLATE (NeurIPS Workshop). New Orleans, LA, 2022.
Project
BibTeX
* Authors contributed equally
SMURF: SeMantic and linguistic UndeRstanding Fusion for Caption Evaluation via Typicality Analysis
Joshua Feinglass,
Yezhou Yang
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL). Online, 2021.
Project
BibTeX