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Alex Gaudio

Explainable Machine Learning

for Medical Image Analysis

Bio

My research focuses on explainable machine learning for medical image analysis. I am a dual degree PhD candidate at Carnegie Mellon University and at the University of Porto. I also co-founded a non-profit, NYC Makerspace, to bring together diverse communities of people, give them advanced tools and education, and ignite individuals with the life-long passions to innovate, teach as a means of learning, and have fun by helping their friends grow. Previously, I worked as a data scientist and engineer in New York City for 7 years. I studied in jazz performance and composition at Bard College. I am fascinated by the ways people create and interpret their life paths.

Visionary people embrace challenge by inventing opportunities and pursuing ideas. Their success is achieved not by meeting requirements or emphasizing credentials, but by giving others the ability to appreciate, use and adapt the things they love most.

Research Interests

  • Explainable Deep and Machine Learning
  • Computer Vision
  • Signal Processing
  • Medical Image Analysis

Five Year Plan:

  • Develop next generation machine learning, vision, and signal processing algorithms, primarily for medical image analysis.
  • Lead my own R&D lab
  • Incubate a community of uncommonly diverse individuals that applies our research to the real world, especially for the creation of sustainable growth in underserved communities.
  • Teach all people about learning machines, in the university and also in the local community.
  • Inspire amazing people like you to join me in accomplishing these goals.

Education

  • Carnegie Mellon University

    Ph.D. Candidate in Electrical Computer Engineering (expected 2023)
    Advisors: Prof. Asim Smailagic, Prof. Aurelio Campilho

  • University of Porto

    Ph.D. Candidate in Electrical Computer Engineering (expected 2023)
    (via CMU Portugal dual degree program)

  • Carnegie Mellon University

    M.S. in Electrical Computer Engineering (expected 2021)

  • Bard College

    Bachelor of Arts in Music, 2010

Current Publications

Journal, peer reviewed

2020, Asim Smailagic, Pedro Costa, Alex Gaudio, Kartik Khandelwal, Mostafa Mirshekari, Jonathon Fagert, Devesh Walawalkar, Susu Xu, Adrian Galdran, Pei Zhang, Aurélio Campilho, and Hae Young Noh (publisher) (arxiv) (code)
O-MedAL: Online active deep learning for medical image analysis

Conference, peer reviewed

2020, Alex Gaudio, Asim Smailagic, and Aurélio Campilho (publisher) (arxiv) (code)
Enhancement of Retinal Fundus Images via Pixel Color Amplification
2019, Asim Smailagic, Anupma Sharan, Pedro Costa, Adrian Galdran, Alex Gaudio, and Aurélio Campilho (publisher) (arxiv)
Learned Pre-processing for Automatic Diabetic Retinopathy Detection on Eye Fundus Images
2019, Qiqi Xiao, Jiaxu Zou, Muqiao Yang, Alex Gaudio, Kris Kitani, Asim Smailagic, Pedro Costa, and Min Xu (publisher) (arxiv) (code)
Improving Lesion Segmentation for Diabetic Retinopathy Using Adversarial Learning

Patent

2020, Alex Gaudio, and Gerald Isaac Kestenbaum
Physical asset recognition platform

Invited Talks

2015, Alex Gaudio (publisher)
Challenges in Optimizing Job Scheduling on Mesos
2015, Alex Gaudio (publisher)
Balancing Infrastructure with Optimization and Problem Formulation
2011, Alex Gaudio (publisher)
Tmux + IPython = Awesome

Contact Me

I am interested in collaborations of many kinds and with people of a wide variety of different experiences and skill-sets. While I complete my Ph.D. I'm especially focused on academic collaboration. I am also usually looking for students to help with research projects.

Email: click@to.reveal.com