Scott Freitas

I work at the intersection of applied and theoretical machine learning, with a strong application focus on cybersecurity. My goal is to develop explainable next-generation defenses to protect systems against adversarial attacks.

At Georgia Tech I work with Polo Chau as a member of the Polo Club of Data Science. During this time, I have co-authored several winning research proposals, including a $1.3 million DARPA grant.

I have been fortunate to work with amazing engineers and scientists at Microsoft Advanced Threat Protection, Microsoft Research, Intel and Naval Air Warfare Center.

My research is generously supported by the NSF GRFP and Raytheon research fellowships.

Education

Present —Aug. 2018Ph.D. in Machine Learning
Aug. 2018Georgia Institute of Technology, Atlanta, GA
Advisor: Duen Horng (Polo) Chau Anticipated Graduation: Spring 2022

May 2018Summer 2017M.S. in Computer Science
Summer 2017Arizona State University, Tempe, AZ
Advisor: Hanghang Tong, Thesis: "Mining Marked Nodes in Large Graphs"
Overall GPA: 4.00/4.00

May 2017 —Aug. 2015B.S. in Computer Science
Aug. 2015Arizona State University, Tempe, AZ
Overall GPA: 3.98/4.00

May 2014 —Aug. 2010B.S.E. in Electrical Engineering
Aug. 2010Arizona State University, Tempe, AZ
Overall GPA: 3.64/4.00

Honors and Awards

2019Raytheon Research Fellowship
Awarded for my PhD work in adversarial machine learning

2018 — 2023NSF Graduate Research Fellowship
National Science Foundation recognizes and supports outstanding graduate students in STEM fields

2018Outstanding Computer Science Masters Student (ASU)
Awarded to single master student demonstrating exemplary performance

2017Best Demo Award, Runner Up at CIKM '17
For "Rapid Analysis of Network Connectivity"

2017CIKM Travel Grant
Funding from NSF and SIGWEB to present at CIKM

2016 — 2017FURI Grant
Undergraduate research grant awarded for work in network connectivity

2016 — 2017Arizona Graduate Scholar Award
Merit scholarship awarded to select number of master students

2010 — 2014Provost's Scholarship
Merit scholarship awarded to select number of incoming undergraduate students

Industry Research Experience

Summer 2020Microsoft, Seattle, WA
Research Intern, Microsoft ATP + Microsoft Research
Mentor: Karishma Sanghvi, Yuxiao Dong
Developed graph neural network approach to detect malware

Summer 2019Microsoft, Seattle, WA
Research Intern, Microsoft Advanced Threat Protection (ATP)
Mentor: Andrew Wicker, Joshua Neil
Designed graph based approach to quantify and mitigate network vulnerability to adversarial attacks

Summer 2013Naval Air Warfare Center, Point Mugu, California
Research Intern, Naval Research Entperprise Internship Program (NREIP)
Mentor: Balaji Iyer
Explored methods of preventing electromagentic interference from coupling into superconducting receivers

Academic Research Experience

Present —Aug. 2018Georgia Institute of Technology, Atlanta, GA
Aug. 2018Graduate Research Assistant, School of Computational Science and Engineering
Advisor: Duen Horng (Polo) Chau
Member of the Polo Club of Data Science where we innovate scalable, interactive, and interpretable tools that amplify human's ability to understand and interact with billion-scale data and machine learning models

May 2018 —Summer 2017Arizona State University, Tempe, AZ
Summer 2017Graduate Research Assistant, School of Computing, Informatics, and Decision Systems Engineering
Advisor: Hanghang Tong
Conducted research in graph based connectivity analysis to improve local graph partitioning. Developed web-based prototype for explainable ranking in complex multi-layered networks.

Summer 2017Arizona State University, Tempe, AZ
Summer Research Assistant, School of Computing, Informatics, and Decision Systems Engineering
Mentor: Ross Maciejewski
Developed interactive augmented reality (AR) graph models in the Microsoft Hololens.

May 2017 —Jan. 2016Arizona State University, Tempe, AZ
Jan. 2016Undergraduate Research Assistant, School of Computing, Informatics, and Decision Systems Engineering
Mentor: Hanghang Tong
Developed fast graph mining algorithms for network connectivity analysis, and award winning web platform for visualization and analysis.

Publications

A Large-Scale Database for Graph Representation Learning
Scott Freitas, Yuxiao Dong, Joshua Neil, Duen Horng (Polo) Chau
arXiv (arXiv). Online, 2020.
Project Demo PDF Blog Code BibTeX

			@article{freitas2020large,
  title={A Large-Scale Database for Graph Representation Learning},
  author={Freitas, Scott and Chen and Dong, Yuxiao and Neil, Joshua and Chau, Duen Horng},
  journal={arXiv},
  year={2020},
  publisher={arXiv}
}
		

UnMask: Adversarial Detection and Defense Through Robust Feature Alignment
Scott Freitas, Shang-Tse Chen, Zijie J. Wang, Duen Horng (Polo) Chau
IEEE International Conference on Big Data (Big Data). Atlanta, GA, 2020.
Project PDF Blog Code BibTeX

			@article{freitas2020detecting,
  title={UnMask: Adversarial Detection and Defense Through Robust Feature Alignment},
  author={Freitas, Scott and Chen, Shang-Tse and Wang, Zijie J. and Chau, Duen Horng},
  journal={IEEE Big Data},
  year={2020},
  publisher={IEEE}
}
		

Evaluating Graph Vulnerability and Robustness using TIGER
Scott Freitas, Duen Horng (Polo) Chau
arXiv (arXiv). Online, 2020.
PDF Blog Code BibTeX

			@article{freitas2020evaluating,
  title={Evaluating Graph Vulnerability and Robustness using TIGER},
  author={Freitas, Scott and Chau, Duen Horng},
  journal={arXiv},
  year={2020},
  publisher={arXiv}
}
		

ELF: An Early-Exiting Framework for Long-Tailed Classification
Rahul Duggal, Scott Freitas, Sunny Dhamnani, Duen Horng (Polo) Chau, Jimeng Sun
arXiv (arXiv). Online, 2020.
PDF BibTeX

			@article{duggal2020elf,
  title={ELF: An Early-Exiting Frameworkfor Long-Tailed Classification},
  author={Duggal, Rahul and Freitas, Scott and Dhamnani, Sunny and Chau, Duen Horng and Sun, Jimeng},
  journal={arXiv},
  year={2020},
  publisher={arXiv}
}
		

Argo Lite: Open-Source Interactive Graph Exploration and Visualization in Browsers
Siwei Li, Zhiyan Zhou, Anish Upadhayay, Omar Shaikh, Scott Freitas, Haekyu Park, Zijie J. Wang, Susanta Routray, Matthew Hull, Duen Horng (Polo) Chau
ACM International Conference on Information and Knowledge Management (CIKM). Online, 2020.
Demo PDF Code BibTeX

			@inproceedingst{li2020argo,
  title={Argo Lite: Open-Source Interactive Graph Exploration and Visualization in Browsers},
  author={Li, Siwei and Zhou, Zhiyan and Upadhayay, Anish and Shaikh, Omar and Freitas, Scott and Haekyu, Park and Zijie, Wang and Routray, Susanta and Hull, Matthew and Chau, Duen Horng},
  journal={CIKM},
  year={2020},
  publisher={ACM International Conference on Information and Knowledge Management}
}
		

REST: Robust and Efficient Neural Networks for Sleep Monitoring in the Wild
Rahul Duggal*, Scott Freitas*, Cao Xiao, Duen Horng (Polo) Chau, Jimeng Sun
The Web Conference (WWW). Taipei, Taiwan, 2020.
Project PDF Blog Code BibTeX * Authors contributed equally

			@inproceedings{duggal2020rest,
  title={REST: Robust and Efficient Neural Networks for Sleep Monitoring in the Wild},
  author={Duggal, Rahul and Freitas, Scott and Xiao, Cao and Chau, Duen Horng and Sun, Jimeng},
  journal={WWW},
  year={2020},
  publisher={The Web Conference}
}
		

D²M: Dynamic Defense and Modeling of Adversarial Movement in Networks
Scott Freitas, Andrew Wicker, Duen Horng (Polo) Chau, Joshua Neil
SIAM International Conference on Data Mining (SDM). Cincinnati, Ohio, 2020.
Project PDF Blog BibTeX

			@inproceedings{freitas2020d2m,
  title={D2M: Dynamic Defense and Modeling of Adversarial Movement in Networks},
  author={Freitas, Scott and Wicker, Andrew and Chau, Duen Horng and Neil, Joshua},
  journal={SIAM International Conference on Data Mining},
  year={2020},
  publisher={SIAM}
}
		

Extracting Knowledge For Adversarial Detection and Defense in Deep Learning
Scott Freitas, Shang-Tse Chen, Duen Horng (Polo) Chau
KDD Workshop: Learning and Mining for Cybersecurity (LEMINCS). Anchorage, Alaska, 2019.
PDF BibTeX

			@article{freitas2019extracting,
  title={Extracting Knowledge For Adversarial Detection and Defense in Deep Learning},
  author={Freitas, Scott and Chen, Shang-Tse and Chau, Duen Horng},
  journal={KDD LEMINCS Workshop},
  year={2019},
  publisher={ACM}
}
		

Local Partition in Rich Graphs
Scott Freitas, Nan Cao, Yinglong Xia, Duen Horng (Polo) Chau, Hanghang Tong
IEEE International Conference on Big Data (Big Data). Seattle, Washington, 2018.
Project PDF BibTeX

			@inproceedings{freitas2018local,
  title={Local Partition in Rich Graphs}, 
  author={Freitas, Scott and Cao, Nan and Xia, Yinglong and Duen Horng, Chau and Tong, Hanghang}, 
  booktitle={IEEE International Conference on Big Data}, 
  year={2018}, 
  publisher={IEEE}
}
		

X-Rank: Explainable Ranking in Complex Multi-Layered Networks
Jian Kang*, Scott Freitas*, Haichao Yu, Yinglong Xia, Hanghang Tong
ACM International Conference on Information and Knowledge Management (CIKM). Turin, Italy, 2018.
Project PDF BibTeX * Authors contributed equally

			@inproceedings{kang2018xrank,
  author = {Kang, Jian and Freitas, Scott and Yu, Haichao and Xia, Yinglong and Cao, Nan and Tong, Hanghang},
  title = {X-Rank: Explainable Ranking in Complex Multi-Layered Networks},
  booktitle = {Proceedings of the 27th ACM International Conference on Information and Knowledge Management},
  year = {2018},
  location = {Torino, Italy},
  publisher = {ACM}
} 
		

Rapid Analysis of Network Connectivity
Scott Freitas, Hanghang Tong, Nan Cao, Yinglong Xia
ACM International Conference on Information and Knowledge Management (CIKM). Singapore, 2017.
Project PDF Video Code BibTeX Best Demo Paper, Runner up

			@inproceedings{Freitas:2017:RAN:3132847.3133170,
  author = {Freitas, Scott and Tong, Hanghang and Cao, Nan and Xia, Yinglong},
  title = {Rapid Analysis of Network Connectivity},
  booktitle = {Proceedings of the 2017 ACM on Conference on Information and Knowledge Management},
  year = {2017},
  location = {Singapore, Singapore},
  publisher = {ACM},
} 
		

Talks

Exploring Graph Neural Networks for Malware Detection
July 2020Microsoft Advanced Threat Protection

D²M: Dynamic Defense and Modeling of Adversarial Movement in Networks
Aug. 2019Microsoft Advanced Threat Protection Research Expo

Mining Marked Nodes in Large Graphs
Dec. 2018Microsoft Advanced Threat Protection Group
May 2018ASU Thesis

Local Partition in Rich Graphs
Dec. 2018IEEE International Conference on Big Data

Rapid Analysis of Network Connectivity
Nov. 2017ACM International Conference on Information and Knowledge Management (CIKM)

Network Connectivity Analysis and Visualization in Large Graphs
April 2017Keynote Speaker: ASU Fulton Undergraduate Research Initiative (FURI)
Nov. 2016ASU FURI Research Symposium

Press

April. 2020"Georgia Tech and Intel Awarded Multimillion-Dollar Program to Defend Against Attacks on AI",

April. 2020"DARPA Snags Intel to Lead its Machine Learning Security Tech",

April. 2020"Machine Learning Technique Helps Wearable Devices Get Better at Diagnosing Sleep Disorders and Quality",

Feb. 2019"Raytheon Awards Two ML@GT Students Graduate Research Assistantships",

July 2018"NSF Graduate Research Fellow wants to use computer science to solve society’s toughest problems",

Grants and Funding

2020Google Cloud Research Grant
Large Scale Malware Analysis
Funded: $5,000 Google cloud credits

2018 — 2022Guaranteeing AI Robustness against Deception (GARD)
DARPA Research Grant
Co-PIs: Jason Martin, Duen Horng (Polo) Chau
Funded: $1.35 million
Helped formulate adversarial defense techniques

2018Amazon AWS Research Grant
Adversarial Re-Training and Model Vaccination for Robust Deep Learning
Funded: $5,000 AWS cloud credits

2018Nvidia GPU Grant
Defending Adversarial Attacks by Robust, Inference-time Local Linear Approximation
Funded: Nvidia Titan V GPU worth $3,000

2019Raytheon Research Fellowship
Extracting Knowledge For Adversarial Detection and Defense
Funded: $25,000

2018 — 2023NSF Graduate Research Fellowship Program (GRFP)
Multi-level Interdiction and Assistance Modeling for Natural Disasters
Funded: Full tuition + $102,000

2016 — 2017FURI Grant
Network Connectivity Analysis and Visualization in Large Graphs
Funded: $3,000

Teaching

Fall 2020Graduate Teaching Assistant
Georgia Institute of Technology, Atlanta, GA
Data and Visual Analytics, Instructor: Duen Horng (Polo) Chau

Fall 2013Undergraduate Teaching Assistant
Arizona State University, Tempe, AZ
Fulton Undergraduate Research Experience (FSE 294), Instructor: Joshua Lyon
Designed and taught introductory lesson plans to new engineering students

Mentoring

Present —Spring 2020Omar Shaikh
Spring 2020B.S. in Computer Science, Georgia Institute of Technology

Present —Spring 2020Jon Saad-Falcon
Spring 2020B.S. in Computer Science, Georgia Institute of Technology

Present —Spring 2020Frank Zhou
Spring 2020B.S. in Computer Science, Georgia Institute of Technology

Present —Summer 2020Kevin Li
Summer 2020B.S. in Computer Science, Georgia Institute of Technology

Service

Program Committee

Association for the Advancement of Artificial Intelligence (AAAI) at AAAI 2021

ACM International Conference on Information and Knowledge Management (CIKM) at ACM CIKM 2020

Reviewer

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2019

International Conference on Machine Learning (ICML) 2019