Dr. Euijin Alley Choo


Postdoctoral researcher
Cyber Security

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Research Focus at QCRI

Dr. Euijin Alley Choo is a Postdoctoral Researcher at Qatar Computing Research Institute. Before she joined QCRI, she was a visiting Assistant Professor at Missouri University of Science and Technology. She received her Ph.D from North Carolina State University in 2015. She earned dual B.S. from Dept. of Computer Science & Engineering and Dept. of Mathematics at Korea University. She also earned M.S. from Dept. of Computer Science & Engineering at Korea University.

Since 2006, she has conducted research in the field of computer and network security including encryption, key management, mitigation of DDoS attacks, malware detection, resilience evaluation of reputation systems, and spam detection in public forums. Her current research interests include malicious traffic analysis, spam detection in public forums, and security and information assurance in e-commerce market and industrial control systems. She earned a Provost Fellowship from NCSU during her first year of Ph.D studies. She also received the Best Paper Award at 29th Annual IFIP Working Conference on Data and Applications Security and Privacy in 2015.

Dr. Choo's current research interests include network traffic analysis and spam detection.

Previous Experience

2015-2016: Visiting Assistant Professor, Computer Science, Missouri University of Science and Technology

2009-2015: Research / Teaching Assistant, Computer Science, North Carolina State University

Professional Experience


Professional Associations and Awards

- July 2015; Best Paper Award; 29th Annual IFIP Working Conference on Data and Applications Security and Privacy; Washington D.C, USA
- May 2014; IEEE S&P Travel Award; IEEE Symposium on Security and Privacy; San Jose, CA,USA
- July 2013; UIUC Formal Methods for the Science of Security Summer School Scholarship; Information Trust Institute at University of Illinois at Urbana-Champaign; Urbana-Champaign, IL, USA
- Oct 2010; ACM CCS Travel Award; ACM Computer and Communication Security Conference; Chicago, IL, USA
- May 2010; Trusted Infrastructure Workshop Travel Award; Carnegie Mellon University; Pittsburg, PA, USA
- Fall 2009 - Spring 2010; Provost Fellowship; North Carolina State University; Raleigh, NC, USA
- Spring 2006 - Winter 2009; Brain Korea 21 Scholarship; Korea Research Foundation; Seoul, Korea
- Spring 2007; Best Research Lab Award, Brain Korea 21 Annual Exhibition;  Korea Research Foundation; Seoul, Korea
- Summer 2003; Samsung Networks Academy Scholarship; Samsung Networks; Seoul, Korea

Education

Ph.D, North Carolina State University, Raleigh, NC. USA, 2015

M.Sc, Korea University, Seoul, South Korea, 2008

B.Sc, Korea University, Seoul, South Korea, 2006

Selected Research

Euijin Choo, Ting Yu, Min Chi;"Detecting opinion spammer groups and spam targets through community discovery and sentiment analysis"; Journal of Computer Security, vol. 25, no. 3, pp. 283-318, 2017

Euijin Choo, Ting Yu, Min Chi; Detecting Opinion Spammer Groups through Community Discovery and Sentiment Analysis; Data and Applications Security and Privacy XXIX. Springer International Publishing, 2015. 170-187 (Best Paper Award)

Euijin Choo, Ting Yu, Min Chi, Yan Sun;"Revealing and Incorporating Implicit Communities to Improve Recommender Systems"; 15th ACM Conference on Economics and Computation (ACM EC 2014),pp. 489-506, June. 2014.
Euijin Choo, Jianchun Jiang, Ting Yu;"COMPARS: Toward an Empirical Approach for Comparing the Resilience of Reputation Systems"; 4th ACM conference on Data and application security and privacy (ACM CODASPY 2014), pp. 87-98, Mar. 2014.

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In the Media

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Can AI Put An End To Fake News? Don't Be So Sure

07/10/2018

Fake news was the Collin’s word of the year for 2017 with good reason. In a year where politics-as-usual was torn apart at the seams, high-profile scandals rocked our faith in humanity and the ...

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MIT/QCRI system uses machine learning to build road maps

22/04/2018

Map apps may have changed our world, but they still haven’t mapped all of it yet. Specifically, mapping roads can be difficult and tedious: even after taking aerial images, companies still have to ...

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Improving disaster response efforts through data

08/02/2018

Extreme weather events put the most vulnerable communities at high risk. How can data analytics strengthen early warning systems and and support relief efforts for communities in need? The size and ...

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Upcoming Events

Past Events

2018

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QCRI Summer Internship Program

Download ICS File 06/05/2018  - 05/07/2018 , Hamad Bin Khalifa Research Complex

Each year, Qatar Computing Research Institute organizes a summer internship program for undergraduate students studying computer science, computer engineering and other disciplines. The internship is unpaid, and QCRI does not provide any visa support.

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Public Talk by Prof. Regina Barzilay "Artificial Intelligence for Oncology: Learning to Cure Cancer from Images and Text"

Download ICS File 27/03/2018 ,

Artificial Intelligence for Oncology: Learning to Cure Cancer from Images and Text A talk by Professor Regina Barzilay, MIT CSAIL Winner of 2017 MacArthur ‘genius grant’ At Education City Student ...

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QCRI & MIT-CSAIL Annual Project Review 2018

Download ICS File 27/03/2018 ,

Executive Overview Sessions Open to public Date:    Tuesday, March 27, 2018 Time:    9:00AM – 3:00PM Venue:  HBKU Research Complex Multipurpose Room To view full agenda, please click here . To RSVP, ...

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News Releases

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QCRI to offer kids’ computing activities at this year’s Darb Al Saai

03/12/2018

Tech fun and robotics computing activities will be available to children attending the annual family celebration from December 12 to 20.

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Global experts in artificial intelligence for transportation to visit Qatar for TASMU-QCAI workshop

18/11/2018

Urban computing experts from Europe, the US and Qatar are to discuss state-of-the-art advances in artificial intelligence for transportation with local stakeholders.

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QCAI to Conduct Joint Machine Learning School with BigML

16/10/2018

Two-day crash course to provide hands-on introduction to machine learning for industry practitioners, developers, graduate students and undergraduates.

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