MOHAMMADREZA EBRAHIMI CURRICULUM VITAE

E-mail: ebrahimi@email.arizona.edu , **Website: https://mohammadrezaebrahimi.github.io
Artificial Intelligence Lab, 1130 E. Helen St. McClelland Hall 430, Tucson, Arizona 85721.

EDUCATION

  • Doctor of Philosophy (Ph.D.), The University of Arizona 2016- 2021 (expected)

    Major: Management Information Systems

    Minor: Computational Linguistics

  • Master of Science, Concordia University, Montreal 2014- 2016

    Major: Computer Science

    Thesis Title: Automatic Identification of Online Predators in Chat Logs by Anomaly Detection and Deep Learning

  • Bachelor of Science, Azad University at Qazvin 2004- 2008

    Major: Computer Science and Engineering

    Thesis Title: A Framework for Intelligent Crime Matching with Neural Network

RESEARCH INTERESTS

  • AI-enabled Security Analytics: Adversarially Robust AI Agents, Cross-lingual Cybersecurity Analytics, Automatic Cyber Threat Identification
  • Business Intelligence and Analytics: Social Media Analytics, Multilingual Product Review Analysis in E-commerce
  • Statistical Machine Learning and AI: Adversarial Machine Learning,Transfer Learning and Domain Adaptation, Cross-lingual Knowledge Transfer, Reinforcement Learning, Deep Learning
  • Crime Data Analytics: Online Predator Identification in Social Media, Supervised Methods for Categorizing Behavior of Offenders in Crime Incidents

DOCTORAL DISSERTATION

  • Thesis Title: AI-enabled Cybersecurity Analytics with Transductive Learning, Transfer Learning, Adversarial Learning, and Reinforcement Learning Theory
  • Committee: Dr. Hsinchun Chen (Chair), Dr. Sue Brown, Dr. Jay F. Nunamaker, Dr. Mihai Surdeanu
  • Dissertation Summary: Cyber-attacks are a great societal concern. Many organizations rely on manual collection of cyber threat intelligence (CTI) to mitigate attacks. However, the fast-paced growth of data sources precludes obtaining actionable intelligence via manual approaches or ad-hoc software agents. AI-enabled cybersecurity is an emerging approach that draws upon statistical and machine learning theories to invent AI agents that address this issue. These agents can automatically gather CTI at a large scale and improve incident response. Although promising, these agents are vulnerable to adversarial attacks from AI-enabled adversaries. Given the crucial need for effective, robust cybersecurity AI agents, my dissertation presents five essays contributing to two major areas of AI-enabled cybersecurity: (1) AI-enabled cyber threat identification in international online hacker communities (three essays) and (2) Robustness of cybersecurity AI agents against adversarial attacks (two essays).

JOURNAL PUBLICATIONS & BOOK CHAPTERS

  • M. Ebrahimi , J. F. Nunamaker Jr., H. Chen, "Semi-Supervised Cyber Threat Identification in Dark Net Markets: A Transductive and Deep Learning Approach," Journal of Management Information Systems (JMIS), Volume (38), 2020 (Forthcoming).

  • M. Ebrahimi , J.D. Martinez. "Involuntary Embarrassing Exposures in Online Social Networks: A Replication Study," AIS Transactions on Replication Research (TRR), Volume 5(1), p. 7, 2019.

  • M. Ebrahimi , C. Y. Suen, O. Ormandjieva, "Detecting Predatory Conversations in Social Media by Deep Convolutional Neural Networks," Journal of Digital Investigation, Elsevier, Volume 18, pp. 33-49, 2016.

  • M. Keyvanpour, M. Ebrahimi , N. G. Nayebi, O. Ormandjieva, C. Y. Suen, "Automated Identification of Child Abuse in Chat Rooms by Using Data Mining," Data Mining Trends and Applications in Criminal Science and Investigations, IGI-Global publications, 2016.

  • M. Keyvanpour, M. Ebrahimi , M. Javideh, "Designing Efficient ANN Classifiers for Matching Burglaries from Dwelling Houses," Applied Artificial Intelligence, Taylor and Francis, Volume 26 (8), pp. 787-807, 2012.

  • M. Keyvanpour, M. Javideh, M. Ebrahimi , "A Hybrid Geospatial Data Clustering Method for Hotspot Analysis," Journal of Computer and Robotics, Qazvin Azad University, Volume 2(1), pp 53-67, 2010. available from http://www.qjcr.ir

JOURNAL PUBLICATIONS UNDER REVIEW (Dissertation Chapters)

  • M. Ebrahimi , Y. Chai, S. Samtani, H. Chen, "Cross-Lingual Security Analytics: Cyber Threat Detection in the International Dark Web with Adversarial Deep Representation Learning," 3rd round of Review in MIS Quarterly (MISQ).

  • M. Ebrahimi , Y. Chai, H. Zhang, H. Chen, "Heterogeneous Domain Adaptation with Deep Adversarial Representation Learning: Experiments on E-Commerce and Cybersecurity," Submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI).

JOURNAL PUBLICATIONS IN PROGRESS (Dissertation Chapters)

  • M. Ebrahimi, Y. Chai, J. Pacheco, W. Li, H. Chen, "RADAR: A Framework for Developing Adversarially Robust Cybersecurity AI Agents with Deep Reinforcement Learning," to be submitted to MIS Quarterly (MISQ).

  • M. Ebrahimi , N. Zhang, J. Hu, H. Chen, "Protecting Deep Learning-based Malware Detectors with Adversarial Example Generation: A Recurrent Neural Network Approach," to be submitted to the Journal of Management Information Systems (JMIS).

REFEREED CONFERENCE PROCEEDINGS  (* indicates that I was the presenting author)

  • *M. Ebrahimi , S. Samtani, Y. Chai, H. Chen, "Detecting Cyber Threats in Non-English Hacker Forums: An Adversarial Cross-Lingual Knowledge Transfer Approach," IEEE Symposium on Security and Privacy (IEEE S&P), Deep Learning and Security Workshop, May 2020, San Francisco.

  • *M. Ebrahimi , M. Surdeanu, S. Samtani, H. Chen, "Detecting Cyber Threats in Non-English Dark Net Markets: A Cross-Lingual Transfer Learning Approach," 2018 IEEE International Conference on Intelligence and Security Informatics (ISI), Miami, FL, 8-10 November, 2018, pp. 85-90, (Best Paper Award Runner-up).

  • *M. Ebrahimi, C. Y. Suen, O. Ormandjieva, A. Krzyzak, "Recognizing Predatory Chat Documents using Semi-supervised Anomaly Detection," 23rd Document Recognition Retrieval Conference (DRR16), San Francisco, CA, 14-18 February, 2016, pp. 1-9(9).

  • P. Du, M. Ebrahimi , N. Zhang, H. Chen, R. A. Brown and S. Samtani, "Identifying High-Impact Opioid Products and Key Sellers in Dark Net Marketplaces: An Interpretable Text Analytics Approach," 2019 IEEE International Conference on Intelligence and Security Informatics (ISI), Shenzhen, China, 2019, pp. 110-115.

  • N. Arnold, M. Ebrahimi , N. Zhang, B. Lazarine, M. Patton, H. Chen, S. Samtani, "Dark-Net Ecosystem Cyber-Threat Intelligence (CTI) Tool," 2019 IEEE International Conference on Intelligence and Security Informatics (ISI), Shenzhen, China, 2019, pp. 92-97.

  • P. Du, N. Zhang, *M. Ebrahimi , S. Samtani, B. Lazarine, N. Arnold, R. Dunn et al. "Identifying, Collecting, and Presenting Hacker Community Data: Forums, IRC, Carding Shops, and DNMs," 2018 IEEE International Conference on Intelligence and Security Informatics (ISI), Miami, FL, 8-10 November, 2018, pp. 70-75.

  • M. Keyvanpour, M. Javideh, M. Ebrahimi , "Detecting and Investigating Crime by Means of Data Mining: A General Crime Matching Framework," 2010 World Conference on Information Technology, Procedia Computer Science, Volume 3, Edited by AdemKarahoca, Sezer, 2011, pp. 872-880.

REFEREED CONFERENCES UNDER REVIEW

  • M. Ebrahimi, N. Zhang, J. Hu, T. Raza, "Black-box Attacks Against Deep Learning-based Static Malware Detectors: An Adversarial Example Generation Approach," to be submitted to ACM Workshop on Artificial Intelligence and Security (AISec), 13 November, 2020.

  • N. Zhang, M. Ebrahimi , W. Li, H. Chen, "A Generative Adversarial Learning Framework to Break Text-Based CAPTCHA in the Dark Web," to be submitted to IEEE International Conference on Intelligence and Security Informatics (ISI), 16-18 November, 2020.

GRANT & REPORT WRITING SKILLS

  • D-ISN (Disrupting Operations of Illicit Supply Networks), Title: Disrupting Illicit Trafficking by Dissecting Geometry of Darkweb and Cryptocurrency Transactions, Source: National Science Foundation (NSF) , Grant Period: 2020-2023 , Status: Under review , Amount: $349,896 , Role: Assisting Grant writer.

  • SaTC (Secure & trustworthy Cyberspace), Title: Cybersecurity Big Data Research for Hacker Communities: A Topic and Language Modeling Approach, Source: National Science Foundation (NSF) , Grant Period: 2019-2022 , Grant No.: 1936370, Status: Funded , Funded Amount: $510,624 , Role: Assisting Grant writer.

  • SaTC-DGE (Secure & trustworthy Cyberspace - Division of graduate Education), Title: Cybersecurity Big Data and Analytics Sharing Platform, Source: National Science Foundation (NSF) , Reporting Year: 2019 , Grant No.: 1719477, Status: Funded , Funded Amount: $180,000 , Role: Assisting Report writer.

RESEARCH EXPERIENCE

Artificial Intelligence Lab, Eller College of Management, University of Arizona 2016-** Now**

  • Role: Research associate (AI-enabled cybersecurity analytics)
  • Advisor: Dr. Hsinchun Chen
  • Address: 1130 E. Helen St. McClelland Hall 430, Tucson, Arizona 85721, phone: (520) 621-6219

Centre of Pattern Recognition and Machine Intelligence at Concordia University 2014-2016

  • Role: Research assistant (Social media analytics for online predator identification).
  • Advisor: Dr. Ching Y. Suen
  • Address: Computer Science & Software Engineering (CSE) Department, EV 11.155, 1455 de Maisonneuve West Montréal, Québec, Canada H3G 1M8.

Alzahra University 2011-2013

  • Role: Research associate (Crime data mining, text mining)
  • Advisor: Dr. Mohammadreza Keyvanpour
  • Address: Computer Engineering Department, North Sheikh Bahaee St., Deh-e Vanak, Tehran, Iran, 1993891176.

TEACHING EXPERIENCE

Instructor (University of Arizona):

  • MIS 562 "Cyber Threat Intelligence," Graduate level, Online, Summer 2020

    • Class size: 27
    • All instructor ratings are greater than 4.55 / 5.00 (82% response rate)
  • MIS 562 "Cyber Threat Intelligence," Graduate level, Online, Summer 2019

    • Class size: 23
    • All instructor ratings are greater than 4.23 / 5.00 (100% response rate)

Teaching Assistant (University of Arizona) :

  • MIS 464 "Data Analytics," Undergraduate, On-site, Spring 2020

    • Instructor: Dr. Hsinchun Chen
    • Lecturer of the lab sessions (Python, Weka, Tableau)
    • Assisted with class material preparation, grading
  • MIS 511/411 " Social and Ethical Issues of the Internet," **Grad/Undergrad, On-site Spring 2019

    • Instructor: Dr. Laura Brandimarte
  • MIS 331: "Database Management Systems," Undergraduate, On-site. Fall 2018

    • Instructor: Dr. Lusi Yang

Teaching Assistant (Concordia University):

  • COMP 6321 "Machine Learning," Graduate level, Fall 2015

    • Instructor: Dr. Adam Krzyzak
    • Lecturer (one session), Course grader

PROFESSIONAL AFFILIATIONS

  • Association of Information Systems (AIS), Student Member

  • Association of Computing Machinery (ACM), Student Member

  • Institute of Electrical and Electronics Engineers (IEEE), Student Member

  • Institute for Operations Research and the Management Sciences (INFORMS), Student Member

PROFESSIONAL SERVICES  (Reviewed Journals & Conferences)

Journal Reviews

  • Journal of Management Information Systems (JMIS): 4 reviews, 2019-2020
  • International Journal of Electronic Commerce (IJEC): 1 review, 2020
  • ACM Transactions on Management Information Systems (TMIS): 2 reviews, 2020
  • Information Systems Frontiers: 2 reviews, June 2018 and 2020

Program Committee and Editorial Board

  • IEEE International Conference on Data Mining (ICDM), Deep Learning for Cyber Threat Intelligence Workshop (DL-CTI)
  • Review Editor on the Editorial Board of Data Mining and Management (specialty section of Frontiers in Big Data)

Conference Reviews

  • International Conference of Information Systems (ICIS): 2 reviews, June 2019 and 2020
  • Workshop on Information Technologies & Systems (WITS): September 2019
  • Design Science Research in Information Systems & Technology (DESRIST): June 2019

AWARDS & HONORS

  • Selected for Doctoral Consortium of International Conference on Information Systems (ICIS), 2020.
  • IEEE S&P Student Travel and Registration Award for Deep Learning and Security Workshop, May 2020.
  • IEEE ISI 2018 Best Paper Award Runner-up, November 9, 2018 (First author of the paper titled: Detecting Cyber Threats in Non-English Dark Net Markets: A Cross-Lingual Transfer Learning Approach).
  • Concordia University 25th Anniversary Fellowship – Engineering and Computer Science Department, January 2015 (Awarded based on academic excellence to a few students each year).
  • Power Corporation of Canada Graduate Fellowship, May 2015 (Awarded based on academic excellence to 5 students each year).
  • Graduate Conference and Exposition Award, Concordia University, December 2015.
  • Team Ranked 1st in RoboCup Iran Open International Competitions 2007- Middle Size Robots.
  • Ranked with the highest GPA among university students in fall 2007 and spring 2008 with GPA of 18.43/20.00 and 19.50/20.00, respectively.

WORK EXPERIENCE

SAP Canada (Internship) 2015-2015 (4-month internship)

  • Role: Data & Software Engineer (Users behavior analysis for order management systems)
  • Address: 999 Boulevard de Maisonneuve West Montreal, Quebec H3A 3L4 Canada.

RELEVANT SKILLS

Data Mining and Machine Learning

  • Deep Learning for Text and Image
  • Text Mining and Information Retrieval
  • Big Data Tools: Hadoop, Spark
  • Data Mining: RapidMiner, SPSS, WEKA
  • Developing new Data Mining Algorithms for RapidMiner
  • Dimensionality Reduction Techniques (SVD, PCA, Supervised Feature Selection)
  • Open-source Machine Learning Tools: S-Space Library, JavaML Library, LibSVM Library, Autoclass, Waffles machine learning toolkit

Programming and Software Engineering

  • Object-Oriented Analysis and Design
  • Programming Languages: Python, Java, R, C/C++, C#
  • Database: MySQL, Microsoft SQL Server, Mongo DB, PostgreSQL
  • Rational Unified Process (RUP), Agile Scrum
  • Software Requirement Analysis, Use-case point estimation
  • Source code/build management: Git, SVN, Jenkins
  • Unified Modeling Language (UML): UML 2.0
  • IDEs and Tools: Eclipse, Microsoft Visual Studio

Essentials

  • Operating System: Linux, Microsoft Windows
  • Typesetting: LATEX, Microsoft Office

SELECTED GRADUATE & UNDERGRADUATE COURSES

Graduate:

Statistical Machine Learning, Machine Learning, Theory of Probability, Pattern Recognition, Statistical Natural Language Processing, Natural Language Understanding, Advanced Computational Linguistics, Cyber Threat Intelligence, Information Security Risk Management, Software Requirement Analysis, Enterprise Data Management

Undergraduate:

Artificial Intelligence, Neural Networks, Software Requirement Analysis, Decision Support Systems, Foundation of Compiler Design, Operating Systems, Software Engineering (I and II), Database Design, Object-Oriented Analysis & Design, Web Programming

REFERENCES

  • Hsinchun Chen, Ph.D. (Dissertation Committee Chair)

    Professor, University of Arizona, Eller College of Management, Department of Management Information Systems, 1130 E Helen St., McClelland Hall 430, Tucson, AZ 85721

    e-mail: hchen[@]eller.arizona.edu

    Phone: (520) 621-6219

  • Sue Brown, Ph.D. (Dissertation Committee Member)

    Professor & Department Head, University of Arizona, Eller College of Management, Department of Management Information Systems, 1130 E Helen St., McClelland Hall 430Q, Tucson, AZ 85721

    e-mail: suebrown[@]eller.arizona.edu

    Phone: (520) 621-2429

  • Jay F. Nunamaker Jr., Ph.D. (Dissertation Committee Member)

    Professor, University of Arizona, Department of Management Information Systems, 1130 E Helen St., McClelland Hall 430, Tucson, Arizona 85721

    e-mail: jnunamaker[@]cmi.arizona.edu

    Phone: (520) 621-4475

  • Mihai Surdeanu, Ph.D. (Minor Advisor)

    Professor, University of Arizona, Computer Science Department, Gould-Simpson 745, 1040 E 4th St., Tucson, AZ 85721

    e-mail: msurdeanu[@]email.arizona.edu

  • Helen Hao Zhang, Ph.D. (Co-author)

    Professor, University of Arizona, Department of Mathematics, 617 North Santa Rita Ave, ENR2 S323

    e-mail: hzhang[@]math.arizona.edu

    Phone: (520) 621-6868

  • Ching Y. Suen, Ph.D. (Master's Advisor)

    Professor, Concordia University, Computer Science & Software Engineering (CSE) Department, EV 3.105, 1455 de Maisonneuve West, Montréal, Québec, Canada H3G 1M8

    e-mail: suen[@]cse.concordia.ca

    Phone: (514) 848-2424 (ext. 3006)

  • Olga Ormandjieva, Ph.D. (Master's Advisor)

    Professor, Concordia University, Computer Science & Software Engineering (CSE) Department, EV 3.165, 1455 de Maisonneuve West, Montréal, Québec, Canada H3G 1M8

    e-mail: ormandj[@]cse.concordia.ca

    Phone: (514) 848-2424 (ext. 7810)

  • Adam Krzyzak, Ph.D. (Co-author)

    Professor, Concordia University, Computer Science & Software Engineering (CSE) Department, EV 3.279, 1455 de Maisonneuve West, Montréal, Québec, Canada H3G 1M8

    e-mail: krzyzak[@]cse.concordia.ca

    Phone: (514) 848-2424 (ext. 3007)