Hamed Alhoori

Hamed Alhoori

I am an Associate Professor (tenured) in the Department of Computer Science at Northern Illinois University and am the Director of the Data Analytics Theory and Applications (DATA) Laboratory. My research aims to advance new data-driven scientific discoveries by quantifying dynamic global research patterns and needs, mining and learning from massive unstructured scholarly datasets, modeling emerging multidimensional web indicators, recommending scholarly content pertinent to researchers’ activities and interests, and predicting the societal impact of research. My current work span several new directions which include building explainable artificial intelligence models to identify reproducible research, predicting the broader impact of research, understanding public engagement with science, and developing exceptionally effective new technologies that improve the research process and leverage scientific knowledge.

Acknowledgments: My research has been supported by NSF, ANL, NIU, TAMU, UOB, QNRF, and ADHO. Thank you!


  • Data Science
  • AI
  • Text Mining
  • Machine Learning
  • Science of Science
  • Social Media Analytics
  • Computational Social Science


  • PhD in Computer Science

    Texas A&M University, College Station, Texas

  • M.S. in Computer Science

    Texas A&M University, College Station, Texas

  • BSc in Computer Science

    University of Bahrain


Research Assistant positions

I am looking for highly motivated and hard-working undergraduate and graduate (MS/PhD) students to work on exciting projects in Data Science, AI, Text Analytics, and Social Media Mining. If you are interested, please send me your CV, transcripts, TOEFL and GRE scores (if applicable), and all other supporting documents.

Grants and Awards

Predicting Scientific Fields using Machine Learning and Text Mining Techniques

Graduate Student Travel Grant Award

Scholarship for PhD in Computer Science

Student scholarship

Scholarship for MS in Computer Science

Scholarship for a Bachelor in Computer Science

Recent & Upcoming Talks



Visiting Scientist

Argonne National Laboratory

2016 – 2016 Illinois

Research Associate

Qatar University

2013 – 2014 Qatar

Research Assistant

Texas A&M University

2011 – 2015 Texas


Identifying Reproducible Research Using Human-in-the-loop Machine Learning

Create datasets, reproducibility metrics, and machine learning models that estimate a confidence level in the reproducibility of a published work.


Quickly discover relevant content by filtering publications.

Early indicators of scientific impact: Predicting citations with altmetrics

Identifying important scholarly literature at an early stage is vital to the academic research community and other stakeholders such as …

Evaluating the Effects of Acid Fracture Etching Patterns on Conductivity Estimation Using Machine Learning Techniques

The successful design of an acid fracture job requires accurate prediction of fractured well productivity. Productivity estimation …

Analyzing Twitter Bot Activity on Academic Articles

Given its ascendancy as a way to make connections worldwide, social media is affecting all areas of people’s lives. This paper focuses …

Data-Driven Acid Fracture Conductivity Correlations Honoring Different Mineralogy and Etching Patterns

Acid-fracturing operations are mainly applied in tight carbonate formations to create a highly conductive path. Estimating the …

Measuring the Diversity of Facebook Reactions to Research

Online and in the real world, communities are bonded together by emotional consensus around core issues. Emotional responses to …


Ph.D. Dissertation Supervisor

  1. Akhil Pandey Akella (Spring 2020 – present) Reproducibility, Uncertainty in Deep Learning, Explainable Artificial Intelligence
  2. Abdul Rahman Shaikh (Fall 2020 – present) Machine Learning, Computer Vision
  3. Harish Varma Siravuri (Fall 2020 – present) Social Data Science, Public Understanding of Science
  4. Mrinmoy Roy (Fall 2020 – present) Health Informatics
  5. Murtuza Shahzad Syed (Fall 2020 – present) Automated Machine Learning
  6. Rahul Reddy Thummala (Fall 2020 – present) Explainable Artificial Intelligence
  7. Shahadat Hossain (Fall 2020 – present) Data Visualization, Reproducibility
  8. Miftahul Jannat Mokarrama (Fall 2021 – present) Reproducibility, Social Data Science

M.S. Thesis Supervisor

  1. Abdul Rahman Shaikh (Spring 2018 – present) Machine Learning, Computer Vision
  2. Murtuza Shahzad Syed (Fall 2017 – Fall 2020) Development of Machine Learning Models to Predict the Online Impact of Research
  3. Ashiqur Rahman (Fall 2020 - present) Detecting COVID-19 Misinformation
  4. Cole Freeman (Spring 2020) The Emotions of Science: Using Social Media to Gauge Public Emotions Toward Research Topics
  5. Akhil Pandey Akella (Fall 2019) Using Machine Learning Models to Discover Promising Research
  6. Harish Varma Siravuri (Spring 2018) Assessment of Societal Impact of Research. Data Scientist at Nielsen

M.S. Thesis Committee Member

  1. Venkata Devesh Seethi (Fall 2019 – present)
  2. Manohar Sai Jasti (Fall 2019) Data Scientist at Kaizen Analytix
  3. Mrinal Kanti Roy (Fall 2019) Software Engineer at Coyote Logistics
  4. Vishrant Krishna Gupta (Fall 2018) Software Engineer III at Groupon
  5. Ashli Fain (Fall 2018) Software Engineer at American Express
  6. Eric Lavin (Spring 2018) Data Scientist at Allstate
  7. Bharat Kale (Spring 2018) PhD student in Data Visualization

M.S. Students Advising (Semester-Long Research Project)

  1. Ashiqur Rahman (Spring 2020 - Summer 2020) Research Assistant
  2. Srikanth Nagidi (Summer 2019 – Fall 2019)
  3. Pavan Kondamudi (Spring 2017 – Spring 2018) Data Scientist at Oracle
  4. Pradeep Maddipatla (Fall 2017 – Spring 2018)
  5. Vishal Panguru (Spring 2017) Data Engineer III at Anthem, Inc.
  6. Yaswanth Vayalpati (Fall 2017) Developer at Mastech Digital
  7. Brian Homerding (Spring 2017) Engineer at Argonne Laboratory
  8. Jagadeesh Vinnakota (Fall 2016) AI Consultant at Home Depot
  9. Saiteja Yagni (Fall 2016) Data Engineer at Cloudwick
  10. Reajeswari Gundu (Fall 2016) Full stack developer at UCLA Health
  11. Kartheek Chintalapati (Fall 2016) Developer at K-Rise Systems
  12. Sai Krishna Vemuri (Fall 2016) Engineer at HERE Technologies
  13. Aparajita Kamath (Fall 2016) Senior Software Developer at Westpac
  14. Wesam Alruwaili (Summer 2016 – Fall 2016) Instructor at the Jouf University
  15. Himanshu Verma (Summer 2016 – Fall 2016) AI Engineer at Ford Motor Company
  16. Kavya Devarapally (Summer 2016) Engineer at Cerner Corporation
  17. Avinash Chirumamilla (Summer 2016) Software Engineer at Microsoft


  1. Enrique Nueve (Fall 2018 – Spring 2020) Machine Learning Researcher at Argonne Laboratory
  2. Ethan Pitre (Summer 2019) Software Developer at Epic
  3. Sahithi Challapalli (Fall 2018 – Spring 2019) Research rookie
  4. Aleena Ahmed (Fall 2018) Business Intelligence Intern at Zebra
  5. Luis Arredondo (Fall 2017 – Spring 2018) Honors capstone project. “A Study of Altmetrics Using Sentiment Analysis,” MS in CS at UIC
  6. Joseph McDade (Fall 2017 – Spring 2018) Honors capstone project. “Can We Predict Reproducible Scholarly Research?” Consultant at Red Hat
  7. Olsi Shehu (Fall 2017) Research rookie. Consultant at NxT Team
  8. Shawn Dust (Summer 2017 – Fall 2017) Software Engineer at TransUnion
  9. Justin Bradley (Summer 2017)
  10. James Bonasera (Summer 2017) Campus Innovator at Discover
  11. Eric Youngberg (Spring 2017) Honors capstone project, “Improving Speech and Speaker Recognition For Multi-Speaker Conversations,” Software Developer at Sasaki
  12. Bradley Protano (Spring 2017) Software Engineer at Discover
  13. Jamieson Walker (Fall 2016 – Spring 2017) Software Engineer at Broadcom Inc.
  14. Jonathan Gaff (Spring 2016 – Summer 2016) Engineer at University of Chicago
  15. Christian Bailey (Summer 2016 – Summer 2017)
  16. Alexandre Sopha (Summer 2016) Software Engineer at Capital One


  • CSCI 637: Pattern Recognition and Data Mining II (Spring 2021)
  • CSCI 636 - Pattern Recognition and Data Mining I (Fall 2020)
  • CSCI 490/642, Information Storage and Retrieval (Spring 2020, Spring 2019)
  • CSCI 490/641, Big Data Analytics (Fall 2019, Fall 2018, Spring 2018)
  • CSCI 490/680, Data Science and Analytics (Spring 2017)
  • CSCI 490/680, Mining Massive Datasets (Spring 2016)
  • CSCI 630, Computer Networks (Fall 2017, Fall 2016)
  • CSCI 490/512, Computer Networks (Spring 2020, Fall 2019, Spring 2018)
  • CSCI 340, Data Structures and Algorithm Analysis (Fall 2018, Spring 2018, Fall 2017, Spring 2017, Fall 2016, Spring 2016, Fall 2015)


Editorial Board

  • International Journal of Digital Libraries (IJDL) (2020 – present)

Program Committee Member

  • The International AAAI Conference on Web and Social Media (ICWSM) 2018, 2019, 2020, 2021
  • ACM/IEEE Joint Conference on Digital Libraries (JCDL) 2016, 2017, 2018, 2019, 2020, 2021
  • The International ACM Conference on Web Science 2020, 2021
  • Empirical Methods in Natural Language Processing (EMNLP) 2021
  • IEEE International Conference on Multimedia Big Data 2021
  • International Conference on Theory and Practice of Digital Libraries (TPDL) 2017, 2018, 2019, 2020, 2021
  • The annual conference of the Asia-Pacific chapter of the Association for Computational Linguistics (AACL) 2020
  • International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (KMIS) 2020
  • Second Workshop on Scholarly Document Processing (SDP) at NAACL 2021
  • ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR) 2018 Doctoral Consortium
  • The International Conference on Social Informatics (SocInfo) 2019, 2020
  • The International Conference on Advanced Collaborative Networks, Systems and Applications (COLLA) 2018, 2019
  • The ACM International Conference on Information and Knowledge Management (CIKM), 2018
  • Southern Data Science conference 2019
  • The Eleventh International Conference on Creative Content Technologies CONTENT 2019
  • Workshop on Altmetrics for Research Outputs Measurement and Scholarly Information Management (AROSIM) 2018
  • Workshop “Scholarly Big Data: AI Perspectives, Challenges, and Ideas” at the International Joint Conference on Artificial Intelligence 2016


  • ACL/IJCNLP 2021
  • Computer Supported Cooperative Work (CSCW) 2021
  • BMC Medical Informatics and Decision Making 2021
  • Expert Systems with Applications, 2020
  • Journal of Informetrics, 2020
  • Journal of Network and Computer Applications, 2019
  • Journal of the Association for Information Science and Technology (JASIST), 2017, 2018
  • International Journal on Digital Libraries (IJDL), 2015, 2017, 2018, 2019
  • Social Network Analysis and Mining (SNAM), 2017, 2018
  • iConference 2015, 2017, 2018, 2019, 2020, 2021
  • Scientometrics 2018
  • PLOS ONE 2017, 2020

Conference Session Chair

  • “Scholarly Documents,” JCDL 2019, University of Illinois at Urbana-Champaign.
  • “High Performance towards Big Data”, CIKM 2016: The 25th ACM International Conference on Information and Knowledge Management.

Internal Service

  • Member, Personnel Committee (Fall 2021 – present)
  • Member, College Council (Fall 2021 – present)
  • Chair, Colloquium Committee (Fall 2018 – Spring 2020)
  • Member, Undergraduate Studies Committee (Fall 2018 – present)
  • Member, Colloquium Committee (Fall 2015 – Spring 2018)
  • Member, Graduate Studies Committee (Fall 2016 – Spring 2019)
  • Member, Advisory Committee (Fall 2017 – Spring 2018)
  • Member, Grade Review Board Committee (Fall 2017 – Spring 2019)


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