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Hong Liu was awarded a Ph.D. in Mathematics and an M.S. in Computer Science from the University of Arkansas, Fayetteville in 2000. Since then, he has ascended the academic ranks from Assistant to Full Professor, specializing in Mathematics and Computing. In 2019, he pioneered the Master of Science in Data Science program and serves as a professor in Data Science. He serviced on the National Selection Committee for the prestigious Presidential Awards for Excellence in Science, Mathematics, and Engineering Mentoring (PAESMEM) in recently years, and the NSF panels in Education and Human Resources (EHR) and Computer and Information Science and Engineering (CISE). His exceptional service was honored with the President and Board of Trustee’s Special Service Award at ERAU in 2014.

Dr. Liu is an interdisciplinary scholar with an extensive publication record, having authored 42��peer-reviewed articles across a variety of disciplines including partial differential equations, model-checking, robotics, data science, and STEM education. As a lead investigator and collaborator, Dr. Liu has contributed significantly to 15 sponsored research projects, successfully securing over $3 million in funding from prestigious bodies such as the NSF, the US Air Force, and the DOE, with him directly overseeing approximately $2 million.

At present, Dr. Liu is spearheading a pioneering collaborative effort involving 11 universities, which focuses on advancing adaptive distributed learning technologies, automating learning assessments, and enhancing data science workforce development. Furthermore, in partnership with peers at New Mexico State University and the University of Maryland at Baltimore County, Dr. Liu is applying AI and ontological frameworks to enhance data accessibility within the aviation and space industries.

1. PI of IUCRC Planning Grant ��ݮ��Ƶ: Center for Aviation and Space Data Analytics (NSF 2231629, $20,000). ����
2. Lead PI of the $1,600,000 NSF collaborative grant, Engaged Student Learning: Dev & Impl Level 2: Distributed Learning Data Science Program for Diverse Universities.” (PI of NSF $973,000 to ERAU).����
3. Project Evaluator, REU Site: Swarms of UAS. NSF 2150213 (PI R. Stansbury) ��
4. Co-PI, Engaged Student Learning: Dev & Impl, Level 1: Coalition for Undergraduate CDSE Education, (NSF1626602, 2017-2020, PI, M. Ikle. $510,000).�� ��
5. PI of NSF Grant, Coalition for Undergraduate Computational Science & Engineering Education, Co-PIs: A. Ludu & A. Gretarsson, 2013-2016, (NSF 1244967, $199,044).

Dr. Hong Liu looks forward to working together to enhance data accessibility and analytics within the aviation and space industries.��

1.����Founded Leverage (Learning enhancement via experimentation research and guided exploration) Research Lab in 2011��

2. Supervise and lead the development of the Eco-Dolphin AUV (Autonomous Underwater Vehicle), a REU project in progress sponsored primarily by ERAU undergraduate research grants ($30,000 to date).

3. Offer SeaPerch Robotics Summer Camp to middle school students��

4. ��Investigated and built a SBS Driver of Kmax data acquisition system for Jefferson Lab with the helps of three students in 2003-2004. This project results in three releases:�� KSBS Driver 1.2 for Winow-XP, KSBS Driver 1.2 for MacOS-X , KSBS Driver 2.2 for MacOS-X (Funded $7,0000 to R.B. Piercey and J.E. McKisson)��http://www.sparrowcorp.com/downloads/user-area-downloads,��ID12090502, Lui_KSBS-617

5.���� Investigated and built a device driver of Kmax data acquisition system that operates a family of NI-DIO cards for Jefferson Lab with the helps of three students 2004 – 2005.

6.���� Supervise students to implement a project on Gamma Camera Images Calibration for�� Jefferson Lab (2005 – 2006)

SERVICE

Advising the SIAM Student Chapter at Embry-RIddle Aeronautical University��

COMPUTER SKILLS��

• ��Mastered many software CASE/Computation tools (MATLAB, OSATE, Statemates, NuSMV, UPPAAL, Stella, OpCat, ANNIE, Weka, GATE, ParaView, etc.) and skills for math modeling, model-checking, and visualization
• Commanded many programming languages (C/C++, Java, Objective C, JNI, etc.) and developed several software packages, including real-time embedded systems.

PROFESSIONAL DEVELOPMENT
��
1.���� Awarded 5 professional certificates in Software Testing from the summer workshops sponsored by International Institute for Software Testing in Orlando in 2001.
2.���� Awarded a certificate of a summer course: ��System Development with
UML and Object-Process Methodology from MIT in 2002.
3. Summer�� Workshop on Computational Geometry and Applications - DIMACS (Discrete Math and Computer Science) sponsored by NSF, University of Rutgers in 2002.
4.���� Awarded 4 certificates in Computational Science Education in the summer workshops of NCSI (National Computational Science Institute, or Shodor), or 2003-2004, one in 2011.
�� 5.���� Awarded a certificate in Natural Language Processing and Visualization, summer ����workshop offered by CCICADA, a Department of Homeland Security Center of Excellence, 2010.��
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PROFESSIONAL MEMBERSHIPS
��
Member of ACM, Association for Computing Machinery
Member of SIAM, Society of Industry and Applied Mathematics��
Member of CUR,�� ��Council of Undergraduate Research��

Undergraduate��Mathematics courses: Statistics, ��College Algebra, Trigonometry, all Calculus Series, Ordinary Diff. Equations,�� Advance Engineering Mathematics��

Undergraduate Computer/Computational Science Courses,����Discrete Math and Data Structure, Data Mining,��Scientific Visualization (co-teach),��Mathematical Modeling and simulation

Graduate Math and Computer Science Courses: Partial Differential Equations, Model-Based Verification
(co-teach), Data Mining, Data Visualization, Data-Driven Modeling, and Graduate Research Project for Software Engineering, and Data Science.

1. ��H. Liu, The Global Solutions of the Cauchy Problem of Holomorphic PDE and Schwarz Potential Conjecture, J. of Mathematical Analysis and Appl, Oct 2000,Vol. 250, P.387–405.
2. H. Liu, J. Ryan, The Cayley Transformation on spherical and Hyperbolas via Clifford��Analysis, Clifford Analysis, and Its App, Nato Science Series: II, Vol 25, 2001, P.255 - 266.
   
3. H. Liu, J. Ryan, Clifford Analysis Techniques for Spherical PDE, The Journal of��Fourier Analsisand Appliaton, Volume 8, Issue 6, 2002, Pages 535 – 563.
4. H. Liu and D. P. Gluch, A Proposal for Introduction Model Checking into an Undergraduate Software Engineering Curriculum, The Journal of Computing Science in Colleges, Vol. 18, Num. 2, 2002, P. 259 – 270.
5. H. Liu, D. P. Gluch, Conceptual Modeling with the Object-Process Methodology in Software Architecture, The Journal of Computing Science in Colleges, Vol. 19, Num. 3, 2004, P.10– 21.
6. H. Liu, D. P. Gluch, Query Generation Guidelines and Consideration to Statecharts of Object-Oriented Designs, Proceeding of the Conference of Advances in Computer Sciences and Technology sponsored by IASTED (International Association of Science and Technology For Development) 2004, page 209-214.
7. H. Liu, J. E. McKisson, P. B. Piercey, Judy Chou, Yishi Li, An Empirical Solution to a Portable Device Driver for NI-DAQ-Card, Presented in Kmax Conference Sponsored by Sparrow Corp. Daytona Beach, March 2005.
8. H. Liu, P. B. Piercey, J. E. McKisson, B. Maisler, Y. Li, J. McKisson, J. Schuck, An Empirical Solution to a Kmax Device Driver for a Family of PCI-VME Adapters, Proceedings of Conference on Advances in Computer Science and Technology (IASTED), 2005, p. 42-47.
9. H. Liu, D. P. Gluch, Query Generation Template, and Temporal Query Generation, the Proceedings of the 44th Southeast ACM conference, 2006, page 80-84.
10. B. D Maisler, H, Liu, J.E. McKisson, Yishi Li, Eric Kvam,�� Voronoi Diagram and its Application to Spatial Calibration for Gamma Camera Images, the Proceedings of the third International Conference on Computer Graphics Theory and Applications, 2008, P. 68-73.
11. H. Liu, D. P. Gluch, Formal Verification of AADL Behavior Models: A Feasibility Investigation, the Proceedings of the 47th Southeast ACM conference, 2009
12. Pu Gao, Hong P. Liu, D. P Gluch, (2012) On Modeling, Simulating and Verifying a Decentralized Mission Control Algorithm for a Fleet of Collaborative UAVs, Procedia Computer Science, Volume 9, 792-801.
    
13. Hong Liu, Xudong Shi, Junzhen Shao, Qi Zhou,�� Stacey Joseph-Ellison, Johnathan Jaworski , The Mechatronic System of Eco-Dolphin - a Fleet of Autonomous Underwater Vehicles, Proceeding of International Conference of Advanced Mechatronics System 2015, Beijing, August 24-27, 2015. ��
14. Hong Liu, Tianyu Yang, and Jing Wang, Model Checking for the Fault Tolerance of Collaborative AUVs, to appear in IEEE High Assurance Systems Engineering Symposium, Orlando, Florida, January 7-9, 2016.
15. Hong Liu, Rufa Cheng, Tianyu Yang, and Jing Wang, Modeling and Verifying the Communication and Control of a Fleet of Collaborative Autonomous Underwater Vehicles, the Proceeding of 43rd Annual Conference of the IEEE Industrial Electronics Society, Beijing, Oct 2017.��
16. H. Liu, Mathematical Modeling and Visualization, a Preliminary Course Design for Computational Science Curriculum, Proceeding of Frontiers in Education Conference, 2005.
17. Jayathi Raghavan, Leslie Sena, David Bethelmy, Hong Liu, Problem solving experience through light-dose computational mathematical modules for Engineering students, the proceedings of the 2008 ASEE Annual Conference, (Nominated as best paper awards)
18. H. Liu, Offering Honors Course Option within an Ordinary Mathematical Course for Undergraduate Students in Engineering Majors, the Proc. of the 2008 ASEE Annual Conference
19. Leslie Sena, Hong Liu, David G. Bethelmy, and Jayathi Raghavan, Panel Discussion: Cultivating Students' Problem Solving Ability: Developing a Framework for Computational Science Modules, the Proceedings of CCSC-SE Conference, 2008.
20. Hong Liu, Jayathi Raghavan, A Mathematical Modeling Module with System Engineering Approach for Teaching Undergraduate Students to Conquer Complexity , The Proceedings of Conference ICCS 09 , Part II, LNCS5545, pp 93-102, 2009.
21. Jayathi Raghavan, Hong Liu, An Innovative Undergraduate Computational Math Curriculum for Engineering Students Seeking Dual Majors, the proc. of the ASEE Annual Conference, 2010.
22. Hong P. Liu, Andrei Ludu, ACE - A Model Centered REU Program Standing on the Three Legs of CSE: Analysis, Computation, and Experiment, Procedia Computer Science, Volume 9, 1773-1782, 2012.
23. Ming Wang, Hong P. Liu, Drew Hwang, Applying Data Analytics to Development of the Web-based Information Security Career System,�� International Journal of Information and Electronics Engineering, Vol. 2, No. 5, September 2012.
24. Liu, H. Klein, J. (2013), Using REU Project and Crowdsourcing to Facilitate Learning on Demand, Proceedings of IADIS International Conference on Cognition and Explorative Learning at Digit Ages, Fort Worth, Texas, pp 251-258. ��
25. Simpson, A. Ludu , H. J. Cho and H. Liu, 2014, Experimental and theoretical studies on visible light attenuation in water, Atmospheric and Oceanic Physics, retrievable from http://arxiv.org/abs/1408.3883
26. Lyons, T, Ginther, M. Mascarenas, P. Rickard, E. Robinson, J.�� Braeger, J, Liu, H., and Ludu A. 2014, Nonlinear Decelerator for Payloads in Aerial Delivery Systems. I: Design and Testing, Nonlinear Dynamics, retrievable from http://arxiv.org/abs/1408.4190.
27. Book chapter, Hong P. Liu, Maria Ludu, and Douglas Holton, Can K-12 Math Teachers Train Students to Make Sound Logic Reasoning?�� – A Question Affecting 21st Century Skills, Book Chapter in “Emerging Technologies for STEAM Education’, Edited by Xu Ge, Michael Spector, and Dirk Ifenthaler, 2015, Springers, pp 331-353.
    
28. Book Chapter, Hong P Liu, Jerry Klein, and Sirani Perera, Chapter 10: Using Model-Based Learning to Promote Computational Thinking Education, Educational Communications Technology Issues & Innovations, Peter Rich and Charles B. Hodges (Eds): “Emerging Research, Practice, and Policy on Computational Thinking”, Springer, 2017, pp 153-172. ��
29. Hong Liu, Matthew Ikle, Michael Spector, and Jerry Klein, Using cyberlearning, coalitions, and model-based learning to provide specialized courses for small numbers of students, AAAS PI Symposium Envisioning the Future of Undergraduate STEM Education, Research and Practice, April 27 - 29 in Washington DC, 2016, http://www.enfusestem.org/projects/coalition-for-undergraduate-computational-science-engineering-education-proof-of-concept-5/.
30. Steven Lehr, Hong Liu, Sean Klinglesmith, Alex Konyha, Natalia Robaszewska, Jacob Medinilla, Use Educational Data Mining to Predict Undergraduate Retention, Submitted to the 16th IEEE International Conference on Advanced Learning Technologies ‐ ICALT2016, Austin, Texas.
31. Hong Liu, Andrei Ludu, Jerry Klein, Michael Spector, and Matthew Ikle, Innovative Model, (2017) Tools, and Learning Environments to Promote Active Learning for Undergraduates in Computational Science & Engineering, the Journal of Computational Science Education, Volume 8 Issue 3 pp. 11 – 18, https://doi.org/10.22369/issn.2153-4136/8/3/2 .
32. Liu H, Spector JM, Ikle M. Computer technologies for model-based collaborative learning: A research-based approach with initial findings. Comput Appl Eng Educ. 2018;1–10. https://doi.org/10.1002/cae.22049. ��
33. Liu, H, Warner, T., Ikle, M, and Mittal S. (2020) Harness Big Data by iCycle - Intelligent Computer-supported Hybrid Collaborative Learning Environment, Int. J. Smart Technology and Learning, Vol. 2, No. 1, 2020, pp 31-47.
34. Hong Liu, Timothy Bernard & Keshav Acharya, (2020) Using GIFT to Develop Adaptive Remedial Courses for Graduate Degree Programs in Data Science, Proceedings of the 8th Annual GIFT Users Symposium, 61-68.
35. Hong Liu, Tim Bernard, Elif Cankaya, Alex Hall, Task-Agnostic Team Competence Assessment and Metacognitive Feedback for Transparent Project-Based Learning in Data Science, to appear on the Int. Journal of Smart Learning Technology https://www.inderscience.com/info/ingeneral/forthcoming.php?jcode=ijsmarttl .
36. Hong Liu and Xiaoqing Gu, Leveraging AI, Big Data, and Educational Technology to Promote Collaborative Learning and Improve Cyberlearning Courses, Synopsis and Linked Presentations of the Workshop at Orlando, Florida, June 4-6, 2019, and the Online Workshop August 13-14, 2020, to appear on the Int. Journal of Smart Learning Technology, https://www.inderscience.com/info/ingeneral/forthcoming.php?jcode=ijsmarttl .
37. Sheldon Liang, Melanie Van Stry, Hong Liu, UnIX-CARE: Universal Interface & Experience via Collaborative Archive Repository Express, Open Access book, "E-service Digital Innovation" edited by Dr. Kyeong Kang, 2022.�� ��
38. Fadjimata Anaroua, Hong ��Liu, and Naomi Malone, Using GIFT to Develop an Adaptive Distributed Learning Environment Supporting Data Science Competencies, 7., Proceedings of the 11th Annual GIFT Users Symposium, pp, 40-49. ��
39. Ke Feng, Dahai Liu, Yongxin Liu, Hong Liu, Houbin Song, A Graph-Analytic Approach to Dynamic Airspace Configuration, the Proceeding of the 24th IEEE International Conference on Information Reuse and Integration, 2023.
40. Clauditte T. Tchakoua, Lekan Latiwo, Martha Tchounwou1, Hong Liu, Clement G. Yedjou, Leveraging Artificial Intelligence and Interactive Learning Approaches for Enhanced Student Achievement and Perspectives in a Biology Course, International Journal of Science Academic Research, 2023.��
41. Hong Liu, Naomi Malone, Clement Yedjou, Rop Chadwick, Jason Haag, Michael Spector, Automating Formative Assessment for STEM Courses in Hybrid Learning Environments, the IEEE Global Engineering Education Conference (EDUCON), Kos, Greece,��2024.��