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Please see recent publications at Google Scholar.  

  1. B.Taylan, A.Satyanarayana, and S.Samb, “A Writing Tool that Provides Real-Time Feedback to Students on their Grammar Using Deep Learning” 2019 ASEE Mid-Atlantic States Fall Conference, New York, New York, November 1-2, 2019.

  2. K.Goodlad, S.Cheng, J.Sears, M. Diaz, A.Satyanarayana, and P.Kreniske, (2019). “Our Stories”: First-year Learning Communities Students Reflections on the Transition to College. Learning Communities Research and Practice, 7(2), Article 5.

  3. A.Satyanarayana, R.Lansiquot, C.Rosalia. “Using Prescriptive Data Analytics to Reduce Grading Bias and Foster Student Success”, 49th IEEE Annual Frontiers in Education (FIE ’19), Cincinnati, OH, Oct 16th – Oct 19th, 2019.

  4. A.Satyanarayana, K.Goodlad, J.Sears, P.Kreniske, M.Diaz and S.Cheng, “Using Natural Language Processing Tools on Individual Stories from First Year Students to Summarize Emotions, Sentiments and Concerns of Transition from High School to College”, 126th ASEE Annual Conference 2019, Tampa, FL, June 15th – June 19th 2019.

  5. A.Satyanarayana, and L.Baron, “A Peer based Tutoring and Mentoring Model for First Year Computer Science Courses Based on Strategies Used by Songbirds for Learning”, 50th ACM Special Interest Group on Computer Science Education (SIGCSE ’19), February 27– March 2nd, 2019, Minneapolis, Minnesota, USA.

  6. A.Satyanarayana, R.Natarajan, and L.Baron, “How Songbirds Learn to Sing Provides Suggestions for Designing Team Projects for Computing Courses”, ASEE Mid-Atlantic Section Fall 2018 Conference, October 26-27th, 2018.

  7. C. Cabo and A.Satyanarayana, “Promoting students’ social interactions results in an improvement in performance, class attendance and retention in first year computing courses”, 48th IEEE Annual Frontiers in Education (FIE’18), San Jose, California, October 4th–6th, 2018.

  8. A.Satyanarayana, J.Kusyk and Y-W.Chen, “Design of Cloud Based Robots using Big Data Analytics and Neuromorphic Computing”, 31st IEEE Canadian Conference on Electrical and Computer Engineering (CCECE 2018), Quebec, Canada, May 13-16th 2018.

  9. J. Bivens, A.Satyanarayana, J. Chen, “Pros and Cons of Using Data Analytics for Predicting Academic Performance in Computer Science Courses”, 49th ACM Special Interest Group on Computer Science Education (SIGCSE ’18), February 21–24, 2018, Baltimore, MD, USA (BoF discussion).

  10. C. Cabo and A.Satyanarayana, “Building a Community of First Year Students Improves Student Retention and Performance in Computing Courses”, 49th ACM Special Interest Group on Computer Science Education (SIGCSE ’18), February 21–24, 2018, Baltimore, MD, USA (Poster).

  11. A. Satyanarayana, J.Kusyk and H.Li, “Common Assessment of Two Related Courses to Reduce Grading Bias and Improve Readiness of the Students for Corporate Environments”, ASEE Mid-Atlantic Section Fall 2017 Conference, Penn State University (Berks), Reading, PA, Oct 6-7th, 2017.

  12. N.Benakli, B.Kostadinov, A. Satyanarayana and S.Singh, “Introducing computational thinking through hands-on projects using R with applications to calculus, probability and data analysis”, International Journal of Mathematical Education in Science and Technology (Taylor & Francis),(2017), Vol 48(3), pp 393-427.

  13. A. Satyanarayana,Performance modeling of CMOS inverters using support vector machines (SVM) and adaptive sampling”, Journal of Microprocessors and Microsystems (Elsevier) (2016), Volume 46(B), pp 193-201.

  14. A. Satyanarayana and R.Chinchilla “Ensemble Noise Filtering for Streaming Data Using Poisson Bootstrap Model Filtering”, 13th International Conference on Information Technology – New Generations (ITNG 2016), Las Vegas, NV, April 2016, pp 869-879.

  15. A. Satyanarayana and M. Nuckowski, “Data Mining using Ensemble Classifiers for Improved Prediction of Student Academic Performance”, ASEE Mid-Atlantic Section Spring 2016 Conference, George Washington University, Washington D.C, April 2016.

  16. S.Singh, N.Benakli, B.Kostadinov, A. Satyanarayana, “Learning By Visualization and Simulation”, 2015 NYSMATYC Annual Conference, April 17-19, Rochester, NY.

  17. A. Satyanarayana,Intelligent Sampling for Big Data Using Bootstrap Sampling and Chebyshev Inequality”, 27th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE 2014), Toronto, ON, May 2014.

  18. A. Satyanarayana, V. Acquaviva “Enhanced Cobweb Clustering for Identifying Analog Galaxies in Astrophysics”, 27th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE 2014), Toronto, ON, May 2014.

  19. R. Lansiquot, A. Satyanarayana and C. Cabo, “Using interdisciplinary game-based learning to develop problem solving and writing skills”, 121st ASEE Annual Conference 2014, Indianapolis, IN, June 2014.

  20. A. Satyanarayana, H. Li, and J. Braneky. “Improving retention by mentoring and tutoring freshmen studentsIEEE ASEE 2014 Zone 1 Conference, University of Bridgeport, CT, April 3rd-5th, 2014.

  21. B. King and A. Satyanarayana, “Teaching data mining in the era of big data”, 120th ASEE Annual Conference 2013, Atlanta, GA, June 2013.

  22. A. Satyanarayana, “Software Tools for Teaching Undergraduate Data Mining CourseASEE-2013 Mid-Atlantic Fall Conference, University of the District of Columbia, Washington DC, October 11-12th 2013.

  23. N. Benakli, A. Satyanarayana, S. Singh, and A. Taraporevala “Learning while VisualizingASEE-2013 Mid-Atlantic Spring Conference, New York City College of Technology, Brooklyn, NY, April 26-27th 2013.

  24. P. Bailey, N. Craswell, R. White, L. Chen, A. Satyanarayana, and S .M . Tahaghoghi, “Evaluating whole-page relevance”, 33rd international ACM SIGIR conference on Research and development in information retrieval (SIGIR 2010), pp. 767-768.

  25. P. Bailey, N. Craswell, R. White, L. Chen, A. Satyanarayana, and S .M . Tahaghoghi, “Evaluating Search Systems Using Result Page Context”, 3rd Symposium on Information Interaction in Context (IIiX 2010), pp 105-114. (Best Paper Finalist)

  26. A. Satyanarayana “Data Mining For Large Datasets: Intelligent Sampling and Filtering”,
    PhD Thesis, State University of New York, Albany, 2006 (Distinguished Dissertation Award).

  27. A. Satyanarayana, “Intelligent Data Selection Using Sampling and Filtering”, Twenty-First National Conference on Artificial Intelligence Doctoral Consortium (AAAI 2006)

  28. A. Satyanarayana and I. Davidson, “A Dynamic Adaptive Sampling Algorithm (DASA) for Real World Applications: Finger Print Recognition and Face Recognition,” 15th International Symposium on Methodologies for Intelligent Systems (ISMIS’05), Saratoga Springs, NY.

  29. I. Davidson, A. Satyanarayana, A. Grover and G.K. Tayi “A General Approach to Incorporate Data Quality Matrices into Data Mining Algorithms,” 10th International Conference on Knowledge Discovery and Data Mining (KDD’04), Seattle, WA.

  30. I. Davidson and A. Satyanarayana, “Speeding up k-means Clustering by Bootstrap Averaging. IEEE International Conference on Data Mining (ICDM 03) Workshop on Clustering Large Data Sets.



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