Smiljana Petrovic, Ph.D.

Dr. Smiljana Petrovic teaches courses in artificial intelligence, data mining, database and advanced database systems, software engineering as well as other undergraduate and graduate courses. Her research interests are in the development of machine learning techniques for authorship attribution and for solving constraint satisfaction problems. Her authorship attribution methodology was actively used for authorship of 18th Century political writing, with special attention to the work of Thomas Paine.

Smiljana Petrovic has been a member of Iona's Computer Science Department since 2008. She has taught artificial intelligence, data mining, database and advanced database systems, software engineering and a variety of undergraduate and graduate courses. Her authorship attribution methodology was actively used for authorship of 18^th Century political writing, with special attention to the work of Thomas Paine. She has been mentoring a number of students working on master theses and independent research projects about applications and implementations of data mining methods. Dr. Petrovic is the recipient of the 2014 Br. William B. Cornelia Distinguished Faculty Award, 2022 Faculty Senate Senior Faculty Award, and the 2023 Br. Arthur A. Loftus Outstanding Student Research Award.

Chapters in edited volumes

• G. Berton, M. Crowder, L. Ivanov, S. Petrovic (2024): Identifying "A Slave": The Iona College Text Analysis Project Explores a Mystifying Letter to Thomas Jefferson, The American Revolutions in the Digital Age (Slonimsky, N., Boonshoft, M. and Wright, B. editors), Cornell University Press (Chapter 11, pp. 201-219)
• Berton G., Petrovic S., Schiaffino R., Ivanov L. (2016), “Examining the Thomas Paine Corpus: Automated Computer Author-Attribution Methodology Applied to Thomas Paine’s Writings”, New Directions in Thomas Paine Studies, Palgrave Macmillan, Editors: S. Cleary, I. Stabell, DOI: 10.1057/9781137589996
• Epstein, S. L. and S. Petrovic (2012) “Learning a Mixture of Search Heuristics” (Y. Hamadi, E. Monfroy and F. Saubion, editors), Autonomous Search, Springer (Chapter 5, pp. 97-124).
• Epstein, S. L. and S. Petrovic (2011) “Learning Expertise with Bounded Rationality and Self-awareness” (M.T. Cox and A. Raja, editors). MetaReasoning: Thinking about Thinking, MIT Press (Chapter 4, pp. 43-58).

Journal Articles

• Petrovic S., Berton G., Campbell S., Ivanov L. (2015), "Attribution of 18th Century Political Writings Using Machine Learning”, Journal of Technologies in Society, Common Ground.
• Petrovic, S and S. L. Epstein (2008). “Tailoring a Mixture of Search Heuristics”. Constraint Programming Letters 4:15-38.
• Petrovic, S. and S. L. Epstein (2008). “Random Subsets Support Learning a Mixture of Heuristics”. International Journal on Artificial Intelligence Tools (IJAIT), pp. 501-520.

Conference Proceedings

• Petrovic I., Petrovic S., Palesi I., Calise A. (2019) “Eliminating Sycophants to Improve Authorship Attribution”, In Proceedings of 32nd International FLAIRS Conference (FLAIRS-32), pp. 44-49, Sarasota, Florida.
• Petrovic, Smiljana, Ivan Petrovic, Ileana Palesi, and Anthony Calise. 2018. “Weighted Voting and Meta-Learning for Combining Authorship Attribution Methods.” In International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2018). Madrid, Spain.
• Lubomir Ivanov, Smiljana Petrovic (2015) "Using Lexical Stress in Authorship Attribution of Historical Texts", 18th International Text, Speech and Dialog Conference (TSD 2015), Plzen, Czech Republic
• Petrovic, S., G.Berton, R.Schiaffino, L.Ivanov (2014) “Authorship Attribution of Thomas Paine Works”, International Conference on Data Mining (DMIN'14), Las Vegas, NV
• Epstein, S. L. and S. Petrovic (2008). “Learning Expertise with Bounded Rationality and Self-awareness”. In Proceedings of AAAI Workshop on Metareasoning, Chicago, Illinois.
• Petrovic, S., S. L. Epstein and R. J. Wallace (2007). “Learning a Mixture of Search Heuristics. Workshop on Autonomous Search”, Principles and Practice of Constraint Programming CP-07, Providence, Rhode Island.
• Epstein, S. L. and S. Petrovic (2007). “Learning to Solve Constraint Problems. Workshop on AI Planning and Learning”, International Conference on Automated Planning and Scheduling, ICAPS-07, Providence, Rhode Island.
• Petrovic, S. and S. L. Epstein (2007) “Preferences Improve Learning to Solve Constraint Problems”, Workshop on Preference for Artificial Intelligence, AAAI-07 pp. 71-78, Vancouver, British Columbia, Canada.
• Petrovic, S. and S. L. Epstein (2007) “Random Subsets Support Learning a Mixture of Heuristics”, In Proceedings of 20th International FLAIRS Conference, pp. 616-621, Key West, Florida.
• Petrovic, S. and S. L. Epstein (2006) “Relative Support Weight Learning for Constraint Solving”, Workshop on Learning for Search, AAAI-06, pp. 115-122, Boston, Massachusetts.
• Petrovic, S. and S. L. Epstein (2006) “Full Restart Speeds Learning”, In Proceedings of the 19th International FLAIRS Conference, Melbourne Beach, Florida.

Conference Presentations, Panels and Published Abstracts

• Ivanov L, S. Petrovic, T. Ruggio (2019): “Identification and Attribution in the Digital Age”, Panel, 30th Annual Conference of the International Information Management Association (IIMA-2019), Iona University, New Rochelle, NY
• Lubomir Ivanov, Smiljana Petrovic, “The Authorship Attribution Project”, Revolutionary Texts in a Digital Age, Thomas Paine’s Publishing Networks, Past and Present (ITPS 2018), New Rochelle, NY
• Smiljana Petrovic, Gary Berton, Sean Campbell: “Data Mining in Authorship Attribution of 18th Century Political Writings”, Eleventh International Conference on Technology, Knowledge, and Society, February 2015, University of California, Berkeley, CA
• Smiljana Petrovic, Lubomir Ivanov, Gary Berton, Robert Schiaffino (2013) “Authorship Attribution of Thomas Paine Works”, Eighth International Conference On Interdisciplinary Social Sciences, Prague, Czech Republic.
• Smiljana Petrovic (moderator), Paul Benjamin, Lubomir Ivanov, Aaron Kershenbaum, Ronald R. Yager (2013): Data Mining Panel, 24th Annual Conference International Information Management Association (IIMA), Iona University, New Rochelle, NY.
• Smiljana Petrovic, Natalie Redcross (2013): "Working with nonprofit organizations to enhance the student learning experience", Great Ideas for Teaching Students (GIFTS) Panel, 71st Annual New York State Communication Association Convention, Ellenville, NY
 Ellenville, NY.
• Sean Campbell, Geoffrey Cawley, S. Lee, S. Petrovic (2013) “Determining the Concentration of Caffeine in CH2Cl2 by Analyzing Near Infrared Spectra Using Artificial Neural Networks and Support Vector Machines”, ACS Northeast Regional Meeting, New Haven, CT.
• Robert Schiaffino, Smiljana Petrovic, Gary Berton (2012) “Author Attribution of Paine and his Contemporaries”, The First International Conference of Thomas Paine Studies at Iona University, New Rochelle, NY.
• Campbell S., Cawley G., Towler K., Ciurczak E., Lee S., Petrovic S. (2012) “Using Machine Learning Techniques to Classify Plastics, Organics, and Documents by Near Infrared Spectroscopy”, Eastern Analytical Symposium (EAS), November 12-15, Somerset, NJ.
• Frances Bailie, Adel Abunawass, Smiljana Petrovic, Deborah Whitfield (2011) “Untangling the maze of pedagogical strategies for introductory programming”, Journal of Computing Sciences in Colleges, Volume 26 Issue 6, Consortium for Computing Sciences in Colleges. Presented at CCSCNE 2011, Springfield, MA.
• Frances Bailie, Keitha Murray, Smiljana Petrovic, Deborah Whitfield (2010) “Incorporating ethics into the computer science curriculum: multiple perspectives”, Journal of Computing Sciences in Colleges, Volume 25, Issue 3, Consortium for Computing Sciences in Colleges. Presented at CCSCE 2009, Villanova, PA.

• Nick Hunziker (2024) "Quantitative Analysis of Chess Strategy Through Machine Learning", Master Thesis research
• Thomas Burger (2023) "Manipulation of Emotive Qualities in Music Through Algorithms and Machine Learning", Master Thesis research
• Catherine DiProperzio (2023) "Detecting Schizophrenia in Texts Using Machine Learning​", Honors Thesis research
• Elijah Williams (2023) "Detection of Phishing Emails Through Natural Language Processing and Supervised Machine Learning", Honors Thesis research
• James Ollen (2021) "The Use of Data Mining in the Criminal Justice System" Honors Thesis research
• Catherine DiProperzio (2021) "Authorship Attribution of Collaborative Writings", CBL Scholarship report
• Madison Lopol (2021) "Predictive Evaluation of Student's Performance", CBL Scholarship report
• Adonis Paulino, Kylie Etwaroo, Diego Rivera (2021): DESIRE Summer Research
• Robert Larca, Diego Rivera (2020): DESIRE Summer Research
• Mariama Njie (2020) "Using Number of Contributor (NoC) analysis to study forensic DNA samples", Master Thesis
• Kathy Nguyen (2020) "Detecting phishing websites", CBL Scholarship report
• Haifa Ateeq Alsubhi (2018) “Reducing the Hairball Effects on the Network Visualization”, MS Thesis
• Eric Geiss (2018): "Improving the Performance of a Feed-forward Artificial Neural Network by Introducing a Genetic Algorithm", MS Thesis
• Taif Alshammari (2018): "The Impact of Outliers on Classification", MS Thesis
• Joshua J. Espinosa (2016): “AI Pathfinding in Video Games: JPS+ with Recursive Goal Bounding”. MS Thesis;
• Sean Campbell (2015) “Author Attribution of Thomas Paine Work Using Stylistic Features and Machine Learning Algorithms”, 29th Annual National Conference on Undergraduate Research (NCUR 2015), Eastern Washington University, Cheney, WA
• Orlando Barreiro, Joshua Espinosa, Brandon McNamara and Damir Hodzic (2015) “AnemiaNova”, 29th Annual National Conference on Undergraduate Research (NCUR 2015), Eastern Washington University, Cheney, WA
• Sean Campbell (2014): “Support Vector Machines and Artificial Neural Networks for Author Attribution of Thomas Paine Work” (Advisors: Dr. Petrovic, Computer Science and Gary Berton, Institute for Thomas Paine Studies). Presented at the 3rd Annual Westchester Undergraduate Research Conference (2014), Dobbs Ferry, NY and at the Fifth Annual Iona Scholars Day (2014).
• Jay Velasco (2014): “Enhancing Bagging and Boosting Machine Learning Methods with a Domain Specific Data”, MS Thesis.
• Stephanie Hickey (2013) Naïve Bayes Classification of Public Health Data With Greedy Feature Selection, 24th at Annual Meeting of the International Information Management Association (IIMA), Iona University, New Rochelle, NY.
• Stephanie Hickey (2013): Naïve Bayes Classification of Public Health Data, MS Thesis
• Sean Campbell, Geoffrey Cawley (2013): “Determining the Concentration of Caffeine in CH2Cl2 Using Near-Infrared Spectroscopy” (Advisors: Dr. Sunghee Lee, Chemistry and Dr. Petrovic, Computer Science), Iona Undergraduate Research Day.
• Jay Velasco (2013): “Using Data Mining to Examine Factors in Misheard Song Lyrics”, (Advisors: Dr. Petrovic, Computer Science and Dr. Behrman, Speech Pathology Department), Iona Undergraduate Research Day.
• Rachel Fraioli (2013): “Applying Data Mining Techniques to Discover Common Characteristics Shared by Individuals with Periods of Sadness, Discouragement, or Disinterest”, MS Thesis
• Kevin Towler, Alexander Soderberg (2012) “Using Machine Learning Techniques to Classify Plastics by Near Infrared Spectroscopy” (Advisors: Dr. Lee, Chemistry and Dr. Petrovic, Computer Science), Iona Undergraduate Research Day.