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Draft:Susan L. Epstein

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Susan L. Epstein
Alma materRutgers University
Websitehttps://www.cs.hunter.cuny.edu/~epstein/

Susan L. Epstein is a computer science professor on the faculty at Hunter College and The Graduate Center of The City University of New York..[1] She is known for her contributions to artificial intelligence, machine learning, cognitive science, computational cognitive science, cognitive architecture, and knowledge representation and reasoning[2]. She has been the chair of the Cognitive Science Society, executive councilor and ethics chair for the Association for the Advancement of Artificial Intelligence (AAAI),[3] and an officer for SIGAI, the Association for Computing Machinery (ACM) special interest group on artificial intelligence. Epstein's interdisciplinary work has advanced the understanding of how knowledge and learning can be simulated and applied in computer systems.[4][5]

Early life and education

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Epstein was born in New York. She earned a BA in mathematics from Smith College, an MS in mathematics from The Courant Institute at New York University, and an MS and PhD in computer science from Rutgers University in 1983.[6] Her doctoral thesis topic was "Knowledge Representation in Mathematics: A Case Study In Graph Theory."[7]

Career and research

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Epstein joined the City University of New York in 1984 as a computer scientist. Her early work includes the Graph Theorist,[8] the first system that hypothesized mathematical concepts then proved theorems about those hypotheses.[9][10] She is a professor of computer science and director of CUNY's Problem Solving and Machine Learning Laboratory at Hunter College[11]. Her tenure at Hunter College and The Graduate Center of CUNY has been marked by her leadership in AI research and dedication to advancing the field through education and collaboration.[12]

Epstein is best known for developing FORR, a novel machine-learning cognitive architecture with the ability to problem solve and make expert decisions. Systems based on FORR have autonomously learned to play multiple games expertly,[13][14] solve challenging constraint satisfaction problems,[15] converse with an expert to achieve a mutual goal,[16] and control a robot as it pragmatically navigates complex, real-world environments.[17][18][19] She has also pioneered work in collaborative intelligence and mathematical discovery by computer.[20] Epstein defines collaborative intelligence as humans and intelligent machines working together to achieve human-specified goals.[21] She has challenged the AI community to develop systems that collaborate effectively with humans, adapt to their needs, and leverage human expertise[22][23]

Epstein's interdisciplinary collaboration has contributed to a broader understanding of knowledge and learning principles in mathematics, psychology, geography, linguistics,[24] microbiology,[25] architecture, and robotics. Epstein's recent significant contributions to the Combined Knowledge and Competency (CKC) Model for Computer Science Curricula[26] and robotic-assisted adaptive landscaping[27] reflect her ongoing commitment to leveraging AI for practical and innovative applications toward social good.[28]

References

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  1. ^ "Susan L. Epstein". scholar.google.com. Retrieved 2024-04-22.
  2. ^ "Susan Lynn Epstein". ACM Digital Library.
  3. ^ "Prof. Susan Epstein Elected to AAAI Executive Council". CUNY Hunter College Pressroom.
  4. ^ "Susan Epstein Coordinator for Education". CBMM, NSF STC.
  5. ^ "Susan L Epstein". Research Gate.
  6. ^ "Susan L. Epstein". CUNY Academic Commons.
  7. ^ Epstein, S L (1983). "Knowledge Representation in Mathematics a Case Study in Graph Theory". Rutgers University.
  8. ^ Epstein, S L (1992). "The Role of Memory and Concepts in Learning". Minds and Machines. 2 (3): 239–265. doi:10.1007/BF02454222.
  9. ^ Epstein, S L; Sridharan, N S (1991). "Knowledge Representation for Mathematical Discovery - Three Experiments in Graph Theory". Applied Intelligence. 1 (1): 7–33. doi:10.1007/BF00117743.
  10. ^ Epstein, S L (1988). "On the Discovery of Mathematical Concepts" (PDF). International Journal of Intelligent Systems. 3 (2): 167–178. doi:10.1002/int.4550030205.
  11. ^ "Directory: Susan Epstein". CUNY.
  12. ^ "SCIENCE FACULTY SPOTLIGHT: SUSAN L. EPSTEIN". CUNY Graduate Center. 14 December 2020.
  13. ^ Bradford, Alexander; Kain Day, J; Hutchinson, Laura; Kaperick, Bryan; Larson, C. E.; Mills, Matthew; Muncy, David; Van Cleemput, Nico (June 2020). "Automated Conjecturing II: Chomp and Reasoned Game Play". JAIR. 68: 447–461. doi:10.1613/jair.1.12188.
  14. ^ Reisinger, Joseph; Bahc ̧eci, Erkin; Karpov, Igor; Miikkulainen, Risto (2007). "Coevolving Strategies for General Game Playing" (PDF). 2007 IEEE Symposium on Computational Intelligence and Games. pp. 320–327. doi:10.1109/CIG.2007.368115. ISBN 978-1-4244-0709-5.
  15. ^ Epstein, S L; Freuder, E C; Wallace, M (2005). "Learning to Support Constraint Programmers" (PDF). Computational Intelligence. 21 (4): 337–371. doi:10.1111/j.1467-8640.2005.00277.x.
  16. ^ Epstein, S L; Passonneau, R J; Gordon, J; Ligorio, T (2012). "The Role of Knowledge and Certainty in Understanding for Dialogue" (PDF). Advances in Cognitive Systems. 1: 93–108.
  17. ^ Epstein, S L; Korpan, R (2021). "Hierarchical Freespace Planning for Navigation in Unfamiliar Worlds". Proceedings of ICAPS-2021. 31: 663–672. doi:10.1609/icaps.v31i1.16015.
  18. ^ Epstein, S L; Korpan, R (2019). "Planning and Explanations with a Learned Spatial Model". Proceedings of 14th International Conference on Spatial Information Theory (COSIT 2019): 22:1–22:20. doi:10.4230/LIPIcs.COSIT.2019.22.
  19. ^ Epstein, SL; Korpan, R (2018). "Online learning for crowd-sensitive planning" (PDF). Proceedings of AAMAS-2018.
  20. ^ Epstein, SL (1988). "Learning and Discovery: One System's Search for Mathematical Knowledge". Computational Intelligence. 4 (1): 42–53. doi:10.1111/j.1467-8640.1988.tb00089.x.
  21. ^ Epstein, SL (2015). "Wanted: Collaborative Intelligence". Artificial Intelligence. 221: 36–45. doi:10.1016/j.artint.2014.12.006.
  22. ^ Shawwa, Hani (9 June 2014). "Computer may be first to pass Turing Test, successfully impersonating a human". CBS.
  23. ^ Mullin, Rick (18 September 2023). "The tricky ethics of AI in the lab". Chemical & Engineering News.
  24. ^ Passonneau, R J; Epstein, S L; Ligorio, T; Gordon, J; Bhutada, P (2010). "Learning about Voice Search for Spoken Dialogue Systems". Proceedings of NACL-HLT-2010.
  25. ^ Coronado, JE; Mniemneh, S; Epstein, SL; Qiu, WG; Lipke, PN (2007). "Conserved Processes and Lineage-Specific Proteins in Fungal Cell Wall Evolution". Eukaryotic Cell. 6 (12): 2269–77. doi:10.1128/EC.00044-07. PMC 2168262. PMID 17951517.
  26. ^ Kumar, A; Anderson, MD; Becker, BA; Pias, M; Oudshoom, M; Jalote, P; Servin, C; Aly, SG; Blumenthal, RL; Epstein, SL (2023). "A Combined Knowledge and Competency (CKC) Model for Computer Science Curricula". ACM Inroads. 14 (2): 22–29. doi:10.1145/3605215.
  27. ^ Zhang, Z; Epstein, SL; Breen, C; Zhu, Z; Volkmann, C (2023). "Robots in the Garden: Artificial Intelligence and Adaptive Landscapes". Journal of Digital Landscape Architecture. arXiv:2305.13019. doi:10.14627/537740028.
  28. ^ "COMPUTER SCIENCE ALUMNUS COMES FULL CIRCLE AS A CUNY FACULTY MEMBER". CUNY Graduate Center. 7 March 2024.
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