Margareta Ackerman. Assistant Professor. Research Interests. Education. Academic Positions. Grants and Fellowships

Transcription

1 Margareta Ackerman Assistant Professor Computer Science Department Florida State University (408) ackerman Research Interests I specialize in artificial intelligence with an emphasis on machine learning, from formal foundations to emerging applications in computational media and big data. Other interests include game theory, information retrieval, cognitive science, automata theory, bioinformatics, and computational creativity. Education Ph.D. in Computer Science, University of Waterloo, ON, Canada. Advisor: Shai Ben-David M.Math in Computer Science, University of Waterloo, ON, Canada. Winner of the outstanding graduate student award B.Math in Computer Science and Combinatorics and Optimization, University of Waterloo, ON, Canada. Cooperative program. Graduate with distinction present Academic Positions Assistant Professor, Florida State University, Tallahassee, Florida Postdoctoral Fellow, University of California, San Diego, La Jolla, CA Postdoctoral Fellow, Caltech, Pasadena, CA. Grants and Fellowships Co-PI, with Marie Roch and Simone Baumann-Pickering. Unsupervised Learning (Clustering) of Odontocete Echolocation Clicks. Office of Naval Research, $400, PI. First Year Assistant Professor Award. Foundations of Incremental Clustering. Florida State University $20, Postdoctoral Fellowship. Natural Sciences and Engineering Research Council of Canada (NSERC), $80, Alexander Bell Canadian Graduate Scholarship. Natural Sciences and Engineering Research Council of Canada (NSERC), $140, President s Graduate Scholarship. University of Waterloo, $50, David R. Cheriton Scholarship. University of Waterloo, $20, Ontario graduate scholarship. Ontario Ministry of Training Colleges and Universities, $51,000. 1/6

2 JMLR 15 NIPS 14 IJBRA 14 AAMAS 14 AISTATS 13 ACM RECSYS 13 AAAI 12 ICCABS 12 COGSCI 12 IJCAI 11 CSP 2011 NIPS 10 COLT 10 CSTL 10 Publications M. Ackerman and Shai Ben-David. A Characterization of Linkage-Based Hierarchical Clustering. Accepted subject to minor revisions to the Journal of Machine Learning Research (JMLR), M. Ackerman and Sanjoy Dasgupta. Incremental Clustering: The Case for Extra Clusters. Neural Information Processing Systems Conference (NIPS), M. Ackerman, Dan Brown, and David Loker. Effects of Rooting via Outgroups on Ingroup Topology in Phylogeny. International Journal of Bioinformatics Research and Application (IJBRA), M. Ackerman and Simina Branzei. Authorship Order: Alphabetical or Contribution? Autonomous Agents and Multiagent Systems (AAMAS), M. Ackerman, Shai Ben-David, David Loker and Sivan Sabato. Clustering Oligarchies. Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS), Hossein Vahabi, M. Ackerman, David Loker, Ricardo Baeza-Yates and Alejandro Lopez-Ortiz. Orthogonal Query Recommendation. ACM Conference on Recommender Systems (ACM RECSYS), M. Ackerman, Shai Ben-David, Simina Branzei, and David Loker. Weighted Clustering. Association for the Advancement of Artificial Intelligence Conference (AAAI), M. Ackerman, Dan Brown, and David Loker.Effects of Rooting via Outgroups on Ingroup Topology in Phylogeny. IEEE International Conference on Computational Advances in Bio and Medical Sciences (ICCABS), Joshua Lewis, M. Ackerman, and Virginia De Sa. Human Cluster Evaluation and Formal Quality Measures. Proc. 34th Annual Conference of the Cognitive Science Society, M. Ackerman and Shai Ben-David. Discerning Linkage-Based Algorithms Among Hierarchical Clustering Methods. International Joint Conference on Artificial Intelligence (IJCAI oral), Daniel Maoz and M. Ackerman. Chavruta: A Novel Teaching Methodology Based on an Ancient Tradition. From Antiquity to the Post-Modern World: Contemporary Jewish Studies in Canada. Newcastle upon Tyne: Cambridge Scholars Publishing, , M. Ackerman, Shai Ben-David, and David Loker. Towards Property-Based Classification of Clustering Paradigms. Neural Information Processing Systems (NIPS), M. Ackerman, Shai Ben-David, and David Loker. Characterization of Linkage-Based Clustering. Conference on Learning Theory (COLT), Daniel Maoz and M. Ackerman, Chavruta and Transformative Learning: A Comparative Analysis, in Opportunities and New Directions: Canadian Scholarship of Teaching and Learning (Edited by N. Simmons. Waterloo: CTE, 2010) pp /6

3 COCOON 09 AISTATS 09 M. Ackerman and Erkki Makinen.Three New Algorithms for Regular Language Enumeration. Computing and Combinatorics: 15th Annual International Conference (COCOON), Lecture Notes in Computer Science 5609, Springer-Verlag, Berlin Heidelberg, pp , M. Ackerman and Shai Ben-David. Clusterability: A Theoretical Study. Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS oral), JMLR: &CP 5, pp. 1-8, TCS 09 M. Ackerman and Jeffrey Shallit. Efficient Enumeration of Words in Regular Languages. Theoretical Computer Science, Volume 410, Issue 37, pp , NIPS 08 CIAA 07 M. Ackerman and Shai Ben-David. Measures of Clustering Quality: A Working Set of Axioms for Clustering. Full oral presentation at the Neural Information Processing Systems conference (NIPS), (Acceptance rate: 2.7%). M. Ackerman and Jeffrey Shallit. Efficient enumeration of regular languages. Conference on Implementation and Application of Automata (CIAA), Lecture Notes in Computer Science, 4783, Springer-Verlag, Berlin Heidelberg, pp , Refereed Workshops GHC 1 M. Ackerman. Towards Theoretical Foundations of Clustering. Grace Hopper Conference (GHC), NIPS 09 M. Ackerman, Shai Ben-David, and David Loker. Characterization of Linkage-Based Clustering. Neural Information Processing Systems workshop, Pre-prints and Working Papers 1. Generative Songwriting, with Andreas Adolfsson and Sam Kiswani Interactive Projections for Dance Performance, with Taylor Brockhoeft, Tim Glenn, Jennifer Petuch, and Gary Tyson An Effective and Efficient Approach for Clusterability Evaluation, with Andreas Adolfsson and Naomi Brownstein Unsupervised Learning of Acoustic Encounters Using KL divergence, with Simone Baumann-Pickering, Scott Lindeneau, Marie Roch, and Yun Trinh Actionable Clustering, with Amit Dhurandhar, Xiang Wang, and Suhib Kiswani When is Clustering Perturbation Robust? with Jarrod Moore, Authorship Order: Alphabetical or Contribution? with Simina Branzei. Journal of Autonomous Agents and Multi-Agent Systems (JAAMAS), Selecting Clustering Algorithms Based on Their Weight Sensitivity, with Shai Ben- David, Simina Branzei, and David Loker. Journal of Machine Learning Research (JMLR), /6

4 IFCS 15 Invited Talks Progress and Open Problems in Clustering. Conference of the International Federation of Classification Societies (IFCS). Bologna, Italy, Purdue 14 Theoretical Foundations of Clustering. Purdue University. West Lafayette, IN, CMU 13 Characterization of Linkage-Based Clustering. Carnegie Mellon University. Pittsburgh, PA eharmony 13 Formal Foundations of Clustering. eharmony. Santa Monica, CA, ID Analytics 13 ITA 13 Formal Foundations of Clustering. ID Analytics. San Diego, CA, Towards Theoretical Foundations of Clustering. Information Theory and Applications Workshop. La Jolla, CA, UCSD 12 Weighted Clustering. University of California, San Diego. La Jolla, CA, Caltech 12 Towards Theoretical Foundations of Clustering. Caltech. Pasadena, CA, Columbia 12 Berkeley 11 UCSD 10 Towards Theoretical Foundations of Clustering. Columbia University. New York, NY, On Theoretical Foundations of Clustering. University of California, Berkeley. Berkeley, CA, Characterization of Linkage-Based Algorithms. University of California, San Diego. La Jolla, CA, Teaching Experience 2016 Computational Creativity (CIS 5930), Florida State University Algorithm Design and Analysis (COP 4531), Florida State University Clustering: Bridging Theory and Practice (CIS 5930), Florida State University Algorithm Design and Analysis (COP 4531), Florida State University Theory of Computation (CS 360), University of Waterloo. Teaching Accomplishments 2015 Student projects in graduate clustering course led to 3 publishable papers Student evaluations for clustering course: Median of 5 (highest possible) in 12 of 13 categories, including overall instructor rating Received the best student evaluations in the history of the course after teaching Algorithm Design and Analysis at Florida State University Recognized among the top instructors at the School of Computer Science at the University of Waterloo after teaching a senior course on the Theory of Computation. 4/6

5 Program Committees, Reviewing, and Workshop Organization Neural Information Processing Systems (NIPS), 2010, 2012, 2013, 2014, International Conference on Machine Learning (ICML), , ACM SIGKDD Conference on Knowledge Discovery and Data Mining, International Conference on Data Mining (ICDM), 2014, Journal of Machine Learning Research. Journal of Pattern Recognition. Springer Machine Learning Journal. Journal of Classification. Journal of Universal Computer Science. IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE Transactions on Information Theory Transactions on Knowledge and Data Engineering. Co-organised a NIPS workshop on principled approaches to clustering, Departmental Services and Student Supervision Committees Faculty Evaluation Committee, PhD Portfolio and Qualifications Committee, Advisor to CS Expo Committee, CS Expo Planning Committee, PhD and Masters Committees Justin Marshall. Game Based Visual-To-Auditory Sensory Substitution Training. PhD committee. PhD in Computer Science. Defended on Nov 7, Shiva Krishna. PYQUERY: A Python Package and Module Search Engine. Masters of Computer Science. Completed on Nov 13, Esra Akbas. Attributed graph clustering. PhD in Computer Science. Chris Mills. Finding a Needle in the Code Stack: Large-Scale Code Search and Query Reformulation. PhD in Computer Science. Jennifer Petuch. The Arrows of Time: Time manipulation resulting from the symbiotic relationship of movement and interactive technology. Masters of Dance. Current Students Supervised Andreas Adolfsson. Practical Approach for Clusterability Evaluation. Sam Kiswani. Generative Music Composition with Lyrics. Jarrod Moore. Perturbation Robust Clustering. Artistic Training and Achievements Vocal technique, with opera singer Kaitlin Puscas. Waterloo, ON Contemporary singing, with singer and composer Griffith Frank. Los Angeles, CA. 5/6

6 Meisner Technique. Bay Area Acting Studio. San Jose, CA. Since 1992 Classical piano and improvisation (level 7) current Youtube channel of my performances and music productions has over 10,000 views Released a book: "Running from Giants: The Holocaust Through the Eyes of a Child," now in use at public schools in Florida. 6/6