The Use of Explanations for Similarity-based Learning. - Andrea Pohoreckyj Danyluk (IJCAI, 1987)

Finding New Rules for Incomplete Theories: Explicit Biases for Induction with Contextual Information. - Andrea Pohoreckyj Danyluk (ML, 1989)

Small Disjuncts in Action: Learning to Diagnose Errors in the Local Loop of the Telephone Network. - Andrea Pohoreckyj Danyluk; Foster J. Provost (ICML, 1993)

Tuning Numeric Parameters to Troubleshoot a Telephone-Network Loop. - Christopher J. Merz; Michael J. Pazzani; Andrea Pohoreckyj Danyluk (IEEE Expert, 1996)

Problem Definition, Data Cleaning, and Evaluation: A Classifier Learning Case Study. - Foster J. Provost; Andrea Pohoreckyj Danyluk (Informatica (Slovenia), 1999)

Feature Selection vs Theory Reformulation: A Study of Genetic Refinement of Knowledge-based Neural Networks. - Brendan Davis Burns; Andrea Pohoreckyj Danyluk (Mach. Learn., 2000)

Event-driven programming is simple enough for CS1. - Kim B. Bruce; Andrea Pohoreckyj Danyluk; Thomas P. Murtagh (ITiCSE, 2001)

A library to support a graphics-based object-first approach to CS 1. - Kim B. Bruce; Andrea Pohoreckyj Danyluk; Thomas P. Murtagh (SIGCSE, 2001)

Events and objects first: an innovative approach to teaching JAVA in CS 1. - Kim B. Bruce; Andrea Danyluk; Thomas P. Murtagh (J. Comput. Sci. Coll., 2001)

Event-driven programming facilitates learning standard programming concepts. - Kim B. Bruce; Andrea Pohoreckyj Danyluk (OOPSLA Companion, 2004)

Java: an eventful approach. - Kim Bruce 001; Andrea Danyluk; Thomas P. Murtagh (J. Comput. Sci. Coll., 2004)

Why structural recursion should be taught before arrays in CS 1. - Kim B. Bruce; Andrea Pohoreckyj Danyluk; Thomas P. Murtagh (SIGCSE, 2005)

Artificial Intelligence for Non-Majors at Multiple Levels. - Andrea Pohoreckyj Danyluk (AAAI Spring Symposium: Using AI to Motivate Greater Participation in Computer Science, 2008)

Deep Transfer as Structure Learning in Markov Logic Networks. - David Andrew Moore; Andrea Pohoreckyj Danyluk (StarAI@AAAI, 2010)

Introducing concurrency in CS 1. - Kim B. Bruce; Andrea Pohoreckyj Danyluk; Thomas P. Murtagh (SIGCSE, 2010)

Case Studies of Liberal Arts Computer Science Programs. - Douglas Baldwin; Alyce Brady; Andrea Pohoreckyj Danyluk; Joel C. Adams; A. Lawrence (ACM Trans. Comput. Educ., 2010)

Feature Selection via Probabilistic Outputs. - Andrea Pohoreckyj Danyluk; Nicholas Arnosti (ICML, 2012)

Making the most of undergraduate research (abstract only). - Andrea Danyluk; Nancy M. Amato; Ran Libeskind-Hadas; Lori L. Pollock; Susan H. Rodger (SIGCSE, 2013)

ACM/IEEE computer science 2013 exemplar-fest. - Andrea Danyluk; Steve Roach; Elizabeth K. Hawthorne; Henry MacKay Walker; Ruth E. Anderson; Christa M. Chewar (SIGCSE, 2013)

Experiences mapping and revising curricula with CS2013. - David Reed 001; Andrea Danyluk; Elizabeth K. Hawthorne; Mehran Sahami; Henry M. Walker (SIGCSE, 2014)

Small or Liberal Arts Colleges Adapting to CS2013: Making It Work (Abstract Only). - Andrea Danyluk; Michael J. Jipping; Rhys Price Jones; David Reed 001; Brad Richards; Richard Wicentowski (SIGCSE, 2015)

SIGCSE 2016 new educators workshop. - David Reed 001; Andrea Danyluk (ACM SIGCSE Bull., 2015)

Predicting Expressive Bow Controls for Violin and Viola. - Lauren Jane Yu; Andrea Pohoreckyj Danyluk (EvoMUSART, 2017)

Can we really do it?: Conducting Significant Computer Science Research in Primarily Undergraduate Institutions (PUIs) (Abstract Only). - Farzana Rahman; Suzanne J. Matthews; Kelly A. Shaw 001; Andrea Danyluk (SIGCSE, 2017)

SIGCSE 2018 new educator workshop. - Andrea Danyluk; Zachary Dodds (ACM SIGCSE Bull., 2017)

Artificial Intelligence Competencies for Data Science Undergraduate Curricula. - Andrea Danyluk; Scott Buck (AAAI, 2019)

Building Bridges for Data Science Education. - Mine Çetinkaya-Rundel; Andrea Danyluk; Jeff Forbes 001; Michael Posner (SIGCSE, 2019)

ACM Task Force on Data Science Education: Draft Report and Opportunity for Feedback. - Andrea Danyluk; Paul M. Leidig; Lillian N. Cassel; Christian Servin (SIGCSE, 2019)

An MS in CS for non-CS Majors: Moving to Increase Diversity of Thought and Demographics in CS. - Carla E. Brodley; Megan Barry; Aidan Connell; Catherine Gill; Ian Gorton; Benjamin Hescott; Bryan Lackaye; Cynthia LuBien; Leena Razzaq; Amit Shesh; Tiffani L. Williams; Andrea Pohoreckyj Danyluk (SIGCSE, 2020)

An Update on the ACM Data Science Taskforce. - Andrea Danyluk; Paul M. Leidig; Lillian N. Cassel (SIGCSE, 2020)

ACM data science task force calls for curricula feedback and example courses. - Andrea Danyluk; Paul M. Leidig (ACM SIGCSE Bull., 2020)

Computing Competencies for Undergraduate Data Science Programs: an ACM Task Force Final Report. - Andrea Danyluk; Paul M. Leidig; Andrew D. McGettrick; Lillian N. Cassel; Maureen Doyle; Christian Servin; Karl Schmitt; Andreas Stefik (SIGCSE, 2021)