• Ph.D. in Computer Science and Engineering (2012), University of Michigan, Ann Arbor, MI
• M.S. in Computer Science and Engineering (2008, GPA: 8.187/9), University of Michigan, Ann Arbor, MI
• B.S. in Computer Science (2006, GPA: 4.000/4), North Carolina State University, Raleigh, NC

• Visiting Research Associate (2012), Kerstin Dautenhahn, University of Hertfordshire, Hatfield, UK
• Research Fellow (2012), John E. Laird, University of Michigan, Ann Arbor, MI
• Graduate Student Research Assistant (2007-2012), John E. Laird, University of Michigan, Ann Arbor, MI

I am interested in developing software that exhibits human-level intelligence: real-time systems that persist for long periods of time while autonomously contending with, and continually improving performance on, a wide variety of complex problems. [bib]

2012

• A Multi-Domain Evaluation of Scaling in a General Episodic Memory
  Proc. of the 26th AAAI Conference on Artificial Intelligence (AAAI). Toronto, Canada.
  Nate Derbinsky and Justin Li and John E. Laird. [paper], [bib]
• Functional Interactions between Memory and Recognition Judgments
  Proc. of the 26th AAAI Conference on Artificial Intelligence (AAAI). Toronto, Canada.
  Justin Li and Nate Derbinsky and John E. Laird. [paper], [bib]
• Exploring Reinforcement Learning for Mobile Percussive Collaboration
  Proc. of the 12th International Conference on New Interfaces for Musical Expression (NIME). Ann Arbor, MI, USA.
  Nate Derbinsky and Georg Essl. [paper], [bib]
• Demonstrations of Multiple Architectural Capabilities
  The Soar Cognitive Architecture, pp. 287-306, MIT Press, Cambridge.
  John E. Laird and Nate Derbinsky and Nicholas A. Gorski and Samuel Wintermute and Joseph Xu. [publisher], [amazon], [bib]
• Episodic Memory
  The Soar Cognitive Architecture, pp. 225-246, MIT Press, Cambridge.
  John E. Laird and Andrew Nuxoll and Nate Derbinsky. [publisher], [amazon], [bib]
• Semantic Memory
  The Soar Cognitive Architecture, pp. 203-224, MIT Press, Cambridge.
  John E. Laird and Yongjia Wang and Nate Derbinsky. [publisher], [amazon], [bib]
• Competence-Preserving Retention of Learned Knowledge in Soar's Working and Procedural Memories
  Proc. of the 11th International Conference on Cognitive Modeling (ICCM), 205-210. Berlin, Germany.
  Nate Derbinsky and John E. Laird. [paper], [talk], [bib]
• Computationally Efficient Forgetting via Base-Level Activation Best Poster Award
  Proc. of the 11th International Conference on Cognitive Modeling (ICCM), 109-110. Berlin, Germany.
  Nate Derbinsky and John E. Laird. [paper], [poster], [bib]
• Algorithms for Scaling in a General Episodic Memory (Extended Abstract)
  Proc. of the 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS). Valencia, Spain.
  Nate Derbinsky and Justin Li and John E. Laird. [paper], [poster], [bib]

2011

• Effective and Efficient Management of Soar's Working Memory via Base-Level Activation
  Papers from the 2011 AAAI Fall Symposium Series: Advances in Cognitive Systems (ACS), 82-89. Arlington, VA, USA.
  Nate Derbinsky and John E. Laird. [paper], [talk], [bib]
• A Case Study in Integrating Probabilistic Decision Making and Learning in a Symbolic Cognitive Architecture: Soar Plays Dice
  Papers from the 2011 AAAI Fall Symposium Series: Advances in Cognitive Systems (ACS), 162-169. Arlington, VA, USA.
  John E. Laird and Nate Derbinsky and Miller Tinkerhess. [paper], [bib]
• A Functional Analysis of Historical Memory Retrieval Bias in the Word Sense Disambiguation Task
  Proc. of the 25th AAAI Conference on Artificial Intelligence (AAAI), 663-668. San Francisco, CA, USA.
  Nate Derbinsky and John E. Laird. [paper], [talk], [bib]
• Cognitive Architecture in Mobile Music Interactions
  Proc. of the 11th International Conference on New Interfaces for Musical Expression (NIME), 104-107. Oslo, Norway.
  Nate Derbinsky and Georg Essl. [paper], [poster], [bib]
• A Preliminary Functional Analysis of Memory in the Word Sense Disambiguation Task
  Proc. of the 2nd Symposium on Human Memory for Artificial Agents (AISB), 25-29. York, England.
  Nate Derbinsky and John E. Laird. [paper], [talk], [bib]
• Performance Evaluation of Declarative Memory Systems in Soar
  Proc. of the 20th Behavior Representation in Modeling and Simulation Conference (BRIMS), 33-40. Sundance, UT, USA.
  John E. Laird and Nate Derbinsky and Jonathan Voigt. [paper], [bib]

2010

• Towards Efficiently Supporting Large Symbolic Declarative Memories
  Proc. of the 10th International Conference on Cognitive Modeling (ICCM), 49-54. Philadelphia, PA, USA.
  Nate Derbinsky and John E. Laird and Bryan Smith. [paper], [talk], [bib]
• Extending Soar with Dissociated Symbolic Memories
  Proc. of the 1st Symposium on Human Memory for Artificial Agents (AISB), 31-37. Leicester, UK.
  Nate Derbinsky and John E. Laird. [paper], [talk], [bib]
• Exploring the Space of Computational Memory Models
  Proc. of the 1st Symposium on Human Memory for Artificial Agents (AISB), 38-41. Leicester, UK.
  Nate Derbinsky and Nicholas A. Gorski. [paper], [talk], [bib]

2009

• Efficiently Implementing Episodic Memory
  Proc. of the 8th International Conference on Case-Based Reasoning (ICCBR), 403-417. Seattle, WA, USA.
  Nate Derbinsky and John E. Laird. [paper], [talk], [bib]
• A Year of Episodic Memory Invited Paper
  Proc. of the Workshop on Grand Challenges for Reasoning from Experiences (IJCAI), 7-10. Pasadena, CA, USA.
  John E. Laird and Nate Derbinsky. [paper], [talk], [bib]

• Best Poster Award, 11th International Conference on Cognitive Modeling (2012)
• Rackham Predoctoral Fellowship, Rackham School of Graduate Studies, University of Michigan (2011)
• Distinguished Leadership Award, College of Engineering, University of Michigan (2010)
• Senior Award for Leadership, College of Engineering, North Carolina State University (2006)
• Park Scholarship, North Carolina State University (2002)
• Thomas J. Watson Scholarship, IBM Corp. (2002)

I am passionate about computer science and I strive to develop an inclusive learning environment where I can share my excitement for challenging ideas and problems, while being respectful of and responsive to student needs.

2011

• Program Instructor, CSE Department, LEAD Computer Science Institute, University of Michigan
• Supplemental Instruction Leader, Engineering Learning Center, Engin. 101 (Intro. to Computers and Programming)

2010

• Lead Instructor, CSE Department, LEAD Engineering, University of Michigan
• Guest Lecturer, "Basics of Web Development," EECS 497 (EECS Major Design Projects)

2008

• Graduate Student Instructor, EECS 376 (Foundations of Computer Science)
• Graduate Student Instructor, EECS 280 (Programming and Introductory Data Structures)
• Student, ENGR 580 (Teaching Engineering)
• Participant, University of Michigan College of Engineering GSI Teacher Training Program

2005

• Teaching Assistant, CSC 540 (Database Management Concepts and Systems)
• Teaching Assistant, BUS 495 (Leadership Seminar)

I believe that the best account of what you have is what you give.

2012

• Co-Chair, Special Interest Group on Faculty (SIG-Faculty), University of Michigan

2011

• Program Committee, Twenty-Second International Joint Conference on Artificial Intelligence (IJCAI)
• Program Committee, 2nd Symposium on Human Memory for Artificial Agents, AISB
• President, Computer Science and Engineering Graduate student organization (CSEG), University of Michigan

2010

• Project Leader, CSE Department, LEAD Engineering, University of Michigan
• Outreach Chair, Computer Science and Engineering Graduate student organization (CSEG), University of Michigan

2009

• President, Computer Science and Engineering Graduate student organization (CSEG), University of Michigan
• Volunteer Teacher & Consultant, The Technology Tent (Powering Potential) @ Banjika, Tanzania
• Graduate Student Representative, University of Michigan CS Curriculum Committee

2008

• Graduate Student Representative, University of Michigan CS Curriculum Committee

2006

• Chair, Legacy Committee, Park Scholarships, North Carolina State University

2005

• Assistant to Electronic Proceedings Chair, ACM SIGMOD/PODS

BitX Solutions, Inc., President
Cary, NC (1998-2009)

• Secured and maintained contracts with corporate, university, government, and non-profit clients
• Oversaw hiring and subcontracting of software development teams
• Managed system architecture, database schema, coding, testing, and product development
• Developed and deployed commercial desktop- and web-applications

• Soar: a general cognitive architecture for developing systems that exhibit intelligent behavior.
• JSoar: a Pure Java implementation of the Soar cognitive architecture
• urMus: audio and media interactions and interfaces on mobile phones

2011

• Effective Scaling of Long-term Memory for Reactive Rule-based Agents Invited Talk
  The 2011 International Conference on Reasoning Technologies (Rules Fest). San Francisco, CA.
• SoarQnA: Standardized Access to External Knowledge
  The 31st Soar Workshop. Ann Arbor, MI.
• The State of Soar: v9.3.1
  The 31st Soar Workshop. Ann Arbor, MI.
• Soaring to New Platforms: 2011 Update
  The 31st Soar Workshop. Ann Arbor, MI.
• Efficient Activation-based Working Memory Forgetting
  The 31st Soar Workshop. Ann Arbor, MI.
• Effective and Efficient Historical Memory Retrieval Bias in Soar's Semantic Memory
  The 31st Soar Workshop. Ann Arbor, MI.
• Episodic & Semantic: Soar's Long-Term Declarative Memory Systems
  The 31st Soar Workshop. Ann Arbor, MI.
• The Soar Cognitive Architecture: Towards Human-level Intelligence
  Michigan Student AI Lab, University of Michigan. Ann Arbor, MI.
• Databases & Your Research
  Soar Group, University of Michigan. Ann Arbor, MI.

2010

• Soaring to New Platforms
  The 30th Soar Workshop. Ann Arbor, MI.
• Soar2Soar
  The 30th Soar Workshop. Ann Arbor, MI.
• Large Semantic Stores in Soar
  The 30th Soar Workshop. Ann Arbor, MI.
• Long-Term Symbolic Memories for Long-Living Learning Agents
  The 30th Soar Workshop. Ann Arbor, MI.
• Speedy: A Lightweight Platform for Logging, Analyzing, and Visualizing Experimental Data
  Database Research Group, University of Michigan. Ann Arbor, MI.

2009

• What Does Cyc Know?
  Soar Technology, Inc. Ann Arbor, MI.
• iSoar: Soar on the iPhone OS
  The 29th Soar Workshop. Ann Arbor, MI.
• Soar-SMem: A Public Pilot
  The 29th Soar Workshop. Ann Arbor, MI.
• Efficiently Implementing Episodic Memory
  The 29th Soar Workshop. Ann Arbor, MI.
• Only Process Changes: Efficiently Implementing Episodic Memory
  Soar Group, University of Michigan. Ann Arbor, MI.

2008

• Episodic Memory: A DBMS Perspective
  Database Research Group, University of Michigan. Ann Arbor, MI.
• Soar-RL: A Year of "Learning"
  The 28th Soar Workshop. Ann Arbor, MI.
• Episodic Memory and Databases: A Year to "Remember"
  The 28th Soar Workshop. Ann Arbor, MI.
• SoarSim: An Experimentation Framework
  The 28th Soar Workshop. Ann Arbor, MI.

2011

• SML Tutorial
  The 31st Soar Workshop. Ann Arbor, MI.
• Soar-EpMem Tutorial
  The 31st Soar Workshop. Ann Arbor, MI.
• Soar-SMem Tutorial
  The 31st Soar Workshop. Ann Arbor, MI.
• Soar-RL Tutorial
  The 31st Soar Workshop. Ann Arbor, MI.

2010

• Soar-EpMem Tutorial
  The 30th Soar Workshop. Ann Arbor, MI.
• Soar-SMem Tutorial
  The 30th Soar Workshop. Ann Arbor, MI.
• Soar-RL Tutorial
  The 30th Soar Workshop. Ann Arbor, MI.

2009

• Soar-EpMem Tutorial
  The 29th Soar Workshop. Ann Arbor, MI.
• Soar-RL Tutorial
  The 29th Soar Workshop. Ann Arbor, MI.

2012

• Effective and Efficient Memory for Generally Intelligent Agents (talk)
  PhD Dissertation. Chair: John E. Laird

2010

• Long-Term Declarative Memory for Generally Intelligent Agents (talk)
  Thesis Proposal. With: John E. Laird

2008

• Efficiently Implementing Episodic Memory in Soar (talk)
  Preliminary Examination Report. With: John E. Laird

2007

• Investigating the Soar-RL Implementation of the MAXQ Method for Hierarchical Reinforcement Learning
  Course Project (EECS 592). With: John E. Laird

2006

• A Novel Approach for Bulk Motif Matching Using Suffix Trees
  Course Project (EECS 584). With: Willis Lang, Jignesh Patel
• Architecture Pipeline Translator from HMDES to GCC DFA
  Independent Research. With: Tom Conte, Chad Rosier, Balaji Iyer

2005

• Algorithm Analysis and Implementation of Index Selection in OLAP
  Independent Research. With: Rada Chirkova, Andrew Frick
• The Electronic Medical Record: Applications of Cryptographic Access to Published Data
  Independent Research. With: Ting Yu

2004

• Standardized Online Data Reporting: Minimizing Redundancies of Data Reporting in an Online Environment While Maintaining a High Level Of Power And Flexibility
  Independent Research. With: Jaewoo Kang

2003

• Developing an Intelligent Feedback System To Aid Understanding of Formal Logic: The Axiom Identification Routine
  Independent Research. With: Tiffany Barnes, Donald Bitzer

• Teaching Statement

Programming and Introductory Data Structures, Winter 2008

• Discussion Slides
• Course Evaluations: Section 11 (individual, summary)
• Course Evaluations: Section 13 (individual, summary)

• Basics of Web Development, Capstone Project Course (Michigan)
• MSaiL, Undergraduate AI Lab (Michigan)
  
  

• LEAD Engineering (Michigan)
  
  
  
  
  
  
• SITE Summer Program (NC State)
  
  

• ashima: a lightweight platform for logging, analyzing, and visualizing experimental data (my instance)
• vitagen: a lightweight web-based system for producing web, mobile, and print views to a CV (my instance)

• Service to my community
• Engaging in teaching and learning experiences
• Physical fitness and personal health
• Business entrepreneurship
• Exploring creativity and technology

• Powering Potential: using technology to enhance education and stimulate imaginations of students in Tanzania while respecting and incorporating values of the local culture
• United2Heal: student-run, humanitarian aid organization at the University of Michigan working to ship surplus medical supplies from local hospitals to countries in need around the world
• TED: riveting talks by remarkable people, free to the world
• Trekking For Kids: organizes purpose-driven treks for socially-conscious hikers in some of the world’s most remote and iconic locations