• Contact Info

Reckwerdt, Eric Asher

Teaching Associate Professor

Positions

Research Areas research areas

Research

research overview

  • Exploring different implementations of computation as networks and understanding their limits and similarities.

keywords

  • Tensor Networks, string diagrams, category theory

Teaching

courses taught

  • CSCI 3104 - Algorithms
    Primary Instructor - Fall 2018 / Spring 2019
    Covers the fundamentals of algorithms and various algorithmic strategies, including time and space complexity, sorting algorithms, recurrence relations, divide and conquer algorithms, greedy algorithms, dynamic programming, linear programming, graph algorithms, problems in P and NP, and approximation algorithms. Same as CSPB 3104.
  • CSPB 3022 - Introduction to Data Science with Probability and Statistics
    Primary Instructor - Summer 2021
    Introduces students to the tools methods and theory behind extracting insights from data. Covers algorithms of cleaning and munging data, probability theory and common distributions, statistical simulation, drawing inferences from data, and basic statistical modeling. Same as CSCI 3022.
  • CSPB 3104 - Algorithms
    Primary Instructor - Summer 2019 / Fall 2019 / Spring 2020 / Summer 2020 / Fall 2020 / Spring 2021 / Summer 2021 / Fall 2021 / Spring 2022 / Summer 2022 / Fall 2022 / Spring 2023 / Summer 2023 / Fall 2023 / Summer 2024 / Fall 2024
    Covers the fundamentals of algorithms and various algorithmic strategies, including time and space complexity, sorting algorithms, recurrence relations, divide and conquer algorithms, greedy algorithms, dynamic programming, linear programming, graph algorithms, problems in P and NP, and approximation algorithms. Same as CSCI 3104.
  • CSPB 3155 - Principles of Programming Languages
    Primary Instructor - Summer 2022 / Fall 2022 / Spring 2023 / Summer 2023 / Fall 2023 / Spring 2024 / Summer 2024 / Fall 2024
    Studies principles governing the design and analysis of programming languages and their underlying execution models. Explores values, scoping, recursion, higher-order functions, type systems, control structures, and objects. Introduces formal semantics as a framework for understanding programming features. Introduces advanced programming concepts such as functional programming, higher-order functions, immutable values and structures, inductive types, functors, continuation-passing; and object-oriented programming using inheritance, generics and covariance/contravariance in a functional programming language such as Scala. Same as CSCI 3155.
  • CSPB 3702 - Cognitive Science
    Primary Instructor - Fall 2020 / Spring 2021 / Fall 2021 / Spring 2022 / Summer 2022 / Fall 2022 / Summer 2023 / Fall 2023 / Fall 2024
    Introduces cognitive science, drawing from psychology, philosophy, artificial intelligence, neuroscience, and linguistics. Studies the linguistic relativity hypothesis, consciousness, categorization, linguistic rules, the mind-body problem, nature versus nurture, conceptual structure and metaphor, logic/problem solving and judgment. Emphasizes the nature, implications and limitations of the computational model of mind. Recommended prerequisites: LING 2000 or PHIL 2440 or PSYC 2145. Same as LING 3005 and PHIL 3310 and PSYC 3005 and SLHS 3003 and CSCI 3702.

Background