Christopher Anderson

About

Christopher Anderson is a lecturer in Film and Television at Boston University College of Communication. He is a musician, audio engineer, and sound designer with extensive experience working on acclaimed series such as Frontline, American Experience, and NOVA, as well as feature films including Detroit and American Hustle. His work also encompasses supervising sound editing on various features and shorts, and he has contributed to the Front Row Boston music series and several independent documentaries and short films. Anderson is on the staff at the Outpost at WGBH and runs his own business, Harpswell Sound Company, which specializes in independent feature audio consulting and sound supervision. His expertise emphasizes the importance of planning and knowledge in achieving good sound, and he enjoys exploring innovative ways to create unique sounds.

Research topics

• Computer science
• Political science
• Artificial intelligence
• Environmental science
• Machine learning

Selected publications

• Self-training superconducting neuromorphic circuits using reinforcement learning rules

  arXiv (Cornell University) · 2024-04-29

  preprintOpen accessSenior author

  Reinforcement learning algorithms are used in a wide range of applications, from gaming and robotics to autonomous vehicles. In this paper we describe a set of reinforcement learning-based local weight update rules and their implementation in superconducting hardware. Using SPICE circuit simulations, we implement a small-scale neural network with a learning time of order one nanosecond. This network can be trained to learn new functions simply by changing the target output for a given set of inp…

  PublisherOA PDFDOI

• SRViT: Vision Transformers for Estimating Radar Reflectivity from Satellite Observations at Scale

  arXiv (Cornell University) · 2024-06-20

  preprintOpen accessSenior author

  We introduce a transformer-based neural network to generate high-resolution (3km) synthetic radar reflectivity fields at scale from geostationary satellite imagery. This work aims to enhance short-term convective-scale forecasts of high-impact weather events and aid in data assimilation for numerical weather prediction over the United States. Compared to convolutional approaches, which have limited receptive fields, our results show improved sharpness and higher accuracy across various composite…

  PublisherOA PDFDOI

• A SYMPOSIUM ON THE MORAL COMMONWEALTH

  Anthem Press eBooks · 2021-08-17

  book-chapter1st authorCorresponding
  PublisherDOI

Recent grants

• HCC: Medium: Removing Barriers to the Practical Use of Non-Invasive Brain-Computer Interfaces

  NSF · $1.2M · 2011–2018

• Geometric Pattern Analysis and Mental Task Design for a Brain-Computer Interface

  NSF · $834k · 2002–2012

• Alternate Modes of Human-Computer Interaction: EEG Recognition with Neural Networks

  NSF · $285k · 1992–1996

Frequent coauthors

• Shlomo Avineri

  3535 shared

• Frederick Crosson

  3485 shared

• Gerald Garvey

  Bowdoin College

  3455 shared

• Philip Gleason

  3396 shared

• Ernest L. Fortin

  3391 shared

• Arend Lijphart

  3346 shared

• Glenn Tinder

  3334 shared

• Donald P. Kommers

  3227 shared

Education

• Ph.D., Computer Science

  University of Massachusetts Amherst

  1986

• M.S., Computer Science

  University of Massachusetts Amherst

  1982

• B.S., Computer Science

  University of Nebraska-Lincoln

  1978

Similar researchers at Boston University

• Raymond Carneyh-44