Alric Althoff

About Me

My face

I am a Ph.D. candidate working under professor Ryan Kastner at the University of California, San Diego's Computer Science and Engineering department. I graduated from UCSD in 2013 with majors in both cognitive science and mathematics, specializing in the computational aspects of those fields.

My primary areas of interest are statistics, signal processing, and machine learning, focusing on hardware security, experimental design in environments where individual experiments are costly, and high-throughput data analysis.

I am grateful to receive support from both UCSD and the National Science Foundation in the form of San Diego and GRFP fellowships.

I have worked as both a software developer and audio engineer professionally.

Selected Coursework

  • Algorithms & data structures
  • Computer vision
  • Parallel computing
  • Optimization & numerical analysis
  • Cognitive & systems neuroscience
  • Discrete mathematics & graph theory
  • Abstract algebra (groups, rings, fields)
  • Computational neurobiology
  • Machine learning & mathematical statistics
  • Cryptography
  • RTL design & high level synthesis

Conference Papers

Dajung Lee, Alric Althoff, Dustin Richmond, and Ryan Kastner, A Streaming Clustering Approach Using a Heterogeneous System for Big Data Analysis, International Conference on Computer Aided Design (ICCAD), Nov. 2017 (pdf)

Alric Althoff and Ryan Kastner, An Architecture for Learning Stream Distributions with Application to RNG Testing, Design Automation Conference (DAC), Jun. 2017 (pdf)

Wei Hu, Alric Althoff, Armaiti Ardeshiricham, and Ryan Kastner, Towards Property Driven Hardware Security, Microprocessor Test and Verification Conference (MTV), Dec. 2016 (pdf Invited Paper

Quentin Gautier, Alric Althoff, Pingfan Meng, and Ryan Kastner, Spector: An OpenCL FPGA Benchmark Suite, International Conference on Field-Programmable Technology (FPT), Dec. 2016 (pdf)

Pingfan Meng, Alric Althoff, Quentin Gautier, and Ryan Kastner, Adaptive Threshold Non-Pareto Elimination: Re-thinking Machine Learning for System Level Design Space Exploration on FPGAs, Design Automation and Test in Europe (DATE), Mar. 2016 (pdf)
Janarbek Matai, Dajung Lee, Alric Althoff, and Ryan Kastner, Composable, Parameterizable Templates for High Level Synthesis, Design Automation and Test in Europe (DATE), Mar. 2016 (pdf)

Ryan Kastner, Wei Hu, and Alric Althoff, Quantifying Hardware Security Using Joint Information Flow Analysis, Design Automation and Test in Europe (DATE), Mar. 2016 (pdf – Invited Paper

Baolei Mao, Wei Hu, Alric Althoff, Janarbek Matai, Jason Oberg, Dejun Mu, Timothy Sherwood, and Ryan Kastner, 
Quantifying Timing-Based Information Flow in Cryptographic Hardware, International Conference on Computer-Aided Design (ICCAD), Nov. 2015 (pdf)

Alric Althoff and Ryan Kastner, 
A Scalable FPGA Architecture for Nonnegative Least 
Squares Problems
, International Conference on Field Programmable Logic and Applications (FPL), Sep. 2015 (pdf)

Journal Papers

Baolei Mao, Wei Hu, Alric Althoff, Janarbek Matai, Yu Tai, Dejun Mu, Timothy Sherwood, and Ryan Kastner, Quantitative Analysis of Timing Channel Security in Cryptographic Hardware Design
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), Nov. 2017

Christopher Barngrover, 
Alric Althoff, Paul DeGuzman, and Ryan Kastner, A Brain–Computer Interface (BCI) for the Detection of Mine-Like Objects in Sidescan Sonar Imagery, IEEE Journal of Oceanic Engineering, Mar. 2015 (pdf)


John McGarry, Alric Althoff, inventors; Cognex Corporation, assignee. Machine Vision System with Large Depth of Field, filed 3/6/15 Patent Pending.