Teaching

Course Development

Service

I offer PHYS 699, 800, and ICS 499, 699, 700 and 800 EVERY SEMESTER.

PHYS 311

Spring 2023

PHYS 311 Classical Mechanics II

Spring 2022

PHYS 485 Professional Ethics for Physicists

Spring 2021

ICS 635 Machine Learning

Fall 2020

ICS 636 Machine Learning

Fall 2019/Spring 2020: Sabbatical.

Spring 2019

ICS 435 Machine Learning Fundamentals

ICS 636 Machine Learning

Fall 2018

ICS 235 Machine Learning Fundamentals

ICS 635 Machine Learning

Spring 2018

ICS 435 Machine Learning Fundamentals

ICS 635 Machine Learning

Fall 2017

ICS 101 Tools for the Information Age

ICS 435 Machine Learning Fundamentals

Spring 2017

ICS 636 Information Theory in Machine Learning

ICS 435 Machine Learning Fundamentals

Fall 2016

ICS 635 Machine Learning

ICS 101 Tools for the Information Age

Spring 2016

ICS 101 Tools for the Information Age

ICS 141 Discrete Mathematics

Fall 2015

ICS 636 Information Theory in Machine Learning

ICS 141 Discrete Mathematics

Spring 2015

ICS 101 Tools for the Information Age

Fall 2014

ICS 101 Tools for the Information Age

Spring 2014

ICS 141 Discrete Mathematics

ICS 101 Tools for the Information Age

Fall 2012/Spring 2013: Sabbatical.

Spring 2012

ICS 635 Machine Learning

ICS 141 Discrete Mathematics

Fall 2011

ICS 691 Applications of Machine Learning

ICS 141 Discrete Mathematics

Spring 2011

ICS 435 Machine Learning Fundamentals

ICS 141 Discrete Mathematics

Fall 2010

ICS 691 Advanced Topics in Robotics

ICS 141 Discrete Mathematics

Spring 2010

ICS 635 Machine Learning

ICS 141 Discrete Mathematics

Fall 2009

ICS 141 Discrete Mathematics

Spring 2009

ICS 636 Information Theory in Machine Learning

ICS 141 Discrete Mathematics

Fall 2008

ICS 635 Machine Learning

Spring 2008

ICS 491 Neuroinformatics and Machine Learning: From synapses to algorithms. An Introduction.

ICS 141 Discrete Mathematics

Spring 2007

ICS 635 Computational Intelligence / Machine Learning

Fall 2006

ICS 691 Machine Learning

Spring 2005

ICS 691 Bioinformatics, Machine Learning and Quantitative Biology

SYLLABI FOR: ICS 141 Discrete Mathematics, ICS 435 Machine Learning Fundamentals, ICS 635 Machine Learning, ICS 636 Information Theory in Machine Learning.

I developed the ICS machine core curriculum consisting of the following classes:

Undergraduate classes:

- Machine Learning Foundations, ICS 235: Mathematical
foundations for machine learning.

- Machine Learning Fundamentals, ICS 435:
Undergraduate level machine learning class.

Graduate Classes:

- Machine Learning, ICS 635: Graduate level machine learning class.
- Information Theory in Machine Leraning, ICS 636: Advanced graduate level class.

- Advances in Complex Systems
- CHAOS
- Computer Vision and Pattern Recognition
- European Biophysical Journal (EBJ)
- Entropy
- IEEE Robotics and Automation Letters
- IEEE Transactions on Neural Networks and Learning Systems IEEE Transactions on Knowledge and Data Engineering
- Journal of Banking and Finance
- Journal of Machine Learning Research

- Nature

- Neural Computation
- Physical Review Letters (PRL)
- Physical Review E
- Physical Review X

- Proceedings of the National Academy of Sciences (PNAS)
- Transactions on Pattern Analysis and Machine Intelligence
- Transactions on Knowledge and Data Engineering

Proposal reviewing: National Science Foundation
(NSF), Panelist

Conference Organization:

Organizer (2005-present):

Mānoa Seminar Series on Physics of Information Processing

(formerly: Manoa Seminar Series in Machine Learning and Computational Neuroscience)

Conference Organization:

- Manoa Mini-Symposium on Physics of Adaptive Computation, January 7, 2019, Organizer. (CCC sponsored)
- Thermodynamic Computing CCC workshop, Honolulu January 3-5, 2019, Co-organizer.
- Modeling Neural Activity (MONA): Statistics, Dynamical Systems and Networks, Lihue, HI, June 26-28, 2013. Local Chair. (NSF sponsored)

Organizer (2005-present):

Mānoa Seminar Series on Physics of Information Processing

(formerly: Manoa Seminar Series in Machine Learning and Computational Neuroscience)

- (AY 2021/20) CNS planing committee for a CNS Faculty Senate

- (AY 2017/18) Excellence in Teaching Committee
- (AY 2017/18) TPRC
- (AY 2016/17) Excellence in Teaching Committee (Convener)

- (AY 2015/16) Search Advisory Committee for the Dean of the College of Natural Sciences (CNS)
- (AY 2015/16) HHMI 2017 Undergraduate Science Ed Grant: Working Group no.2 (“killer" courses)
- (AY 2015/16) CNS Interim Associate Dean Search Committee
- (AY 2009/10) Foundations FS (focus on symbolic reasoning)
Working Group

- (AY 2017/18) Curriculum committee, Chair Fall 2017

- (AY 2016/17) Space and infrastructure committee, Chair
Spring 2017

- (AY 2015/16) Department Personnel Committee, Chair for contract renewal cases

- Hiring Comittee
- Department Personnel Committee
- Curriculum Committee
- Various hiring Committees
- Graduate Committee
- Space and Infrastructure Committee
- ICS basic math education working group