Designed tools for Instructional Designers using Vue.js

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Deep Learning for Classifying and Characterizing Atmospheric Ducting within the Maritime Setting

Two-step deep learning model for predicting refractivity profile parameters under various ducting conditions

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Software Resource for Mathematical Modeling of Natural and Engineered Systems

Resource created for CEE 5735 students about Anaconda, machine learning libraries, FEniCS, etc.

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Gaussian Process Regression for Estimating EM Ducting Within the Marine Atmospheric Boundary Layer

GPR implementation addressing severe sensor noise on radar observations

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Quick Start to Gaussian Process Regression

A quick guide to understanding Gaussian process regression (GPR) and using scikit-learn’s GPR package; > 192K Views

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Getting started with GPU Computing for machine learning

A quick guide for setting up Google Cloud virtual machine instance or Windows OS computer to use NVIDIA GPU with Pytorch and Tensorflow

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Characterizing Evaporation Ducts Within the Marine Atmospheric Boundary Layer Using Artificial Neural Networks

Demostrated the suitability of artificial neural networks for the duct characterization problem

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Designed club management application and built backend using Flask and SQLAlchemy
Best Documentation & Runner-up for Best Application Design, Spring '20 backend course

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Computational Study of Hydrogel Ring Device for Ocular Drug Delivery

Modeled Ofloxicin pharmakinetics from a hydrogel ring to the posterior eye using COMSOL Multiphysics and AutoCAD

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CEE GSA Website Redesign

Redesigned a responsive website for CEE GSA using HTML5/CSS3/JS/jQuery

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Neural Network Mini-Course

Guides and activities for Summer 2018 interns to introduce them to neural networks and their implementation with Tensorflow

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About Me

I received my Ph.D. in Remote Sensing from Cornell University. My dissertation focuses on examining the application of machine learning methods for characterizing electromagnetic ducting within maritime settings. More broadly, my research interests lie at the intersection of computing and engineering.


Ph.D. Remote Sensing, Cornell University, 2021

M.S. Remote Sensing, Cornell University, 2020

B.S. Biological Engineering, Cornell University, 2018

  • Sit, H., Earls, C.J. (2021) “Deep learning for classifying and characterizing atmospheric ducting within the maritime setting,” Computers and Geosciences, Vol. 157, Elsevier, 107545.
  • Sit, H., Earls, C.J. (2020) “Gaussian process regression for estimating EM ducting within the Marine Atmospheric Boundary Layer,” Radio Science, American Geophysical Union, Vol. 55, Issue 6, pp. 1-14.
  • Sit, H., Earls, C.J. (2019) “Characterizing evaporation ducts within the marine atmospheric boundary layer using artificial neural networks,” Radio Science, American Geophysical Union, Vol. 54, Issue 12, pp. 1181-1191.
Teaching & Advising

Teaching Assistant

  • CEE 5735: Mathematical Modeling of Natural and Engineered Systems, Fall 2020
  • PLBIO 2400: Green World Blue Planet, Spring 2018
  • CS 1300: Introductory Design and Programming for the Web, Fall 2017

Civil and Environmental Engineering Graduate Peer Mentor, Fall 2020

Research Mentor

  • Cornell undergraduate intern, Summer 2019
  • High school student interns, Summer 2018

Engineering Peer Advisor, Fall 2016 & Fall 2017

Involvement & Service

Cornell Alumni Admissions Ambassador, 2020 - present

Civil and Environmental Graduate Student Association

  • President, 2020 - 2021
  • Treasurer, 2019 - 2020
  • Field Representative, 2018 - 2019

IEEE Access Peer Reviewer, 2020

Code-4-Kids Volunteer Instructor, 2020

Alpha Phi Omega National Service Fraternity Volunteer, 2015 - 2017

Cornell Society of Women Engineers Outreach, 2014 - 2016

Awards & Honors

Alpha Epsilon Agricultural & Biological Engineering Honor Society, 2017

John McMullen Deans Scholar, College of Engineering, 2014 - 2018

Hunter R. Rawlings III Cornell Presidential Research Scholar, Cornell Commitment, 2014 - 2018

Selected Coursework
  • CS 6780 Advanced Machine Learning
  • CS 6670 Computer Vision
  • CS 4780 Large-Scale Machine Learning
  • CEE 6000 Numerical Methods
  • CEE 5780 Finite Element Analysis
  • MATH 4210 Nonlinear Dynamics and Chaos
  • BEE 4530 Computer-Aided Engineering
  • NBA 5380 Business Factory Idea