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Rachneet Kaur

I am a PhD student in the Department of Industrial and Enterprise Systems Engineering at UIUC working with Richard Sowers. I am named the William A. Chittenden II graduate fellow.

I did my bachelors from the University of Delhi and masters from the Indian Institute of Technology (IIT), Delhi in Mathematics.

My research interests lie at the intersection of Computer Vision, Deep Learning and Healthcare.

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Highlights and News
Mar 2024 Organizing the tutorial on Rating AI Trustworthiness at ACM International Conference on AI in Finance 2024.
Mar 2024 Invited talk on 'Mathematics and AI in the Financial Industry' at Punjab Engineering College, India.
Feb 2024 Organizing the first workshop on AI in Finance for Social Impact at AAAI 2024.
Nov 2023 Organizing Women in AI and Finance workshop at ACM International Conference on AI in Finance 2023.
Apr 2021 Recieved the 2021 UIUC ISE Sharp Outstanding Graduate Student Award
Dec 2020 Paper accepted at the IEEE Transactions on Biomedical Engineering (TBME) journal
Aug 2020 Renamed the William A. Chittenden II Graduate Fellow for academic year 2020-2021
Oct 2019 Recieved the Kanako Miura Award by the IEEE RAS Technical Committee on Humanoid Robotics
Aug 2019 Renamed the William A. Chittenden II Graduate Fellow for academic year 2019-2020
Aug 2018 Awarded the William A. Chittenden II Graduate Fellowship for academic year 2018-2019
Mar 2018 Recieved the 2018 Illinois Geometry Lab Research Award. Thanks Department of Mathematics@UIUC!
Dec 2017 Selected as the 1st runner up for Mottier Innovation Challenge in Systems Engineering Award
Mar 2015 Awarded the Charpak Research Intern Scholarship for summer of 2015
Dec 2012 Won the Legacy of Srinivasa Ramanujan Coding Competition
(Awarded at the International conference on Legacy of Srinivasa Ramanujan, 2012)

About Me

I am currently a Ph.D. student in the Department of Industrial Engineering at the University of Illinois at Urbana-Champaign. I am advised by Richard Sowers and also collaborated closely with Manuel Hernandez. My current research is focused on applications of machine learning for unfolding problems in health and finance domain.

Prior to joining PhD, I have earned a B.S. (with honours) in Mathematics from the University of Delhi and an M.S. in Mathematics from the Indian Institute of Technology (IIT), Delhi. During my masters, my thesis was advised by Aparna Mehra.

To pursue my interests in quantitative finance and AI, I have spent time as a research intern at:

VISA Research, Summer 2019
Mentors: Carolina Barcenas, Chiranjeet Chetia, Shubham Agrawal
3M Electronics, Software & AI Research, Summer 2018
Mentors: David Redinger, Brian J. Stankiewicz
Quantitative Research, Quantlab Financial LLC, Summer 2017
Mentors: Areez Mody, Matteo Nicoli
Statistique, Analyse et Modélisation Multidisciplinaire (SAMM), Université
Paris 1 Panthéon-Sorbonne,
Summer 2015

Mentor: Julien Randon Furling
Tata Institute of Fundamental Research (TIFR), India, Summer 2014
Mentor: Mythily Ramaswamy
National Program on Differential Equations - Theory, Computation and Applications
Held at National Institute of Technology (NIT), Calicut, India, Winter 2013
Mentors: Satyananda Panda, T. Suman Kumar

See some excerpts from my journey here.


Journal Publications
A Vision-Based Framework for Predicting Multiple Sclerosis and Parkinson's Disease Gait Dysfunctions - A Deep Learning Approach
Rachneet Kaur, Robert W. Motl, Manuel E. Hernandez, Richard Sowers
IEEE Journal of Biomedical and Health Informatics (JBHI), 2022
Project page | Paper | Code | Cite

We demonstrate the potential of deep learning with a multi-view digital camera-based gait analysis framework for neurological gait dysfunction prediction. This study suggests the viability of inexpensive vision-based systems for diagnosing certain neurological disorders.

Identification and prediction of Parkinson's disease subtypes and progression using machine learning in two cohorts
Anant Dadu, Vipul Satone, Rachneet Kaur, Hampton Leonard, Hirotaka Iwaki, Mary Makarious, Lana Sargent, Ali Daneshmand, Sonja W. Scholz, Mike A. Nalls, Roy H. Campbell, Faraz Faghri
npj Parkinson's Disease, Nature Publishing Group 2022
Project page | arXiv | Code | Interactive website | Cite

The machine learning techniques presented in this study may assist providers in identifying different progression rates and trajectories in the early stages of the disease, hence allowing for more efficient and personalized healthcare deliveries.

Machine Learning and Price-Based Load Scheduling for an Optimal IoT Control in the Smart and Frugal Home
Rachneet Kaur, Clara Schaye, Kevin Thompson, Daniel C Yee, Rachel Zilz, RS Sreenivas, Richard Sowers
Energy and AI, Elsevier 2021
Project page | Paper | Video | Cite

We pose and study a scheduling problem for an electric load to develop an Internet of Things (IoT) control system for power appliances, which takes advantage of real-time dynamic energy pricing.

Predicting Multiple Sclerosis from Gait Dynamics Using an Instrumented Treadmill – A Machine Learning Approach
Rachneet Kaur, Zizhang Chen, Robert Motl, Manuel Hernandez, Richard Sowers
IEEE Transactions on Biomedical Engineering (TBME), 2020
Project page | Paper | Video | Code | Cite

Evaluating the effectiveness of a spatiotemporal and kinetic gait data-based machine learning framework for Multiple Sclerosis prediction.

Predicting Alzheimer's Disease Progression Trajectory and Clinical Subtypes Using Machine Learning
Vipul Satone, Rachneet Kaur, Anant Dadu, Hampton Leonard, Hirotaka Iwaki, Mary Makarious, Lana Sargent, Ali Daneshmand, Sonja W. Scholz, Mike A. Nalls, Roy H. Campbell, Faraz Faghri
Under Submission, 2020
Project page | arXiv | Code | Interactive website | Cite

The machine learning techniques presented in this study may assist providers in identifying different progression rates and trajectories in the early stages of the disease, hence allowing for more efficient and personalized healthcare deliveries.


Conference Proceedings
Exploration of Machine Learning to Identify Community Dwelling Older Adults with Balance Dysfunction Using Short Duration Accelerometer Data
Yang Hu*, Alka Bishnoi*, Rachneet Kaur, Richard Sowers, Manuel Hernandez
42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2020
Project page | Paper | Slides | Video | Cite

Examining the feasibility of using wearable sensors, when walking, to identify older adults who have trouble with balance at an early stage.

Automatic Identification of Brain Independent Components in Electroencephalography Data Collected while Standing in a Virtually Immersive Environment - A Deep Learning-Based Approach
Rachneet Kaur, Maxim Korolkov, Manuel Hernandez, Richard Sowers
42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2020
Project page | Paper | Slides | Video | Cite

Automated removal of unwanted artifacts on noisy and visually engaging upright stance Electroencephalography (EEG) data.

Using Virtual Reality to Examine the Neural and Physiological Anxiety-Related Responses to Balance-Demanding Target-Reaching Leaning Tasks
Rachneet Kaur, Rongyi Sun, Liran Ziegelman, Richard Sowers, Manuel Hernandez
IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids), 2019
Project page | Paper | Slides | Video | Cite

Letting NeRF reason about occluders and appearance variation produces photorealistic view synthesis using only unstructured internet photos.

Using Virtual Reality to Examine the Correlation between Balance Function and Anxiety in Stance
Rongyi Sun*, Rachneet Kaur*, Liran Ziegelman, Shuo Yang, Richard Sowers, Manuel Hernandez
IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2019
Project page | Paper | Slides | Video | Cite

Examining the interaction between balance function and anxiety via a VR-based experimental setup, designed to simulate stressful environments involving postural threats.

Using Virtual Reality to Examine the Neural and Physiological Responses to Height and Perturbations in Quiet Standing
Rachneet Kaur, Rongyi Sun, Liran Ziegelman, Richard Sowers, Manuel Hernandez
41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2019
Project page | Paper | Poster | Cite

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Exploring Characteristic Features in Gait Patterns for Predicting Multiple Sclerosis
Rachneet Kaur, Sanjana Menon, Richard Sowers, Manuel Hernandez
41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2019
project page | Paper

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Learning the progression and clinical subtypes of Alzheimer's disease from longitudinal clinical data
Vipul Satone, Rachneet Kaur, Faraz Faghri, Mike A Nalls, Andrew B Singleton, Roy H Campbell
Machine Learning for Health (ML4H), Neural Information Processing Systems (NeurIPS), 2018
Project page | arXiv | Poster | Code | Blog

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Virtual Reality, Visual Cliffs, and Movement Disorders
Rachneet Kaur, Xun Lin, Alexander Layton, Richard Sowers, Manuel Hernandez
40th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2018
Paper

XXX Description XXX


Patents
Methods and systems of path-based mapping and routing
3M Innovative Properties Company, 3M Company
Patent | Project background | Cite

Systems and methods of path-based mapping and routing are provided. Translation information and absolute orientation information of mobile objects in environments are determined based on a fusion of sensing data from a radar and an inertial measurement unit (IMU) including a gyroscope and an accelerometer, from which path-based maps and optimal routes can be generated.


Book Chapters
Virtual Reality and Movement Disorders
Rachneet Kaur, Manuel Hernandez, Richard Sowers
Virtual Reality: Recent Advancements, Applications and Challenges, River Publishers, 2020
Project page | Chapter | Book | Cite (chapter) | Cite (book)

This chapter is primarily aimed at establishing and understanding underlying fluctuations relative to anxiety in human postural control using immersive virtual conditions.


Posters and Talks
Sep 2021 Deep Learning for Multiple Sclerosis Prediction using Multi-Stride Dynamics in Gait
11th International Symposium on Gait and Balance in Multiple Sclerosis
Aug 2021 Adaptive Control of Stride Length in Response to Perturbations While Walking in Older Women with Osteoarthritis
American Society of Biomechanics (ASB) Annual Meeting, 2021
Predicting Multiple Sclerosis from Gait Dynamics
Nov 2020 Graduate Seminar Series, Industrial & Enterprise Systems Engineering (ISE), UIUC [Video]
Sept 2020 ACM poster presentation session, Virtual Grace Hopper Celebration for Women [Poster]
Nov 2019 Using Virtual Reality High Fall-Risk Condition Training to Improve Postural Control Accuracy and Speed
American Congress of Rehabilitation Medicine 96th Annual conference, Progress in Rehabilitation Research
Oct 2019 Using Virtual Reality to examine the correlation between balance function and anxiety in a quiet stance
Biomedical Engineering Society (BMES) Annual Meeting
Predicting Multiple Sclerosis Disorder from Gait Patterns [Slides]
May 2019 Illinois Geometry Lab Poster Session, Department of Mathematics, UIUC
Mar 2019 9th International IEEE EMBS Conference on Neural Engineering (NER)
IoT Dishwasher [Slides]
Mar 2019 Presented by ISE undergraduate students at the Undergrad Research Symposium, UIUC and
the Engineering Open House, UIUC
Apr 2018 Demo for John Deere's visit, ISE, UIUC
Nov 2017 Demo at the Mottier Innovation Challenge in Systems Engineering, UIUC
Sept 2018 Visual Cliffs, Virtual Reality and Movement Disorders [Poster]
ACM poster presentation session, Grace Hopper Celebration for Women
Apr 2018 Predicting the progressions of Alzheimer’s disease using Machine Learning [Poster]
2nd Illinois Health Data Analytics Summit
Feb 2018 Optimal IoT Control for Power Consumption
Coordinated Science Laboratory Student Conference, UIUC [Poster]
IEEE Power and Energy Conference (PECI) at Illinois [Poster]
Oct 2017 A Brain computer interface approach to examine changes in anxiety while walking in a virtually infinite world
Biomedical Engineering Society (BMES) Annual Meeting [Video]
Apr 2015 Computing with words [Poster]
Engineering Open House, Indian Institute of Technology (IIT) - Delhi

Projects
Show and Tell: A Neural Image Caption Generator
Class project for CS598 Deep learning, Fall 2018, UIUC
Taught by Prof. Justin Sirignano
PDF report | Slides | Code




Deep Patient
Paper presentation for CS598 Health Data Analytics, Spring 2018, UIUC
Taught by Prof. Roy Campbell
Slides




Pairwise Learning to Rank for MeTA
Class project for CS510 Advanced Information Retrieval, Fall 2017, UIUC
Taught by Prof. ChengXiang Zhai
PDF report | Slides | Video | Code




Distributed K means
Class project for IE529 Stats of Big Data, Fall 2017, UIUC
Taught by Prof. Carolyn L Beck
PDF report | Slides | Code




Maxit game
Class project for IE498 Computing for ISE, Spring 2017, UIUC
Taught by Prof. Jugal Garg
Project description | Code



Academic Service and Leadership
Program Committee:
Medical Imaging meets NeurIPS (MED-NeurIPS), NeurIPS [2021]
Machine Learning for Health (ML4H), NeurIPS [2020] [2021]
Fair ML for Health, NeurIPS [2019]

Reviewer:
Medical Imaging meets NeurIPS (Med-NeurIPS), NeurIPS [2019] [2021]
Machine Learning for Health (ML4H), NeurIPS [2019] [2020] [2021]
Machine Learning in Public Health, NeurIPS [2021]
Machine Learning and the Physical Sciences, NeurIPS [2020]
Fair ML for Health, NeurIPS [2019]
Women in Machine Learning (WiML), NeurIPS [2018]
Illinois Geometry Lab Graduate Mentor:
Illinois Geometry Lab, Department of Mathematics, UIUC, Spring 2017, Fall 2017, Spring 2018, Fall 2018, Spring 2019
University of Illinois at Urbana Champaign Graduate Teaching Assistant:
CS547/IE534 Deep Learning, UIUC, Fall 2019
IE361 Production Planning and Control, UIUC, Spring 2019
IE 300 Analysis of Data, UIUC, Fall 2016, Spring 2017, Fall 2017, Spring 2018, Fall 2018
IIT-Delhi Leadership:
Open House Coordinator, IIT-Delhi, Mar-Apr 2016
Event Management Volunteer, Rubic's Cube Indian Nationals, IIT Delhi, Feb-Mar 2016
Publicity Volunteer, Spic Macay, IIT Delhi, Jan-Mar 2016
Event Management Volunteer, Tryst, IIT Delhi, Jan-Mar 2015

Collaborations and Mentorship

At UIUC, I have had a chance to work with and mentor some excellent students:

Daan Michiels (Currently Senior Quantitative Researcher at G-Research)
Vivek Kaushik (Currently PhD candidate at the Department of Mathematics, UIUC)
Yankun Zhao (Currently MS in Computer Science candidate at Yale University)
Zhonghao (Dennis) Zhao (Currently MS in Analytics candidate at Northwestern University)
Maxim Korolkov
Zizhang Chen

Contact Me
Room 205, Transportation building,
University of Illinois at Urbana-Champaign
Email rk4@illinois.edu
kaurrachneet6@gmail.com


Template credits: Joe