People
Director
Director
Machine learning to inform clinical care, focusing on rehabilitation and wearables.
"If you have build castles in the air, your work need not be lost; that is where they should be, now put the foundations under them." - Thoreau
Dr. Albert's professional goal in life is to leverage machine learning to automate the collection and inference of clinically useful health information to improve clinical research. His projects in wearable sensor analytics have improved the measurement of health outcomes for individuals with Parkinson's disease, stroke, and transfemoral amputations with a variety of additional populations and contexts including children with cerebral palsy as well as healthy toddler activity tracking. Current projects include video-based activity tracking and mobile robotic platforms, all in an effort to improve measures of clinical outcomes to justify therapeutic interventions.
PhD Students (9)
Ph.D. Candidate, also with Dr. Ting Xiao
Predicted modeling of clinically relevant score outcomes using natural language processing.
ThasinaTabashum at my.unt.edu
Thasina is our lab manager coming all the way from Bangladesh in 2019. Generally, she is applying machine learning strategies to more precisely measure health outcomes due to therapeutic interventions of cerebral palsy subjects. Her current research focus is applying in-context learning methods utilizing large language models to predict clinical outcomes such as pain scores and fall risk scores.
Steve (Shou-Jen) Wang
Ph.D. Candidate
Masters of Science in Technology from Eastern Illinois University
Shou-JenWang at my.unt.edu
Steve has developed a machine learning model for sensors placed on the arm to automatically measure spasticity (a condition in certain muscles are continuously contracted causing stiffness or tightness of the muscles and can interfere with normal movement) to enable more precision in discerning spasticity treatments.
He is currently working with the Shriners Hosptials for Children on a predictive model of surgical outcomes for children with cerebral palsy, aiding surgeons in the selection of therapeutic options to improve gait.
Himanshu Sharma
PhD Candidate
himanshusharmaat my.unt.edu
Himanshu joined UNT in Fall 2018 and completed his Master’s in Computer Science (Spring 2020). Now he has joined Computer Science PhD program in Fall 2020. He is currently working on EKG signal compression using deep neural network autoencoders. His interest includes computational neuroscience and natural language processing. He has interest in cognitive computing, natural language processing and computational robotics.
Chandrashekhar Ramamurthi
PhD Student
ChandrashekharRamamurthi at my.unt.edu
Chandrashekhar joined UNT in 2020 currently pursuing his PhD with specialization in Machine learning and Deep learning. His is currently working on scoring symptoms of Parkinson's Disease through measurements during quiet standing. He is currently involved in applying the predictive models to clinical decision support. He is interested in application of Artificial Intelligence in clinical care.
I am a Computer Science and Engineering PhD student at the University of North Texas, involved in different research project such as non-marked tumor tracking in lung imaging, emotion based recommender system, multispectral image analysis, point cloud clustering and many more. My most recent project, involves developing and assessing physiologically appropriate efficient coding models for LGN/V1 spontaneous neural activity and describing their role in binocular vision evolution, and other modalities of data such as audio, images, and video.
Riyad Bin Rafiq
PhD Candidate, also with Dr. Weishi Shi
https://riyadrafiq.github.io/
RiyadBinRafiq at my.unt.edu
Riyad joined the Biomedical AI Lab in the Spring of 2021. His research interest lies in the field of biomedical application and deep learning. He is specifically interested in exploring the use of transfer learning, continual learning, and meta-learning for custom gesture learning strategy in the small-data paradigm. Currently, he is working on wearable gesture recognition for use in medical applications, particularly for individuals unable to speak. Previously, Riyad completed his undergrad in CSE at Chittagong University of Engineering and Technology (CUET) in Bangladesh.
Ziruo Yi
Ziruo is a Computer Science and Engineering PhD student in our lab. Her research focuses on multimodal machine learning, natural language processing, computer vision, large language models, image captioning, visual question answering and artificial intelligence in healthcare.
Guna Sindhuja Siripurapu
Sindhuja joined the lab as a PhD student in Fall 2023. She is currently working on a project that focuses on Bayesian Analysis to decode Human Preferences, combining the elements of both computer science and neuroscience. Previously, Sindhuja worked as a Research Assistant in the domain of VR/AR/XR and Game Development, which provided her with a strong foundation for exploring new research areas and expanding her knowledge horizons. Now, she is passionate and curious about delving deeper into the human mind through computational neuroscience and cognitive computing. Additionally, she has a keen interest in the domains of Artificial Intelligence, Machine Learning, and Human-Computer Interaction and desires to make significant contributions in these fields.
Sekhar Lanka
PhD Student
MS Students
William joins us with a BS in Materials Science. Pursuing a MS in Artificial Intelligence, his research is focused on ML-based alloy design, particularly studying deformation-induced transformations in High Entropy Alloys using Few-Shot Learning, Active Learning, and NLP. Additionally, William is exploring predictive modeling of crystallographic shifts through nanoindentation using various ML techniques such as Logistic Regression, SVM, and Decision Trees. His work aims to bridge the gap between traditional materials science and modern machine learning approaches to unlock new potentials in alloy design and predictive modeling.
Hari Kiran Keerthipati
Bhavani Rachakatla combines a solid 4.5 year background in software engineering at Vistex Inc with a burgeoning interest in machine learning and predictive analytics. Her existing publications in CRC Press and Springer highlight her commitment to applying data insights in solving real-world problems, a focus that will continue in her forthcoming MS thesis on Fall Detection and Real-time response.
Undergrad
Arlene Makia
Aditya Nallaparaju
General Science and Mathematics Track at the Texas Academy of Mathematics and Science
aditya.nallaparaju at gmail.com
As a junior at the Texas Academy of Mathematics and Science pursuing the General Science and Mathematics Track, I am fascinated by the intersection of biomedicine, computer science, and health administration. The opportunity to conduct research in this lab aligns perfectly with my academic interests, allowing me to examine the connections between biomedical engineering and computer science firsthand. With my background in the sciences and mathematics, I am well-prepared to contribute to the innovative work being done in the lab while gaining invaluable hands-on research experience at the interface of these exciting fields.
Lab Affiliated
Namratha Urs
Ph.D. Student, member of HiLT lab
Efficient neural coding of sensory signals
NamrathaUrs at my.unt.edu
Namratha regularly participates in projects through the adjoining Human Intelligence and Language Technologies (HiLT) Lab. She is pursuing a computational neuroscience project demonstrating how the early visual and auditory systems can be understood through efficient coding - in essence you can "derive" a visual system from a (neurally) appropriate efficient coding of natural scenes. She has created a Jupyter notebook demonstrating this in a number of modalities (black and white, color, and "natural" audio input) and presented at SfN 2019 (the Society for Neuroscience conference), with a goal of making the notebook readily accessible to anyone, computational or not, that is interested in understanding a link between computer science and neuroscience.
Past students
PhD
Sahar Behpour --> Deloitte
Md Mosharaf Hossain --> Amazon
Abdullah Albanyan --> Prince Sattam bin Abdulaziz University
Shiva Ebrahimi
Masters
Havish Nallapare --> WholeFoods
Kiana Poole --> iRhythm Technologies
Sri Sravya Comerica --> Walmart
Munazza Ali --> USPTO
Hannah Helgesen --> PhD Candidate at Linköping University
Chengping Yuan
Theo Medeiros --> TRG
Ryan Hunter Moye --> State Farm
Akansha Goel
Phillip Merritt --> PwC
Syed Araib Karim --> Amazon
Lakshmi Vandana Nunna --> Walmart
Jerline Jeyaraj --> eShipGlobal
Cooper Snyder -- State Farm
Kishen Prakashlal Patel --> MicroAI
Annie Liu --> Elm Street
Ranak Bansal --> MIS and Econ at UT-Austin
Rickey Dixon Jr.
Trevor Exley --> Robotics and STEM LLC
Ishan Ranasinghe --> Southwest Minnesota State University
Cindy Liang --> Cornell
Former Thesis Graduate Students
Pinky Sindhu (Fall 2017 - Summer 2018) --> Allstate
Ilona Shparii (Aug 2015 - Aug 2017) --> Google
Anne Zhao (Aug 2015 - Aug 2017) --> Panasonic
Pichleap (Jessie) Sok (Sep 2015 - Aug 2016) --> Amazon
Former Graduate Students, non-thesis research
Albert Sugianto (Summer 2018 - Spring 2019)
Rejoice Jabamalaidass (Fall 2018 - Spring 2019)
Liz Sink (Summer 2017 - Fall 2017) --> Avant
Irina Rabkina, Computer Science graduate student (Spring - Summer 2015) --> Northwestern University PhD Program in Computer Science
Lailson Nogueira (Fall 2014 - Spring 2015) --> Oracle
Asma Mehjabeen (Spring 2013 - Fall 2014) --> Procured Health
Daneih Ismail (Fall 2013 - Spring 2014) --> DePaul Ph.D. Program in Computer Science
Undergrad and TAMS
Bassam Metwally --> GridUnity
Austin Meek
Rhea Pookulangara
William Flinchbaugh
William Zamudio --> University of North Texas
Kane Dong --> Texas A&M
Abhijay Achukola --> Purdue
Phillip Nelson --> UT-Dallas
Ted Kwee-Bintoro
Arvind Ganesh
Brianna Chan
Adheesh Kadiresan --> Complex Resilient Intelligent Systems Lab
Kaushik Akula
Lisa Li
Kanav Bengani --> Northeastern
Cindy Liang
Ranak Bansal
Nora Xiao
Zoe El-Zayaty
Venkat Ayalavarapu
Brian (Joonghyun) Kim Abhijay Achukola
Zhihao Zhou (Spring 2018 - Fall 2018) --> MS program at Carnegie Mellon University, Silicon Valley campus
Sam Sendelbach (Fall 2017 - Spring 2018) --> Founder, TensorTask
David Saffo (Summer 2016 - Spring 2018) --> PhD program at Northeastern University
Jack Blandin (advised post graduation in 2017/18) --> GoHealth, then Ph.D. Program at University of Illinois Chicago
Anirrudh Krishnan (Spring 2018) --> Quansight
Mary Makarious (Spring 2015 - Fall 2016) --> NIH
Gordon Kratz (Spring - Summer 2014) --> Group One Trading
Neil Rao (Spring - Fall 2014) Biology undergrad --> Co-founder REPRIMX