Work related to our US Space Force’s UCRO project will be presented during the Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging meeting at SPIE DCS on April 23. The talk, Using neural networks to classify hyperspectral signatures of unresolved resident space objects, will discuss our work on using deep learning methods. The paper includes undergraduate Luis Cedillo and masters student Kevin Acosta as authors in addition to Drs. DeBlasio and Velez-Reyes who are the co-investigators on the project.
Author: Dan DeBlasio
Luis Cedillo presents poster at UCRO 1.0
Undergraduate student Luis Cedillo will present work related to our project “Innovative Analysis of Spectra-Temporal Signatures using Machine Learning for Ground-Based Remote Sensing of Unresolved Resident Space Objects”, collaborative work with Kevin Acosta and Dr. Miguel Velez-Reyes (Electrical and Computer Engineering) at the University Consortium Research Opportunity meeting in Boulder, CO. This stands as our one year anniversary of the project funded by the US Space Force through the University Consortium Research Opportunity.
Parametric Sequence Alignment
This lecture describes parametric sequence alignment as presented in Section 13.1 of Dan Gusfield’s book Algorithms on Strings, Trees, and Sequences.
Given two sequences, can you determine how many choices of values of the standard sequence alignment objective function’s parameters give distinct optimal alignments. In other words, how many alignments are optimal for some setting of the objective function’s parameters. This lecture discusses how to approach and answer this question.
Building an Automated Scientist:
Using Machine Learning to Configure Algorithms
In this talk I give an overview of the current background of the projects being performed in our lab as well as some fundamental background on pairwise sequence alignment, one of the underpinnings of much of the work we’re doing.
Demetrius to present poster at Great Minds in STEM
Following his win for best poster (covered in UTEP News article) at the UTEP COURI Symposium in the Spring and a well received reception at the RECOMB 2022 poster session, lab member Demetrius Hernandez will be participating in the poster competition at the Great Minds in STEM meeting in Pasadena, CA on October 6th. The poster is tentatively titled “Efficient minimizer schemes using deep networks”.
Talk at New Mexico Tech on 26 September 2022
Dr. DeBlasio will be giving a talk titled “Building an Automated Scientist: Three stories of accelerating scientific discovery” in the Computer Science Department Seminar Series at New Mexico Tech (New Mexico Institute of Mining and Technology) in Socorro, NM on Monday, 26 September 2022 at 5:30 pm. The slide deck used is attached below. This talk will discuss several of the major projects currently happening in the group and the background from Dr. DeBlasio’s previous work that is relevant. The abstract is also below the fold.
Continue reading “Talk at New Mexico Tech on 26 September 2022”3 lab members present, Demetrius wins best poster
On Saturday, 30 April 2022 3 members of the lab presented posters at the annual UTEP COURI (Campus Office for Undergraduate Research Initiatives) Symposium. Approximately 115 undergraduates presented 110 posters from across the university. From those, our own Demetrius Hernandez won best poster presentation in the “Engineering, Computational, and Applied Science” category (covered in UTEP news). Congratulations Demetrius!
The lab’s contributions are listed below in no particular order:
- Hector Richart — Increasing protein multiple sequence alignment parameter advising accuracy by considering secondary structure information
- Luis Cedillo — Facet-NN: Improved accuracy estimation using neural networks
- Demetrius Hernandez — Efficient minimizer schemes using deep networks
UTEP IDR Event on 30 March 2022
I will be giving two talks at the UTEP Interdisciplinary Engagement Event on 30 March 2022. My talk, titled “Who needs a manual? Automating scientific tools to accelerate innovation. Building an Automated Scientist: Parameter Advising for Accelerated Discovery” (slides below) will be conducted twice: once at 1:00pm at Station B and once at 3:00pm at Station A in the Interdisciplinary Research Building (IDRB) Room 2.204. The full schedule of presentations can be found here, with the other speakers including colleagues from around campus and including here within Computer Science.
Demetrius to present poster at RECOMB 2022
Demetrius will present a poster titled “Efficient Minimizer Schemes using Deep Networks” at the 26th Annual International Conference on Research in Computational Molecular Biology (RECOMB) in San Diego, CA in May.
Spring 2022 Course
I will be teaching a special topics in data science course this spring. The information can be found below or at http://specialtopics.deblasiolab.org/s22/. The course numbers are CS 4364 for undergrads and CS 5364 for graduates (the CRNs can be found on the CS department course schedule).