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Coffee, pastries and fruit available.

Presenters

Mridul Gautam, vice president for research and innovation
As vice president for research and innovation and professor of mechanical engineering at the �Ƽ��Ӱ�ԭ��, Mridul Gautam, Ph.D., leads the articulation and implementation of a shared vision for research. Under his leadership, Research & Innovation provides high quality services and infrastructure to enable faculty, students and staff to excel in their research, scholarly and creative endeavors and to advance innovation and commercialization.

Lakshmi Kumar Matukumalli, program director, National Institute of General Medical Sciences (NIGMS)
Lakshmi Kumar Matukumalli, Ph.D., is a program director in the Networks and Development Programs Branch in the Division for Research Capacity Building, where he manages grants for the and programs. Matukumalli serves as the NIGMS program officer for the Nevada INBRE, including the supplemental award for Building Data Science Capacity providing support for the conference.

Juli Petereit, director of Nevada Bioinformatics Center
Juli Petereit, Ph.D. is a bioinformatics scientist, life science data scientist, or computational scientist, depending on who you ask. She supports researchers at the �Ƽ��Ӱ�ԭ�� and of the Mountain West IDeA Clinical and Translational Research-Infrastructure Network (CTR-IN) by providing state-of-the-art bioinformatics and (bio)statistics services for individual research projects. Petereit is the coordinator of this inaugural Data Science Conference.

Tshaka Cunningham, Ph.D., a distinguished molecular biologist and advocate for diversity in genomics, stands at the forefront of advancements in data science and data ethics. He is the co-founder and chief scientific officer of , a pioneering precision genomics biotechnology company in Rockville, Maryland. In the rapidly evolving landscape of data science and precision medicine, Cunningham's advocacy for diversity and data ethics positions him as a thought leader shaping the future of responsible and equitable healthcare practices.

A ten-minute break in the schedule.

A message from our conference sponsor, Amazon Web Services.

Presenters

Andrey Sarantsev, Ph.D., “Financial Simulator”
We present a stochastic financial simulator based on time series analysis. A portfolio of stocks and bonds is simulated for chosen time. There are options for regular withdrawals or contributions. A user can choose initial market conditions.

Emily Hand, Ph.D., “Understanding and Recognizing what Makes Faces Unique”
Automated face verification research focuses on improving a computer’s ability to say whether or not two face images belong to the same person. No part of this process involves truly understanding what a face looks like. Face verification systems are built on black box deep learning models, and so we cannot even really dissect them to determine which features are used for verification. The Machine Perception Lab works to develop explainable face verification systems using prominent facial features, aka caricatures.

Mark Lescroart, Ph.D., “Data-driven Visualization of Visual Selectivity in the Brain”
Different regions in the human visual system respond to different features of a stimulus. For example, some regions are known to respond to convex shapes, some to biological forms (faces and bodies), some to landscapes. In this talk, I will demonstrate a technique developed in my lab to investigate fine-grained response properties of the brain at the level of individual voxels (the smallest parcels of the brain measured by functional MRI). We model brain responses as a function of image features.

Kevin Shoemaker, Ph.D., “Data Science to Support Wildlife Conservation”
Simulation models of wildlife populations, known as Population Viability Analyses (PVA), are often used for decision-making in wildlife conservation and management—for instance, determining which species warrant protection under the U.S. Endangered Species Act (ESA). Currently, PVAs are often performed using ad hoc computer code that can be opaque and difficult to review. This lack of transparency and reproducibility has resulted in flawed models being used to support important conservation decisions. In my sabbatical year (2024-25 academic year) I will focus on starting a consortium for defining standards and best practices for transparent and reproducible PVA.

Stanislav Jabuka, Ph.D., “Machine Learning in Knot Theory”
Knot Theory is a branch of low-dimensional topology that studies how strings can be tied into knots in 3-dimensional space. Knots are of great importance in constructing 3- and 4-dimensional spaces, in understanding recombination of DNA molecules, and are even used in modern encryption algorithms. Even so, understanding when two knots are the same remains an elusively difficult problem. This talk will show how Machine Learning has recently been used to untangle some of the complexities of knots.

Jacqueline Walsh-Snow, Ph.D., “Can Artificial Intelligence be Leveraged for Human Assistive Vision?
This talk introduces a new research direction in my lab, in which we propose to explore whether emerging artificial intelligence (AI) systems that rely on large visual language models, such as newly released iterations of Generative Pre-trained Transformer (GPT), can identify objects and environments from images of naturalistic visual scenes, similarly to the way human observers do. The work will provide critical building blocks towards harnessing AI as a tool for assistive vision, ultimately leading to the development of powerful and effective technologies for patients with visual and cognitive deficits, thereby reducing the challenges associated with human disabilities.

Laura Smithers, Ph.D., “Datafication and Higher Education: Becoming More Than Our Optimizations”
Datafication is a term in the social studies of science that describes developments of the last 100 years that render human activity through data. We have come to understand ourselves as our data; e.g., we are A students, researchers with a smashing h-index, institutions that have earned performance-based funding. In this talk, I review my research on datafication’s entanglements with productivity logic in higher education, and how we might come to revalue the work of college in the era of data optimization.

A five-minute break in the schedule.

Panelists

Kathy Hanselman, Ph.D., is the assistant director of instructional design and educational technology in the Office of Digital Learning at the �Ƽ��Ӱ�ԭ��. She has worked in instructional design at the University for 14 years, advising faculty on best practices in course design and technology implementation. Her research focus is on engaging students in online spaces. Since ChatGPT burst onto the scene in November 2023, she has facilitated a number of faculty-focused workshops and trainings on AI in teaching and learning and has put AI to work in her own teaching practice.

Carlvin Paris is an IBM Americas data science business unit executive helping business and technology leaders to achieve their financial and operational performance goals and strategic business initiatives by leveraging IBM's leading data science and AI technology, world class business transformation services, and proven skills and experience to deliver AI for business.

Bridget Algee-Hewitt, Ph.D., is a computational biologist and anthropologist, whose research interrogates the hierarchies of identity ingrained within our immigration, medical, and legal systems and explores their relationships to displacement, poverty and violence among marginalized communities, especially in transborder spaces of the U.S. and across Latin America. She has also held positions in industry in R&D data science, hardware and software development, optimizing ML models, deracializing algorithms and business analytics and has led workstreams and divisions in big tech.

Nicole “Nikki” Lemire-Garlic, J.D., LL.M., Ph.D., is a lead faculty member in the �Ƽ��Ӱ�ԭ��'s justice management program. As a former court supervisor and practicing attorney, Lemire-Garlic brings a pragmatic approach to the classroom. Her work sits at the intersection of communication technologies, equity, and meaningful access to the courts. She uses data science techniques in her teaching and research.

Jeremy Tiedt, M.S., is the assistant dean of undergraduate student success in the College of Business at the �Ƽ��Ӱ�ԭ��. Tiedt has been working in higher education in a variety of roles since 2010, typically teaching entrepreneurship-based courses, and always enjoys meeting with students to discuss potential business ideas or ways to scale their current businesses.

Tolkyn Takishova, CFA is currently pursuing a graduate degree in information systems with an emphasis on data analytics in the College of Business at the �Ƽ��Ӱ�ԭ��. Last semester, Takishova authored a paper on the role of ChatGPT in higher education, based on a survey of faculty and students. Takishova has more than ten years of experience working in various government-led organizations in Kazakhstan. She holds a bachelor’s degree in economics from the University of Nottingham (Nottingham, England) and was a visiting researcher at the University of Southern California in Los Angeles.

An hour break in the schedule for a sandwich and salad bar lunch.

Bridget Algee-Hewitt, Ph.D., is a computational biologist and anthropologist, whose research interrogates the hierarchies of identity ingrained within our immigration, medical, and legal systems and explores their relationships to displacement, poverty and violence among marginalized communities, especially in transborder spaces of the U.S. and across Latin America. As a data scientist, she develops new computational techniques in ML, AI and NLP to decompose complex patterns of human biology and behavior at scale, building models that leverage genetic, skeletal, linguistic, life-history and social-context information to shed light on past and present histories. 

A ten-minute break in the schedule.

Moderator

Albert Gonzales, Ph.D., assistant professor of physiology and cell biology, is a member of the Data Science Initiative committee, and will be moderating the Showcase of Academic Programs.

Program representatives

Adam Csank, Ph.D., associate professor of geography, is representing the geographic information systems (GIS) and Sciences certificate program in the College of Science.

Amir Talaei-Khoei, Ph.D., associate professor of information systems, is representing the information systems bachelor’s and minor program in the College of Business.

Anna Panorska, Ph.D., professor of mathematics and statistics, is representing the statistics and data science master’s and doctoral program in the College of Science.

Lei Yang, Ph.D., associate professor of computer science and engineering, is representing the big data minor program in the College of Engineering.

Marta Elliott, Ph.D., professor of sociology, is representing the social research analytics bachelor’s, minor and certificate program in the College of Liberal Arts.

Praveen Durgamapudi, Ph.D., associate professor in the School of Public Health, will be representing the public health data management and analysis certificate program.

A five-minute break in the schedule.

Panelists

Kyra Stull, Ph.D., is a biological anthropologist and a board-certified forensic anthropologist in the Department of Anthropology at the �Ƽ��Ӱ�ԭ��. She primarily uses machine learning techniques to better understand the data used to capture human variation in growth and development and to build predictive and inferential models.

Christopher Golias, Ph.D., is a technology anthropologist, currently with Google, who has conducted applied research across various areas including retail, healthcare, indigenous rights, substance use, ecommerce, ecological design, machine learning, localization and information technology. He holds a doctoral degree in anthropology from the University of Pennsylvania.

Derek Ross is a senior solutions architect for Amazon Web Services (AWS) specializing in code quality and delivery velocity, with a profound focus on the DevOps software development lifecycle. With extensive experience in mobile technology, aviation engineering, logistics sales, and operations, Ross has consistently utilized technology to excel in various roles. Previously serving as a Special Forces medical sergeant, small business owner and sales associate, Ross brings a diverse set of experiences to his leadership, technical expertise and teamwork.

Matthew Myers serves as a cryptologic engagement officer for the National Security Agency (NSA) at the U.S. Strategic Command in Bellevue, Nebraska, overseeing access to compartmented intelligence reporting. He began his career in intelligence in 2003, joining the U.S. Navy as a cryptologic technician interpretive. After graduating from the Defense Language Institute (Spanish), he deployed three times, receiving the Navy and Marine Corps Medal twice. During most of his career, he has focused on illicit finance networks. He joined the NSA in 2015 to lead a team of intelligence analysts in developing anti-money-laundering strategies. Prior to working at U.S. Strategic Command, Myers served as the deputy cryptologic national intelligence officer for the western hemisphere.

Christopher Tong, Ph.D., has been a nonclinical and clinical biostatistician for more than 20 years, first in the pharmaceutical industry, and now in the federal government at the U.S. Department of Agriculture (USDA). He claims you can learn more about data science from Johannes Kepler, Andrew Carnegie and Marie Tharp, than from any statistics textbook.

Francesco Zuniga, Ph.D., is a senior data scientist at NV Energy, contributing to the Natural Disaster Protection Plan. He holds a statistics and data science doctoral degree from the �Ƽ��Ӱ�ԭ��. Francesco's research focuses on creating Machine Learning models for forecasting and classifying extreme events, extending across various domains, including climate, engineering, insurance and finance. Additionally, he holds a temporary faculty position at the �Ƽ��Ӱ�ԭ��, within the Department of Mathematics and Statistics.

A message from our conference sponsor, IBM.

Jeffrey S. Thompson, Ph.D., serves as the executive vice president and provost at the �Ƽ��Ӱ�ԭ��. He was appointed to the position on December 28, 2020. Thompson came to the role with extensive leadership and administrative expertise, having served as dean of the College of Science since 2008. In each of his administrative leadership roles, Thompson has remained devoted to advancing the reputation of the University with a focus on student success, well-being and belonging.

Sponsor booths open. Drinks and appetizers will be available.

Do Large Language Models Show Human-like Biases? Exploring Confidence-Competence Gap in AI
Authors: Aniket Singh, Bishal Lamichhane, Suman Devkota, Uttam Dhakal, Chandra Dhakal

Exploring the Role of the Occipital Face Area in Illusory Face Perception using TMS-EEG
Authors: Arianna Thoksakis, Edward Ester

Predicting Minority STEM Attrition: Leveraging Machine Learning for Retention Policy-making
Author: Md Ohiul Islam

Using R for Factor Analysis and Visualization of Multivariate Data: A Pilot Study of Parenting Values Among Nonreligious Parents in the United States
Authors: Jordan C. Reuter, Colleen I. Murray

Upscaling Reactive Transport Simulations with Deep Learning
Authors: Marc Berghouse, Rishi Parashar

Making Data Accessible to All: UNR's Research Data Services Team
Authors: Ashley Thompson, Carlos Ramirez-Reyes

Stats Chats
Authors: Ashley Thompson, Carlos Ramirez-Reyes

Findings from the Campus-wide Data Science Climate Survey and the Data Science Initiative
Authors: The Data Science Initiative, Nicole Falk-Smith

Presented by Amazon Web Services (AWS)

provides a comprehensive understanding of building ML use cases. Using SageMaker Studio Inetgrated Development Environment (IDE), participants will learn available feature engineering methods, built-in algorithms and steps for training, tuning and deploying ML models. The workshop guides participants in building their own model and demonstrates a "lift-and-shift" from on-premises machine learning (ML) workloads to Amazon SageMaker. It explores advanced concepts like Model Debugging, Monitoring, AutoML, and offers guidance on evaluating participants’ ML workload with the AWS ML Well-Architected lens. This workshop is accessible to anyone interested in AWS machine learning.

Presented by the �Ƽ��Ӱ�ԭ�� Cybersecurity Center

This workshop on safe data management provides an overview of the importance of handling data securely. Attendees will learn about the dangers of data breaches and how to best protect themselves, especially when working with health data and personally identifiable information. Acting as members of a fictitious research lab, attendees will work together to create a robust Data Safety Plan that shields their groundbreaking research from potential risks.

Presented by the Nevada Bioinformatics Center and Office of Digital Learning

ChatGPT and other generative AI are revolutionizing academia and changing the way we do things. This technology is constantly changing, with new functionality added at an astonishing pace. Come and join a roundtable discussion of what this new technology means for academia. We will cover an introduction to ChatGPT, the ethics of generative AI use, and how chatbots can be used in research and teaching. Bring your ideas, opinions, and experiences for an interesting and informative discussion.

Presented by the Nevada Bioinformatics Center and Pronghorn

Morning session: Introduction to Linux/Unix and HPC

In the first session of our comprehensive workshop, we will guide participants through the essential aspects of Linux/Unix and high-performance computing (HPC). We will cover fundamental concepts and commands that are crucial for participants to understand and navigate effectively within a Linux/Unix environment.

Session highlights:

• Directory structure of a Linux/Unix system
• Anatomy of a Linux command
• Understanding the concept of a shell
• Command line options and TAB completion
• Navigation techniques: Relative vs absolute pathing
• CONDA installation: A tool for user-level program installations
• Working with files using fundamental Linux commands
• Introduction to piping commands
• Covered commands: ls, cd, mkdir, mv, touch, tree, htop, nano, cat, less, wc, grep, rm, rmdir, history

Afternoon session: Utilizing Pronghorn and Interacting with SLURM Job Scheduler

The second half of the day will focus on practical applications, delving into the effective use of Pronghorn and interaction with the SLURM job scheduler while running automated analysis execution.

Session Highlights:

• Working with compressed data
• Utilizing screen commands
• Initiating your first SLURM job
• SLURM interactive session for testing
• Scripting for automated analysis execution
• Converting scripts into SBATCH scripts for Pronghorn
• Transferring data files to/from Pronghorn
• Singularity containers: Rstudio server use case
• Processing multiple samples in parallel with array SBATCH scripts

Presented by Professor Kyra Stull and the Nevada Bioinformatics Center

The R language, along with its amazing collection of libraries, is one of the most powerful tools you can use to tackle data analysis and to generate informative visualizations.

Morning session: Getting started with R programming

Discover the fundamentals of R programming and RStudio in this hands-on workshop, designed for beginners with no prior knowledge. Dive into essential data manipulation, organization, and exploration using base R and tidy format with provided example datasets. Covering R basics, including command line calculations, variable usage, and data structures, the workshop guides participants in loading, accessing, and summarizing data through statistics and plots. This session provides a practical introduction to programming with R, emphasizing its application in data science and research.

Afternoon session: Data visualization with R

This session will teach participants how to display their data appropriately using ggplot2, which is an R package dedicated to data visualization. We will cover visualizations for univariate, bivariate, and multivariate relationships and for both categorical and continuous data. This includes bar plots, histograms, boxplots, line plots, lollipops, scatterplots, bubble plots, correlations, and more.

Presented by Research Data Services (part of University Libraries)

Learn how to easily tackle grant funder requirements for a data sharing and management plan (NIH, NSF, and others by request). This workshop, aimed at faculty and researchers, will help you enhance your data handling skills and ensure your research meets the highest standards. Engage in a step-by-step process to create your DMS through hands-on exercises and gain a set of resources and tools for continuous support in data management planning. Feel free to bring your existing DMS for the peer-review session, offering constructive discussions and refinements.

Presented by the School of Business and Office of Digital Learning

This roundtable session invites undergraduate students to engage in an interactive exploration of the exciting possibilities and challenges presented by artificial intelligence in higher education. Through open discussions and collaborative brainstorming, participants will have the opportunity to share their perspectives on how AI can enrich their learning experiences, address academic needs, and shape the future of undergraduate education. Together, we will delve into real-world examples and potential applications of AI, fostering a student-centered conversation that empowers undergraduates to become active contributors in the advancement of AI technology in higher education. 

First hour: Tips and tricks for success

• Facilitated discussion by University faculty and staff on AI applications and advice for practical use for students
• Demonstrations showcasing successful strategies, tools, and prompts
• Sharing of resources, case studies, and best practices for integrating AI in undergraduate learning.
• Q&A sessions for participants

Second hour: Open discussion with students

• A student-led conversation where participants can openly share their experiences with AI
• Opportunities for students to discuss challenges, innovative uses, and personal stories related to AI in education
• Peer-to-peer knowledge exchange and brainstorming sessions
• Encouragement for students to propose new ideas or initiatives involving AI in their educational journey at the University

Presented by IBM

Learn how IBM watsonx unlocks the new potential of AI Assistants powered with generative AI and automation to drive productive employee and customer experiences.

Presented by Professor Theresa McKim in collaboration with the Nevada Bioinformatics Center

Python is a high-level, general-purpose, and open-source programming language. It is emerging as one of the most popular programming languages, both for scientific computing and general use. In this Python crash course, we will cover an overview of Python and programming fundamentals, and then describe how to use Python for data processing, analysis and visualization. At the end of this module, you will be able to:

• Understand the basic components of a Jupyter notebook
• Write and debug basic Python code
• Use functions, loops, conditional statements, and apply programming fundamentals applicable across computing languages
• Analyze a dataset using Python libraries built for data science
• Learn and discuss best practices for data visualization to communicate your results

Are you interested in government service? Federal executive branch roles? Top national positions? Security clearances? Join us for a round table discussion of questions such as:

• How could interested students take the first steps toward government service?
• What is the application process for internships? Full-time positions?
• What should students focus on in their studies to be competitive for these positions?
• What is the polygraph test like? Do I need to take it?
• What is a security clearance?

Curious about AWS cloud computing services? Interested in exploring additional training opportunities or overcoming challenges from past projects? Or if you're unsure where to start your cloud computing journey, join us for an engaging meet and greet with the AWS team!