A Bit About Us

New Mexico Big Data & Analytics Summit is a gathering of knowledge from industry and tech leaders. Together we aim to bring you the latest in all aspects of the digital world.



Charles Rath
Big Data and Analytics in the state of New Mexico

Charles R. Rath is the President and CEO of RS21, one of the fastest growing companies in America, created with the desire to help businesses and communities prepare for a dynamic and changing world.  As RS21’s CEO, Charles is a global thought leader in the field of data analytics and community resilience.  He was formerly the head of the Resilient Cities initiative at Sandia National Laboratories, and served the previous two Administrations in a variety of different leadership capacities in the resilience space.  Charles speaks globally on the future of technology, with a particular focus on next generation applications for data, analytics, and visualizations.  He holds a Master’s Degree in Public Policy from American University in Washington, D.C., and a Bachelors from the University of Missouri.

Lissa Moore
Los Alamos National Labs
Explainable Machine Learning Systems With Applications to Monitoring of Computing Systems

Elisabeth Moore (Lissa) is a research scientist in the High Performance Computing Division at Los Alamos National Laboratory and at the Ultrascale Systems Research Center. Her research focuses on machine learning within the high performance computing space, as well as methods for explainable machine learning, and computational social science. Lissa has previously held positions in LANL’s Center for Nonlinear Studies and MIT Lincoln Laboratory’s Human Language Technology group.

John Korbin and Matthew Smith
Sandia National Labs
Accelerated Modeling — Physics Constrained Machine Learning

Matthew Smith leads the Sandia Interdisciplinary Machine Learning Research (SIMLR) group, a multi-organization umbrella focused on leveraging the latest machine learning research in an effort to fulfill the mission needs of Sandia National Laboratories. His research has focused primarily on image classification, object detection, and 3D segmentation. He holds a BS and MS in Computer Science and has been working at Sandia Labs for 6 years.

Kevin Potter
Sandia National Labs
Modeling in an Imperfect World — Digital Twins and Batteries

Kevin Potter is a machine learning researcher on the Sandia Interdisciplinary machine learning research (SIMLR) team focused on finding ways to apply the latest machine learning research to the extensive portfolio of Sandia National Laboratories.  His research spans 2D/3D segmentation, fragment characterization, aerodynamic drag prediction, meshing with uncertainty and computer vision.  He holds a BS in Physics and has over 10 years of research and software engineering experience. Since joining Sandia in May, Kevin has contributed to several breakthroughs leading to multiple patent filings.

Garrett Kenyon
Los Alamos National Labs
Using the Brain as a Guide to More Causal Data Analysis

Dr. Garrett T. Kenyon received his Bachelor’s degree in Physics from the University of California, Santa Cruz and his Ph.D. in Physics from the University of Washington, Seattle. He has worked for over thirty years on problems involving various aspects of neural computation. He has recently started a research project with Prof. Ed Kim, Villanova, funded through the Intel Neural Research Community, to investigate robustness to adversarial examples using sparse coding algorithms implemented on the Loihi neuromorphic processor.

Austin Trent
Rogue ML
Deep Learning Revolutionizes Modern Document Processing

Austin Trent is currently a Program Manager at Rapid7, the developers of Metasploit. Before Rapid7, Austin spent 7 years at Sandia Labs as a Project Manager on big data and network analytics projects. He recently founded a startup called RogueML which is looking to bring process automation and machine learning to local Albuquerque companies.

Daniel Bowen
Silent Falcon
Using Unmanned Aircraft to Collect and Analyze Images

Daniel has been with Silent Falcon UAS for five years, working on hardware platform development and performing various types of data collection (photogrammetry, hyperspectral, multispectral, gas imaging, etc). Prior to Silent Falcon, he worked as a software developer at Sandia National Laboratories. He holds B.S. degrees in Mechanical Engineering, Computer Engineering, and Physics from the University of New Mexico.

Monty Vesselinov
Los Alamos National Labs
Unsupervised Machine Learning Applications

Monty Vesselinov’s expertise is in machine learning, big-data analytics, uncertainty quantification, risk assessments, optimal experimental design, decision support, high-performance and quantum computing. He is a co-inventor of a LANL patent on unsupervised machine learning (Source identification by non-negative matrix factorization combined with semi-supervised clustering; U.S. Patent US20180060758A1 Application). He is the leading developer of novel algorithms and codes for unsupervised machine learning at LANL https://github.com/TensorDecompositions. He has more than 150 publications referenced more than 1200 times with h-index 18 (https://goo.gl/8mU1jd).

Mark Fidel and Ben Mixon-Baca
Cyber Risk: Using Analytics to Accept, Avoid, Transfer, Mitigate and/or Exploit Cyber Risk

RiskSense co-founder Mark Fidel is responsible for advocating and growing RiskSense’s client portfolio in Arizona and New Mexico where RiskSense is headquartered. Mr. Fidel is also a licensed New Mexico attorney, and brings more than 16 years’ experience in law and litigation. Mr. Fidel earned an Executive Master of Business Administration degree from UNM and his law degree from the University of Denver – Sturm College of Law.

Ben Mixon-Baca is innovation team lead where he is responsible for creating novel product for RiskSense. He specializes in privacy, security, and statistics. He is a Ph.D. candidate at the University of New Mexico and holds both his Bachelor’s and Master’s in computer science from UNM. He has been a researcher in the security space for 7 years.

Darryl Ackley
New Mexico Tech
Analytics & Industrial IOT

CTO, Institute for Complex Additive Systems Analysis
Darryl Ackley is the Chief Technology Officer at the Institute for Complex Additive Systems Analysis (ICASA) at New Mexico Tech (NMT).  His duties include overseeing the development of enabling technologies from the basic and applied research mission for the institute, as well as in overseeing the technology strategy for the institute.  Prior to this role, Mr. Ackley served as New Mexico’s Chief Information Officer, and also as the Cabinet Secretary under Governor Susana Martinez for the state’s Department of Information Technology.  During that time, he also served a term as the President of the National Association for State CIO’s (NASCIO), and as a long-standing member on both the federal Public Safety Advisory Committee (PSAC) to FirstNet, and as a member of the DHS SAFECOM committee.  During his career, he has served as the Principal Investigator for a number of a number of federal grants totaling more than $60M in funding. Mr. Ackley has a B.S. and an M.S. in Computer Science from NMT.

Dr. Chris Lippett
University of New Mexico
Towards Realizing the Latent Potential of Remote Sensing

Dr Chris Lippitt is a faculty member in UNM’s Geography and Environmental Studies dept. His interests include Remote Sensing; Geographic Information Science; Time-Sensitive Geographic Information His current projects include “Development of a Remote Sensing Network for Time-sensitive Detection of Fine Scale Damage to Transportation Infrastructure” and “Collaborative Proposal: Optimization of Remote Sensing Networks for Time-sensitive Detection of Fine Scale Damage to Critical Infrastructure”

Karla Melendez and Nathan Friedman
State of New Mexico Department of Workforce Solutions
Using Big Data to Identify Misinformation and Save Money

DWS Power Point Presentation

Nathan Friedman is a senior economist with the New Mexico Department of Workforce Solutions. He works on the Local Area Unemployment Statistics program, and he’s been the analyst for the department’s behavioral economics and analytics initiatives for the past three years.

Karla Meléndez is the Policy Analyst for the New Mexico Department of Workforce Solutions (NMDWS). Ms. Meléndez began her public service career with NMDWS in 2014 where she has since provided research and analysis support. She currently serves as Team Lead for the Improper Payment Prevention Initiative (IPPI) and Employer Misclassification Predictive Analytics (EMPA) Oversight Team.  


Adolfo Mendez and Paul Crickard
State of New Mexico District Attorney
Impact Prosecution

Paul Crickard is the CIO at the 2nd Judicial District Attorney’s Office where he works to implement technical solutions to the modernization of law while also keeping the lights on. He holds a Masters Degree in Political Science from Utah State University and is the Author of Leaflet.js Essentials and Mastering Geospatial Analysis with Python. He came to the District Attorney’s Office after 5 years at the City of Albuquerque working in IT for the Albuquerque Police Department and Department of Municipal Development. 

Adolfo Mendez, Chief of Policy and Planning, serves at New Mexico’s 2nd Judicial District Attorney’s Office. Having started his tenure along with the election of District Attorney Raul Torrez, he is focused on modernizing the practice of law and improving workflow processes in the office. Adolfo is fueled by the mission of finding justice for victims of crime. He works toward implementing data informed decision making to swiftly interrupt criminal activity. Adolfo earned his BA degree from Stanford University, an MTS from Harvard University, and law degree from UNM