Dr. Hassan Khaniani is an Assistant Professor at the Petroleum Recovery Research Center (PRRC) and the Department of Mineral Engineering at New Mexico Tech. He holds B.Sc. and M.Sc. degrees in Petroleum Exploration Engineering and earned his Ph.D. in Exploration Geophysics from the University of Calgary. Prior to joining New Mexico Tech, he worked in research and development (R&D) within the energy industry, including positions with Nexen Energy, Suncor Energy, and Absolute Imaging, where he contributed to the development of geophysical technologies and computational methods for subsurface characterization and imaging. He also conducted academic research as a postdoctoral researcher at the University of Calgary, focusing on advanced geophysical imaging and subsurface characterization.

Dr. Khaniani’s research integrates geophysics, mineral engineering, advanced sensing, robotics, and artificial intelligence to address challenges in subsurface characterization, mineral exploration, ground control, and underground safety. His work focuses on developing and applying seismic and ultrasonic sensing, distributed fiber-optic sensing, embedded sensor systems, geophysical imaging, and AI-enabled data analysis for detecting and characterizing geological structures, fractures, underground voids, and changes in rock and ground conditions. A major component of his research involves integrating geophysical and environmental sensing with robotic and autonomous platforms, including ground robots and unmanned aerial systems. Through projects supported by agencies including CDC-NIOSH, his research advances intelligent monitoring, digital-twin, and autonomous sensing technologies for mine safety, emergency response, ground characterization, and situational awareness in hazardous underground environments. His broader research program bridges sensor and electronics development, laboratory experimentation, field-scale measurements, computational modeling, and artificial intelligence to develop practical technologies for mining, energy, subsurface exploration, and critical infrastructure monitoring.

Vanessa Viterbo Christopherson is a mining engineer who earned her B.S. in Mining Engineering from the Federal University of Minas Gerais (UFMG), Brazil. She holds an M.S. in Mineral Engineering with a specialization in Geotechnical and Geomechanical Engineering and is currently a Ph.D. candidate at the New Mexico Institute of Mining and Technology (New Mexico Tech). Her career began in academic research, contributing to publications on inverse problem solving and computational methods before transitioning to the mining industry. Since 2002, she has built an international career spanning Brazil, Peru, Chile, and the United States. Since joining Freeport-McMoRan in 2007, Vanessa has held leadership roles of increasing responsibility across engineering, geology, and mine operations, including Manager of Engineering and Geology and Mine Manager.

Her PhD research integrates these two paths together, using equipment telemetry and interpretable machine learning to identify early indicators of human fatigue to improve safety and operational performance in mining.

Richard is a PhD candidate and research assistant working in the Mine Automation Laboratory in the Mineral Engineering Department at the New Mexico Institute of Mining and Technology.

His research focuses on developing robust emergency evacuation systems that remain reliable under sensor failure, delayed alarms, and uncertainty forecasts, while ensuring evacuation decisions are actionable and interpretable in underground coal mining operations. 

I am a Graduate Research Assistant and M.Sc. student in Mechatronics & Intelligent Systems at NMT. With a B.Eng. in Electrical/Electronic Engineering background, I focus on intelligent sensor integration for real-world engineering systems. My current work explores ultrasonic sensing for structural assessment and non-destructive testing, combining instrumentation design with embedded data acquisition and signal analysis. I am particularly motivated by problems where performance depends on both hardware and algorithms, designing robust front-ends, managing noise, and validating detection performance through structured experiments. Beyond ultrasonics, I am interested in autonomous systems, robotics, and distributed sensing/IoT architectures for monitoring and inspection.

I am a graduate student in Mining Engineering at New Mexico Tech, specializing in

mine safety systems, real-time hazard mitigation, and intelligent pathfinding for

emergency scenarios in underground environments. My research focuses on the

development of predictive models using Graph Neural Networks (GNNs) integrated with

Unity-based digital twins to support miner decision-making under hazardous conditions.

Through my current project, Canary, I have built a system that combines machine

learning, sensor-driven data interpretation, and 3D simulation to identify and visualize

optimal escape routes in the event of toxic gas leaks or structural compromise. The

project leverages tools such as Python, PyTorch Geometric, NetworkX, and Unity to

dynamically interpret survival probabilities based on live environmental conditions. The

system is designed with both educational and operational applications in mind, including

use cases for command center oversight and training environments.

In addition to my academic and technical work, I have been an active member of

the New Mexico Tech Rugby Club, where I’ve developed teamwork, leadership, and time

management skills that directly support my collaborative engineering efforts. My

interdisciplinary approach combines field experience, computational modeling, and a

strong focus on human-centered safety solutions within the mining sector.

Simon is graduated in mining and geotechnical engineer specializing in mine safety, geomechanics, and underground emergency evacuation. He earned an M.S. in Mineral Engineering with a specialization in Geotechnical and Geomechanical Engineering from New Mexico Tech. His graduate research focused on optimizing emergency evacuation routes in underground mines using dynamic network-flow methods and mine-fire simulations. He has also contributed to research on mine self-escape and rescue practices and currently works with Freeport-McMoRan.