Invited Speakers and Panelists
Jonathan Ashdown
Air Force Research Laboratory
▼ Talk Details
“Tactical Edge Computing: Research Challenges and Opportunities“
Abstract
A plethora of tactical mobile devices require continuous, real-time, streamlined execution of computation-heavy artificial intelligence and/or machine learning (AI/ML) tasks executed at the tactical edge. For example, in addition to leveraging AI/ML for mission-specific surveillance and tracking operations, unmanned autonomous (air or ground) vehicles (UXVs) require constant edge computing support to detect sudden obstacles due to adverse weather conditions, loss of power, and/or GPS connectivity. Edge-assisted AI/ML algorithms will also be used to achieve real-time situational awareness of the radio frequency (RF) spectrum and other networking-related information across time, frequency, and devices. In addition to securing AI/ML algorithms against intentional and unintentional interference, tactical edge computing will require networking with low probability of interception/detection (LPI/D) to guarantee seamless and continuous operations in congested and contested environments. In other words, tactical edge computing systems need to satisfy Reliable, Effective, Efficient LPI/PD guarantees (REEL). Existing wireless edge computing paradigms were designed for civilian scenarios and are thus incapable of meeting all the critical REEL constraints simultaneously. Hence, clean-slate approaches encompassing new computing and communications paradigms may be needed to address REEL constraints. This talk will discuss research challenges and opportunities related to meeting REEL constraints at the tactical edge.
Speaker Biography
Dr. Jonathan Ashdown was born in Niskayuna, NY, USA. He received the B.S., M.S., and Ph.D. degrees from Rensselaer Polytechnic Institute, Troy, NY, USA, in 2006, 2008, and 2012, respectively, all in electrical engineering. His Ph.D. dissertation was on a high-rate ultrasonic through-wall communication system using MIMO-OFDM in conjunction with interference mitigation techniques. In 2012, he was a recipient of the Best Unclassified Paper Award at the IEEE Military Communications Conference. From 2012 to 2015, he worked as an electronics engineer with the Department of Defense (DoD), Naval Information Warfare Center Atlantic, Charleston, SC, USA where he was involved in several basic and applied research projects for the U.S. Navy, mainly in the area of software defined radio and underwater communications. In 2015, he transferred within DoD to the Air Force Research Laboratory, Rome, NY, USA, where he serves as senior electronics engineer and is involved in the research and development of advanced emerging communications and networking technologies for the U.S. Air Force.
Manish Bhattarai
Los Alamos National Laboratory
▼ Talk Details
“Harnessing Unsupervised Learning to Mitigate LLM Challenges in Scientific Discovery”
Abstract
Generative AI and Large Language Models (LLMs) have revolutionized scientific research, boosting productivity, accelerating discoveries, and enhancing efficiency. However, significant challenges persist: LLMs frequently generate “hallucinations”—plausible yet inaccurate information—and are susceptible to adversarial attacks that can spread toxic content and misinformation. Their high computational demands also raise questions of practicality and accessibility.
In this talk, I will present our novel solution that leverages Unsupervised Learning, focusing on Matrix and Tensor factorizations coupled with denoising diffusion models. First, I’ll demonstrate how our approach uses contrastive learning to refine representations, effectively minimizing hallucinations and increasing reliability in tasks like code translation and information retrieval. I’ll also illustrate how our tensor methods compress LLMs, enhancing performance and making deployment feasible on resource-constrained hardware. Furthermore, I’ll show how combining Tensor factorizations with denoising diffusion strengthens model defenses against adversarial attacks, improving robustness in multimodal applications. Finally, I’ll emphasize the critical role of High-Performance Computing (HPC) in scaling these advancements, enabling LLMs to tackle large-scale scientific challenges.
Speaker Biography
Manish Bhattarai is a Staff Scientist at Los Alamos National Laboratory with expertise in generative AI, natural language processing, reinforcement learning, high-performance computing and tensor methods. He leads multiple projects focused on enhancing explainability, adversarial robustness, and efficient fine-tuning of large language models. Manish developed prominent HPC libraries for tensor methods which have enabled the decomposition of datasets up to an exabyte scale on Oak Ridge National Lab’s Summit cluster, comprising 25,000 GPUs. This work contributed to his team’s recognition with the prestigious 2021 R&D 100 Award. At LANL, Manish and his team employ deep learning frameworks and tensor methods to solve complex problems across material science, NLP, chemistry, and biology, working with multimodal datasets that include images, text, DNA sequences, molecular structures, and signal-based data. A dedicated mentor, he has guided over 20 students through programs like the ISTI Advanced Machine Learning School, Cybersecurity School, NSF-MSGI, and various GRA initiatives, helping students advance their expertise in Generative AI, reinforcement learning, and tensor methods.
Eric Breckenfeld
NVIDIA
▼ Talk Details
“Revolutionizing Semiconductor Manufacturing with Digital Twins and IoT”
Abstract
The enormous complexity of semiconductor manufacturing at the device, process, and facility levels creates serious practical barriers to optimization, experimentation, and in some cases commercialization. In this talk, we will explore the interplay between digital simulation, IoT data collection, and physical assets to produce high fidelity digital twins. We will also discuss recent funding announcements from the CHIPS R&D Office (CRDO) in support of a Manufacturing USA Institute focused on semiconductor process digital twins.
Speaker Biography
Eric Breckenfeld serves as NVIDIA’s Director of Technology Policy, where he helps educate decision makers from the administration and congress in the areas of semiconductor design and supply chains as well as AI technology. Prior to this, Eric held a role at the Semiconductor Industry Association, DARPA MTO, and the White House’s National Nanotechnology Initiative. He received his B.S. in Physics from the University of Wisconsin-Madison and his Ph.D. in Materials Science and Engineering from the University of Illinois Urbana-Champaign.
Massi Corba
Draper Laboratory
Eric Dean
Rohde & Schwarz USA, Inc.
Robert Denz
Riverside Research
▼ Talk Details
“Mind the Gap: Vulnerabilities and Opportunities for Cyber R&D at the Edge”
Abstract
Commercial or defense systems are often developed first to meet a mission or customer need. Security of many of these systems is often developed at a component level by each components product team. The product teams often maintain robust security for their component within the system, but security gaps begin to form when the complete system is assembled. Adversaries will seek to exploit these gaps in the overall system design as they look for the path of least resistance to achieve their goals. These adversaries do not limit themselves to one exploitation domain and will often pivot across domains in their execution of an attack. To guard against these multi-domain threats, we as security practitioners and researchers need to work together to adjust our world view on the larger system of system security challenge that we face. This presentation begins the process of enumerating some of these gaps, how gaps came into existence, and provides potential research avenues to address them.
Speaker Biography
Dr. Robert Denz is an experienced technology executive and strategic leader at Riverside Research. As the Vice President of The Open Innovation Center, he leads a research and development business unit focused on critical technology areas such as Cyber Security, Artificial Intelligence & Machine Learning, Radio Frequency, and Optics. These cross-functional teams drive innovation and deliver impactful solutions for national security, leveraging Riverside Research’s open innovation model to foster collaboration and accelerate the development of cutting-edge technologies.
Dr. Denz earned a Ph.D. in Computer Engineering from Dartmouth College and a B.S. in Computer Engineering and Computer Science from Rensselaer Polytechnic Institute. His academic background, coupled with his industry experience, provides him with a strong foundation for leading technical teams and driving innovation.
Dr. Denz has co-authored numerous publications in security, virtualization, and operating systems. His contributions to the field of cyber security have been significant, and he continues to mentor others to make an impact on the national security research base.
Darnell Diggs
Air Force Research Laboratory
▼ Talk Details
“Air Force Research Laboratory Munitions Directorate (RW) Overview”
Abstract
Speaker Biography
Nij Dorairaj
Intel
Jesse Dunietz
NIST
▼ Talk Details
“The NIST AI Risk Management Framework and Ongoing NIST Work on AI“
Abstract
In January 2023, NIST released the AI Risk Management Framework (AI RMF), a set of voluntary guidelines for governing, mapping, managing, and measuring risks from AI systems. This talk will review the motivation behind the framework, the outcomes it seeks to help AI actors achieve, and the four “organizational functions” that encapsulate the framework’s core recommendations for risk management. Tools to assist with implementing the framework will also be discussed. Finally, the talk will cover recent NIST follow-on work, much of it under the October 2023 executive order on AI. This work builds on the AI RMF with additional guidelines, research, and other activities on topics such as risk management and secure software development for generative AI, technical standards for AI, and risk and impact assessment.
Speaker Biography
Jesse Dunietz is a computer scientist at NIST’s AI Innovation Lab, where he leads international engagements on AI, technical assistance on AI policy, and AI standards work. He holds a bachelor’s from MIT and a Ph.D. from Carnegie Mellon University (CMU), both in computer science. His technical background includes research in natural language processing and linguistic annotation at CMU, MIT, Google, and a small startup. He has also trained hundreds of researchers in science communication and written many articles and video scripts for mass media outlets. Prior to his current position, he was a AAAS Science and Technology Policy Fellow at the U.S. Department of State, where he led the Department’s international work on AI and human rights.
Ken Gall
restor3d
▼ Talk Details
“Scaling personalized orthopedic implants using automation, AI, and 3D printing”
Abstract
In this talk we will examine the development of coupled digital design and production to scale the costs and effectiveness of implants designed off of the anatomy of individual patients. Topics to be covered include AI based design and image segmentation, CAD based design automation, and 3D printing of digital materials. The motivation for this approach will be provided based on a large dataset of human CT scans in the knee.
Speaker Biography
Ken Gall is a tenured Professor of Mechanical Engineering and Materials Science and Orthopedic Surgery at Duke University and an active entrepreneur in the medical device space. He received his BS, MS and PhD from the University of Illinois in Mechanical Engineering. His expertise is in engineering design and materials science with a particular emphasis on the creation, modification, understanding, and commercialization of synthetic biomaterials. On the academic side his research has been cited approximately 27,000 times with an H-index of 87. He has been a co-founder of 10 companies and a director of 15 different early stage ventures. To date, his startup companies have been acquired through a series of five different transactions: Vertera (Nuvasive), MedShape (Conmed), MedShape (Enovis), Kinos (restor3d), and InnAVasc (W. L. Gore). One of his companies (restor3d) has acquired three other businesses: Kinos (private), Nushoco (private), and Conformis (public) and since spinning out of Duke in 2017, is a private orthopedic company with over 400 employees.
John Hallman
Siemens
Uma Jha
L3Harris
▼ Talk Details
“IoT in Aerospace and Defense Environment”
Abstract
The IoT devices are becoming pervasive across aerospace and defense platforms and domains, which allows for the connectivity across the systems, platforms, and domains. The requirements for these applications are quite different. This talk would discuss the issues and possible mitigation ideas. The topics being tackled include Security and cybersecurity challenges, Supply chain issues, Reliability and performance, Self-management and self-healing, Autonomy, limited Connectivity, Scalability, Power/Energy, Regulatory and compliance challenges, spoofing, anti-repudiation, Life cycle maintenance issues.
Speaker Biography
Dr. Uma S. Jha is a Senior Fellow at L3 Harris Technologies. Prior to L3 Harris, he served as Technical Fellow at Raytheon & Boeing, Director at Qualcomm and many other fortune 100 companies, as well as high profile start-ups in various executive roles. As a Director of Product Management at Qualcomm, a fabless semiconductor company specializing in wireless SOC development, he managed multi-billion dollar chip business spanning tier-1 OEM accounts globally. At Morphics, a startup in Silicon Valley, he led the development of waveform agnostic signal processing core, a key technology enabler for multimode/multiband smartphones for cellular industry. The company was acquired by Infineon and the IP developed by his team was used in the 1st Apple iPhone, which changed the cellular landscape forever. Dr. Jha has 30 patents in the consumer electronics domain and actively participates at industry consortia, standards fora, and academia as a keynote speaker, panelist, and advisor. He has published more than 40 papers and is the primary author of a book on next generation broadband communication systems. He is a Fellow of IEEE and AI IA Fellow and serves on Technical Program Committee (TPC) for IEEE and International conferences. He has organized an international conference, WPMC 2006, as the General Chair where more than 600 people participated from 43 countries. Dr. Jha received a joint Ph.D. from University of Southern California, Los Angeles, California and Aalborg University, Denmark, a MSEE from California State University, and BSEE from BIT Sindri. Additionally he received an Engineering Management certification from California Institute of Technology, USA.
Shovan Maity
Ixana
▼ Talk Details
“Energy Efficient, Secure Internet of Body (IoB) Using Electro Quasistatic Human Body Communication (EQS-HBC)”
Abstract
Decades of scaling in semiconductor technology has resulted in a drastic reduction in the cost and size of unit computing. This has enabled computing capabilities in small form factor wearable and implantable devices. These devices communicate with each other to form a network around the body, called as the Internet of Body (IoB). Wireless communication protocols such as Bluetooth, Zigbee, Wifi is the commonly used method of communication among these devices. However, the human body can be used as the communication medium by utilizing its electrical conductivity property. This has given rise to Human Body Communication (HBC), which provides higher energy efficiency and enhanced security compared to over the air radio wave communication enabling applications like remote health monitoring, secure authentication, video transfer for augmented reality devices. These energy efficiency and security benefits are enhanced when we operate in the electro quasistatic regime using a technique called Electro Quasistatic Human Body Communication (EQS-HBC).
In this talk we will discuss about the recent developments on the modeling of the human body as a communication channel, the recent developments in energy efficient integrated circuit design for EQS-HBC, the security benefits of EQS-HBC and its theoretical origins and the new Human Computer interaction modalities that can be enabled through the strictly touch based communication property of EQS-HBC. EQS-HBC enables communication up to 30Mbps data rate at an energy efficiency of <10 pj/bit which is 100x more efficient compared to wireless communication protocols such as Bluetooth. EQS-HBC also enables signals to be confined within 15 cm of the body making it hard for a malicious attacker to snoop the ongoing signal transmission, increasing the private space of communication significantly compared to traditional wireless protocols. All these benefits make EQS-HBC a promising alternative to traditional wireless communication as the medium of choice for the Internet of Body.
Speaker Biography
Shovan Maity received the B.E. degree from Jadavpur University, Kolkata, India, in 2012, the M.Tech. degree in electrical engineering from IIT Bombay, Mumbai, India, in 2014, and the Ph.D. degree in electrical engineering from Purdue University, West Lafayette, IN, USA, in 2019. He worked as an Analog Design Engineer with Intel, Bengaluru, India, from 2014 to 2016 and a Senior Circuit Design Engineer with Qualcomm, San Diego, CA, USA from 2019-2021. Currently he is a Co-founder and Head of Research at Ixana, a Purdue University spin-off startup working on developing low power communication in wearable devices. His research interests lie in the area of mixed-signal circuits and systems for the Internet of Things, and biomedical and security applications.
Dr. Maity received the Institute Silver Medal from IIT Bombay in 2014, the IEEE HOST Best Student Paper Award in 2017, the CICC 2019 Best Paper Award.
Naren V. Masna
Cadence Design Systems
Jon Mellott
Mercury Systems
Vinod Mishra
DEVCOM Army Research Laboratory
▼ Talk Details
“Recent Progress in Supervised Learning”
Abstract
Supervised Learning (SL) is one of the three classical areas of machine learning, the other two being Unsupervised and Reinforcement learnings. One of the important problems in SL is dealing with the large dimensions of the data. In the present talk I will highlight the progress made in solving this problem using a new technique called Subspace Learning Machne (SLM).
SLM is a new idea for reducing the data dimensions to manageable proportions without affecting the ability to classify them correctly. We will present both the theoretical aspects of this approach and some relevant applications as well.
Speaker Biography
Vinod Mishra received his Ph.D. in Physics from State University of New York (SUNY) at Stony Brook in 1983, with area of focus in Theoretical Nuclear Physics. He was a post-doctoral researcher at various universities and research institutions before joining Lucent Technology Bell Labs, where he worked in many areas of Optical and Wireless Networking. Later he came to Defense Information Systems Agency (DISA) and focused on advanced networking technologies. Currently he is a Research Scientist at DEVCOM Army Research Laboratory (ARL) conducting research in Software Defined Networking, Dynamic Optical Networking, Quantum Communication, and AI/ML.
Robinson Pino
U.S. Department of Energy
▼ Talk Details
“Emerging Computing Technologies for Advance Scientific Computing Research”
Abstract
Advances in emerging computing technologies offers potentially new opportunities and capabilities for the advancement of the U.S. Department of Energy (DOE) and Office of Science mission. The DOE Office of Science operates scientific infrastructure, supporting some of the nation’s most advanced intellectual discoveries, spanning the country and including 30 world-class user facilities from supercomputers to accelerators. This talk will present a brief overview of research and development activities in the areas of Artificial Intelligence, Neuromorphic Computing, Microelectronics, and Advanced Wireless at the DOE, Office of Science, Advanced Scientific Computing Research program office.
Speaker Biography
Dr. Robinson Pino is a Program Manager for the Advanced Scientific Computing Research (ASCR) program office in the U.S. Department of Energy’s (DOE) Office of Science, previous Senior Advisor to the CHIPS Program Office in the U.S. Department of Commerce (DOC). Dr. Pino focuses on basic research and development efforts for high performance computing, edge computing, neuromorphic computing, artificial intelligence, advanced wireless, microelectronics, and their applications. Dr. Pino has a Ph.D. and M.Sc. degrees in Electrical Engineering with honors from Rensselaer Polytechnic Institute and a B.E. in Electrical Engineering with honors, summa cum laude, from the City University of New York, City College. Dr. Pino is the recipient of numerous awards and professional distinctions; has published over 55 technical papers and reports, including four books; and holds nine patents.
Arnab Raha
Intel
▼ Talk Details
“Synergy at Scale: Transforming AIoT with Approximate Systems“
Abstract
As IoT and AI continue to reshape the tech landscape, the challenge of performing energy-efficient inference on edge devices takes center stage. This talk introduces Approximate Systems, a groundbreaking methodology that synergizes approximations across multiple subsystems in deep neural network-based inference systems, delivering unmatched energy savings compared to isolated optimizations. From its roots in classical machine learning to cutting-edge multisensory and multimodal platforms, the evolution of Approximate Systems paves the way for energy-scalable IoT designs. Real-world demonstrations will showcase how this methodology transforms IoT scenarios, from single-device deployments to distributed multimodal systems, unlocking unprecedented efficiency across the IoT spectrum. Join us to explore the future of scalable, energy-efficient IoT design!
Speaker Biography
Dr. Arnab Raha, received a Ph.D. degree in Electrical and Computer Engineering from Purdue University, West Lafayette, IN, USA, in 2017. He is currently a Senior Research Scientist with the Advanced Architecture Research Group, Intel Client AI, Santa Clara, CA. He is one of the lead architects of Intel’s Neural Processing Unit (NPU) IP that forms the core of Intel’s latest Core Ultra-based AIPC systems. In addition to multiple best paper nominations, he has received two Best Paper Awards at the IEEE International Conference on VLSI Design (VLSID) in 2016 and the IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH) in 2019 and the Best Design Award at the IEEE International Conference on VLSI Design (VLSID) in 2015. He is also the recipient of multiple Intel Division/Group Recognition Awards and has also received 10 Intel High-5 Patent Awards for his work on low power AI inference accelerators at Intel Corporation. Dr. Raha also received the SRC Mahboob Khan Outstanding Industry Liaison Award in 2022. He has authored more than 90 papers in reputed conferences and journals in the field of embedded systems and VLSI design and have more than 60 US patent applications issued or pending.
Doug Recker
Duos Edge AI
Lynn Ren
RTX Technology Research Center
▼ Talk Details
“IoT Security for Energy Systems”
Abstract
Energy systems, especially smart grids, are recognized as one of the 6 major research fields on smart city technologies. New technologies such as smart meters, demand side flexibility and distributed energy resources are designed and deployed to improve the operations and the efficacy of the smart grid; nevertheless there is a cost associated with these technologies: increased system exposure and expanded attack surface. Example attacks include an attacker who potentially takes control of a large number of smart IoT appliances and commands them to simultaneously perform a disconnect and reconnect. Grid operators currently lack the visibility to detect and quickly respond to attacks emerging from the grid-edge systems. In this talk, we present two technologies: INGRESS and CYDRES, to enable grid-edge cyber monitoring through data-driven methods leveraging physical measurements and network traffic data. INGRESS: Integration of Green Renewable Energy Resources with Electric Power Systems and Buildings (INGRESS), is an inline security device that uses advanced analytics to autonomously learn and develop models of the controlled grid-edge assets by leveraging various classes of data streams. CYDRES: Securing Grid-interactive Efficient Buildings (GEB) through Cyber Defense and Resilient System (CYDRES), is a real-time advanced building resilient platform, aims to enhance the cyber-attack-immune capabilities of buildings through multi-layered prevention, detection, and adaptation mechanisms.
Speaker Biography
Dr. Lingyu Ren is a Principal Research Engineer in Cyber-Physical Security at the RTX Technology Research Center. Her research interest is on cyber-physical security for industrial control systems. She’s PI on multiple DOE sponsored research projects to develop novel cyber security solutions for smart buildings and power systems. She is a certified ethical hacker with InfoSec and has ISA/IEC 62443 Certificate for cyber security in Industrial Control System.
Viktor Reshniak
Oak Ridge National Laboratory
▼ Talk Details
“Integrated Edge-to-Exascale Workflow for Real-Time Steering in Neutron Scattering Experiments“
Abstract
We introduce a computational framework that integrates artificial intelligence (AI), machine learning (ML), and high-performance computing (HPC) to enable real-time steering of neutron scattering experiments using an edge-to-exascale workflow. Focusing on time-of-flight (TOF) neutron event data at the Spallation Neutron Source (SNS), our approach combines temporal processing of four-dimensional (4D) neutron event data with predictive modeling for multidimensional crystallography. The system incorporates edge computing for rapid data preprocessing and exascale computing via the Frontier supercomputer for large-scale AI model training, enabling adaptive, data-driven decisions during experiments. This framework optimizes neutron beam time, improves experimental accuracy, and lays the foundation for automation in neutron scattering.
Speaker Biography
I am a staff mathematician in the Data Analysis and Machine Learning Group at Oak Ridge National Laboratory.
I received my Ph.D. in Computational Science from Middle Tennessee State University (MTSU) under the supervision of professors Yuri Melnikov and Abdul Khaliq. My work at MTSU was in the field of computational partial differential equations and numerical integration of stiff stochastic systems. After graduating from MTSU in 2017 I started a postdoctoral position in the CAM group at ORNL where I worked with Clayton Webster on several projects in compressed sensing, image processing and machine learning.
My current research at ORNL is primarily focused on the design and analysis of new robust machine learning and image processing algorithms.
Steve Trimberger
The Trimberger Family Foundation
▼ Talk Details
“Changing the World with Technology”
Abstract
This talk deals with how technology matures to enable applications. As exciting as new technologies are, they do not change the world, at least not directly. It is the innovative application of those technologies that changes the world. The applications require a threshold of capability, often in multiple dimensions. They also often require a little “something extra.” What does this mean for the technologies of AI and IoT? What improvements are needed to enable these technologies to change the world?
Speaker Biography
Dr. Steve Trimberger is a member of the National Academy of Engineering, Fellow of the ACM, Fellow of the IEEE, and recipient of the 2018 IEEE Don Pederson Award for outstanding contributions to solid state circuits. He is a member of the Board of Governors of the National Space Society and Board of Directors of the SETI Institute.
From 1988 until 2017, Dr. Trimberger was employed at Xilinx. In his career at Xilinx, he touched every aspect of Field Programmable Gate Array (FPGA) technology, including EDA software for the XC4000 and architecture definition of the XC4000X. He designed the first FPGA serdes I/O circuits. He designed the bitstream security functions in the Xilinx Virtex and subsequent families of FPGAs. He led the group that developed the first die-stacked 3D FPGA prototype and supply chain at Xilinx, ushering in the era of “chiplets”. A named inventor on approximately 250 US patents, his innovations appear today in nearly all commercial FPGA devices.
After retiring from Xilinx, Dr. Trimberger was a Program Manager in the Microelectronics Technology Office at DARPA, where he led activities in high-performance semiconductor technology and systems. He is currently Professor of Practice at the University of Florida.
Dr. Trimberger is founder and president of the Trimberger Family Foundation, a non-profit organization with charitable programs in several areas.
Matthew Vanture
The Whiting-Turner Contracting Company
▼ Talk Details
“Building Smarter: Integrating IoT into Construction for Enhanced Productivity and Safety”
Abstract
The construction industry stands on the brink of a technological revolution, driven by the Internet of Things (IoT). This talk will explore the transformative potential of IoT technologies in construction, focusing on real-world applications that enhance operational efficiency, worker safety, and project management. We’ll discuss the implementation of IoT solutions and examine their impact on reducing costs, improving timelines, and ensuring compliance with safety standards. The session will also cover the challenges of adopting such technologies, including data security, interoperability, and the cultural shifts required within traditional construction environments.
Speaker Biography
Matthew Vanture is a seasoned Construction Technologist and VDC Manager at Whiting-Turner, specializing in integrating innovative technologies into construction practices. With a background in HVAC equipment procurement and installation for complex facilities in the education, healthcare, and pharmaceutical sectors, Matthew brings a wealth of practical experience to his role. He is a passionate advocate for the adoption of IoT in construction, aiming to drive efficiency and enhance project outcomes through cutting-edge solutions. Outside of his professional pursuits, Matthew is a devoted father and avid sailor, bringing the same enthusiasm and leadership to his family and recreational activities.
Maggie Wigness
DEVCOM Army Research Laboratory
▼ Talk Details
“Internet of Things in the Battlefield”
Abstract
The future battlefield will to be more data-centric than ever before, and the underlying “things” networked together will need to be strategically used to provide the underlying analytics to support decision making for command and control. This talk will discuss the concept of the Internet of Battlefield Things (IoBT) and some important factors that distinguish it from traditional IoT research. Several science and technology gaps in the IoBT space will be discussed, and example scientific innovations and research directions from ARL’s IoBT Collaborative Research Alliance will be presented.
Speaker Biography
Maggie Wigness is a Senior Computer Scientist at the U.S. Army Combat Capabilities Development Command (DEVCOM) Army Research Laboratory (ARL) in the Science for Intelligent Systems Division. She earned her PhD in Computer Science from Colorado State University in 2015, and since joining ARL has led and shaped research directions in many ARL collaborative research alliances (CRAs). She currently serves at the Collaborative Alliance Manager for the Internet of Battlefield Things CRA, where she oversees a portfolio of research focused on the underlying science of intelligent sensing, computation and communication in dynamic, large-scale, and distributed sensor networks. Maggie also leads research efforts focused on autonomous mobility for ground vehicles in off-road and unstructured environments, and multi-agent teaming to support tactical maneuver.