Announcements

The AIAA Intelligent Systems Technical Committee (ISTC) is concerned with the application of Intelligent System (IS) technologies and methods to aerospace systems, the verification and validation of these systems, and the education of the AIAA membership in the use of IS technologies in aerospace and other technical disciplines.

Announcements

These are announcements originally posted to the main page.

Announcements
2025 Announcements:
- News: 2025 Apr 26, 5:21pm EDT (by Cat McGhan)
  - ISTC Technical Seminar Series – Saptarshi Bandyopadhyay, on Zoom
- News: 2025 Feb 4, 3:38pm EDT (by Cat McGhan)
  - ISTC Technical Seminar Series – Nathaniel Hamilton, on Zoom
2024 Announcements:
2023 Announcements:
2022 Announcements:
2021 Announcements:
- News: 2021 December 20, 9:50pm EST (by Cat McGhan)
  - Jon How’s keynote at SciTech 2022
- News: 2021 March 6, 2:57pm EST (by Cat McGhan)
  - 1st Workshop on AI for Space in conjunction with CVPR 2021: June 2021
2020 Announcements:
2019 Announcements:
- News: 2019 January 08, 4:40pm EST (by Cat McGhan)
  - 2018 IS Workshop presentation links are online
2018 Announcements:
- News: 2018 September 13, 1:39am EST (by Cat McGhan)
  - 2018 IS Workshop presentation links coming soon!
- News: 2018 September 13, 1:38am EST (by Cat McGhan)
  - AIAA Sharepoint site issues
Wayback Machine site:
- Wayback Machine Version of Old Website – January 2, 2018 version
Stubs for old announcements (2011-2017):

2025 Announcements:

News: 2025 Apr 26, 5:21pm EDT (by Cat McGhan)

ISTC Technical Seminar Series – Saptarshi Bandyopadhyay, on Zoom

ISTC Technical Seminar Series

Don’t miss Dr. Saptarshi Bandyopadhyay’s seminar Tuesday April 29 at 12:00pm ET on Zoom!

Speaker: Saptarshi Bandyopadhyay, PhD
NASA Jet Propulsion Laboratory
California Institute of Technology

Date/time: Tuesday, April 29th, 2025 – 12:00pm-1:00pm Eastern time

Title: Multi-Spacecraft Concept and Autonomy Tool (MuSCAT): An open-source low-fidelity simulator to develop and test spacecraft autonomy

Meeting link: https://aiaa.zoom.us/j/2481320441?pwd=djhZZVJITi9ja0UzRGZJM0tRN3ptZz09&omn=86832525066
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Meeting ID: 248 132 0441
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Abstract: Autonomy is the ability of a system (e.g. spacecraft) to achieve goals while operating independently of external control (e.g. ground operations). This talk focuses on autonomy for JPL’s cruising and orbiting spacecraft missions; the needs, the challenges, and the future directions. I will present an open-source low-fidelity simulator called Multi-Spacecraft Concept and Autonomy Tool (MuSCAT, link: https://github.com/nasa/muscat); which provides an integrated platform for low-fidelity simulations of single/multiple cruising/orbiting spacecraft’s navigation, attitude determination and control, power, communication (both direct-to-Earth and inter-spacecraft), science instruments and testing autonomy algorithms. I will discuss the evolution of the open-source MuSCAT simulator across various projects, its current state-of-the-art capabilities, and various challenges that lie ahead.

Bio: Dr. Saptarshi Bandyopadhyay is a robotics technologist at the NASA Jet Propulsion Laboratory, California Institute of Technology, where he develops novel algorithms for future autonomous and multi-agent missions. In 2020, he was named a NASA NIAC fellow for his work on the Lunar Crater Radio Telescope on the far side of the Moon. He received his Ph.D. in Aerospace Engineering in 2016 from the University of Illinois at Urbana-Champaign, USA, where he specialized in probabilistic swarm guidance and distributed estimation. He earned his bachelor’s and master’s degrees in Aerospace Engineering in 2010 from the Indian Institute of Technology Bombay, India, where as an undergraduate, he co-founded and led the institute’s student satellite project, Pratham, which was launched into low Earth orbit in September 2016. His engineering expertise stems from a long-standing interest in the science underlying space missions, since winning the gold medal for India at the 9th International Astronomy Olympiad held in Ukraine in 2004.

Currently, Saptarshi is focused on conceptualizing space missions that can leverage the unique capabilities of multiple spacecraft. His research interests include studying the evolution of the Solar System by probing the interiors of small bodies, using interferometry to image exoplanets, and gaining insights into the origin of life and our place in the Universe. He has published more than 70 papers in journals and refereed conferences.

News: 2025 Feb 4, 3:38pm EDT (by Cat McGhan)

ISTC Technical Seminar Series – Nathaniel Hamilton, on Zoom

ISTC Technical Seminar Series

Don’t miss Dr. Nathaniel Hamilton’s seminar Friday February 7 at 1:00pm ET on Zoom!

Speaker: Nathaniel Hamilton, PhD
Safe Reinforcement Learning Lead
Autonomy Capability Team (ACT3)
Air Force Research Laboratory

Date/time: Friday, February 7th, 2025 – 1:00pm-2:00pm Eastern time

Title: Safe and Robust Autonomy

Meeting link: https://aiaa.zoom.us/j/2481320441?pwd=djhZZVJITi9ja0UzRGZJM0tRN3ptZz09&omn=88346108786
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Meeting ID: 248 132 0441
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Abstract: Autonomous systems that are capable of operating self-sufficiently and independent of external control are crucial for the space domain. The biggest advancements in autonomy have been limited to simulated systems, but recent work has demonstrated promise in the real world. However, there are still issues with ensuring the autonomy acts safely and in a trustworthy manner. To this end, we must ensure the safe and robust transfer of high- performing autonomy from the simulated environments they are trained in, to the real-world, physical systems. In this talk, we overview our recent work in training and deploying safe Neural Network Controllers (NNCs) and bringing the solutions from simulation to the real world.

Bio: Nathaniel “Nate” Hamilton is the Safe Reinforcement Learning Lead on the Safe Autonomy Team at the Air Force Research Laboratory’ Autonomy Capability Team (ACT3). There he investigates Safe Reinforcement Learning (SafeRL) approaches and how we can better integrate safety into the learning process to enable safe, trusted, and certifiable autonomous and learning-enabled controllers for aircraft and spacecraft applications. His previous experience includes studying how Run Time Assurance (RTA) impacts the learning and performance of SafeRL agents, and work in simulation to real-world (sim2real) transfer for learning-enabled controllers. In 2019, Dr. Hamilton was awarded the National Defense Science and Engineering Graduate (NDSEG) Fellowship. Dr. Hamilton has a BS in Electrical and Computer Engineering from Lipscomb University, and an MS and Ph.D. in Electrical Engineering from Vanderbilt University.

2024 Announcements:

News: 2024 Dec 2, 8:08pm EDT (by Cat McGhan)

ISTC Technical Seminar Series – Isaac Weintraub, on Zoom

ISTC Technical Seminar Series

Don’t miss Dr. Isaac Weintraub’s seminar Friday December 6 at 1:00pm ET on Zoom!

Speaker: Isaac E. Weintraub, PhD
Aerospace Systems Directorate
Air Force Research Laboratory

Date/time: Friday, December 6th, 2024 – 1:00pm-2:00pm Eastern time

Title: Mission Driven Autonomy

Meeting link: https://aiaa.zoom.us/j/2481320441?pwd=djhZZVJITi9ja0UzRGZJM0tRN3ptZz09&omn=83071345164
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Meeting ID: 248 132 0441
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Abstract: In the midst of growing near peer adversary threats, it is clear the United States will leverage autonomous assets to establish and maintain air superiority. Toward this end, this seminar focuses on enabling techniques for posing and solving critical aspects for future engagements. Methods such as differential game theory and optimal control theory can and have been used to obtain strategies for weapon engagement zone denial, optimize killing, mutual support, and vehicle control and coordination. This seminar demonstrates some of the recent advances in these relevant problems and highlights first-principles based approaches for posing and solving them.

Bio: Dr. Isaac Weintraub is a senior electronics engineer at The Air Force Research Laboratory. He received his PhD in Electrical Engineering from the Air Force Institute of Technology in 2021, MS in Electrical Engineering from the University of Texas at Arlington in 2011, and BS in Mechanical Engineering from Rose-Hulman Institute of Technology in 2009. He is a senior member in the American Institute of Aeronautics and Astronautics (AIAA) and a senior member of the Institute of Electrical and Electronics Engineers (IEEE). He is currently serving as the Technical Discipline Chair and Local Workshop Chair for the AIAA Intelligent Systems Technical Committee.

News: 2024 Oct 21, 3:22pm EDT (by Cat McGhan)

ISTC Technical Seminar Series – Dimitra Panagou, on Zoom

ISTC Technical Seminar Series

Don’t miss Dr. Dimitra Panagou’s seminar Tuesday October 29 at 12:00pm ET on Zoom!

Speaker: Dimitra Panagou, Ph.D.
Associate Professor
Department of Robotics
Department of Aerospace Engineering
University of Michigan

Date/time: Tuesday, October 29th, 2024 – 12:00pm-1:00pm Eastern time

Title: Towards safe and resilient autonomy using synergistic control, observation and learning

Meeting link: https://aiaa.zoom.us/j/2481320441?pwd=djhZZVJITi9ja0UzRGZJM0tRN3ptZz09&omn=89153417424
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Abstract: Enabling autonomy for robotic and cyber-physical systems with provable safety and resilience guarantees has been an ongoing area of research. Despite significant progress over the years, there are still open challenges due to constraints (e.g., safety and time specifications; sensing, computation and communication limitations), and environmental uncertainty. This talk will present some of our recent results and ongoing work on a framework that interconnects control, planning and learning methods towards provably-correct safety-critical systems under constraints and uncertainty.

Bio: Dimitra Panagou received the Diploma and PhD degrees in Mechanical Engineering from the National Technical University of Athens, Greece, in 2006 and 2012, respectively. In September 2014 she joined the Department of Aerospace Engineering, University of Michigan as an Assistant Professor. Since July 2022 she is an Associate Professor with the newly established Department of Robotics, with a courtesy appointment with the Department of Aerospace Engineering, University of Michigan. Prior to joining the University of Michigan, she was a postdoctoral research associate with the Coordinated Science Laboratory, University of Illinois, Urbana-Champaign (2012-2014), a visiting research scholar with the GRASP Lab, University of Pennsylvania (June 2013, Fall 2010) and a visiting research scholar with the University of Delaware, Mechanical Engineering Department (Spring 2009). Her research program spans the areas of nonlinear systems and control; multi-agent systems, autonomy and control; and aerospace robotics. She is particularly interested in the development of provably-correct methods for the safe and secure (resilient) operation of autonomous systems in complex missions, with applications in robot/sensor networks and multi-vehicle systems (ground, marine, aerial, space) under uncertainty. She is a recipient of the NASA Early Career Faculty Award, the AFOSR Young Investigator Award, the NSF CAREER Award, the George J. Huebner, Jr. Research Excellence Award, and a Senior Member of the IEEE and the AIAA.

News: 2024 July 21, 8:18pm EDT (by Cat McGhan)

ISTC Technical Seminar Series – Melkior Ornik, on Zoom

ISTC Technical Seminar Series

Don’t miss Dr. Melkior Ornik’s seminar Tuesday July 23 at 2:00pm ET on Zoom!

Speaker: Melkior Ornik, Ph.D.
Department of Aerospace Engineering
University of Illinois Urbana-Champaign

Date/time: Tuesday, July 23rd, 2024 – 2:00pm-3:00pm Eastern time

Title: Control of Unknown Systems in Unlearnable Environments: Fundamental Limits of Knowledge

Meeting link: https://aiaa.zoom.us/j/2481320441?pwd=djhZZVJITi9ja0UzRGZJM0tRN3ptZz09&omn=89524782672
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Meeting ID: 248 132 0441
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Abstract: High-level autonomy in previously unseen or abruptly changed conditions faces a critical conceptual challenge: if the controller has no comprehensive system model and no prior opportunity to collect data and train its strategy, how can we form guarantees about system safety or performance? In fact, how do we know whether the system’s task is even feasible? Indeed, standard approaches of learning-based control require a wealth of available data, while classical methods of robust and adaptive control respond to highly structured uncertainties. Additionally, attempting to determine a control strategy to complete a predetermined task does not reflect the limits of the system’s capabilities: the system might be unable to perform the old task in novel conditions. Instead, an intelligent planner should understand which tasks can certifiably be completed given the current knowledge, and then formulate appropriate control laws. To move towards that goal, in this talk I will present an emergent twin efforts of design-time guaranteed resilience and mission-time guaranteed performance. Combining methods of optimal control, reachability analysis, and differential geometry, these approaches compute a set of tasks completable under all system dynamics consistent with the planner’s partial knowledge, and synthesize appropriate control laws using online learning and adaptation. In describing this framework, this talk will briefly present several applications to aerial and space vehicles, identifying promising future directions of research such as safety-assured reachability, verifiable performance with faulty sensing, and data-driven incremental certification.

Bio: Melkior Ornik is an assistant professor in the Department of Aerospace Engineering at the University of Illinois Urbana-Champaign, also affiliated with the Coordinated Science Laboratory, as well as the Discovery Partners Institute in Chicago. He received his Ph.D. degree from the University of Toronto in 2017. His research focuses on developing theory and algorithms for control, learning and task planning in autonomous systems that operate in uncertain, changing, or adversarial environments, as well as in scenarios where only limited knowledge of the system is available. He is a senior member of AIAA and IEEE, his recent work has been extensively funded by NASA grants and Department of Defense programs, and he has been awarded the 2023 Air Force Young Investigator Program grant.

News: 2024 May 8, 10:00am EDT (by Cat McGhan)

ISTC Technical Seminar Series – Jun Chen, on Zoom

ISTC Technical Seminar Series

Don’t miss Dr. Jun Chen’s seminar Tuesday May 14 at 4:00pm ET on Zoom!

Speaker: Jun Chen, Ph.D.
Department of Aerospace Engineering
San Diego State University

Date/time: Tuesday, May 14th, 2024 – 4:00pm-5:00pm Eastern time

Title: Safety-Assured Online Planning for Large-scale Autonomy under Uncertainty

Meeting link: https://aiaa.zoom.us/j/2481320441?pwd=djhZZVJITi9ja0UzRGZJM0tRN3ptZz09&omn=82685514209
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Meeting ID: 248 132 0441
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Abstract: With the booming of artificial intelligence and autonomy in a new era, the field of systems and control has recently been facing newly emerged research in the control and optimization of large-scale networked autonomous systems, most of which heavily rely on the fidelity of the models and efficient computational techniques to execute optimized control actions. Meanwhile, the physical autonomous systems are inherently subject to uncertainties and disturbances. This seminar will present a suite of modeling, optimization, and computation algorithms and tools that can efficiently support safety-assured real-time decision-making for large-scale autonomous systems, with a focus on Unmanned Aerial Vehicle (UAV) autonomy and Advanced Air Mobility (AAM) applications under dynamic and uncertain environments.

Bio: Dr. Jun Chen is an Assistant Professor in the Department of Aerospace Engineering at San Diego State University. Dr. Chen’s research area includes dynamics, control, machine learning, and artificial intelligence, particularly in data-driven modeling, control, and optimization for large-scale networked dynamical systems, with applications in mechanical and aerospace engineering such as air traffic control, traffic flow management, and autonomous air/ground vehicle systems. His research spans theory and practice, including both algorithm development and real-world field tests. Dr. Chen’s research has been supported by NSF, FAA, and NASA. Dr. Chen earned his Ph.D. and M.S. degrees in Aerospace Engineering from Purdue University and a B.S. degree in Aeronautics Engineering from Beihang University. He is a recipient of the Purdue College of Engineering Outstanding Research Award in 2018.

News: 2024 Apr 9, 7:40pm EDT (by Cat McGhan)

ISTC Technical Seminar Series – Naira Hovakimyan, on Zoom

ISTC Technical Seminar Series

Don’t miss Dr. Naira Hovakimyan’s seminar Tuesday April 23 at 5:00pm ET on Zoom!

Speaker: Naira Hovakimyan, Ph.D.
W. Grafton and Lillian B. Wilkins Professor
Mechanical Science and Engineering
University of Illinois Urbana-Champaign

Date/time: Tuesday, Apr 23th, 2024 – 5:00pm-6:00pm Eastern time

Title: Safe Learning in Autonomous Systems

Meeting link: https://aiaa.zoom.us/j/2481320441?pwd=djhZZVJITi9ja0UzRGZJM0tRN3ptZz09&omn=85452117558
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Abstract: Learning-based control paradigms have seen many success stories with various robots and co-robots in recent years. However, as these robots prepare to enter the real world, operating safely in the presence of imperfect model knowledge and external disturbances is going to be vital to ensure mission success. We introduce a class of distributionally robust adaptive control architectures that ensure robustness to distribution shifts and enable the development of certificates for V&V of learning-enabled systems. An overview of different projects at our lab that build upon this framework will be demonstrated to show different applications.

Bio: Naira Hovakimyan received her MS degree in Applied Mathematics from Yerevan State University in Armenia. She got her Ph.D. in Physics and Mathematics from the Institute of Applied Mathematics of Russian Academy of Sciences in Moscow. She is currently W. Grafton and Lillian B. Wilkins Professor of Mechanical Science and Engineering and the Director of AVIATE Center of UIUC. She has co-authored two books, eleven patents and more than 500 refereed publications. She is the 2011 recipient of AIAA Mechanics and Control of Flight Award, the 2015 recipient of SWE Achievement Award, the 2017 recipient of IEEE CSS Award for Technical Excellence in Aerospace Controls, and the 2019 recipient of AIAA Pendray Aerospace Literature Award. In 2014 she was awarded the Humboldt prize for her lifetime achievements. She is Fellow of AIAA, IEEE, ASME, and senior member of National Academy of Inventors. She is cofounder and chief scientist of Intelinair. Her work was featured in the New York Times, on Fox TV and CNBC.

News: 2024 Jan 29, 7:19pm EDT (by Cat McGhan)

ISTC Technical Seminar Series – Yan Wan, on Zoom

ISTC Technical Seminar Series

Don’t miss Dr. Yan Wan’s seminar tomorrow (this Tuesday) at 3:00pm EDT on Zoom!

Speaker: Yan Wan, Ph.D.
Distinguished University Professor
Electrical Engineering
University of Texas at Arlington

Date/time: Tuesday, Jan 30th, 2024 – 3:00pm-4:00pm Eastern time

Title: Uncertainty Modeling and Evaluation for Cyber-Physical Control Systems

Meeting link: https://aiaa.zoom.us/j/2481320441?pwd=djhZZVJITi9ja0UzRGZJM0tRN3ptZz09
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Abstract: Uncertainties often modulate modern cyber-physical system dynamics in a complicated fashion. They lead to challenges for real-time control, considering the significant computation load needed for uncertainty evaluation. We introduce scalable uncertainty models and uncertainty evaluation methods that break the curse of dimensionality for optimal control, learning control and differential games. Applications include UAV networking, UAV traffic management, air traffic management, and autonomous driving.

Bio: Yan Wan is a Distinguished University Professor in the Electrical Engineering Department at the University of Texas at Arlington (UTA). She received her Ph.D. degree in Electrical and Computer Engineering from Washington State University and then did Postdoctoral training in the Institute for Collaborative Biotechnologies at the University of California Santa Barbara. Her research interests lie in the modelling, evaluation, and control of large-scale dynamical networks, cyber-physical systems, stochastic networks, decentralized control, learning control, networking, uncertainty analysis, algebraic graph theory, and their applications to urban aerial mobility, autonomous driving, robot networking, air traffic management, microgrids, and edge computing. She received research grants from federal agencies such as NSF, ONR, ARO, NIST, and DOE as well as industry support from Ford Motors, Toyota Motors, Lockheed Martin, Dell Technologies, and MITRE Corporation as subcontracts from the FAA. Her research has led to over 230 publications and technology transfer outcomes. For her work, she has been recognized with several prestigious awards, including the NSF CAREER Award, RTCA William E. Jackson Award, U.S. Ignite and GENI demonstration awards, IEEE WCNC and ICCA Best Paper Awards, UTA Outstanding Research Achievement or Creative Accomplishment Award, UNT Early Career Award for Research and Creativity, UTA STARS Award, Lockheed Martin Aeronautics Excellence in Teaching Award, and Tech Titan of the Future – University Level Award. She was a Board of Governors (BOG) member of the IEEE Control Systems Society and is currently a BOG member of the IEEE Systems, Man, and Cybernetics Society. She also serves in the Technical Committees of AIAA Intelligent Systems, IEEE CSS Nonlinear Systems and Control, and IEEE CSS Networks and Communication Systems. She is an Associate Fellow of AIAA and a Senior Member of IEEE.

2023 Announcements:

News: 2023 Nov 20, 1:06pm EDT (by Cat McGhan)

ISTC Technical Seminar Series – John Valasek, on Zoom

ISTC Technical Seminar Series

Don’t miss Dr. John Valasek’s seminar today at 4:00pm EDT on Zoom!

Speaker: Dr. John Valasek
Texas A&M University

Date/time: Monday, Nov 20th, 2023 – 4:00pm-4:50pm Eastern time

Title: Preparing for AIAA Fellow Nomination and Selection

Abstract: In this talk I will discuss how you can assess your preparation for nomination to AIAA Fellow. The talk will focus on evaluating your career readiness, what is required for a nomination packet, who to ask for what, and how to helpfully provide information to your nominator and references. I will also present the timeline of the nomination and selection process, and what the ISTC can do to help you.

Bio: John Valasek is Director, Vehicle Systems & Control Laboratory (https://vscl.tamu.edu), Thaman Professor of Undergraduate Teaching Excellence, Professor of Aerospace Engineering, and member of the Honors Faculty at Texas A&M University (TAMU), which he joined in 1997. He has been actively conducting autonomy and flight controls research of Unmanned Air Systems (UAS) in both Industry and Academia for 36 years. He began his career as a Flight Control Engineer for the Northrop Corporation, Aircraft Division where he worked in the Flight Controls Research Group, and on the AGM-137 Tri-Services Standoff Attack Missile (TSSAM) program. He is co-inventor on a patent for Autonomous Air Refueling (AAR) of UAS and a patent for the design of a UAS. John is the TAMU Site Director for the NSF Center for Autonomous Air Mobility and Sensing (CAAMS), and the TAMU Site Director for the FAA Partnership to Enhance General Aviation Safety, Accessibility and Sustainability (PEGASAS). He has conducted more than 600 fixed-wing and rotorcraft UAS test flights on 33 funded research programs over a 23 year period at TAMU.

John is co-author of the book Nonlinear Multiple Time Scale Systems in Standard and Non-Standard Forms: Analysis and Control, (SIAM, 2014), and editor of the books Morphing Aerospace Vehicles and Structures (Wiley, 2012), Advances in Intelligent and Autonomous Aerospace Systems (AIAA, 2012), and Advances in Computational Intelligence and Autonomy for Aerospace Systems (AIAA, 2018).

John is a Fellow of AIAA, member of the AIAA Autonomy Task Force, Chair of the AIAA Intelligent Systems Technical Committee, and Associate Editor of the Journal of Guidance, Control, and Dynamics.

News: 2023 Oct 23, 2:00pm EDT (by Cat McGhan)

ISTC Technical Seminar Series – Justin Bradley, on Zoom

ISTC Technical Seminar Series

Don’t miss Dr. Justin Bradley’s seminar tomorrow (this Tuesday) at 3:00pm EDT on Zoom!

Speaker: Dr. Justin Bradley
Richard L. and Carol S. McNeel Associate Professor
School of Computing
University of Nebraska-Lincoln

Date/time: Tuesday, Oct 24th, 2023 – 3:00pm-4:00pm Eastern time

Title: Preparing for AIAA Associate Fellow Nomination and Selection

Abstract: In this talk I will discuss how you can assess your preparation for nomination to AIAA Associate Fellow. The talk will focus on evaluating your career readiness, what is required for a nomination packet, who to ask for what, and how to helpfully provide information to your nominator and references. I will also present the timeline of the nomination and selection process, and what the ISTC can do to help you.

Bio: Justin Bradley is a Richard L. and Carol S. McNeel Associate Professor in the School of Computing at the University of Nebraska-Lincoln. He holds a B.S. in computer engineering (2005) and M.S. in electrical engineering (2007) from Brigham Young University, and M.S. (2012) and Ph.D. (2014) degrees in aerospace engineering from the University of Michigan. He has worked with Unmanned Aircraft Systems (UAS) for over 17 years, starting at the Multi-AGent Intelligent Coordination and Control (MAGICC) lab at BYU, the A2Sys lab at the University of Michigan, and most recently as a co-director of the Nebraska Intelligent MoBile Unmanned System (NIMBUS) lab since 2015. He is a recipient of a 2021 NSF CAREER award, an AIAA Associate Fellow, and chair-elect of the AIAA ISTC. Justin’s research lies at the intersection of computing, control, and aerospace disciplines.

News: 2023 Sept 19, 10:57pm EDT (by Cat McGhan)

ISTC Technical Seminar Series – Kerianne Hobbs, on Zoom

ISTC Technical Seminar Series

Don’t miss Dr. Kerianne Hobbs’s seminar tomorrow (this Wednesday) at 3:00pm EDT on Zoom!

Speaker: Kerianne Hobbs, Ph.D.
Safe Autonomy and Space Lead
Autonomy Capability Team (ACT3)
Air Force Research Laboratory

Date/time: Wednesday, Sept 20th, 2023 – 3:00pm-4:00pm Eastern time

Title: Safe Autonomy

Abstract: How do you know an autonomous system will do what you want? How do you know an autonomous system won’t do what you don’t want? What if the autonomous system is based on Machine Learning? This talk introduces the machine learning autonomy projects at the AFRL ACT3 Research Team, and the research by the AFRL Safe Autonomy Research Team over the last four years to analyze and assure safety of learning-based autonomous systems.

Bio: Dr. Kerianne Hobbs is the Safe Autonomy and Space Lead on the Autonomy Capability Team (ACT3) at the Air Force Research Laboratory. There she investigates rigorous specification, analysis, bounding, and intervention techniques to enable safe, trusted, ethical, and certifiable autonomous and learning controllers for aircraft and spacecraft applications. Her previous experience includes work in automatic collision avoidance and autonomy verification and validation research. Dr. Hobbs was selected for the 2020 AFCEA 40 Under 40 award and was a member of the team that won the 2018 Collier Trophy (Automatic Ground Collision Avoidance System Team), as well as numerous AFRL Awards. She serves on the AIAA Intelligent Systems Technical Committee, the NASA Formal Methods Program Committee, the IEEE Aerospace Conference Committee, and the IEEE Space Mission Challenges for Information Technology - IEEE Space Computing Conference Program Committee. Dr. Hobbs has a BS in Aerospace Engineering from Embry-Riddle Aeronautical University, an MS in Astronautical Engineering from the Air Force Institute of Technology, and a Ph.D. in Aerospace Engineering from the Georgia Institute of Technology.

News: 2023 June 12, 2:30pm EDT (by Cat McGhan)

ISTC Technical Seminar Series – Srikanth Saripalli, on Zoom

ISTC Technical Seminar Series

Don’t miss Prof. Srikanth Saripalli’s seminar this Wednesday at 5:00pm EDT on Zoom!

Speaker: Professor Srikanth Saripalli
Mechanical Engineering department
Texas A&M University

Date/time: Wednesday, June 14th, 2023 – 5:00pm-6:00pm Eastern time

Title: High Speed Off-Road Autonomy: Perception and Control in the Wild

Abstract: The talk focuses on perception and planning algorithms for autonomous vehicles in off-road situations. A particular emphasis is on why off-road vehicles are different than on-road vehicles and how can we solve autonomy in the off-road domain. A major portion of the talk will be on applications of the above algorithms to real vehicles and the lessons that we have learned i.e. what worked and what didn’t and how we should go about building such systems. I will also briefly touch on our work on Autonomous Landing and Obstacle Avoidance for UAVs.

Bio: Srikanth Saripalli is a Professor in Mechanical Engineering department and the Director for Center for Autonomous Vehicles and Sensor Systems (CANVASS) at Texas A&M University. He holds the J. Mike Walker ’66 Professorship. His research focuses on robotic systems: particularly in air and ground vehicles and necessary foundations in perception, planning, control and system integration for this domain. He is currently leading several efforts in off-road autonomous ground vehicles. He has also led several long-term (> 6 month) on-road deployments of autonomous 18 wheeler trucks and slow-moving shuttles in Texas. He is currently interested in developing and deploying Autonomous Shuttles on campus and in cities. He is also interested in developing such autonomous shuttles for mobility challenged and para transit applications.

Flyer: https://drive.google.com/file/d/1xVeI9XYPGJJbaFWfz6zfmXD9gm3c6mpj/view?usp=sharing

News: 2023 May 24, 1:45pm EDT (by Cat McGhan)

ISTC Technical Seminar Series – Woong-Je Sung, on Zoom

ISTC Technical Seminar Series

Don’t miss Dr. Woong-Je Sung’s seminar today(/Wednesday) at 3:00pm EDT on Zoom!

Speaker: Woong-Je Sung, Ph.D.
Research Engineer, School of Aerospace Engineering
Georgia Institute of Technology

Date/time: Wednesday, May 24th, 2023 – 3:00pm-4:00pm Eastern time

Title: Deep Learning Strategy for Aerodynamics

Meeting link (UPDATED): https://aiaa.zoom.us/j/2481320441?pwd=djhZZVJITi9ja0UzRGZJM0tRN3ptZz09
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Abstract: The recent progress in deep learning and generative AI provides active challenges as well as remarkable opportunities in aerodynamics research where the highly non-linear flow phenomena (e.g., shock waves and flow separations) are not uncommon and the available data are not always abundant considering the high dimensionality of flow boundary conditions. In this talk, first, the applications of deep learning techniques are briefly reviewed in the context of surrogate modeling and dimensionality reduction and, second, several research snapshots are discussed including a CFD (Computational Fluid Dynamics)-WTT (Wind Tunnel Test) data fusion using deep representation learning, a geometric deep learning for 3-D mesh, and an aerodynamic shape optimization using deep reinforcement learning.

Bio: Dr. Woong-Je Sung Studied CFD, FEM, and MDO in Seoul National Univ (BS/MS in Aerospace Engineering). He worked on experimental and computational aerodynamics in Agency for Defense Development (1999-2004, Korea). He studied meta-modeling with neural network in Georgia Tech (PhD in Aerospace Engineering, 2012). Dr. Sung has worked on various projects on M&S and ML/AI as Post-Doc and Research Engineer in Georgia Tech (2012-Present).

News: 2023 March 28, 12:11pm EDT (by Cat McGhan)

ISTC Technical Seminar Series – Junfei Xie, on Zoom

ISTC Technical Seminar Series

Don’t miss Dr. Junfei Xie’s seminar this coming Wednesday at 5:00pm EDT on Zoom!

Speaker: Junfei Xie, Ph.D.
Associate Professor, Department of Electrical and Computer Engineering
San Diego State University

Date/time: Wednesday, March 29th, 2023 – 5:00pm-6:00pm Eastern time

Title: Networked Airborne Computing: Empowering Reliable and Efficient Computing in the Skies

Meeting link: https://aiaa.zoom.us/j/85610194482?pwd=M1dwZGlCMWFIN0ROZXhWaVRCVDRBdz09
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Meeting ID: 856 1019 4482
Passcode: 013418

Abstract: Unmanned aerial vehicles (UAVs) have emerged as a crucial technology in various civilian and commercial applications. While most UAV applications involve a single UAV, many new applications are expected to demand cooperative computing capabilities among multiple UAVs. This trend presents opportunities for researchers to address fundamental challenges across a range of disciplines, from aerospace to control, communication, networking, and computing. With multiple UAVs sharing computing resources, the networked multi-UAV system can also provide on-demand computing services to ground users, essentially functioning as a flying cloud. However, enabling reliable and efficient networked airborne computing requires overcoming many formidable challenges such as 3-dimensional node mobility, highly uncertain operating environment, and strict safety requirements. In this talk, this new and cross-disciplinary area will be explored, and recent research results we have developed to enable networked airborne computing will be presented.

Bio: Dr. Junfei Xie is an Associate Professor in the Department of Electrical and Computer Engineering at San Diego State University (SDSU). She received her B.S. degree in Electrical Engineering from University of Electronic Science and Technology of China (UESTC), Chengdu, China, in 2012. She received her M.S. degree in Electrical Engineering in 2013 and Ph.D. degree in Computer Science and Engineering in 2016 from University of North Texas (UNT), Denton, TX. Prior to joining SDSU, she was an Assistant Professor in the Department of Computing Sciences at Texas A&M University-Corpus Christi (TAMUCC). Dr. Xie’s research interests span several areas, including large-scale dynamic system design and control, unmanned aerial systems, networked airborne computing, mobile edge computing, air traffic flow management, uncertainty quantification, spatiotemporal data analysis, and complex information systems. She is the recipient of multiple prestigious awards such as the NSF CAREER Award, SDSU Presidential Research Faculty Fellow Award, Top 50 Women of Influence in Engineering by San Diego Business Journal, etc. She currently serves as the Associate Editor for IEEE Transactions on Systems, Man, and Cybernetics – Systems, Associate Editor for IEEE Transactions on Circuits and Systems II: Express Briefs, and Guest Editor for Unmanned Systems.

Flyer: https://drive.google.com/file/d/1rXQI5mf5B_iEYujxSooeAn-t7h6f6-tD/view?usp=share_link

News: 2023 February 11, 2:54pm EST (by Cat McGhan)

ISTC Technical Seminar Series – Stanley Bak, on Zoom

ISTC Technical Seminar Series

Don’t miss Dr. Stanley Bak’s seminar this coming Wednesday at 3:00pm EST on Zoom!

Speaker: Stanley Bak, Ph.D.
Assistant Professor, Department of Computer Science
Stony Brook University

Date/time: Wednesday, February 15th, 2023 – 3:00pm-4:00pm Eastern time

Title: Safe Autonomy through Surrogate Verification

Meeting link: https://aiaa.zoom.us/j/86978612062?pwd=ZFJXTlVJaTE0K1Q0VWNzMVVjTWF6dz09
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Meeting ID: 856 3509 8501
Passcode: 553696

Abstract: Using autonomy within safety-critical applications demands strong assurances the system will not misbehave. Rather than direct analysis and verification, which can be hard, we instead explore using surrogate modeling. With surrogate modeling, we can create models that closely approximate system behaviors while being more amenable to formal verification methods that can prove system safety. We explore this strategy in two contexts: one for closed-loop neural network control system verification and one for approximating nonlinear dynamical systems using Koopman Operator approximations.

Bio: Stanley Bak received his PhD from the the Department of Computer Science at the University of Illinois at Urbana-Champaign (UIUC) in 2013 and then worked for several years at the Air Force Research Laboratory (AFRL) in the Verification and Validation (V&V) group of the Aerospace Systems Directorate. In 2020, he received the AFOSR Young Investigator Research Program (YIP) award. He is currently an assistant professor in the Department of Computer Science at Stony Brook University.

2022 Announcements:

News: 2022 December 13, 9:30pm EST (by Cat McGhan)

ISTC Technical Seminar Series – Chetan S. Kulkarni, on Zoom

ISTC Technical Seminar Series

Don’t miss Dr. Chetan S. Kulkarni’s seminar on Wednesday at 4:00pm EST on Zoom!

Speaker: Chetan S. Kulkarni, Ph.D.
Staff Researcher, Prognostics Center of Excellence and the Diagnostics and Prognostics Group
Intelligent Systems Division, NASA Ames Research Center

Date/time: Wednesday, December 14th, 2022 – 4:00pm-5:00pm Eastern time

Title: Hybrid Approaches for Systems Health Management and Prognostics

Abstract: To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision making. In principle, data driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for an effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system’s components health solving a calibration problem in the deep learning approach.

Bio: Chetan S. Kulkarni is a staff researcher at the Prognostics Center of Excellence and the Diagnostics and Prognostics Group in the Intelligent Systems Division at NASA Ames Research Center. His current research interests are in Systems Diagnostics, Prognostics and Health Management. Specifically focused in the area of developing physics-based and hybrid modeling approaches for diagnosis and prognosis of complex systems. He completed his MS (09), Ph.D. (13) from Vanderbilt University, TN where he was a Graduate Research Assistant with the Institute for Software Integrated Systems and Department of Electrical Engineering and Computer Science. He completed his BE (`02) from the University of Pune, India. Prior to joining Vanderbilt, he was a Research Fellow at the Department of Electrical Engineering, IIT-Bombay, where his research work focused on developing low-cost substation automation system monitoring and control devices and partial discharge of high voltage transformers. Earlier to that he was a member of the technical team of the Power Automation group at Honeywell, India where he was involved in turnkey power automation projects and product development in the area of substation automation. He is KBR Technical Fellow, AIAA Associate Fellow and Associate Editor for IEEE, SAE, IJPHM Journals on topics related to Prognostics and Systems Health Management. He has been Technical Program Committee co-chair at PHME18, PHM20 and PHM21. He co-chairs the Professional Development and Education Outreach subcommittee in the AIAA Intelligent Systems Technical Committee.

News: 2022 October 24, 2:07pm EDT (by Cat McGhan)

ISTC Technical Seminar Series – K. Merve Dogan, on Zoom

ISTC Technical Seminar Series

Don’t miss Dr. K. Merve Dogan’s seminar today at 5:00pm EDT on Zoom!

Speaker: K. Merve Dogan, Ph.D.
Department of Aerospace Engineering; Assistant Professor
Embry-Riddle Aeronautical University, Daytona Beach, Florida, USA

Date/time: Monday, October 24th, 2022 – 5:00pm-6:00pm Eastern time

Title: Verifiable Adaptive Architectures for Control of Safety-Critical Systems

Meeting link: https://aiaa.zoom.us/j/87121537657?pwd=TW82Z05aMWZ2ekRGTXRQRkxrVld4UT09
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Meeting ID: 871 2153 7657
Passcode: 261822

Abstract: Model reference adaptive control (MRAC) methods are powerful mathematical tools for safety-critical sole and multiagent systems, where they have the capability to suppress the effect of exogenous disturbances and system uncertainties for achieving a desired level of closed-loop system response. However, the closed-loop system stability with these methods can be challenged for a wide array of applications that involve unmodeled dynamics (e.g., rigid body systems coupled with flexible appendages, airplanes with high aspect ratio wings, and high-speed vehicles with rigid body and flexible dynamics coupling) and actuator dynamics (e.g., cooperation of low and high speed autonomous vehicles). Motivated by this standpoint, this seminar will introduce verifiable MRAC architectures for both sole and multiagent systems, where we will show the stability tradeoffs of these architectures in the presence of unmodeled and actuator dynamics as well as system uncertainties. In order to bridge the gap between theory and practice, several simulation and experimental results will be also presented.

Bio: Dr. K. Merve Dogan is an Assistant Professor of the Department of Aerospace Engineering at the Embry-Riddle Aeronautical University and the director of Foundational Autonomous Systems and Technologies Research Group (FAST- https://www.fastresearchgroup.com) since August 2020. Prior to joining the Embry-Riddle Aeronautical University, she held the Research Assistant position in the Department of Mechanical Engineering at the University of South Florida between 2015 and 2020, where she received her Doctor of Philosophy degree in 2020. Before joining the University of South Florida, she held a Research/Teaching Assistant position in the Department of Electrical and Electronics Engineering at the Izmir Institute of Technology between 2012 and 2015, where she received her Master of Science degree in 2016. Dr. Dogan is a Co-Director of the Forum on Robotics and Control Engineering (FoRCE), and is a member of AIAA and IEEE, including several technical committees.

News: 2022 July 12, 8:28pm EST (by Cat McGhan)

Call for Papers – 2nd Workshop on AI for Space in conjunction with ECCV 2022

Call for Papers – 2nd Workshop on AI for Space in conjunction with ECCV 2022:

AI4Space focuses on the role of AI, particularly computer vision and machine learning, in helping to solve technical challenges related to space, from autonomous spacecraft, space mining, debris monitoring and mitigation, to answering fundamental questions about the universe. The workshop will highlight the space capabilities that draw from and/or overlap significantly with vision and learning research, outline the unique difficulties presented by space applications to vision and learning, and discuss recent advances towards overcoming those obstacles.

Website:

https://aiforspace.github.io/2022/

Call for Papers:

We solicit papers for AI4Space. Papers will be reviewed and accepted papers will be published in the proceedings of ECCV Workshops. Authors of accepted papers will also be invited to present at the workshop (in hybrid mode) at ECCV 2022, Tel-Aviv, late October 2022.

The general emphasis of AI4Space is vision and learning algorithms in off-Earth environments, including in the orbital region, surface and underground environments on other planetary bodies (e.g., the moon, Mars and asteroids), interplanetary space and solar system, and distant galaxies. Target application areas include autonomous spacecraft, space robotics, space traffic management, astronomy, astrobiology and cosmology. Emphasis is also placed on novel sensors and processing hardware for vision and learning in space, mitigating the challenges of the space environment towards vision and learning (e.g., solar radiation, extreme temperatures), and solving practical difficulties in vision and learning for space (e.g., lack of training data, unknown or partially known characteristics of operating environments).

A specific list of topics is as follows:

Visual navigation for spacecraft operations
Vision and learning for space robotics
GPS-denied positioning on the moon and Mars
Space debris monitoring and mitigation
Vision and learning for astronomy, astrobiology and cosmology
Novel sensors for space applications
Processing hardware for vision and learning in space
Mitigating challenges of the space environment to vision and learning
Datasets, transfer learning and domain gap for space problems

Paper deadline: 11:59pm 15 July 2022

More details: https://aiforspace.github.io/2022/

2021 Announcements:

News: 2021 December 20, 9:50pm EST (by Cat McGhan)

Jon How’s keynote at SciTech 2022

Don’t miss Prof. Jonathan How’s keynote at SciTech 2022 on January 3rd at 11:30am PST. Professor How will talk about “Deploying Autonomy in an Uncertain World”. More info at https://www.aiaa.org/SciTech/program and below!

Date/time: Monday, January 3rd, 2022 – 11:30 PST

Title: Deploying Autonomy in an Uncertain World

Abstract: As autonomy capabilities have matured, there is growing interest in transitioning algorithms from the laboratory to the field. However, this typically leads to a painful exercise in which prior assumptions end up being violated and algorithms tend to break down, leading to poor performance in the real-world. The types of challenges faced in the real-world include disturbances (e.g., wind gusts) and modeling errors, imperfect communication networks, and the limited capabilities of onboard perception systems. This talk will describe recent advances in accounting for these types of real-world uncertainties in autonomy algorithms. To handle disturbances, I will describe a new learning approach that uses Robust Tube MPC during training to augment an expert’s training set, which is shown to enable a multirotor to learn to fly through turbulence from only a few demonstrations collected without any disturbances acting on the vehicle. To support distributed autonomy and estimation with limited communication resources, I will discuss developing censoring rules and learned communication policies to enable agents to determine if communicating for a specific navigation or planning task is justified given the message importance and network congestion. To account for the constraints of onboard perception systems (e.g., limited range and field-of-view, and corrupted by noise) I will highlight recent work on targetless multi-sensor calibration and perception-aware motion planning. Finally, the talk will motivate and outline methods for certifying the safety and performance properties of learning-based approaches, which requires ensuring that the uncertainty in the understanding of the real world is appropriately captured in the models used by the autonomous systems.

Bio: Jonathan P. How is the Richard C. Maclaurin Professor of Aeronautics and Astronautics at the Massachusetts Institute of Technology. He received a B.A.Sc. (aerospace) from the University of Toronto in 1987, and his S.M. and Ph.D. in Aeronautics and Astronautics from MIT in 1990 and 1993, respectively, and then studied for 1.5 years at MIT as a postdoctoral associate. Prior to joining MIT in 2000, he was an assistant professor in the Department of Aeronautics and Astronautics at Stanford University.

Dr. How was the editor-in-chief of the IEEE Control Systems Magazine (2015-19) and is an associate editor for the AIAA Journal of Aerospace Information Systems and the IEEE Transactions on Neural Networks and Learning Systems. He was an area chair for International Joint Conference on Artificial Intelligence (2019) and will be the program vice-chair (tutorials) for the Conference on Decision and Control (2021). He was elected to the Board of Governors of the IEEE Control System Society (CSS) in 2019 and is a member of the IEEE CSS Technical Committee on Aerospace Control and the Technical Committee on Intelligent Control. He is the Director of the Ford-MIT Alliance and was a member of the USAF Scientific Advisory Board (SAB) from 2014-17.

His research focuses on robust planning and learning under uncertainty with an emphasis on multiagent systems, and he was the planning and control lead for the MIT DARPA Urban Challenge team. His work has been recognized with multiple awards, including the 2020 IEEE CSS Distinguished Member Award, the 2020 AIAA Intelligent Systems Award, the 2015 AeroLion Technologies Outstanding Paper Award for Unmanned Systems, the 2015 IEEE CSS Video Clip Contest, the 2011 IFAC Automatica award for best applications paper, and the 2002 Institute of Navigation Burka Award. He also received the Air Force Commander’s Public Service Award in 2017. He is a Fellow of IEEE and AIAA and was elected to the National Academy of Engineering in 2021.

News: 2021 March 6, 2:57pm EST (by Cat McGhan)

1st Workshop on AI for Space in conjunction with CVPR 2021: June 2021

AI4Space focuses on the role of AI, particularly computer vision and machine learning, in helping to solve technical challenges related to space, from autonomous spacecrafts, space mining, debris monitoring and mitigation, to answering fundamental questions about the universe. The workshop will highlight the space capabilities that draw from and/or overlap significantly with vision and learning research, outline the unique difficulties presented by space applications to vision and learning, and discuss recent advances towards overcoming those obstacles.

Website: https://aiforspace.github.io/2021/

Featuring keynotes by:

Shirley Ho (Flatiron Institute), Deep learning for cosmology
Courtney Mario (Draper Lab), Vision for precision landing and sample return
Dario Izzo (ESA), AI for spacecraft guidance, dynamics and control
Yang Gao (Surrey Space), Space autonomous systems

Call for papers on:

Visual navigation for spacecraft operations
Vision and learning for space robotics
Positioning, mapping and SLAM for the moon and Mars
Autonomous celestial positioning
Space debris monitoring and mitigation
Vision and learning for astronomy, astrobiology and cosmology
Sensors for space applications
AI and learning-based satellite communications and IoT
Processing hardware for vision and learning in space, including satellite on-board processing
Mitigating challenges of the space environment to vision and learning
Datasets, transfer learning and domain gap for space problems

Paper deadline: extended to 11:59pm 20 Mar 2021 (PST)

Submission details: https://aiforspace.github.io/2021/#cfp

2020 Announcements:

News: 2020 August 19, 9:35pm EST (by Cat McGhan)

Two of our TC members were featured in a news article recently!

Analysis: Sanitization Drones Could Improve Campus Safety
EDTECH Magazine (8/10, Stone) reports that “at the University of Michigan, Aerospace Engineering Professor Ella Atkins envisions a school using UAVs to clean learning spaces.” Said Atkins, “If the drone can pop up above the tables and chairs and spray a fast-drying solution, just zipping back and forth in a regular pattern, there’s no way a human could do that nearly as fast. That has real possibilities.” A small drone “likely couldn’t carry enough cleaning fluid to get the job done,” but “running a lightweight hose from the drone back to a bucket of solution introduces challenges.” Said Kelly Cohen, interim head of the Department of Aerospace Engineering and Engineering Mechanics at the University of Cincinnati, “There are spaces where you have a lot of students congregating, maybe moving from one building to another, and that open space could be disinfected by drones.”

News: 2020 April 29, 12:33pm EST (by Cat McGhan)

2020 IS Workshop has been POSTPONED

The 2020 IS Workshop has been POSTPONED UNTIL SUMMER 2021. We thank you for your patience and forbearance in these COVID-19 times. You can learn more about the virus and stay up to date on the situation and safety measures to deal with it at the WHO website (or the CDC website for more USA-specific information). In the meantime, please practice social distancing and best practices under these evolving circumstances, and we all hope you stay safe and well. We will all get through this together.

News: 2020 February 28, 3:42pm EST (by Cat McGhan)

2020 IS Workshop Call for abstracts

The call for abstracts for the student talks and poster competition for the 2020 IS Workshop has now been posted.

Pdf flyer is available here!

2019 Announcements:

News: 2019 January 08, 4:40pm EST (by Cat McGhan)

2018 IS Workshop presentation links are online

Presentations from the 2018 IS Workshop are online and available at this location.

The 2019 IS Workshop page is also online! View it at: https://istcws2019.org/

2018 Announcements:

News: 2018 September 13, 1:39am EST (by Cat McGhan)

2018 IS Workshop presentation links coming soon!

Links to the presentations from the 2018 IS Workshop will be made available at this website domain later today. Stay tuned!

News: 2018 September 13, 1:38am EST (by Cat McGhan)

AIAA Sharepoint site issues

The AIAA Sharepoint site seems to have been having issues for a couple of weeks now. Not sure what’s going on, but it’s sped up our move to another webhost for public dissemination of ISTC-related information.

Wayback Machine site:

Wayback Machine Version of Old Website – January 2, 2018 version

If you want to see the old site as of January 2, 2018 (prior to recent updates), you can visit it via the Internet Archive’s Wayback Machine at this location.

Stubs for old announcements (2011-2017):

These are old announcements from the previous website, and will be filled in soon!

2017 Intelligent Systems Workshop – University of Michigan, July 26-27

7/3/2017 4:56 PM (by ?)

ISTC Members Selected for AIAA Fellow, Associate Fellow

2/3/2017 11:27 AM (by ?)

Roadmap for Intelligent Systems in Aerospace Released

1/14/2017 2:02 PM (by ?)

2016 Intelligent Systems Workshop – NASA Langley, Aug. 3-5

10/11/2016 5:38 PM (by ?)

ISTC 2015 Workshop: Intelligent Systems - Enabling Future Autonomy

10/11/2016 5:38 PM (by ?)

Kristin Rozier on NASA TV

8/12/2014 2:31 PM (by Nicholas D. Ernest)

Our own Kristin Rozier has been aired on NASA TV presenting her work on Formal Methods V&V. Her presentation is titled “No More Helicopter Parenting: Intelligent Autonomous UAS’s”. Watch the video on Youtube here.

2014 Intelligent Systems Workshop

7/14/2014 9:45 AM (by ?)

Two AIAA JAIS special issues:

12/5/2013 8:18 AM (by ?)

Juddges needed for the 2013-2014 Spirit of Innovation Challenge

10/28/2013 7:37 AM (by ?)

Attachment

ISTC Meeting Aug 19th 7pm EST

8/18/2013 10:17 AM (by ?)

NASA ARMD Research Opportunities in Aeronautics (ROA) 2013

7/15/2013 1:26 PM (by ?)

AIAA Joins with S&E Societies to Ask Congress to Modify Government Travel Rules

6/26/2013 3:26 PM (by ?)

Position Opening: Chair or Senior Lecturer in Computational Biology

6/26/2013 3:25 PM (by ?)

NASA Call for Proposals for Leading Edge Aeronautics

6/3/2013 8:40 AM (by ?)

Inspiring words from Lotfi A Zadeh - father of fuzzy logic

6/3/2013 7:36 AM (by ?)

ISTC member Missy Cummings on The Daily Show

1/28/2013 11:11 PM (by ?)

Lotfi Zadeh, inventor of fuzzy logic, wins the BBVA Foundation Frontiers of Knowledge Award for enabling computers and machines to behave and decide like human beings