Students
| Current Students: | |
James Dingley
James is a first-year graduate student and Fulbright Scholar in the Engineering Systems Laboratory. His research focus is on the use of machine learning for satellite revenue management.
James graduated from the University of Western Australia with First Class Honours in Mechanical Engineering and Finance. He is the host and lead writer for popular engineering YouTube channel Atomic Frontier (youtube.com/atomicfrontieronline).
Contact: jdingley@mit.edu
| [2022] | Contract Structures for SatCom: How will Competition from LEO Mega Constellations Change How Communications Services Are Purchased? , In New Space (under review), 2022. ( )
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| [2022] | Winning the Internet: A tool for simulating the competitive strategies of satellite-based internet providers , In International Astronautical Congress, 2022. ()
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Skylar Eiskowitz
Skylar Eiskowitz is a second year graduate student and NSF Fellow in the AeroAstro department. Prior to MIT, she received her B.S. in Mechanical Engineering from The Cooper Union for the Advancement of Science and Art in New York City. She is interested in applying techniques for analyzing complex systems to a wide range of industries. As an undergraduate, Skylar interned at Avascent under the Brooke Owens Fellowship, and after graduating, she interned at The Aerospace Corporation.
Contact: eiskowit@mit.edu
| [2021] | Connecting the Other Half: Exploring Options for the 50% of the Population Unconnected to the Internet , In Telecommunications Policy, volume 45, 2021. ()
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| [2022] | Towards Autonomous Satellite Communications: An AI-based Framework to Address System-level Challenges , In International Astronautical Congress, 2022. ()
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| [2022] | Towards Autonomous Satellite Communications: An AI-based Framework to Address System-level Challenges , In AI to Accelerate Science and Engineering Workshop at AAAI Conference on Artificial Intelligence 2022, 2022. ()
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| [2021] | Forecasting Internet Demand in a Satellite Communication Network Using Transfer Learning , In ASCEND 2021, 2021. ()
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| [2020] | Impact of the Lunar Gateway Location on the Human Landing System in case of Permanent Base at the Lunar South Pole , In International Astronautical Congress, 2020. [bib] |
| [2020] | Quantifying the Impact of Cryo-Management, ISRU, and Fuel Cell Lunar Technology Infusion to a Notional Mars LOX/LH2 Architecture , In 2020 IAC Conference, 2020. ()
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| [2020] | Benchmarking of Crewed Lunar and Mars Mission Architectures , In 2020 IAAA Ascend, 2020. ()
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Juan José Garau Luis
Juan José is a PhD candidate in the System Architecture Group/Engineering Systems Lab of the AeroAstro department at MIT. He works on the application and deployment of Machine Learning algorithms to address complex real-world problems, such as Dynamic Resource Management in satellite communications and molecular optimization. In 2017, under the CFIS program, he received two BSc degrees in Telecommunications Engineering and Industrial Engineering from Universitat Politècnica de Catalunya, in Spain. Earlier that year, he was a visiting student at the System Architecture Group, where he carried out his Bachelor Thesis on the architecture design of a large-scale IoT network. He previously worked as a data scientist at Arcvi and at Barcelona Supercomputing Center. In 2019 he was awarded a La Caixa fellowship. In 2020, he received his Master's degree in Aerospace Engineering from MIT. Later that year, he interned at Novartis AI Innovation Lab. In 2021, he interned at Google Brain. His research interests include autonomous systems, Deep Reinforcement Learning, Meta Learning, and real-world decision-making.
Contact: garau@mit.edu
| [2022] | Frequency Plan Design for Multibeam Satellite Constellations Using Linear Programming (under review) , In IEEE Transactions on Wireless Communications, 2022. ()
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| [2022] | Towards Autonomous Satellite Communications: An AI-based Framework to Address System-level Challenges , In International Astronautical Congress, 2022. ()
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| [2022] | Multi-objective Evolution for Generalizable Policy Gradient Algorithms , In Generalizable Policy Learning in the Physical World Workshop at ICLR 2022, 2022. ()
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| [2022] | Towards Autonomous Satellite Communications: An AI-based Framework to Address System-level Challenges , In AI to Accelerate Science and Engineering Workshop at AAAI Conference on Artificial Intelligence 2022, 2022. ()
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| [2022] | Dynamic Frequency Assignment for Mobile Users in Multibeam Satellite Constellations , In International Astronautical Congress, 2022. ()
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| [2022] | Dynamic resource management algorithm reconfiguration for multibeam satellite constellations , In 2022 IEEE Aerospace Conference, 2022. ()
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| [2021] | Evaluating the progress of Deep Reinforcement Learning in the real world: aligning domain-agnostic and domain-specific research , In Reinforcement Learning for Real Life Workshop at 2021 International Conference on Machine Learning, 2021. ()
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| [2021] | Integrating LSTMs and GNNs for COVID-19 Forecasting , In Time Series Workshop at 2021 International Conference on Machine Learning, 2021. ()
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| [2021] | Applicability and Challenges of Deep Reinforcement Learning for Satellite Frequency Plan Design , In 2021 IEEE Aerospace Conference, 2021. ()
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| [2020] | Allocating Power and Bandwidth in Multibeam Satellite Systems using Particle Swarm Optimization , In 2020 IEEE Aerospace Conference, 2020. ()
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| [2020] | Policy Gradient RL Algorithms as Directed Acyclic Graphs , In arXiv, 2020. ()
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| [2020] | Artificial Intelligence Algorithms for Power Allocation in High Throughput Satellites: A Comparison , In 2020 IEEE Aerospace Conference, 2020. ()
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| [2019] | Problem representation of dynamic resource allocation for flexible high throughput satellites , In 2019 IEEE Aerospace Conference, 2019. ()
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| [2019] | Deep Reinforcement Learning Architecture for Continuous Power Allocation in High Throughput Satellites , In Reinforcement Learning for Real Life Workshop at 2019 International Conference on Machine Learning, 2019. ()
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| [2019] | Deep Reinforcement Learning for Continuous Power Allocation in Flexible High Throughput Satellites , In 2019 IEEE Cognitive Communications for Aerospace Applications Workshop, 2019. ()
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| [2018] | System Architecture for Tracking Passengers inside an Airport Terminal Using RFID , In 2018 IEEE Aerospace Conference, 2018. ()
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| [2020] | A Comparison of Artificial Intelligence Algorithms for Dynamic Power Allocation in Flexible High Throughput Satellites , Master's thesis, Massachusetts Institute of Technology Department of Aeronautics and Astronautics, 2020. ()
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| [2017] | Architecting Internet of Aerospace Things: A System For Tracking Passengers Inside An Airport Terminal , Master's thesis, UPC BarcelonaTech, Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2017. ()
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Joel Jurado
Joel Jurado is in the final year of a BSc in Telecommunications Engineering at Universitat Politècnica de Catalunya (UPC). He is currently working on his Bachelor Thesis on dynamic resource management and optimization in satellite constellations as a visiting student in the System Architecture Group, in the Department of Aeronautics and Astronautics at Massachusetts Institute of Technology (MIT).
As an undergraduate, he participated in the CBI program, in a project that combines technologies from ATTRACT EU and CERN with a multi-disciplinary team to give solutions that impact society positively. He also interned in SENER Engineering, where he worked on the development of a cybersecurity methodology in order to assess and mitigate threats in the transportation sector.
Contact: jurado@mit.edu
Kir Latyshev
Kir holds a Master's degree in Space and Engineering Systems from the Skolkovo Institute of Science and Technology, and two Bachelor’s degrees, in Rocket Engineering and in Management, from the Moscow Aviation Institute. Kir’s industry experience includes working for 8 years at the Energia Rocket Space Corporation where he was involved in trajectory design for the Corporation’s lunar projects. At MIT, his research interests include application of system architecting methodology to space exploration systems.
Contact: latyshev@mit.edu
| [2021] | Lunar Human Landing System Architecture Tradespace Modeling , In Acta Astronautica, volume 161, 2021. ()
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| [2020] | Technology Roadmap for Future Lunar Human Landing Systems , In ASCEND Conference, 2020. [bib] |
| [2020] | Impact of the Lunar Gateway Location on the Human Landing System in case of Permanent Base at the Lunar South Pole , In International Astronautical Congress, 2020. [bib] |
| [2020] | Quantifying the Impact of Cryo-Management, ISRU, and Fuel Cell Lunar Technology Infusion to a Notional Mars LOX/LH2 Architecture , In 2020 IAC Conference, 2020. ()
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Nils Pachler
Nils Pachler is PhD student in the System Architecture Group, in the AeroAstro department at MIT. He has completed a Masters in Aeronautics and Astronautics at MIT, and a double BS degree in Informatics Technology and Aerospace Engineering under the CFIS (Interdisciplinary Higher Education Centre) program from Universitat Politècnica de Catalunya. Nils carried out his Bachelor Thesis at MIT on dynamic allocation of resources in a multibeam satellite system.Nils has previous research experience in the ARCO research group at UPC. This group is specialized in hardware accelerators and neural networks. Within this group, Nils tried to replicate the current state of the art in speech translation neural networks models. He has also previously worked at LudiumLab, a Spanish company for playing videogames on the cloud. Nils was the main responsible of the core product of the company, as well as one of the researchers of future improvements. He mainly worked in video and audio codification algorithms and hardware encoders. Recently, Nils has also been involved in Wise Systems Inc., a company specialized in logistics optimization for delivery services. Within this company, Nils helped move forward the development of the core product to achieve a higher performance.
Contact: pachler@mit.edu
| [2022] | Frequency Plan Design for Multibeam Satellite Constellations Using Linear Programming (under review) , In IEEE Transactions on Wireless Communications, 2022. ()
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| [2020] | Static beam placement and frequency plan algorithms for LEO constellations , In International Journal of Satellite Communications and Networking, 2020. ()
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| [2022] | Beam-to-Satellite Scheduling for High Throughput Satellite Constellations Using Particle Swarm Optimization , In IEEE Aerospace Conference, 2022. ()
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| [2022] | Towards Autonomous Satellite Communications: An AI-based Framework to Address System-level Challenges , In International Astronautical Congress, 2022. ()
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| [2022] | Towards Autonomous Satellite Communications: An AI-based Framework to Address System-level Challenges , In AI to Accelerate Science and Engineering Workshop at AAAI Conference on Artificial Intelligence 2022, 2022. ()
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| [2022] | Dynamic Frequency Assignment for Mobile Users in Multibeam Satellite Constellations , In International Astronautical Congress, 2022. ()
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| [2021] | A Genetic Algorithm for Beam Placement in High-Throughput Satellite Constellations , In IEEE Cognitive Communications for Aerospace Applications Workshop, 2021. ()
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| [2021] | An Updated Comparison of Four Low Earth Orbit Satellite Constellation Systems to Provide Global Broadband , In IEEE International Workshop on Satellite Mega-Constellations in the 6G Era, 2021. ()
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| [2020] | Allocating Power and Bandwidth in Multibeam Satellite Systems using Particle Swarm Optimization , In 2020 IEEE Aerospace Conference, 2020. ()
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| [2020] | Artificial Intelligence Algorithms for Power Allocation in High Throughput Satellites: A Comparison , In 2020 IEEE Aerospace Conference, 2020. ()
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| [2022] | A complete resource allocation framework for flexible high throughput satellite constellations , Master's thesis, Massachusetts Institute of Technology Department of Aeronautics and Astronautics, 2022. ()
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| [2019] | Power and Bandwidth allocation for High-Throughput Satellites using Particle Swarm Optimization , Master's thesis, UPC BarcelonaTech, Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2019. ()
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