I currently work at Planet Labs as an Edge Compute/Machine Learning Engineer. I have worked on Pelican's onboard compute system on the NVIDIA Jetson platform, as the first employee on the Edge Compute team. My previous experience includes integrated photonics at X, the moonshot factory (formerly Google [x]), and I also led all onboard electronics development for Imperial College London Rocketry.
I started this blog for technical sewing projects. There are countless blogs from the early to mid 2010s that have been invaluable to my sewing journey, and I hope to contribute to that body of knowledge. I might occasionally write about fashion, research, or other topics also.
I wrote this blog platform called Spoingo. I also host a tree-based productivity software called Treetrack.
Contact: shreeyam [at] mit [dot] edu
Education
Massachusetts Institute of Technology (MIT)
PhD Spacecraft Systems and Sensors, minor in AI and Computer Vision
2024 - 2025Thesis: Spacecraft Autonomy through Computer Vision and Onboard Planning
SM Aeronautics and Astronautics
2020 - 2022GPA: 5.0/5.0
Thesis: Optical Performance and Prototyping of a Liquid Lens Laser Communications Transceiver
Imperial College London
2016 - 2020MEng Aeronautical Engineering with a Year Abroad
Degree Classification: First Class Honours
Thesis: Design of low leakage MEMS valves for spacecraft applications
Experience
MIT Space Telecommunications, Astronomy and Radiation Laboratory
2020 - PresentResearch Assistant (PI: Prof. Kerri Cahoy) | Cambridge, MA
- Conducted space environment testing and prototyping with NASA for a novel lasercom pointing and tracking system using liquid lenses.
- Trained machine learning models and created a dataset for on-orbit cloud segmentation as part of a computer vision pipeline to identify ocean fronts.
- Tested and validated machine learning algorithms on ESA's OPS-SAT mission.
- Designed algorithms for dynamic alteration of spacecraft imaging schedules based on inputs from external perception systems.
Planet Labs
2022 - 2024Edge Compute/Machine Learning Engineer | San Francisco, CA
- Developed next-generation onboard compute platforms for Earth-observing satellite missions using NVIDIA GPUs.
- Designed, specified, and developed hardware for a low-power computer vision instrument.
- Trained machine learning vision models for spacecraft perception and trajectory planning.
X Development LLC (formerly Google[x])
2021Intern @X | Mountain View, CA
- Interned under Project Taara to provide low-cost free-space optical communications (FSOC) internet access for underdeveloped countries.
- Conducted communications architecture analysis for optically preamplified direct detection and coherent detection techniques.
- Modeled integrated photonics components to assess the capabilities of each architecture.
Intelligent Environments Europe Ltd (ieDigital)
2016Software Developer Intern | London, UK
- Worked as a full stack software developer intern writing C# across teams managed under agile methodology.
- Automated part of the workflow for business analysts using Python, saving tens of hours on importing old functional specifications into JIRA.
- Described by the Chief Architect as a "Senior Software Developer disguised as an Intern."
Skills
Programming Languages
Python, C, C++, C#, MATLAB, Verilog
Software
Microsoft Office, SolidWorks, Altium, PyTorch, Docker
Languages
English (Native), Hindi (Fluent), Korean (Intermediate)
Projects & Extracurricular Activities
Imperial College London Rocketry
June 2019 - July 2020Electronics & Payload Team Lead
- One of four executive leads of an 80-member team.
- Led design and manufacture of all rocket electronics, including avionics systems, telemetry, data acquisition, throttle control system, and payload.
Publications
2024
BeaverCube II: Using AI-Optimized Processors on Earth-Observing CubeSats for Autonomous Image Analysis and Intelligent Data Handling
Adam Bahlous-Boldi, Celvi Lisy, Neelambar Mondal, Brianna Ferro, Shreeyam Kacker, Mary Dahl, Madeline Anderson, Kerri Cahoy
38th Annual AIAA/USU Conference on Small Satellites
Reinforcement-Learned Lookahead Heuristics for Earth-Observing Satellites
Shreeyam Kacker, Kerri Cahoy
38th Annual AIAA/USU Conference on Small Satellites
2023
MOEMS-based lens-assisted beam steering for free-space optical communications
Daniel A Goldman, Paul Serra, Shreeyam Kacker, Lucas Benney, Daniel Vresilovic, Steven J Spector, Kerri Cahoy, Jordan S Wachs
IEEE Journal of Lightwave Technology, Vol.41(9)
Systems and Methods for Cloud Avoidance
Kiruthika Devaraj, Shreeyam Kacker
United States Patent and Trademark Office Application 18/345,883
Fast ocean front detection using deep learning edge detection models
Violet Felt, Shreeyam Kacker, Joe Kusters, John Pendergrast, Kerri Cahoy
IEEE Transactions on Geoscience and Remote Sensing 61
Optical Performance of Commercial Liquid Lens Assemblies in Microgravity
Shreeyam Kacker, Kerri L Cahoy
SPIE Optical Engineering, Vol.62(11)