Pranay Seshadri
Georgia Institute of Technology
Associate Professor,
Daniel Guggenheim School of Aerospace Engineering,
Faculty, Center for Machine Learning
Georgia Institute of Technology.
Email | Publications
Events
Towards Net-Zero Aviation with AI
I am co-organizing a mini-workshop on how AI can supercharge efforts to decarbonize aviation in the short-term. This will be held on June 4-5 2024 at Georgia Tech. For more information, do check out the workshop page.
Teaching
Spring 2024
AE2010/2011: Fluid Fundamentals & Thermodynamics
AE8803: Gaussian Processes for Machine Learning
Research
Turbomachinery & Aviation Lab
My research spans turbomachinery, aviation, and machine intelligence, with a primary focus on leveraging sensor data. I employ both experimental and computational methods to address key grand challenges. To learn more about my team’s contributions within these individual areas, please click the links below.
Turbomachinery
Grand challenges
- More rigorously quantify the performance (and its breakdown) of existing compressors, pumps and turbines.
- Predict the performance of new turbomachinery systems with applcations in heavy and renewable industries.
Civil Aviation
Grand challenges
- Identify operational and policy-level decisions to decarbonize aviation within the next 3-5 years.
- Develop calculators for more precisely predicting airline and airport emissions and their breakdown.
Machine Intelligence
Grand challenges
- Build probabilistic pattern of life models that can forecast well into the future.
- Ensure models are low latency and that they can ingest hetrogenous data.
Team
I serve as the technical and pastrol advisor for the following graduate students:
- Bipin Koirala (PhD, Machine Learning)
- Grant Ewing (MS, Aerospace Engineering)
- Samantha Allen (MS, Aerospace Engineering)
- jointly advised with Dan Koltyar
- Howon Lee (PhD, Aerospace Engineering)
- jointly advised with Juergen Rauleder
Contact
Laboratory
Room 108 Montgomery Knight
270 Ferst Drive,
Atlanta, GA 30332