Aakash Lahoti
PhD Candidate
Pittsburgh, Pennsylvania, United States
Summary
👤
Senior🎓
Top SchoolAakash Lahoti is a PhD candidate in Carnegie Mellon’s Machine Learning Department with nine years of industry experience building production ML systems and backend services. He focuses on designing efficient, theoretically grounded state space models and applying them across domains, from low-latency text-to-speech at Cartesia to harmful-content classifiers at Meta. Previously at Google he developed backend APIs for Google Assistant’s media vertical, bringing product-facing engineering rigor to research problems. His strong academic record (MS and PhD work at CMU, BTech from IIT Kanpur) complements hands-on model training and deployment experience. Notably, he bridges theory and practice by optimizing SSMs for real-world latency constraints—a recurring theme in both research and internships. Based in Pittsburgh, he combines deep ML research with pragmatic engineering for production-scale systems.
8 years of coding experience
1 year of employment as a software developer
Indian Institute of Technology KanpurDoctor of Philosophy - PhD, Machine learning, Doctor of Philosophy - PhD, Machine learning at Carnegie Mellon University
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (5)
cups9
printing9
pdf-files8
printer8
proxies6
Programming languages (2)
Github contributions (5)
aakashlahoti/Google-Summer-Of-Code-2019-The-Linux-Foundation
Jul 2019 - Aug 2019
Contributions:6 commits, 5 pushes, 1 branch in 1 month
aakashlahoti/pappl
May 2020 - Jun 2020
PAPPL - Printer Application Framework
Contributions:14 pushes in 1 month
application-frameworkprinter
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