2D feature tracking algorithm for motion analysis. - Srivatsan Krishnan; Daniel Raviv (Pattern Recognit., 1995)

MAVBench: Micro Aerial Vehicle Benchmarking. - Behzad Boroujerdian; Hasan Genc; Srivatsan Krishnan; Wenzhi Cui; Aleksandra Faust; Vijay Janapa Reddi (MICRO, 2018)

MAVBench: Micro Aerial Vehicle Benchmarking. - Behzad Boroujerdian; Hasan Genc; Srivatsan Krishnan; Wenzhi Cui; Marcelino Almeida; Kayvan Mansoorshahi; Aleksandra Faust; Vijay Janapa Reddi (CoRR, 2019)

Air Learning: An AI Research Platform for Algorithm-Hardware Benchmarking of Autonomous Aerial Robots. - Srivatsan Krishnan; Behzad Boroujerdian; William Fu; Aleksandra Faust; Vijay Janapa Reddi (CoRR, 2019)

The Role of Compute in Autonomous Aerial Vehicles. - Behzad Boroujerdian; Hasan Genc; Srivatsan Krishnan; Bardienus Pieter Duisterhof; Brian Plancher; Kayvan Mansoorshahi; Marcelino Almeida; Wenzhi Cui; Aleksandra Faust; Vijay Janapa Reddi (CoRR, 2019)

Learning to Seek: Autonomous Source Seeking with Deep Reinforcement Learning Onboard a Nano Drone Microcontroller. - Bardienus Pieter Duisterhof; Srivatsan Krishnan; Jonathan J. Cruz; Colby R. Banbury; William Fu; Aleksandra Faust; Guido C. H. E. de Croon; Vijay Janapa Reddi (CoRR, 2019)

Quantized Reinforcement Learning (QUARL). - Srivatsan Krishnan; Sharad Chitlangia; Maximilian Lam; Zishen Wan; Aleksandra Faust; Vijay Janapa Reddi (CoRR, 2019)

The Sky Is Not the Limit: A Visual Performance Model for Cyber-Physical Co-Design in Autonomous Machines. - Srivatsan Krishnan; Zishen Wan; Kshitij Bhardwaj; Paul N. Whatmough; Aleksandra Faust; Gu-Yeon Wei; David Brooks 001; Vijay Janapa Reddi (IEEE Comput. Archit. Lett., 2020)

Tiny Robot Learning (tinyRL) for Source Seeking on a Nano Quadcopter. - Bardienus Pieter Duisterhof; Srivatsan Krishnan; Jonathan J. Cruz; Colby R. Banbury; William Fu; Aleksandra Faust; Guido C. H. E. de Croon; Vijay Janapa Reddi (ICRA, 2021)

RL-Scope: Cross-stack Profiling for Deep Reinforcement Learning Workloads. - James Gleeson 001; Moshe Gabel; Gennady Pekhimenko; Eyal de Lara; Srivatsan Krishnan; Vijay Janapa Reddi (MLSys, 2021)

Machine Learning-Based Automated Design Space Exploration for Autonomous Aerial Robots. - Srivatsan Krishnan; Zishen Wan; Kshitij Bhardwaj; Paul N. Whatmough; Aleksandra Faust; Sabrina M. Neuman; Gu-Yeon Wei; David Brooks 001; Vijay Janapa Reddi (CoRR, 2021)

Widening Access to Applied Machine Learning with TinyML. - Vijay Janapa Reddi; Brian Plancher; Susan Kennedy; Laurence Moroney; Pete Warden; Anant Agarwal; Colby R. Banbury; Massimo Banzi; Matthew Bennett; Benjamin Brown; Sharad Chitlangia; Radhika Ghosal; et al. (CoRR, 2021)

AutoSoC: Automating Algorithm-SOC Co-design for Aerial Robots. - Srivatsan Krishnan; Thierry Tambe; Zishen Wan; Vijay Janapa Reddi (CoRR, 2021)

Air Learning: a deep reinforcement learning gym for autonomous aerial robot visual navigation. - Srivatsan Krishnan; Behzad Boroujerdian; William Fu; Aleksandra Faust; Vijay Janapa Reddi (Mach. Learn., 2021)

The Role of Compute in Autonomous Micro Aerial Vehicles: Optimizing for Mission Time and Energy Efficiency. - Behzad Boroujerdian; Hasan Genc; Srivatsan Krishnan; Bardienus Pieter Duisterhof; Brian Plancher; Kayvan Mansoorshahi; Marcelino Almeida; Wenzhi Cui; Aleksandra Faust; Vijay Janapa Reddi (ACM Trans. Comput. Syst., 2021)

Tiny Robot Learning: Challenges and Directions for Machine Learning in Resource-Constrained Robots. - Sabrina M. Neuman; Brian Plancher; Bardienus Pieter Duisterhof; Srivatsan Krishnan; Colby R. Banbury; Mark Mazumder; Shvetank Prakash; Jason Jabbour; Aleksandra Faust; Guido C. H. E. de Croon; Vijay Janapa Reddi (AICAS, 2022)

Roofline Model for UAVs: A Bottleneck Analysis Tool for Onboard Compute Characterization of Autonomous Unmanned Aerial Vehicles. - Srivatsan Krishnan; Zishen Wan; Kshitij Bhardwaj; Ninad Jadhav; Aleksandra Faust; Vijay Janapa Reddi (ISPASS, 2022)

Automatic Domain-Specific SoC Design for Autonomous Unmanned Aerial Vehicles. - Srivatsan Krishnan; Zishen Wan; Kshitij Bhardwaj; Paul N. Whatmough; Aleksandra Faust; Sabrina M. Neuman; Gu-Yeon Wei; David Brooks 001; Vijay Janapa Reddi (MICRO, 2022)

Multi-Agent Reinforcement Learning for Microprocessor Design Space Exploration. - Srivatsan Krishnan; Natasha Jaques; Shayegan Omidshafiei; Dan Zhang; Izzeddin Gur; Vijay Janapa Reddi; Aleksandra Faust (CoRR, 2022)

QuaRL: Quantization for Fast and Environmentally Sustainable Reinforcement Learning. - Srivatsan Krishnan; Max Lam; Sharad Chitlangia; Zishen Wan; Gabriel Barth-Maron; Aleksandra Faust; Vijay Janapa Reddi (Trans. Mach. Learn. Res., 2022)

ArchGym: An Open-Source Gymnasium for Machine Learning Assisted Architecture Design. - Srivatsan Krishnan; Amir Yazdanbakhsh; Shvetank Prakash; Jason Jabbour; Ikechukwu Uchendu; Susobhan Ghosh; Behzad Boroujerdian; Daniel Richins; Devashree Tripathy; Aleksandra Faust; Vijay Janapa Reddi (ISCA, 2023)

A2Perf: Real-World Autonomous Agents Benchmark. - Ikechukwu Uchendu; Jason Jabbour; Korneel Van den Berghe; Joel Runevic; Matthew Stewart; Jeffrey Ma; Srivatsan Krishnan; Izzeddin Gur; Austin Huang; Colton Bishop; Paige Bailey; Wenjie Jiang 001; et al. (CoRR, 2025)

COSMIC: Enabling Full-Stack Co-Design and Optimization of Distributed Machine Learning Systems. - Aditi Raju; Jared Ni; William Won; Changhai Man; Srivatsan Krishnan; Srinivas Sridharan 002; Amir Yazdanbakhsh; Tushar Krishna; Vijay Janapa Reddi (CoRR, 2025)

Multi-Agent Reinforcement Learning for Sample-Efficient Deep Neural Network Mapping. - Srivatsan Krishnan; Jason Jabbour; Dan Zhang; Natasha Jaques; Aleksandra Faust; Shayegan Omidshafiei; Vijay Janapa Reddi (CoRR, 2025)