Ph.D. 2021 · Computer Vision Engineer, Danfoss Power Solutions (as listed)
Joined Fall 2016Now: Computer Vision Engineer, Danfoss Power Solutions
- Ph.D., Mechanical Engineering, Iowa State University, 2021
- M.S., Computer Science, Iowa State University, 2021
- M.S., Mechanical Engineering, Iowa State University, 2018
- B.Tech., Mechanical Engineering, NIT Rourkela, 2016
Homagni joined the lab in Fall 2016. His research interests included probabilistic graphical modeling, reinforcement learning, and anomaly detection. He has a burning passion for robotics and was the go-to person for any robotics project in the lab. He worked on the design and control of agricultural robots, human-computer interaction for the TurtleBot, and visuomotor control of the one-armed Sawyer robot.
He graduated from the SCS Lab in May 2021 and then joined Danfoss Power Solutions as a Computer Vision Engineer. His recent work spans vision-language models, multimodal representation learning, efficient ML, robotics, and cyber-physical systems.
Research interests: Vision-language models, multimodal representation learning, efficient ML, robotics, cyber-physical systems
Publications with the lab (17)
- Few-shot deep learning for AFM force curve characterization of single-molecule interactions — Patterns (2023)
- A modular vision language navigation and manipulation framework for long horizon compositional tasks in indoor environment — Frontiers in Robotics and AI (2022)
- Multimodal sensor fusion framework for residential building occupancy detection — Energy and buildings (2022)
Show all 17
- Few shot clustering for indoor occupancy detection with extremely low quality images from battery free cameras — Iowa State University (2021)
- Whisper: wireless home identification and sensing platform for energy reduction — Journal of Sensor and Actuator Networks (2021)
- Battery-free camera occupancy detection system — Proceedings of the 5th international workshop on embedded and mobile deep … (2021)
- Data-Driven Performance Monitoring of Dynamical Systems Using Granger Causal Graphical Models — Journal of Dynamic Systems Measurement and Control (2020)
- Granger causality based hierarchical time series clustering for state estimation — IFAC-PapersOnLine (2020)
- A perspective on multi-agent communication for information fusion — NeurIPS 2019 Workshop on Visually Grounded Interaction and Language (2019)
- For publication in 2019 acc a flexible framework for building occupancy detection using spatiotemporal pattern networks — 2019 American Control Conference (ACC) (2019)
- Learning State Switching for Improved Exploration in Multi-sensor Environments — (2019)
- Learning State Switching for Multi-sensor Integration — (2019)
- Occupancy sensing in buildings: A review of data analytics approaches — Energy and Buildings 188 (2019)
- Exploring Granger causality in dynamical systems modeling and performance monitoring — 2018 IEEE Conference on Decision and Control (CDC) (2018)
- Navigation Strategies for a Multi-Robot Ground-Based Row Crop Phenotyping Platform — (2018)
- A novel multirobot system for plant phenotyping — Robotics (2018)
- Autonomous Mobile Sensing Platform for Spatio-Temporal Plant Phenotyping — (2017)
hsaha (@) iastate.eduPersonal WebsiteLinkedInGoogle ScholarGitHub