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* Privacy-preserving crowdsensing (with Bihan Liu, Steven Chai, and Fiodar Kazhamiaka) | * Privacy-preserving crowdsensing (with Bihan Liu, Steven Chai, and Fiodar Kazhamiaka) | ||
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* Designing an index to measure researcher influence and also identify potential research fraud (with Ankai Jie) | * Designing an index to measure researcher influence and also identify potential research fraud (with Ankai Jie) | ||
Revision as of 11:25, 20 January 2022
Contents
What I'm working on
This page is my attempt to keep track of all the things I'm working on...
Energy systems
- Using Reinforcement Learning to control the operation of storage systems (with Arduin Findeis and Fiodar Kazhamiaka)
- Studying the impact of climate change on the transmission grid (with Petr Dolezal and Emily Shuckburgh)
- Controlling EV charging to allow condominiums and commercial building to become 24/7 renewable-powered (with Harsimrat Bhundar and Lukasz Golab, with support from SWTCH Energy, Inc.)
- Studying the impact of soiling on solar panels (with Abhinav Bora (Waterloo), Sharat Singh and Hugh Hunt (Quadrical))
Forest conservation and restoration
- Cambridge Centre for Carbon Credits( with Tom Swinfield, Anil Madhavapeddy, David Coomes, and Andrew Balmford)
- Creating a trusted marketplace for nature-based solutions (with Tom Shan, Hector Wei, Derek Sorensen, Anil Madhavapeddy)
- Estimating the rate of carbon sequestration in tropical forests (with Amelia Holcomb, Simon Mathis and David Coomes)
Misc.
- Privacy-preserving crowdsensing (with Bihan Liu, Steven Chai, and Fiodar Kazhamiaka)
- Designing an index to measure researcher influence and also identify potential research fraud (with Ankai Jie)
Completed work and outcomes
Summer 2021
- Estimating the reduction in lighting levels of commercial buildings from Earth observation (with Abhinav Bora)
Lent 2021
- Using Time-of-flight sensors on mobile phones for depth-assisted segmentation of tree images (with Bill Tong, Megan Penny, and Amelia Holcomb)
- A. Holcomb, B. Tong, M. Penny, and S. Keshav, Measuring Forest Carbon with Mobile Phones, Poster Proc. ACM Mobisys, Winner of the Best Poster Award, June 2021.
- Linking Earth observation to carbon sequestration certificates (with Alan Marko, Tom Shan, and David Liu)
- Computing the solar and storage system sizing for the British Antarctic Survey base in Rothera, Antarctica (with Brad Huang, Fiodar Kazhamiaka, and Nopi Exizidou)
- B.G. Huang, F. Kazhamiaka, and S. Keshav, Sizing Solar Panels and Storage for Multiple Roofs, To Appear, Proc. ACM eEnergy, June 2021.
- Speeding up Hyperledger Fabric with pre-validation (with Rishav Agarwal, Christian Gorenflo, and Lukasz Golab)
- Implementing RCanopus (with Christian Gorenflo, Ashwin Sekhari, Qingnan Duan, Linguan Wang, Lukasz Golab, Bernard Wong, and (at UMass) Stephen Lee and Prashant Shenoy)
Fall 2020
- Improving the performance of Individual-Based Models for forests (with Siyi Ji)
- Supporting time-based smart contracts in Hyperledger Fabric (with Aritra Mitra, Christian Gorenflo, and Lukasz Golab)
- A. Mitra, C. Gorenflo, L. Golab, and S. Keshav, TimeFabric: Trusted Time for Hyperledger Fabric, To Appear, Proc. FAB, May 2021.
- Curating datasets collected from ISS4E over the past decade (with Siqing Huo)
- O. Ardakanian, S. Huo, and S. Keshav, 2020, 6-second load measurement dataset,https://doi.org/10.5683/SP2/R4SVBF, University of Waterloo Dataverse, December 2020.
- J.Y. Lin, C. Ograda-Bratu, S. Huo, and S. Keshav, 2020, Detecting Snow Covered Solar Panels Dataset, https://doi.org/10.5683/SP2/ITQPHZ, University of Waterloo Dataverse, December 2020.
- S. Doubov, C. Ograda-Bratu, S. Huo, S. Keshav, 2020, Camera-based Occupancy Detection Dataset, https://doi.org/10.5683/SP2/X30EPQ, University of Waterloo Dataverse, December 2020.
- Y. Aussat, C. Ograda-Bratu, S. Huo, S. Keshav, "Office Light Level dataset", https://doi.org/10.5683/SP2/3BCADM, University of Waterloo Dataverse, November 2020.
- A. Rabbani, C. Ograda-Bratu, S. Huo, S. Keshav, "Personal thermal comfort and occupancy dataset", https://doi.org/10.5683/SP2/2NWMDY, University of Waterloo Dataverse, November 2020.
- C. Gorenflo, I.Rio, L. Golab, C. Ograda-Bratu, S. Huo, S. Keshav, "Webike dataset", https://doi.org/10.5683/SP2/7OAETS, University of Waterloo Dataverse, November 2020.
Summer 2020
- Designing a trusted smart meter to ensure that data that enters a blockchain can be relied upon. (with Dimcho Karakashev and Sergey Gorbunov)
- D. Karakashev, S. Gorbunov, and S. Keshav, "Making Renewable Energy Certificates Efficient, Trustworthy, and Anonymous," Proc. IEEE SmartGridComm, November 2020.
- Estimating IUCN Red List status of birds from Earth observation (with David Wesby, David Coomes, BirdLife International, and the Royal Society for the Protection of Birds)
- Creating a website for homeowners and businesses to determine how many solar panels and how large a storage battery to buy to achieve a certain level of grid independence (with Brad Huang and Fiodar Kazhamiaka)
Winter/Spring 2020
- Raspberry-Pi system to read analog meters (with Ivy Liu, Yerbol Aussat, and Costin Ograda-Bratu)
- Better teleconferencing (with David Adeboye)
- Determining when to resize home energy storage systems
- Bachelor's thesis
- J. Deller and S. Keshav, "The Benefits of Dynamically Resizing Storage," Proc. Energy Storage Workshop at ACM eEnergy 2020,, June 2020.
Fall 2019
- Conflict resolution for hot keys in Fabric
- C. Gorenflo, L. Golab, S. Keshav, "XOX Fabric: A hybrid approach to blockchain transaction execution," Proc. IEEE ICBC, 2020.
- Using RFID-based sensors for determining soil moisture level
- J. Wang, L. Chang, S. Aggarwal, O. Abari, and S. Keshav, "Soil Moisture Sensing with Commodity RFID Systems," Proc. ACM Mobisys, 2020.
Summer 2019
- Improving the performance of Hyperledger Fabric
- Gorenflo, S. Lee, L. Golab, S. Keshav. FastFabric: Scaling Hyperledger Fabric to 20,000 Transactions per Second, Proc. IEEE ICBC, May 2019.
- Using Fabric to provide an audit trail for electric vehicle charging
- C. Gorenflo, L. Golab, and S. Keshav, Mitigating Trust Issues in Electric Vehicle Charging using a Blockchain, Proc. ACM eEnergy 2019, June 2019.
- Using deep neural networks to compute optimal (MPC-computed) storage operation strategies
- F. Kazhamiaka, S. Keshav, and C. Rosenberg, Adaptive Battery Control with Neural Networks, Proc. AMLIES Workshop at ACM eEnergy 2019, June 2019.
- Using cloud cover and solar panel images to detect panel soiling and shadowing (with Yingjie Chen)
Spring 2019
- Using IoT to reduce energy costs of lighting (with Yerbol Aussat)
- Managing data consent on Fabric
- * R. Agarwal, D. Kumar , L. Golab, S. Keshav, "Consentio: Managing Consent to Data Access using Permissioned Blockchains," Proc. IEEE ICBC, 2020.
- Reducing the cost of personal thermal comfort systems (with Costin Ograda-Bratu)
Winter 2019
- Using computer vision algorithms to estimate the degree of snow cover on solar panels (with Jia Ying Lin)
- Improving the accuracy of RFID-based sensors (with Ju Wang and Omid Abari)
- J. Wang, O. Abari, L. Chang, and S. Keshav, Are RFID Sensing Systems Ready for the Real World?, Proc. Mobisys 2019, June 2019
- Designing and building an off-grid system to capture e-scooter activity and accidents (with Tingyun Liu and Lime Inc.)
- Improving the description of research outcomes from my energy systems research (with Shela Qiu)
Last updated May 2021