By area

This page has papers by area in rough reverse chronological order. Here are papers in Chronological order and a wordcloud.

Earth Systems

Satellite Remote Sensing

These papers develop computational methods to monitor and understand environmental change from space. My recent research has focused on creating better representations from remote sensing data—from developing temporal embeddings that capture surface dynamics (TESSERA) to addressing practical challenges like cloud corruption in time series. A major thread of my work involves using spaceborne lidar (GEDI) to quantify tropical forest disturbance and recovery, developing both the analytical frameworks and computational tools needed to assess forest health at scale. I'm also interested in bridging the gap between raw spectral data and actionable ecological insights, whether through end-to-end learning with physics-based models or multi-modal approaches for tracking restoration efforts in threatened ecosystems like the Atlantic Forest.

• Z. Feng et al. "TESSERA: Temporal Embeddings of Surface Spectra for EarthcRepresentation and Analysis" arXiv preprint arXiv:2506.20380 (August 2025).

• A. Holcomb, P. Burns, S. Keshav, D.A. Coomes, "Quantifying the Impacts of Tropical Forest Disturbance Using Repeat GEDI Footprints", Proc. American Geophysical Union, December 2024.

• F. Begliomini, D.A. Coomes, S. Keshav, P. Brancalion, "Using Multi-Modal Orbital Remote Sensing to Track Ecological Restoration in the Atlantic Forest", Proc. American Geophysical Union, December 2024.

• M. C. Lisaius, A. Blake, S. Keshav and C. Atzberger, "Using Barlow Twins to Create Representations from Cloud-corrupted Remote Sensing Time Series," IEEE J. of Selected Topics in Applied Earth Observations and Remote Sensing , 17 , pp13162-13168, August 2024.

• Y. She, C. Atberger, A. Blake, and S. Keshav, "From Spectra to Biophysical Insights; End-to-End Learning with a Biased Radiative Transfer Model", Proc. ICLR CCAI Workshop, May 2024. (The link is to the extended Arxiv version).

• A. Holcomb, P. Burns, S. Keshav, and D. Coomes, "Repeat GEDI footprints measure moderate-scale tropical forest disturbance," Remote Sensing of the Environment, 308, May 2024.

• A. Holcomb, S. Mathis, S. Keshav, and D. Coomes, Computational tools for assessing forest recovery with GEDI shots and forest change maps, Science of Remote Sensing, 8 , November 2023.

• S. Ghasemitaheri, A. Holcomb, L. Golab, and S. Keshav, On the Data Quality of Remotely Sensed Forest Maps, Proc. VLDB Workshops, April 2023.

UAV and Ground-based Forest Monitoring

Alongside satellite-based monitoring, I've been developing practical tools for forest measurement using accessible technology. A key focus has been enabling accurate tree diameter estimation with mobile phones—moving from proof-of-concept demonstrations to robust algorithms and user-friendly apps that work with coarse optical depth maps. To support this and other computer vision applications in forestry, my students and I have created SPREAD, a large-scale synthetic dataset that provides high-fidelity training data for multiple forest vision tasks. This work is motivated by the need for scalable, low-cost methods to measure forest carbon and monitor forest health on the ground, complementing what we can see from space. By combining UAV imagery, mobile phone technology, and machine learning, I'm working to ease forest monitoring and make it feasible for researchers, land managers, and communities to track changes in their local forests.

• Z. Feng, Y. She, and S. Keshav, SPREAD: A large-scale, high-fidelity synthetic dataset for multiple forest vision tasks, Ecological Informatics, 87, February 2025.

• Z. Feng, M. Xie, A. Holcomb, and S. Keshav, "An app for tree trunk diameter estimation from coarse optical depth maps", Ecological Informatics, 82 , September 2024.

• A. Holcomb, L. Tong, and S. Keshav, Robust Single-Image Tree Diameter Estimation with Mobile Phones, MDPI Remote Sensing, 15, 772, January 2023.

• 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.

Carbon Credits

I'm deeply engaged in addressing the credibility crisis in forest carbon markets and nature-based climate solutions. Much of my work focuses on strengthening the integrity of REDD+ credits through objective assessment methods—including using placebo tests to evaluate counterfactual baselines and developing optimal strategies to anticipate and mitigate the risk of carbon credit reversals. I've contributed to the development of the PACT tropical forest accreditation methodology and explored how to realize the social value of impermanent carbon credits while being forthright about the challenges facing current carbon markets. A key thread of this research involves leveraging computer science and digital technologies to create more robust, comparable, and transparent carbon assets that can support both forest restoration and climate mitigation. Ultimately, I'm working toward trusted marketplaces for nature-based solutions where the environmental claims are verifiable, the risks are properly managed, and the incentives genuinely support forest conservation rather than undermining it.

• E.-P. Rau, et al. "Strengthening the integrity of REDD+ credits: objectively assessing counterfactual methods using placebos." Environmental Research Letters, October 2025.

• E-P. Rau, J. Gross, D. A. Coomes, T. Swinfield, A. Madhavapeddy, A. Balmford, and S. Keshav, "Mitigating risk of credit reversal in nature-based climate solutions by optimally anticipating carbon release", J. Carbon Management ,15 (1), September 2024.

• S. Jaffer, M.W. Dales, P. Ferris, D. Sorensen, T. Swinfield, R. Message, S. Keshav, and A. Madhavapeddy, "Global, robust and comparable digital carbon assets", Poster, Proc. IEEE ICBC 2024, May 2024.

• A. Balmford et al. (2023). PACT Tropical Moist Forest Accreditation Methodology v2.0. Cambridge Open Engage doi:10.33774/coe-2023-g584d-v5 This content is a preprint and has not been peer-reviewed.

• A. Balmford, S. Keshav, F. Venmans et al. Realizing the social value of impermanent carbon credits, Nature Climate Change, 13 , October 2023. Preprint

• A. Balmford et al., Credit credibility threatens forests, Science , 380, 466-467, May 2023.

• G. Gordon, A. Holcomb, T. Kelly, S. Keshav, J. Ludlam, and A. Madhavapeddy, How Computer Science Can Aid Forest Restoration, arXiv, September 2021.

• S. Keshav, Towards a Trusted Marketplace for Nature-based Solutions, Poster at Climate Exp0, May 2021.

Climate Science and Policy

My work in climate science and policy spans from foundational questions about data and modeling to practical pathways for decarbonization. I've explored novel approaches to generating long-term climate datasets using expired weather forecasts and contributed to policy discussions on carbon offsetting and nature-based climate solutions. Recognizing that the computing and communications infrastructure itself has climate impacts, I've worked on understanding how to make internet research more climate-friendly. A significant portion of my research has focused on the energy transition, using agent-based modeling to understand the adoption dynamics of solar photovoltaics, battery storage, and electric vehicles across different jurisdictions, and exploring how policy design—from pricing mechanisms to demand response systems—can accelerate decarbonization. I've also applied data-driven methods to understand public discourse around climate action, including sentiment analysis during the COVID-19 recovery period. Throughout this work, I'm interested in how computational tools, behavioral insights, and thoughtful policy design can work together to address the climate crisis.

• P. Dolezal, S.Keshav, and E. Shuckburgh, Using expired weather forecasts to supply up to 10 000 years of weather data, European Geophysical Union General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-17356.

• Cambridge Zero Policy Forum (2021) Carbon Offsetting & Nature-based Solutions to Climate Change, University of Cambridge, November 2021.

• V. Bajpai, O. Hohlfeld, J. Crowcroft, and S. Keshav, Towards Climate-Friendly Internet Research, Dagstuhl Seminar 21272, Dagstuhl Reports, Vol. 11, Issue 6, pp. 14-37, December 2021.

• M.S. Parsa, L. Golab, and S. Keshav, Climate Action During COVID-19 Recovery and Beyond: A Twitter Text Mining Study, Proc. International Conference on Social, Cultural, and Behavioral Modeling, July 2021.

• A. Adepetu, A. Alyousef, S.Keshav, and H. de Meer, Comparing Solar Photovoltaic and battery adoption in Ontario and Germany: an agent-based approach, Energy Informatics, Vol. 1, No. 1, July 2018.

• F. Kazhamiaka, P. Jochem, S. Keshav, and C. Rosenberg, "On the influence of jurisdiction on the profitability of residential photovoltaic-storage systems: A multi-national case study," Energy Policy, Vol. 109, Oct. 2017.

• A. Pat, K. Larson, and S. Keshav, Big-Data Mechanisms and Energy-Policy Design, Proc. AAAI 2016.

• A. Adepetu, V. Arya, and S. Keshav, An Agent-Based Electric Vehicle Ecosystem Model: San Francisco Case Study, Transport Policy, 46 (2016): 109-122.

• A. Adepetu and S. Keshav, The Relative Importance of Price and Driving Range on Electric Vehicle Adoption: Los Angeles Case Study, Transportation Journal, August 2015 pp. 1-21.

• S. Singla, S. Keshav, Demand Response through a Temperature Setpoint Market in Ontario, IEEE SmartGridComm, November 2012.

Energy Systems

Solar PV and Battery Storage

I've spent over a decade working on the technical and economic challenges of integrating solar photovoltaics and battery storage into homes and energy systems. A central focus has been developing robust, practical methods for sizing PV and storage systems—determining how much solar capacity and battery storage is needed to meet household energy needs, particularly as electric vehicles become part of the home energy ecosystem. My recent work includes tools like SOPEVS and SolExplore that optimize the sizing and operation of PV-EV-integrated homes using successive refinement approaches, building on years of research comparing different sizing methodologies and developing synthetic data generators to create realistic usage patterns for system design.

Underpinning these optimization tools is extensive work on battery modeling and control strategies. I've developed tractable lithium-ion storage models that balance accuracy with computational efficiency, enabling them to be used in large-scale energy system optimization. This includes simple specification-based models derived from manufacturer data sheets, adaptive control strategies using neural networks, and practical approaches for battery operation that work in real-world conditions. I've also explored innovations like dynamic storage resizing, grid-friendly solar panel orientations to flatten the "duck curve," and strategies for firming solar power to make it more reliable and dispatchable.

Beyond the technical optimization, I'm interested in understanding what drives adoption of these technologies and how policy shapes deployment. Through agent-based modeling, I've compared solar and battery adoption patterns across different jurisdictions like Ontario and Germany, examining how factors like electricity pricing, incentives, and regulatory frameworks affect profitability and uptake. I've also worked on practical diagnostic tools using data-driven approaches to identify problems with installed solar systems. This body of work aims to bridge the gap between theoretical optimization and real-world deployment, helping accelerate the transition to distributed renewable energy systems.

• J. Gschwind and S. Keshav, SolExplore: A Successive Refinement Approach for Sizing of PV and Storage Systems in EV-Enabled Homes, To appear, Proc. ACM BuildSys, November 2025.

• J. Gschwind and S. Keshav, Fast Optimal Sizing of Domestic PV Energy Systems, Poster, Proc. ACM eEnergy, June 2025.

• A. Berkes and S. Keshav, SOPEVS: Sizing and Operation of PV-EV-Integrated Modern Homes, Proc. ACM eEnergy 2024, June 2024.

• A. Berkes and S.Keshav, SPAGHETTI: a synthetic data generator for post-Covid electric vehicle usage, Energy Informatics, 7(15), Jan 2024.

• B.G. Huang, F. Kazhamiaka, and S. Keshav, Sizing Solar Panels and Storage for Multiple Roofs, Proc. ACM eEnergy, June 2021.

• J. Deller and S. Keshav, "The Benefits of Dynamically Resizing Storage," Energy Storage Workshop at ACM eEnergy 2020,, June 2020.

• F. Kazhamiaka, Y. Ghiassi-Farokhfal, S. Keshav, and C. Rosenberg, Comparison of Different Approaches for Solar PV and Storage Sizing, Proc. IEEE Transactions on Sustainable Computing, September 2019.

• F. Kazhamiaka, S. Keshav, and C. Rosenberg, Adaptive Battery Control with Neural Networks, Proc. AMLIES Workshop at ACM eEnergy 2019, June 2019.

• S. Sun, F. Kazhamiaka, S. Keshav, and C. Rosenberg, Using Synthetic Traces for Robust Energy System Sizing, Proc. ACM eEnergy 2019, June 2019.

• F. Kazhamiaka, C. Rosenberg, and S. Keshav, Tractable Lithium-Ion Storage Models for Optimizing Energy Systems, Energy Informatics, 2:1, 2019.

• F. Kazhamiaka, S. Keshav, C. Rosenberg, and K.-H. Pettinger, Simple Spec-Based Modelling of Lithium-Ion Batteries, IEEE Transactions on Energy Conversion, Vol 33, No. 4, December 2018.

• A. Adepetu, A. Alyousef, S.Keshav, and H. de Meer, Comparing Solar Photovoltaic and battery adoption in Ontario and Germany: an agent-based approach, Energy Informatics, Vol. 1, No. 1, July 2018.

• F. Kazhamiaka, S. Keshav, and C. Rosenberg, Robust and Practical Approaches for Solar PV and Storage Sizing, Proc. ACM eEnergy 2018, June 2018.

• S. Sun, S. Keshav, C. Rosenberg, M. Peloso, Optimal Matching of Stochastic Solar Generators to Stochastic Loads, Proc. ACM eEnergy 2018, June 2018.

• M. Doroshenko, S. Keshav, C. Rosenberg, Poster: Flattening the Duck Curve Using Grid-friendly Solar Panel Orientation, Proc. ACM eEnergy 2018, June 2018.

• F. Kazhamiaka, P. Jochem, S. Keshav, and C. Rosenberg, "PV-Storage System Profitability in Multiple Jurisdictions," Energy Policy, Vol. 109, Oct. 2017.

• F. Kazhamiaka, C. Rosenberg and S. Keshav, "Practical Strategies for Storage Operation in Energy Systems: Design and Evaluation," IEEE Transactions on Sustainable Energy, vol. 7, no. 4, pp. 1602-1610, Oct. 2016.

• F. Kazhamiaka, C. Rosenberg, S. Keshav, "Li-Ion Storage Models for Energy System Optimization: The Accuracy-Tractability Tradeoff," Proc. ACM e-Energy 2016.

• A. Adepetu and S. Keshav, "Understanding Solar PV and Battery Adoption in Ontario: An Agent-Based Approach," Proc. ACM e-Energy 2016.

• Y. Ghiassi-Farrohkfal, C. Rosenberg, S. Keshav, and M.-B. Adjaho, "Optimal Operation and Design of Hybrid Energy Storage Systems," IEEE Journal on Selected Areas in Communications (JSAC), Special Issue on Emerging Technologies, Vol. 34, # 3, March 2016.

• Y. Ghiassi-Farrokhfal, F. Kazhamiaka, C. Rosenberg, and S. Keshav, Optimal Design of Solar PV Farms with Storage, IEEE Transactions on Sustainable Energy, Vol 6 No. 5, October 2015.

• X.Gao, L. Golab, S. Keshav, What's wrong with my solar panels: a data-driven approach, Proc. Workshop on Energy Data Management, March 2015, pp. 86-93.

• Y. Ghiassi-Farrokhfal, S. Keshav, and C. Rosenberg, Towards a Realistic Performance Analysis of Storage Systems in Smart Grids, IEEE Trans on Smart Grids, Vol 6, No. 1, January 2015, pp. 402-410.

• Y. Ghiassi-Farrokhfal, S. Keshav, C. Rosenberg, and F. Ciucu. Solar Power Shaping: An Analytical Approach, IEEE Transactions on Sustainable Energy, Vol 6, No. 1, Jan. 2015.

• Y. Ghiassi-Farrokhfal, S. Keshav, and Catherine Rosenberg, An EROI-Based Analysis of Renewable Energy Farms with Storage, Proc. ACM e-Energy 2014, June 2014.

• S. Singla, Y. Ghiassi-Farrokhfal, and S. Keshav. Using Storage to Minimize Carbon Footprint of Diesel Generators for Unreliable Grids, IEEE Transactions on Sustainable Energy, Vol 5, No. 4, pp. 1270-1277. 2014.

• S. Singla, Y. Ghiassi-Farrokhfal, and S. Keshav, Battery Provisioning and Scheduling For a Hybrid Battery-Diesel Generator System, ACM Performance Evaluation Review (PER), December 2013.

• S. Singla, Y. Ghiassi-Farrokhfal, and S. Keshav, Near-Optimal Scheduling for a Hybrid Battery-Diesel Generator for Off-Grid Locations, Proc. GreenMetrics Workshop, June 2013.

• Y. Ghiassi-Farrokhfal, S. Keshav, and C. Rosenberg, Firming Solar Power, Extended Abstract/Poster, Proc. ACM SIGMETRICS, June 2013.

Electric Vehicle Systems

My research on electric vehicles spans from understanding real-world usage patterns to developing practical tools for EV integration into energy systems. A major thread has been the WeBike project, where I collected and analyzed extensive data on electric bicycle usage, examining how e-bikes are actually used in practice and comparing these patterns to electric car usage. This work led to insights on range prediction, data stream management challenges, and the factors that influence adoption. I've also developed non-intrusive methods like EVSense for detecting EV charging without requiring smart meters or instrumentation, and explored how blockchain technology can help mitigate trust issues in public charging infrastructure. On the economic and planning side, I've used agent-based modeling to understand EV adoption dynamics—particularly the relative importance of price versus driving range—and analyzed the return on investment for taxi companies transitioning to electric fleets. I've also worked on optimizing EV charging to take advantage of solar generation and developed methods for sizing finite vehicle pools, all aimed at making the transition to electric mobility more practical and economically viable.

• X. Wang, G. Tang, Y. Wang, S. Keshav, and Y. Zhang, EVSense: A Robust and Scalable Approach to Non-Intrusive EV Charging Detection, Proc. ACM eEnergy, June 2022.

• 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.

• C. Gorenflo, L. Golab, and S. Keshav, Mitigating Trust Issues in Electric Vehicle Charging using a Blockchain, Proc. ACM eEnergy 2019, June 2019.

• C. Gorenflo, I. Rios, L. Golab, S. Keshav, "Usage Patterns of Electric Bicycles: An Analysis of the WeBike Project," Journal of Advanced Transportation, October 2017.

• C. Gorenflo, L. Golab, S. Keshav, "Managing Sensor Data Streams: Lessons Learned from the WeBike Project," Proc. SSDBM 2017, June 2017.

• S. Fink, L. Golab, S. Keshav, H. de Meer, "How Similar is the Usage of Electric Cars and Electric Bicycles?", (Invited Paper) Proc. EV-Sys Workshop May 2017.

• I. Rios, L. Golab and S. Keshav, "Analyzing the Usage Patterns of Electric Bicycles,"EV-SYS Workshop at ACM e-Energy, 2016.

• L. Gebhard, L. Golab. S. Keshav, and H. de Meer, "Range prediction for electric bicycles," Proc. ACM e-Energy 2016.

• A. Adepetu, V. Arya, and S. Keshav, An Agent-Based Electric Vehicle Ecosystem Model: San Francisco Case Study, Transport Policy, 46 (2016): 109-122.

• A. Adepetu and S. Keshav, The Relative Importance of Price and Driving Range on Electric Vehicle Adoption: Los Angeles Case Study, Transportation Journal, August 2015 pp. 1-21.

• O. Ardakanian, C. Rosenberg and, S. Keshav, Quantifying the Benefits of Extending Electric Vehicle Charging Deadlines with Solar Generation, Proc. IEEE SMARTGRIDCOMM, November 2014.

• T. Carpenter, S. Keshav, and J.W. Wong, Sizing Finite Population Vehicle Pools, IEEE Trans. on Intelligent Transportation Systems, Volume PP issue 99, Jan 2014.

• T. Carpenter, A. R. Curtis, and S. Keshav, The Return On Investment For Taxi Companies Transitioning To Electric Vehicles, Transportation, June 2013.

• T. Carpenter, Andrew R. Curtis, and S. Keshav, The Return on Investment for Taxi Companies Transitioning to Electric Vehicles, University of Waterloo Tech Report, 2011.

Building and Datacenter Energy Management

My work on building energy management has evolved from developing innovative personal thermal comfort systems to addressing broader challenges of building efficiency and climate resilience. A core thread has been the SPOT series of personalized heating and cooling systems, which allow individuals to maintain thermal comfort while reducing centralized HVAC loads—an approach I've extended by studying how personal environmental comfort systems interact with building-wide climate control. I've developed occupancy detection methods, self-calibrating smart lighting systems, and model predictive control strategies for HVAC that operate across multiple time scales. To support research in this area, I created Beobench, a toolkit that provides unified access to building simulations for reinforcement learning, making it easier to develop and test intelligent building control strategies. Throughout this work, I've also contributed several open datasets on occupancy, thermal comfort, light levels, and snow-covered solar panels to enable broader research in building energy systems.

More recently, my focus has expanded to understanding how buildings perform during climate extremes and how computing infrastructure can be made more energy-efficient. I've developed machine learning approaches for building-level heat risk mapping and fine-grained mapping of urban energy demand during heatwaves, working to assess building liveability through metrics like "activity hours" that capture when indoor conditions remain tolerable during extreme heat events. On the computing side, I've investigated how hybrid heterogeneous clusters can dramatically reduce the energy consumption of large language model inference workloads by developing workload-based energy models and offline optimization strategies. This work reflects a broader interest in making both our built environment and our digital infrastructure more energy-efficient and resilient in the face of climate change.

• A. Domiter and S. Keshav, Fine-Grained Mapping of Urban Energy Demand During Heatwaves, Poster, Proc. ACM eEnergy, June 2025.

• A. Domiter and S. Keshav, Machine Learning for Building-Level Heat Risk Mapping, Proc. ACM eEnergy, June 2025.

• L. Capol, S. Keshav, and Z. Nagy, Activity hours: Assessing liveability during heatwaves, Building and Environment, 269, February 2025.

• G. Wilkins, S. Keshav, and R. Mortier, Offline Energy-Optimal LLM Serving: Workload-Based Energy Models for LLM Inference on Heterogeneous Systems", Proc. HotCarbon Workshop, July 2024.

• G. Wilkins, S. Keshav, and R. Mortier, Hybrid Heterogeneous Clusters Can Lower the Energy Consumption of LLM Inference Workloads", Proc. EEDC workshop at ACM eEnergy 2024, June 2024.

• A. Findeis, F. Kazhamiaka, S. Jeen, and S. Keshav, Beobench: A Toolkit for Unified Access to Building Simulations for Reinforcement Learning, Proc. ACM eEnergy, June 2022.

• Y. Aussat, A. Rosmanis, S. Keshav, A Power-Efficient Self-Calibrating Smart Lighting System, Energy and Buildings Journal version Author's preprint, January 2022.

• S. Doubov, C. Ograda-Bratu, S. Huo, S. Keshav, Camera-based Occupancy Detection Dataset, https://doi.org/10.5683/SP2/X30EPQ, University of Waterloo Dataverse, December 2020.

• J.Y. Lin, C. Ograda-Bratu, S. Huo, and S. Keshav, Detecting Snow Covered Solar Panels Dataset, https://doi.org/10.5683/SP2/ITQPHZ, 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.

• M. Jain, R. Kalaimani, S. Keshav, and C. Rosenberg, "Using Personal Environmental Comfort Systems to Mitigate the Impact of Occupancy Prediction Errors on HVAC Performance," Energy Informatics., December 2018.

• R. Kalaimani, M. Jain, S. Keshav, and C. Rosenberg, On the Interaction between Personal Comfort Systems and Centralized HVAC Systems in Office Buildings, J. Advances in Building Energy Research, August 2018, V7:p.1-29.

• A. Rabbani and S. Keshav, "The SPOT* Personal Thermal Comfort System," Proc. ACM BuildSys'16, November 2016.

• O. Ardakanian, S. Keshav, C. Rosenberg, "Integration of Renewable Generation and Elastic Loads into Distribution Grids," Springer, July 2016.

• R. Kalaimani, S. Keshav, and C. Rosenberg, "Multiple Time-scale Model Predictive Control for Thermal Comfort in Buildings," Poster in ACM e-Energy 2016.

• A. Rabbani and S. Keshav, The SPOT* System for Flexible Personal Heating and Cooling, poster, Best Poster Award, ACM eEnergy 2015, July 2015.

• P.X. Gao and S. Keshav, Optimal Personal Comfort Management Using SPOT+, Proc. BuildSys Workshop, 2013. 'Best Student Paper Award.

• P. X. Gao and S. Keshav, SPOT: A Smart Personalized Thermal Control System, Proc. ACM e-Energy 2013, May 2013.

• O. Ardakanian, S. Keshav, Using Decision Making to Improve Energy Efficiency of Buildings, ICAPS-10 POMDP Practitioners Workshop, May 2010.

Smart Grid and Demand Response

My work on smart grids has focused on developing distributed control algorithms and market mechanisms that enable flexible, responsive electricity systems. A major contribution has been creating real-time distributed control strategies for electric vehicle charging—addressing both the static and dynamic aspects of coordinating large fleets of EVs to avoid grid congestion while meeting user needs. This work, which won Best Paper awards, extends to using EV charging control to provide building load flexibility and exploring how vehicles can provide frequency regulation services through optimal contracting. I've also investigated fundamental concepts like load elasticity and demand response, developing mechanisms such as temperature setpoint markets and analyzing how elastic loads can reduce peak demand and carbon footprints in the residential sector.

Beyond control algorithms, I've worked on the infrastructure and trust mechanisms needed for modern electricity systems. I applied concepts from Internet congestion control and teletraffic theory to power distribution, showing how networking principles can help "green and smarten" the electrical grid. This includes work on efficient demand assignment in multi-connected microgrids, optimal electricity allocation algorithms, and the impact of storage on residential distribution systems. I've also addressed trust and transparency issues by developing efficient, anonymous renewable energy certificate systems using cryptographic techniques, and created tools for processing smart meter data and energy analytics. Throughout this research, I've contributed datasets on high-resolution load measurements and critiqued existing pricing schemes like Ontario's time-of-use tariffs, aiming to make electricity systems both more efficient and more equitable.

• H.S. Bhundar, L. Golab, S. Keshav, Using EV charging control to provide building load flexibility. Energy Informatics, 6(1):5, January 2023.

• O. Ardakanian, S. Huo, and S. Keshav, 6-second load measurement dataset,https://doi.org/10.5683/SP2/R4SVBF, University of Waterloo Dataverse, December 2020.

• D. Karakashev, S. Gorbunov, and S. Keshav, "Making Renewable Energy Certificates Efficient, Trustworthy, and Anonymous," Proc. IEEE SmartGridComm, November 2020.

• N. Koochakzadeh, R. P. Singh, L. Golab, S. Keshav, Computing Electricity Consumption Profiles from Household Smart Meter Data, 3rd Workshop on Energy Data Management, 2014

• O. Ardakanian, S. Keshav, and C. Rosenberg,Real-Time Distributed Control for Smart Electric Vehicle Chargers: From a Static to a Dynamic Study, IEEE Transactions on Smart Grid, vol.5, no.5, pp.2295,2305, Sept. 2014.

• H. Zarkoob, S. Keshav, and C. Rosenberg, Optimal Contracts For Providing Load-Side Frequency Regulation Service Using Fleets of Electric Vehicles, J. Power Sources, Volume 241, 1 November 2013, Pages 94-111.

• A. Adepetu, E. Rezaei, D. Lizotte, and S. Keshav, Critiquing Time-Of-Use Pricing in Ontario, Proc. IEEE SmartGridComm Symposium 2013, Vancouver, October 2013.

• K Kogan, S. Nikolenko, S. Keshav, and A. Lopez-Ortiz, Efficient Demand Assignment in Multi-Connected Microgrids, Extended Abstract, Proc. SustainIT, October 2013.

• S. Alamdari, T. Biedl, T. M. Chan, E. Grant, K.R Jampani, S. Keshav, A. Lubiw and V. Pathak, Smart-grid Electricity Allocation via Strip Packing with Slicing, Proc. WADS 2013, August 2013.

• O. Ardakanian, C. Rosenberg, and S. Keshav, Distributed Control of Electric Vehicle Charging, Proc. ACM e-Energy 2013, May 2013. Winner of Best Paper award

• K. Kogan, S. Nikolenko, S. Keshav, and A. Lopez-Ortiz, Efficient Demand Assignment in Multi-Connected Microgrids, Proc. e-Energy 2013, May 2013. (Poster)

• R.P. Singh, S. Keshav, and T. Brecht, A Cloud-Based Consumer-Centric Architecture for Energy Data Analytics, Proc. ACM e-Energy 2013, May 2013.

• S. Alamdari, T. Biedl, T. M. Chan, E. Grant, K.R. Jampani, S. Keshav, A. Lubiw and V. Pathak. Smart-grid Electricity Allocation via Strip Packing with Slicing, Proc. EuroCG, March 2013.

• P. Srikantha, S. Keshav, C. Rosenberg, Distributed Control for Reducing Carbon Footprint in the Residential Sector, IEEE SmartGridComm, November 2012. Winner of Best Paper Award

• S. Keshav and C. Rosenberg, On Load Elasticity, in IEEE Comsoc MMTC-E letter, #8, Vol. 7 Nov. 2012.

• S. Singla, S. Keshav, Demand Response through a Temperature Setpoint Market in Ontario, IEEE SmartGridComm, November 2012.

• O. Ardakanian, C. Rosenberg, and S. Keshav, Real Time Distributed Congestion Control for Electrical Vehicle Charging (invited paper), Proc. ACM SIGMETRICS Greenmetrics Workshop, June 2012.

• O. Ardakanian, C. Rosenberg, and S. Keshav, On the Impact of Storage in Residential Power Distribution Systems, Proc. Greenmetrics Workshop, June 2012.

• O. Ardakanian, S. Keshav, and C. Rosenberg,On the Use of Teletraffic Theory in Power Distribution Systems, Proc. e-Energy, May 2012.

• P. Srikantha, C. Rosenberg, and S. Keshav, An Analysis of Peak Demand Reductions due to Elasticity of Domestic Appliances, Proc. e-Energy, May 2012.

• T. Carpenter, S. Singla, P. Azimzadeh, and S. Keshav, The Impact of Electricity Pricing Schemes on Storage Integration In Ontario, Proc. e-Energy, May 2012.

• S. Keshav and C. Rosenberg, How Internet Concepts and Technologies Can Help Green and Smarten the Electrical Grid, Selected as one of the best papers in the ACM SIGCOMM Green Networking Workshop 2010, Republished in ACM SIGCOMM CCR, January 2011.

• S. Keshav and C. Rosenberg, How Internet Concepts and Technologies Can Help Green and Smarten the Electrical Grid, Proc. ACM SIGCOMM Green Networking Workshop, August 2010.

Computer Networking

My foundational work in computer networking centers on congestion control and fair resource allocation—problems I tackled in my PhD thesis at UC Berkeley, which won both the Sakrison Prize and later a SIGCOMM Test-of-Time Award. I developed fair queueing algorithms and control-theoretic approaches to flow control that became influential in understanding how to manage congestion in high-speed networks. This early work extended into ATM networks, quality of service mechanisms, and rate-based service disciplines, where I contributed to protocol design, network measurement tools, and the ENTRAPID protocol development environment. I also worked on fundamental questions of network architecture, exploring axiomatic foundations for communication and reflecting on paradoxes and design principles that shape how networks evolve. This theoretical foundation has informed all my subsequent networking research.

A major thread of my work has been in wireless networks and mobile systems, spanning from enterprise WiFi optimization to novel RFID sensing applications. I developed CENTAUR, a hybrid data path architecture for centralized WLANs that won a Best Paper Award at MobiCom, and worked extensively on interference mitigation, spectrum sensing, and self-managing wireless architectures. More recently, I've pioneered the use of commodity RFID systems for environmental sensing—developing battery-free soil moisture sensors for sustainable greenhouse monitoring, creating in-class response systems, and demonstrating practical "RFID hacking" techniques that extend the capabilities of these ubiquitous tags. I've also contributed to understanding energy consumption in mobile devices and developed systems like OmniVoice for mobile communications in resource-constrained settings.

My work on opportunistic and delay-tolerant networks was motivated by bridging the digital divide and providing internet access in challenging environments. I led the development of KioskNet, a system that used "mechanical backhaul"—physically transporting data on storage devices carried by buses—to provide low-cost internet access to rural kiosks in developing regions. This work required rethinking fundamental networking assumptions: developing robust communication protocols for intermittent connectivity, addressing security challenges for disconnected nodes, creating fair scheduling algorithms for data ferrying networks, and understanding vehicular opportunistic communication patterns. The insights from this work extend beyond developing regions to any scenario where connectivity is intermittent or opportunistic, and helped establish design principles for robust communication in constrained computing environments.

My more recent networking research has tackled challenges in data center networks and distributed systems, including blockchain technologies. On the data center side, I've worked on cost-effective network upgrades using heterogeneous equipment (LEGUP), low-latency network designs (Quartz), and optimization frameworks for unstructured topologies (REWIRE), as well as exploring how to make data centers more energy-efficient through VM consolidation strategies. In the blockchain space, I've developed FastFabric to dramatically scale Hyperledger Fabric's transaction throughput, explored hybrid execution approaches, created TimeFabric for trusted time in distributed ledgers, and designed the Canopus consensus protocol for massively parallel agreement. I've also applied blockchain to practical problems like creating trustworthy renewable energy certificates and digital carbon assets, while maintaining a skeptical perspective on when blockchain is—and isn't—the right solution.

Wireless Networks and Mobile Systems

• J. Wang, L. Chang, S. Aggarwal, O. Abari, and S. Keshav. Sustainable and Low-Cost Greenhouse Soil Moisture Monitoring Using Battery-Free RFID Sensors, ACM Transactions on Sensor Networks, January 2025.

• J. Wang, L. Chang, O. Abari, and S. Keshav, How Manufacturers Can Easily Improve Working Range of Passive RFIDs, Proc. IEEE SECON 2022, October 2022.

• J. Wang, L. Chang, S. Aggarwal, O. Abari, and S. Keshav, "Soil Moisture Sensing with Commodity RFID Systems," Proc. ACM Mobisys, 2020.

• L. Chang, J. Wang, O. Abari, and S. Keshav, "A Battery-Free In-Class Response System using RFID Tags, " Proc. IOTDI Conference, 2020.

• J. Wang, O. Abari, and S. Keshav, RFID Hacking for Fun and Profit., GetMobile: Mobile Comp. and Comm. 23, 1 (July 2019), 21-23.

• J. Wang, O. Abari, L. Chang, and S. Keshav, Are RFID Sensing Systems Ready for the Real World?, Proc. Mobisys 2019, June 2019

• J. Wang, O. Abari, and S. Keshav, Challenge: RFID Hacking for Fun and Profit, Proc. ACM MOBICOM, October 2018.

• E. Oliver and S. Keshav, An Empirical Approach to Smartphone Energy Level Prediction, The 13th International Conference on Ubiquitous Computing (UbiComp 2011), September 2011.

• N. Ahmed, S. Keshav, and K. Papagiannaki, OmniVoice: A Mobile Voice Solution for Small-scale Enterprises, Proc. MobiHoc, May 2011.

• V. Shrivastava*, N. Ahmed*, S. Rayanchu*, S. Banerjee, S. Keshav, K. Papagiannaki, A. Mishra. "CENTAUR: Realizing the Full Potential of Centralized WLANs using a Hybrid Data Path." , ACM MobiCom, Beijing, September 2009. Winner of Best paper award

• N. Ahmed, U. Ismail, S. Keshav, and K. Papagiannaki, Online Estimation of RF Interference, Proc. ACM Conext, Madrid, December 2008.

• E. Oliver, S. Keshav, Design Principles for Opportunistic Communication in Constrained Computing Environments Proc. MobiCom Workshop on Wireless Networks and Systems for Developing Regions (WiNS-DR), San Francisco, September 2008.

• N. Ahmed, V. Shrivastava, A. Mishra, S. Banerjee, S. Keshav, K. Papagiannaki, Interference Mitigation in Enterprise WLANs through Speculative Scheduling (Extended Abstract), ACM Mobicom 2007, September 2007.

• N. Ahmed and S. Keshav, SMARTA: A Self-Managing Architecture for Thin Access Points, Proc. CoNEXT'06, December 2006.

• N. Ahmed, D. Hadaller, and S. Keshav, GUESS: Gossiping Updates for Efficient Spectrum Sensing, Proc. ACM MobiShare- 1st International Workshop on Decentralized Resource Sharing in Mobile Computing and Networking, September 2006.

• N. Ahmed and S. Keshav, A Successive Refinement Approach to Wireless Infrastructure Network Deployment, Proc. WCNC, April 2006.

• H.J. Pan and S. Keshav, Detection and Repair of Faulty Access Points, Proc. WCNC, April 2006.

Blockchain and Consensus

• S. Jaffer, M.W. Dales, P. Ferris, D. Sorensen, T. Swinfield, R. Message, S. Keshav, and A. Madhavapeddy, "Global, robust and comparable digital carbon assets", Poster, Proc. IEEE ICBC 2024, May 2024.
• A. Mitra, C. Gorenflo, L. Golab, and S. Keshav, TimeFabric: Trusted Time for Hyperledger Fabric, Proc. Foundations and Applications of Blockchain, May 2021.
• C. Gorenflo, S. Lee, L. Golab, S. Keshav, FastFabric: Scaling Hyperledger Fabric to 20,000 Transactions per Second, International Journal of Network Management, September 2020.
• C. Gorenflo, L. Golab, S. Keshav, "XOX Fabric: A hybrid approach to blockchain transaction execution," Proc. IEEE ICBC, 2020.
• R. Agarwal, D. Kumar , L. Golab, S. Keshav, "Consentio: Managing Consent to Data Access using Permissioned Blockchains," Proc. IEEE ICBC, 2020.
• C. Gorenflo, S. Lee, L. Golab, S. Keshav. FastFabric: Scaling Hyperledger Fabric to 20,000 Transactions per Second, Proc. IEEE ICBC, May 2019.
• S. Keshav, A Skeptical Look at Blockchains, (invited paper), Proc. 2019 Decentralization Conference, Ann Arbor, April 2019.
• S. Keshav How blockchain can democratize green power, The Conversation, January 2018.
• S. Rizvi, B, Wong, and S. Keshav, "Canopus: A Scalable and Massively Parallel Consensus Protocol," Proc. CoNEXT 2017, December 2017. Best Paper Award Nominee.
• A. Allavena and S. Keshav, LOT: Fast, Efficient and Robust In-Network Computation, UW Technical Report 2006-22, July 2006.
• A. Allavena, Q. Wang, I. Ilyas, and S. Keshav, LOT: A Robust Overlay for Distributed Range Query Processing, UW Technical Report 2006-21, July 2006.
• S. Keshav, Efficient and Decentralized Computation of Approximate Global State, ACM Computer Communication Review, Jan. 2006.

Network Architecture and Protocols

• M. Karsten, S. Keshav, S. Prasad, and O. Beg An Axiomatic Basis for Communication, ACM SIGCOMM 2007, August 2007.

• M. Karsten, S. Keshav, and S. Prasad, An Axiomatic Basis for Communication, Proc. HotNets'06, November 2006.

• S. Keshav Paradoxes of Internet Architecture, Invited paper, IEEE Internet Computing, January/February 2018.

• S. Keshav, Why Cell Phones Will Dominate the Future Internet, Editorial in ACM Computer Communication Review, April 2005.

• S. Keshav, The Riches of White Space, Editorial in The Mark News, October 2009.

• S. Keshav, Multimodal Applications and Multiplanar Networks, Unpublished manuscript, March 1999.

Data Center Networks

• Y.J. Liu, P.X. Gao, B. Wong, and S. Keshav, Quartz: A New Design Element for Low-Latency DCNs, Proc. ACM SIGCOMM, August 2014.

• A. Curtis, S. Keshav and A. Lopez-Ortiz, LEGUP: Using Heterogeneity to Reduce the Cost of Data Center Network Upgrades, Proc. ACM CoNEXT, December 2010.

• A. R. Curtis, S. Keshav, and A. Lopez-Ortiz, Reducing Waste in Data Center Network Upgrades, University of Waterloo Technical Report CS-2010-08, April 2010.

• A. R. Curtis, T. Carpenter, M. Elsheikh, A. Lopez-Ortiz and S. Keshav. REWIRE: An Optimization-based Framework for Unstructured Data Center Network Design, Proc. INFOCOM, March 2012.

• X.Gao, A.R. Curtis, B. Wong, and S. Keshav, It's Not Easy Being Green, Proc. ACM SIGCOMM, August 2012.

• R. P. Singh, T. Brecht, and S. Keshav. Towards VM Consolidation Using a Hierarchy of Idle States, Proc. ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments (VEE), March 2015

• R.P. Singh, T. Brecht, and S. Keshav, IP address multiplexing for VEEs, ACM SIGCOMM CCR, April 2014.

Opportunistic and Delay-Tolerant Networks

• S. Guo, M. Derakhshani, M.H. Falaki, U. Ismail, R. Luk, E.A. Oliver, S. Ur Rahman, A. Seth, M.A. Zaharia, S. Keshav, Design and implementation of the KioskNet system, Computer Networks, Available online 10 August 2010.

• S. Keshav, Design Principles for Robust Opportunistic Communication, Proc. ACM SIGCOMM Workshop on Networked Systems for Developing Regions (NSDR 2010), June 2010.

• S. Keshav, Design Principles for Robust Opportunistic Communication, Technical Report CS-2009-35, University of Waterloo, November 2009.

• S. Ur Rahman, U. Hengartner, U. Ismail and S. Keshav, Practical Security for Rural Internet Kiosks, Proc. of ACM SIGCOMM Workshop on Networked Systems for Developing Regions (NSDR 2008), Seattle WA, August 2008.

• S. Guo, M.H. Falaki, E.A. Oliver, S. Ur Rahman, A. Seth, M.A. Zaharia, and S. Keshav Very Low-Cost Internet Access Using KioskNet, ACM Computer Communication Review, October 2007.

• S. Guo and S. Keshav, Fair and Efficient Scheduling in Data Ferrying Networks, Proc. CoNEXT 2007, December 2007.

• M.A. Zaharia, and S. Keshav Fast and Optimal Scheduling Over Multiple Network Interfaces, University of Waterloo Technical Report CS-2007-36, October 2007.

• D. Hadaller, S. Keshav, T. Brecht, S. Agarwal, Vehicular Opportunistic Communication Under the Microscope, Proc. Mobisys 2007, Puerto Rico, June 2007.

• M. Thomas, A. Gupta, and S. Keshav, Group Based Routing in Disconnected Ad Hoc Networks, Proc. 13th Annual IEEE International Conference on High Performance Computing, December 2006.

• D. Hadaller, S. Keshav, and T. Brecht, MV-MAX: Improving Wireless Infrastructure Access for Multi-Vehicular Communication,Proc. SIGCOMM 2006 Workshop on Challenged Networks, September 2006.

• A. Seth, D. Kroeker, M. Zaharia, S. Guo, S. Keshav,Low-cost Communication for Rural Internet Kiosks Using Mechanical Backhaul,Proc. MOBICOM 2006, September 2006.

• S. Guo, M. Ghaderi, A. Seth, S.Keshav,Opportunistic Scheduling in Ferry-Based Networks,Proc. WNEPT 2006, August 2006.

• A. Seth and S. Keshav, Practical Security for Disconnected Nodes, Proc. First Workshop on Secure Network Protocols (NPSEC), November 2005.

Peer-to-Peer Systems

• M.A. Zaharia and S.Keshav,Gossip-based Search Selection in Hybrid Peer-to-Peer Networks, J. Concurrency and Computation: Practice and Experience, 2007.

• M.A. Zaharia, A. Chandel, S. Saroiu, and S. Keshav, Finding Content in File-Sharing Networks When You Can't Even Spell, Proc. IPTPS, Seattle, February 2007.

• M.A. Zaharia and S. Keshav,Gossip-Based Search Selection in Hybrid Peer-to-Peer Networks,Proc. IPTPS, February 2006.

• M. Zaharia and S. Keshav, Adaptive Peer-to-Peer Search, University of Waterloo Technical Report 2004-55, November 2004.

Network Measurement and Performance

• J. Wang, Y. Zhang, and S. Keshav, Understanding End-to-End Performance: Testbed and Preliminary Results, Proc. of IEEE Global Internet Symposium, November 2001.

• L. Qiu, Y. Zhang and S. Keshav, Understanding the Performance of Many TCP Flows, Computer Networks, 37(3-4), pp. 277-306, November 2001

• L. Qiu, Y. Zhang and S. Keshav, On Individual and Aggregate TCP Performance, Proceedings of the 7th IEEE International Conference on Network Protocols (ICNP '99), Toronto, Canada, November 1999.

• Y. Zhang, L. Qiu, and S. Keshav, Speeding Up Short Data Transfers: Theory, Architecture Support, and Simulation Results, Proc. NOSSDAV 2000, Chapel Hill, NC, June 2000.

• J. Wang and S. Keshav Efficient and Accurate Ethernet Simulation, Proceedings of the 24th IEEE Annual Conference on Local Computer Networks 1999.

• R. Siamwalla, R. Sharma, and S. Keshav, Discovering Internet Topology, Unpublished manuscript, July 1999.

• S. Keshav, REAL : A Network Simulator, UCB CS Tech Report 88/472, December 1988.

ATM and QoS

• M. Grossglauser, S. Keshav , D. Tse, RCBR: A Simple and Efficient Service for Multiple Time-Scale Traffic, IEEE/ACM Transactions on Networking, December 1997.

• C.R. Kalmanek, S. Keshav, W.T. Marshall, S.P. Morgan, and R.C. Restrick, Xunet 2: Lessons from an Early Wide-Area ATM Testbed, IEEE/ACM Transactions on Networking, April 1997.

• A.E. Kaplan, S. Keshav, N.L. Schryer and J.H. Venutolo, An Internet Accessible Telepresence, Multimedia Systems Journal, March 1997.

• R. Ahuja, S. Keshav and H. Saran, Design ,Implementation, and Performance Measurement of a Native-Mode ATM Transport Layer (Extended Version), IEEE/ACM Transactions on Networking August 1996.

• A. Jain and S. Keshav, Native-mode ATM in FreeBSD: Experience and Performance, Proc. NOSSDAV '96, April 1996.

• R. Ahuja, S. Keshav and H. Saran, Design, Implementation, and Performance of a Native-Mode ATM Transport Layer, Proc. IEEE INFOCOM '96, March 1996.

• M. Grossglauser and S. Keshav, On CBR Service, Proc. IEEE INFOCOM '96, March 1996.

• S. Keshav , C. Lund, S. Phillips, N. Reingold and H. Saran, " An Empirical Evaluation of Virtual Circuit Holding Time Policies in IP-over- ATM Networks, IEEE Journal on Selected Areas in Communication, October 1995.

• M. Grossglauser, S. Keshav , D. Tse, RCBR: A Simple and Efficient Service for Multiple Time-Scale Traffic, Proc. SigComm '95, August 1995.

• M. Grossglauser, S. Keshav , D. Tse, The Case Against VBR, Proc. NOSSDAV '95, April 1995.

• R. Sharma and S. Keshav, Signaling and Operating System Support for Native-Mode ATM Applications, Proc. ACM SigComm'94, August 1994.

• H. Saran and S. Keshav, An Empirical Evaluation of Virtual Circuit Holding Times in IP-over-ATM Networks, Proc. Infocom '94, June 1994.

• S. Keshav, Experience with Large Videoconferences in Xunet 2, Proc. INET'94 , June 1994.

• S. Keshav and H. Saran, Semantics and Implementation of a Native-Mode ATM Protocol Stack, AT&T Bell Laboratories Technical Memorandum, February 1994.

• H. Saran, S. Keshav and C.R. Kalmanek, A Scheduling Discipline and Admission Control Policy for Xunet 2, Proc. NOSSDAV '93, November 1993; also Multimedia Systems Journal, 1994.

• A. Berenbaum, M.J. Dixon, A. Iyengar and S. Keshav, A Flexible ATM Host-Interface for Xunet 2, IEEE Network Magazine, V7, N4, July 1993.

• A. Banerjea and S. Keshav, Queueing Delays in Rate-Controlled Networks, Proc. Infocom'93, March 1993.

• C. Parris, S. Keshav and D. Ferrari, A Framework for the Study of Pricing in Integrated Networks, ICSI Technical Report TR-92-016 and AT&T Bell Labs Technical Memorandum TM-920105-03, January 1992.

Security and Privacy

• R. P. Singh, B. Cassell, S. Keshav, T. Brecht, "TussleOS: Managing Privacy Versus Functionality Trade-Offs on IoT Devices", ACM SIGCOMM Computer Communication Review July 2016.
• S. Ur Rahman, U. Hengartner, U. Ismail and S. Keshav, Practical Security for Rural Internet Kiosks, Proc. of ACM SIGCOMM Workshop on Networked Systems for Developing Regions (NSDR 2008), Seattle WA, August 2008.
• A. Seth and S. Keshav, Practical Security for Disconnected Nodes, Proc. First Workshop on Secure Network Protocols (NPSEC), November 2005.

Multimedia and Video Systems

• D. Bergmark and S. Keshav, Building Blocks for Internet Telephony, IEEE Communications Magazine, April 2000.

• S. Keshav and S. Paul, Centralized Multicast, Proc. ICNP '99, October 1999.

• M. Grossglauser, S. Keshav , D. Tse, The Case Against VBR, Proc. NOSSDAV '95, April 1995.

• S. Keshav, Experience with Large Videoconferences in Xunet 2, Proc. INET'94 , June 1994.

• A.E. Kaplan and S. Keshav, Talking Heads Made Simple, Presented at the 1993 International Worshop on Facial Animation, Philadelphia, Pennsylvania, November 1993.

Network Tools and Development

• X.W.Huang, R. Sharma, and S. Keshav, The ENTRAPID Protocol Development Environment, Proc. Infocom '99, March 1999.
• S. Keshav and R. Sharma, Achieving Quality of Service through Network Performance Management, Proc. NOSSDAV '98, July 1998.
• S. Keshav and R. Sharma, Issues and Trends in Router Design, IEEE Communications Magazine, May 1998.
• R. Sharma, S. Keshav, M. Wu, and L. Wu, Environments for Active Networks, Proc. NOSSDAV '97, May 1997.

Congestion Control and Flow Control

• S. Keshav, Reflections on "A Control-Theoretic Approach to Flow Control" (invited paper), ACM SIGCOMM CCR, October 2019.
• S. Keshav, Reflections on "Analysis and Simulation of a Fair Queueing Algorithm" (invited paper), ACM SIGCOMM CCR, October 2019.
• S. Keshav and S.P. Morgan, SMART: Retransmission: Performance with Random Losses and Overload, Proc. INFOCOM '97, April 1997.
• S.P. Morgan and S. Keshav, Packet-Pair Rate Control - Buffer Requirements and Overload Performance, Technical Memorandum, AT&T Bell Laboratories, October 1994.
• S. Keshav, Packet-Pair Flow Control -- AT&T Bell Laboratories Technical Memorandum 11272-940927-TM, September 1994.
• H. Kanakia, S. Keshav and P. Mishra, A Benchmark Suite for Comparing Congestion Control Schemes, Technical Memorandum, AT&T Bell Laboratories, July 1992.
• S. Keshav, Flow Control in High-Speed Networks with Long Delays, Proceedings of INET '92, Kobe, Japan, June 1992.
• S. Keshav, Implementing Stop-and-Go using Hierarchical Round Robin Service, Technical Memorandum TM-911018-15, AT&T Bell Laboratories, October 1991.
• S. Keshav, Congestion Control in Computer Networks PhD Thesis, published as UC Berkeley TR-654, September 1991. (Awarded the Sakrison Prize for the best PhD thesis in the EECS department, 1992.)
• S. Keshav, On the Efficient Implementation of Fair Queueing, Journal of Internetworking: Research and Experience, V2, N3, September 1991.
• S. Keshav, A Control-theoretic Approach to Flow Control, Proc. ACM SigComm 1991, September 1991. Winner of Best Student Paper Award and Test-of-Time Award
• H. Zhang and S. Keshav, Comparision of Rate-Based Service Disciplines, Proc ACM SigComm 1991, September 1991.
• S. Keshav, A. Agrawala and S. Singh, Design and Analysis of a Flow Control Algorithm for a Network of Rate Allocating Servers, Protocols for High Speed Networks II, IFIP Press, April 1991.
• C.R. Kalmanek, H. Kanakia, S. Keshav, Rate-Controlled Servers for Very High-Speed Networks, Proc. GLOBECOM '90, San Diego, December 1990.
• S. Singh, A. Agrawala and S. Keshav, Deterministic Analysis of Flow and Congestion Control Policies in Virtual Circuits, University of Maryland Tech Report TR 2490, June 1990.
• A. Demers, S. Keshav and S. Shenker, Analysis and Simulation of a Fair Queueing Algorithm, Journal of Internetworking Research and Experience, V1, N1, pp 3-26, September 1990; also in Proc. ACM SigComm 1989, pp 1-12, September 1989. Winner of Test-of-Time Award
• S. Keshav, A Mechanism for Congestion Control in Computer Networks, Unpublished preprint, April 1989.

Miscellaneous

Beyond my technical research, I've contributed to the computer science research community through education, community building, and reflections on how we organize and conduct research. I've written two textbooks on computer networking—"An Engineering Approach to Computer Networking" and "Mathematical Foundations of Computer Networking"—and created widely-used educational resources including my guide "How to Read a Paper," which has helped countless students learn to navigate academic literature. I've also developed tutorials on topics like model predictive control to bridge different research communities. My service to the field includes leadership roles as SIGCOMM Chair and editor of ACM's Computer Communication Review, experiences I've reflected on in invited papers that examine the health and evolution of our research community.

I care deeply about how we organize and improve our research processes. I've written extensively about scaling academic publication to match the growth of our field, proposed recommendations for designing effective hybrid conferences in the post-pandemic era, and advocated for better research practices through pieces like "The Value of Weekly Reports." I've also engaged with policy and public discourse, including providing testimony to the U.S. Senate on text messaging pricing and contributing to interdisciplinary venues like the Cambridge Journal of Law, Politics, and Art. This work reflects my belief that computer scientists have both an opportunity and responsibility to contribute beyond our immediate technical domains—improving how we work together as a community and engaging with the broader societal implications of our research.

• S. Keshav, The Value of Weekly Reports, Manuscript, October 2023.

• V. Bajpai, O. Hohfield, J. Crowcroft, S. Keshav, H. Schulzrinne, J. Ott, S. Ferlin, G. Care, A. Hines, A. Rake, Recommendations for Designing Hybrid Conference, ACM SIGCOMM Computer Communications Review, July 2022.

• S. Keshav, A Bit of Conversation, Cambridge Journal of Law, Politics, and Art, June 2021.

• S. Keshav, A Tutorial on Model Predictive Control, Dec 2020.

• S. Keshav, Reflections on being SIGCOMM Chair 2013-2017 (invited paper), ACM SIGCOMM CCR, October 2019.

• S. Keshav, Reflections on being CCR Editor 2008-2012 (invited paper), ACM SIGCOMM CCR, October 2019.

• S. Keshav, Mathematical Foundations of Computer Networking, Addison-Wesley, April 2012.

• S. Keshav, The Relevance of Journals to Computer Science, Editorial in ACM SIGCOMM Computer Communication Review, January 2010.

• S. Keshav, The SIGCOMM Community, Editorial in ACM SIGCOMM Computer Communication Review, October 2009.

• S. Keshav, Taking account, Editorial in ACM SIGCOMM Computer Communication Review, July 2009.

• S. Keshav, The cost of text messaging, Testimony at the hearing on Cell Phone Text Messaging Rate Increases and the State of Competition in the Wireless Market held by the Senate Subcommittee on Antitrust, Competition Policy and Consumer Rights, June 16, 2009

• S. Keshav, Bubbles, Editorial in ACM SIGCOMM Computer Communication Review, April 2009.

• J. Crowcroft, S. Keshav, and N. McKeown, Scaling the Academic Publication Process to Internet Scale, Communications of the ACM, January 2009.

• J. Crowcroft, S. Keshav, and N. McKeown, Scaling Internet Research Publication Processes to Internet Scale, Proc. Workshop on Organizing Workshops, Conferences, and Symposia in Computer Systems, April 2008.

• S. Keshav, How to Read a Paper, ACM Computer Communication Review, July 2007.

• S. Keshav, Ensim ServerXchange - the Key to Hosting Automation: A White Paper, Ensim Technical Publication July 2001.

• S. Keshav, An Engineering Approach to Computer Networking, Addison-Wesley, 1997.

• S. Keshav, Report on Workshop on Quality of Service Issues in High Speed Networks, ACM SIGCOMM Computer Communication Review, October 1992.

• P.S. Khedkar and S. Keshav, Fuzzy Prediction of Timeseries, Proc. IEEE Conference on on Fuzzy Systems, March 1992.

• S. Keshav, A Workload Model for Large Distributed File Systems, Proc. 19th Annual Pittsburgh Conference on Simulation and Modeling, May 1988.

• S. Keshav and I.S. Mumick, Implementation of Prolog, Bachelor's thesis, IIT Delhi, May 1986.