| 2026 | AAAI | IMPACT: Integrated Multimodal Pipeline for Rapid Accident Causality Tracking (Student Abstract). | Vashu Chauhan, Avinash Anand, Manisha Luthra, Ulison Jean Lopes dos Santos, Carsten Binnig, Rajiv Ratn Shah |
| 2026 | EDBT | Towards Multimodal Stream Processing Systems. | Ulison Jean Lopes dos Santos, Alessandro Ferri, Szilard Nistor, Riccardo Tommasini, Carsten Binnig, Manisha Luthra |
| 2026 | SIGMOD | Ninth International Workshop on Exploiting Artificial Intelligence Techniques for Data Management (aiDM'26). | Kavitha Srinivas, Manisha Luthra, Selim F. Tekin |
| 2025 | BTW | Workshop on ML4Sys and Sys4ML. | Manisha Luthra, Andreas Kipf, Matthias Bhm |
| 2025 | EDBT | Dema: Efficient Decentralized Aggregation for Non-Decomposable Quantile Functions. | Wang Yue, Martin Boissier, Manisha Luthra, Tilmann Rabl |
| 2025 | SIGMOD | Eighth International Workshop on Exploiting Artificial Intelligence Techniques for Data Management (aiDM). | Renata Borovica-Gajic, Manisha Luthra, Ryan Marcus, Rajesh Bordawekar, Oded Shmueli |
| 2025 | VLDB | Learning What Matters: Automated Feature Selection for Learned Cost Model in Parallel Stream Processing. | Pratyush Agnihotri, Carsten Binnig, Manisha Luthra |
| 2024 | EDBT | Deco: Fast and Accurate Decentralized Aggregation of Count-Based Windows in Large-Scale IoT Applications. | Wang Yue, Rafael Moczalla, Manisha Luthra, Tilmann Rabl |
| 2024 | ICDE | ZERoTuNE: Learned Zero-Shot Cost Models for Parallelism Tuning in Stream Processing. | Pratyush Agnihotri, Boris Koldehofe, Paul Stiegele, Roman Heinrich, Carsten Binnig, Manisha Luthra |
| 2024 | ICDE | Costream: Learned Cost Models for Operator Placement in Edge-Cloud Environments. | Roman Heinrich, Carsten Binnig, Harald Kornmayer, Manisha Luthra |
| 2023 | BTW | A Tutorial Workshop on ML for Systems and Systems for ML. | Manisha Luthra, Andreas Kipf, Matthias Bhm |
| 2022 | Middleware | IoT-opt: the swiss army knife to model and validate the performance of IoT products: demo abstract. | Pratyush Agnihotri, Manisha Luthra, Miguel Rodriguez, Boris Koldehofe |
| 2022 | RTAS | FA2: Fast, Accurate Autoscaling for Serving Deep Learning Inference with SLA Guarantees. | Kamran Razavi, Manisha Luthra, Boris Koldehofe, Max Mhlhuser, Lin Wang |
| 2020 | NOMS | Flexible Content-based Publish/Subscribe over Programmable Data Planes. | Ralf Kundel, Christoph Grtner, Manisha Luthra, Sukanya Bhowmik, Boris Koldehofe |
| 2019 | Middleware | UrbanPulse: Adaptable Middleware to offer City and User Centric Smart City Solution. | Pratyush Agnihotri, Manisha Luthra, Sascha Peters |
| 2019 | Middleware | Highly Flexible Server Agnostic Complex Event Processing Operators. | Manisha Luthra, Sebastian Hennig, Pratyush Agnihotri, Lin Wang, Boris Koldehofe |
| 2019 | Middleware | ProgCEP: A Programming Model for Complex Event Processing over Fog Infrastructure. | Manisha Luthra, Boris Koldehofe |
| 2019 | PERCOM | Demo: Visualizing Adaptation Decisions in Pervasive Communication Systems. | Martin Pfannemller, Janick Edinger, Markus Weckesser, Roland Kluge, Manisha Luthra, Robin Klose, Christian Becker, Andy Schrr |
| 2019 | PERCOM | CoalaViz: Supporting Traceability of Adaptation Decisions in Pervasive Communication Systems. | Martin Pfannemller, Markus Weckesser, Roland Kluge, Janick Edinger, Manisha Luthra, Robin Klose, Christian Becker, Andy Schrr |
| 2018 | Middleware | Understanding the Behavior of Operator Placement Mechanisms on Large-Scale Networks. | Manisha Luthra, Sebastian Hennig, Boris Koldehofe |
| 2017 | ICSE | Quality-Aware Runtime Adaptation in Complex Event Processing. | Pascal Weisenburger, Manisha Luthra, Boris Koldehofe, Guido Salvaneschi |
| 2017 | LCN | Efficient Crowd Sensing Task Distribution Through Context-Aware NDN-Based Geocast. | The An Binh Nguyen, Pratyush Agnihotri, Christian Meurisch, Manisha Luthra, Rahul Chini Dwarakanath, Jeremias Blendin, Doreen Bhnstedt, Michael Zink, Ralf Steinmetz |