Yiwen Zhu
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
23
Venues
12
Active years
2019–2026
Best venue rank
A*
Where they publish
Papers
23 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | HCI | Enhancing Digital Accessibility for Individuals with Essential Tremor Through User-Centered Interaction Strategies. | Yiwen Zhu, Xiangyu Liu |
| 2026 | ISCAS | An RRAM-based Neuromorphic Sleep Monitoring System for Energy-efficient Edge Healthcare Applications. | Jingyi Chen, Fangduo Zhu, Zhicheng Li, Zihan Xu, Yiwen Zhu, Jingsong Zhang, Jinhao Liang, Xumeng Zhang, Qi Liu |
| 2026 | ISCAS | An RRAM-based Multi-Timescale Spiking Processor with Reconfigurable Neurons. | Jinhao Liang, Chenyang Li, Fangduo Zhu, Yiwen Zhu, Siyuan Ouyang, Jingsong Zhang, Xumeng Zhang, Qi Liu, Ming Liu |
| 2026 | ISCAS | A Pipelined NoC-Based Membrane Shortcut SNN Architecture for Low-Latency Spike Sorting. | Jingsong Zhang, Yiwen Zhu, Fangduo Zhu, Chenyang Li, Siyuan Ouyang, Jinhao Liang, Jingyi Chen, Xumeng Zhang, Qi Liu |
| 2026 | KDD | ENCO: Deploying Production-Scale Engineering Copilots. | Yiwen Zhu, Mathieu B. Demarne, Kai Deng, Wenjing Wang, Nutan Sahoo, Hannah Lerner, Anjali Bhavan, Divya Vermareddy, Yunlei Lu, Swati Bararia, William Zhang, Xia Li, Katherine Lin, Miso Cilimdzic, Subru Krishnan |
| 2025 | CIKM | FLAIR: Feedback Learning for Adaptive Information Retrieval. | William Zhang, Yiwen Zhu, Yunlei Lu, Mathieu B. Demarne, Wenjing Wang, Kai Deng, Nutan Sahoo, Katherine Lin, Miso Cilimdzic, Subru Krishnan |
| 2025 | IJCNN | Multi-Reward Fusion: Learning from Other Policies through Distillation. | Yiwen Zhu, Jinyi Liu, Wenya Wei, Zhou Fang |
| 2025 | SIGMOD | Autotuning Systems: Techniques, Challenges, and Opportunities. | Brian Kroth, Sergiy Matusevych, Yiwen Zhu |
| 2025 | SIGMOD | Streaming Democratized: Ease Across the Latency Spectrum with Delayed View Semantics and Snowflake Dynamic Tables. | Daniel Sotolongo, Daniel Mills, Tyler Akidau, Anirudh Santhiar, Attila-Pter Tth, Botong Huang, Boyuan Zhang, Igor Belianski, Ling Geng, Matt Uhlar, Nikhil Shah, Olivia Zhou, Saras Nowak, Sasha Lionheart, Vlad Lifliand, Wendy Grus, Yiwen Zhu, Ankur Sharma, Dzmitry Pauliukevich, Enrico Sartorello, Ilaria Battiston, Ivan Kalev, Lawrence Benson, Leon Papke, Niklas Semmler, Till Merker, Yi Huang |
| 2025 | SIGMOD | Rockhopper: A Robust Optimizer for Spark Configuration Tuning in Production Environment. | Yiwen Zhu, Rathijit Sen, Brian Kroth, Sergiy Matusevych, Andreas C. Mueller, Tengfei Huang, Rahul Challapalli, Weihan Tang, Xin He, Mo Liu, Estera Kot, Sule Kahraman, Arshdeep Sekhon, Dario Bernal, Aditya Lakra, Shaily Fozdar, Dhruv Relwani, Rui Fang, Long Tian, Karuna Sagar Krishna, Ashit Gosalia, Carlo Curino, Subru Krishnan |
| 2025 | VLDB | AutoDebugger: Efficient Root Cause Analysis for Anomaly Jobs. | Fathelrahman Ali, Yiwen Zhu, Lie Jiang, Zhen Li, Manting Li, Kun Huang, Lijing Lin, Long Tian, Xiaolei Liu, Subru Krishnan |
| 2024 | ICDE | VASIM: Vertical Autoscaling Simulator Toolkit. | Anna Pavlenko, Karla Saur, Yiwen Zhu, Brian Kroth, Joyce Cahoon, Jess Camacho-Rodrguez |
| 2024 | IJCAI | vMFER: Von Mises-Fisher Experience Resampling Based on Uncertainty of Gradient Directions for Policy Improvement. | Yiwen Zhu, Jinyi Liu, Wenya Wei, Qianyi Fu, Yujing Hu, Zhou Fang, Bo An, Jianye Hao, Tangjie Lv, Changjie Fan |
| 2024 | SIGMOD | Vertically Autoscaling Monolithic Applications with CaaSPER: Scalable Container-as-a-Service Performance Enhanced Resizing Algorithm for the Cloud. | Anna Pavlenko, Joyce Cahoon, Yiwen Zhu, Brian Kroth, Michael Nelson, Andrew Carter, David Liao, Travis Wright, Jess Camacho-Rodrguez, Karla Saur |
| 2023 | EDBT | Stitcher: Learned Workload Synthesis from Historical Performance Footprints. | Chengcheng Wan, Yiwen Zhu, Joyce Cahoon, Wenjing Wang, Katherine Lin, Sean Liu, Raymond Truong, Neetu Singh, Alexandra M. Ciortea, Konstantinos Karanasos, Subru Krishnan |
| 2023 | SIGMOD | Demonstration of Geyser: Provenance Extraction and Applications over Data Science Scripts. | Fotis Psallidas, Megan Eileen Leszczynski, Mohammad Hossein Namaki, Avrilia Floratou, Ashvin Agrawal, Konstantinos Karanasos, Subru Krishnan, Pavle Subotic, Markus Weimer, Yinghui Wu, Yiwen Zhu |
| 2023 | SIGMOD | Towards Building Autonomous Data Services on Azure. | Yiwen Zhu, Yuanyuan Tian, Joyce Cahoon, Subru Krishnan, Ankita Agarwal, Rana Alotaibi, Jess Camacho-Rodrguez, Bibin Chundatt, Andrew Chung, Niharika Dutta, Andrew Fogarty, Anja Gruenheid, Brandon Haynes, Matteo Interlandi, Minu Iyer, Nick Jurgens, Sumeet Khushalani, Brian Kroth, Manoj Kumar, Jyoti Leeka, Sergiy Matusevych, Minni Mittal, Andreas Mller, Kartheek Muthyala, Harsha Nagulapalli, Yoonjae Park, Hiren Patel, Anna Pavlenko, Olga Poppe, Santhosh Ravindran, Karla Saur, Rathijit Sen, Steve Suh, Arijit Tarafdar, Kunal Waghray, Demin Wang, Carlo Curino, Raghu Ramakrishnan |
| 2021 | SIGMOD | KEA: Tuning an Exabyte-Scale Data Infrastructure. | Yiwen Zhu, Subru Krishnan, Konstantinos Karanasos, Isha Tarte, Conor Power, Abhishek Modi, Manoj Kumar, Deli Zhang, Kartheek Muthyala, Nick Jurgens, Sarvesh Sakalanaga, Sudhir Darbha, Minu Iyer, Ankita Agarwal, Carlo Curino |
| 2020 | CIDR | Cloudy with high chance of DBMS: a 10-year prediction for Enterprise-Grade ML. | Ashvin Agrawal, Rony Chatterjee, Carlo Curino, Avrilia Floratou, Neha Godwal, Matteo Interlandi, Alekh Jindal, Konstantinos Karanasos, Subru Krishnan, Brian Kroth, Jyoti Leeka, Kwanghyun Park, Hiren Patel, Olga Poppe, Fotis Psallidas, Raghu Ramakrishnan, Abhishek Roy, Karla Saur, Rathijit Sen, Markus Weimer, Travis Wright, Yiwen Zhu |
| 2020 | KDD | Vamsa: Automated Provenance Tracking in Data Science Scripts. | Mohammad Hossein Namaki, Avrilia Floratou, Fotis Psallidas, Subru Krishnan, Ashvin Agrawal, Yinghui Wu, Yiwen Zhu, Markus Weimer |
| 2020 | SIGMOD | MLOS: An Infrastructure for Automated Software Performance Engineering. | Carlo Curino, Neha Godwal, Brian Kroth, Sergiy Kuryata, Greg Lapinski, Siqi Liu, Slava Oks, Olga Poppe, Adam Smiechowski, Ed Thayer, Markus Weimer, Yiwen Zhu |
| 2019 | CLOUD | Griffon: Reasoning about Job Anomalies with Unlabeled Data in Cloud-based Platforms. | Liqun Shao, Yiwen Zhu, Siqi Liu, Abhiram Eswaran, Kristin Lieber, Janhavi Suresh Mahajan, Minsoo Thigpen, Sudhir Darbha, Subru Krishnan, Soundar Srinivasan, Carlo Curino, Konstantinos Karanasos |
| 2019 | KDD | Machine Learning at Microsoft with ML.NET. | Zeeshan Ahmed, Saeed Amizadeh, Mikhail Bilenko, Rogan Carr, Wei-Sheng Chin, Yael Dekel, Xavier Dupr, Vadim Eksarevskiy, Senja Filipi, Tom Finley, Abhishek Goswami, Monte Hoover, Scott Inglis, Matteo Interlandi, Najeeb Kazmi, Gleb Krivosheev, Pete Luferenko, Ivan Matantsev, Sergiy Matusevych, Shahab Moradi, Gani Nazirov, Justin Ormont, Gal Oshri, Artidoro Pagnoni, Jignesh Parmar, Prabhat Roy, Mohammad Zeeshan Siddiqui, Markus Weimer, Shauheen Zahirazami, Yiwen Zhu |