Ms. Ekaterina Shumitskaya, Lomonosov Moscow State University, Russia
👩💻 Ms. Ekaterina Shumitskaya is an accomplished scholar currently pursuing a Master’s degree in Computer Science at Lomonosov Moscow State University, specializing in Computational Mathematics and Cybernetics. 🎓 With a stellar academic record, she achieved a remarkable GPA of 4.89 out of 5.0 during her Bachelor’s program from September 2019 to June 2023. 🌐 Ekaterina’s unwavering dedication to excellence in the realm of computational mathematics and cybernetics is evident in her educational journey. 🚀 As a Junior Research Scientist at MSU Graphics & Media Lab since September 2021, based in Moscow, Russia, she actively contributes to pioneering research in image and video quality metrics, specializing in vulnerability analysis. 🖥️ Ekaterina played a key role in the team’s accomplishment of releasing the largest benchmark on video quality metrics robustness analysis. 💡 Additionally, her role as a Junior Developer at MSU Video Codecs Comparisons (June 2022 – October 2023) involves meticulous measurement of cloud video codec services and insightful report preparation, showcasing her commitment to advancing research and development in graphics, media, and video codec technologies. 🌐 Deeply immersed in cutting-edge research, her primary focus includes video quality metrics, adversarial attacks, and Computer Vision, collectively contributing to the advancement of multimedia technologies and demonstrating a dynamic engagement with the intricacies of video quality and security in the evolving landscape of Computer Vision. 🚀✨
🎓 Education :
👩🎓 Ms. Ekaterina Shumitskaya is currently on a scholarly journey at Lomonosov Moscow State University, specializing in Computational Mathematics and Cybernetics. 🌐 Engaged in pursuing a Master’s degree in Computer Science since September 2023, Ekaterina has already showcased her academic prowess during her Bachelor’s program, where she excelled with a remarkable GPA of 4.89 out of 5.0, completing her Bachelor of Computer Science from September 2019 to June 2023. 🏫 Her dedication to the field is evident, and her educational path reflects a commitment to excellence in the realm of computational mathematics and cybernetics. 🚀📚
🌐 Professional Profiles :
Google Scholar
💻 Experience :
👩🔬 Ms. Ekaterina Shumitskaya has been making significant strides in the field of research and development, currently serving as a Junior Research Scientist at MSU Graphics & Media Lab since September 2021. 🌐 Located in Moscow, Russia, she actively contributes to the exploration of image and video quality metrics performance, specializing in vulnerability analysis. Ekaterina played a pivotal role in the team’s accomplishment of releasing the largest benchmark on video quality metrics robustness analysis. 🚀 Additionally, her expertise extends to her role as a Junior Developer at MSU Video Codecs Comparisons from June 2022 to October 2023. In this capacity, she meticulously measured the results of cloud video codec services, conducted thorough analyses, and prepared insightful reports. 💻📊 Ekaterina’s multifaceted experience reflects her dedication to advancing research and development in the realm of graphics, media, and video codec technologies.
🧠 Research Interests 🔬🌐 :
👩💻 Ms. Ekaterina Shumitskaya is deeply immersed in the realm of cutting-edge research, with a primary focus on video quality metrics, adversarial attacks, and Computer Vision. 🎥 Her keen interest in video quality assessment and robustness verification is evident in her work, demonstrating a commitment to ensuring the reliability and resilience of multimedia systems. 🌐 Ekaterina’s expertise extends to adversarial attacks and vulnerability analysis, where she explores innovative approaches to fortify systems against potential threats. 💡 Her diverse research interests collectively contribute to the advancement of multimedia technologies, showcasing a dynamic engagement with the intricacies of video quality and security in the evolving landscape of Computer Vision. 🚀🔍
Publications Top Notes :
1. Universal perturbation attack on differentiable no-reference image-and video-quality metrics
Published Year : 2022, Cited By: 6
2. Towards adversarial robustness verification of no-reference image-and video-quality metrics
Published Year : 2023
3. Comparing the robustness of modern no-reference image-and video-quality metrics to adversarial attacks
Published Year : 2023
4. Fast Adversarial CNN-based Perturbation Attack on No-Reference Image-and Video-Quality Metrics
Published Year : 2023