Vanshika Vats
Computer Vision | Deep Learning | Vision for Autonomous Vehicles
Computer Vision | Deep Learning | Vision for Autonomous Vehicles
I am a third-year Computer Science and Engineering Ph.D. student with Visualization and Interactive Systems (VIS) group at the University of California, Santa Cruz, advised by Prof. James Davis.
My research interests lie in Computer Vision and Deep Learning, with a primary focus on Vision for Autonomous Vehicles.
Prior to this, I was working as a Research Scientist with Mercedes-Benz Research and Development, India, broadly on motion forecasting and deep learning-based evaluation framework for perception and fusion algorithms.
[Sept 2024] Presented Few-shot Novel View Synthesis using Depth Aware 3D Gaussian Splatting at ECCV'24 held in Milan, Italy.
[July 2024] A first-author work on few-shot 3D Gaussian splatting got accepted at S3DSGR @ ECCV'24!
[July 2024] Received Graduate Dean's Travel Grant for presenting my work at ICCV'23.
[Apr 2024] Excited to have been awarded the AnitaB.org Advancing Inclusion Scholarship to attend GHC'24!
[Oct 2023] Presented the first-author work at ICCV'23 held in Paris, France.
[Aug 2023] My first-author work "Adversarial Examples with Specular Highlights" got accepted at AROW @ ICCV'23.
[Sept 2022] Joined UCSC as a CSE Ph.D. student advised by Prof. James Davis!
[Jul 2022] My first-author work "Early Prediction of Hemodynamic Shock in Pediatric Intensive Care Units With Deep Learning on Thermal Videos" with TAVLAB-IIITD has been published in Frontiers in Physiology.
[Apr 2022] Innovation Contribution Recognition by Mercedes-Benz R&D India
[Jan 2022] Awarded Google AI Research Week Scholar-2022 being among 150 candidates selected from India and Singapore
[Dec 2021] Awarded Rising Star Alumnus Award by IGDTUW for recognition of outstanding achievement in the career
[Oct 2020] Joined Mercedes-Benz R&D India as a Research Scientist
[Sept 2020] Graduated from IIIT-Delhi with a Master's in ECE
VaLID: Verification as Late Integration of Detections for LiDAR-Camera Fusion
Vanshika Vats*, Marzia Binta Nizam*, and James Davis (*Equal contribution)
arXiv preprint arXiv:2409.15529
2024 [Link]
Few-shot Novel View Synthesis using Depth Aware 3D Gaussian Splatting
Raja Kumar* and Vanshika Vats* (*Equal contribution)
European Conference on Computer Vision (ECCV) Workshops
2024 [Link]
A Survey on Human-AI Teaming with Large Pre-Trained Models
Vanshika Vats*, Marzia Binta Nizam*, Minghao Liu, et al.
arXiv preprint arXiv:2403.04931
2024 [Link]
Assessing the Impact of Prompting Methods on ChatGPT's Mathematical Capabilities
Yuhao Chen, Chloe Wong, Hanwen Yang, ..., Vanshika Vats, James Davis
arXiv preprint arXiv:2312.15006
2024 [Link]
Adversarial Examples with Specular Highlights
Vanshika Vats, Koteswar Rao Jerripothula
IEEE/CVF International Conference on Computer Vision Workshops (ICCVw)
2023 [Link]
Early Prediction of Hemodynamic Shock in Pediatric Intensive Care Units With Deep Learning on Thermal Videos
Vanshika Vats, Aditya Nagori, Pradeep Singh, Raman Dutt, Harsh Bandhey, Mahika Wason, Rakesh Lodha, Tavpritesh Sethi
Frontiers in Physiology, 1284
2022 [Link | PDF]
A Prospectively Validated Generalizable Model for Outcome Prognostication Using Shock Index in Intensive Care Units
Aditya Nagori, Pradeep Singh, Sameena Firdos, Vanshika Vats, Arushi Gupta, Harsh Bandhey, Anushtha Kalia, Arjun Sharma, Prakriti Ailavadi, Raghav Awasthi, Wrik Bhadra, Ayushmaan Kaul, Rakesh Lodha, Tavpritesh Sethi
2021 [Link]
SURF-SVM Based Identification and Classification of Gastrointestinal Diseases in Wireless Capsule Endoscopy
Vanshika Vats, Pooja Goel, Amodini Agarwal, Nidhi Goel
IEEE-ICSPVCE 2019
2019 [Link]
Graduate Student Researcher, VIS Group, UC Santa Cruz, CA
Sept 2022 - Present
Working with Visualization and Interactive Systems (VIS) group on advanced sensing technology for autonomous vehicles
Exploring context-aware object detection and segmentation in urban driving with the help of VLMs and LLMs
Working towards better object detection methods with model-agnostic camera-LiDAR late fusion for improved perception in AVs
Research Scientist, Mercedes-Benz R&D, India
Oct 2020 - July 2022
Motion forecasting through Graph Neural Networks (GNNs)
Responsible for building and scaling an end-to-end framework to assess deep learning based perception and fusion algorithms for large scale drive data at Level-4 automation
Computer Vision Researcher, NeatAI ServoLab, IIIT Delhi
Aug 2021 - April 2022
Examined natural adversaries affecting the deep neural vision models noting a ∼35% drop in the model performance. Found significant shifts in model attention after introducing the adversaries leading to exploring solutions [Manuscript under review]
Researcher, TavLab, IIIT Delhi
Jan 2021 - May 2021
Worked on elevating the limited generalization of Intensive Care Unit (ICU) vitals in predicting hemodynamic shock by bridging the gap across age-groups, ICU settings, geographies, and non-real-time settings by Deep Learning methods
Achieved AUPRC > 90% across each considered ICU site along with identifying 92% of all shock events up to more than 8 hours in advance
Doctor of Philosophy, 2022 - Present
University of California, Santa Cruz | Computer Science and Engineering
Master of Technology, 2018 - 2020
Indraprastha Institute of Information Technology, Delhi | Electronics and Communication Engineering
Bachelor of Technology, 2014 - 2018
Indira Gandhi Delhi Technical University for Women, Delhi | Electronics and Communication Engineering
Outside of my professional life, I actively pursue my passion for photography and continually work to improve my skills and techniques. I also enjoy exploring the great outdoors.
[Instagram: @vanshikavats.nef]