Hi there! I'm Shivangi. I recently started my PhD in Visual Computing Lab advised by Prof. Matthias Nießner . Prior to that, I completed my Master’s degree in Informatics (specialization in Computer Vision and Deep Learning ) from Technical University of Munich. I joined the lab during my master thesis titled “Generalized Zero and Few-Shot Transfer for Facial Forgery Detection”. I hold a Bachelor’s degree in Computer Science from the National Institute of Technology, India, where I graduated with a Gold Medal for academic excellence. In the past, I have done a couple of deep learning projects related to computer vision and biomedicine (check my GitHub for details).
Selected for poster presentationa at WiML Workshop (2019). This will be co-located with Neural Information Processing Systems (NeurIPS) conference.
Selected as one of the 150 participants (out of 700+ applicants) to attend the EEML Summer School on Deep Learning and Reinforcement Learning. This was held in Bucharest, Romania from 1-6 July 2019. Lectures and hands-on practical sessions were given by one of the best researchers in the domain. I was also awarded full scholarship to attend the school.
Selected as one of the students to attend the ATHENS exchange programme at one of the parter universities. A one week exchange programme to facilitate exchanges between students of the major European technical institutions. I was selected for the course Finite Element Algorithms at TU Delft. It was held from 16-23 March 2019. Full travel grant was awarded for the programme.
A Guided Research where the 3D Multi-modal (FLAIR and T1) brain MRI scans were used in a semi-supervised setting to perform semantic segmentation. The results were slightly improved by leveraging the unannotated scans. GANs were used for this task.
A Machine Learning in Medical Imaging (MLMI) practical course where the aim was to detect polyps in the image. First, the results were evaluated on standard benchmark CVC-Polyp dataset (which consits of colonoscopy videos from different studies), and then on the dataset provided by the hospital. For this project, SSD (Single Shot Multibox Detector) was used. Presented this work during poster session at EEML Summer School.
A (team)project as part of my Advanced Deep Learning for Computer Vision course where we could build a model that creates realistic composite images. Conditional GANs along with specialized loss for the generator were used to achieve this task.
A practical course offered by Computer Vision Research Group at the university wherein my project was to improve clustering accuracy on various toy datasets like MNIST, CIFAR-10, and STL. I experimented with autoencoders for this.
A Sofware Engineering Course where we developed a full-stack web application (using MERN stack) to organize barbeque parties. Functionalities include inviting friends, organizing food potluck, notifying users, group chat, etc.
Bachelor Thesis: Secondary users could use spectral band when not used by primary users. Local and cooperative sensing was used for energy detection.
Magna Cum Laude
Awarded Gold Medal for graduating top of Computer Science Batch (2011-2015)
Awarded Roll Of Honour for graduating top of the High School (Science and Mathematics).
Masters: Introduction To Deep Learning, Advanced Deep Learning for Computer Vision, Machine Learning, Machine Learning for Computer Vision, Machine Learning In Medical Imaging Practical Course, Natural Language Processing Seminar, Deep Learning for Computer Vision and Biomedicine Practical Course, Protein Prediction For Computer Scientists
Bachelors: Analysis & Design of Algorithms, Probability and Queuing Models, Data Structures, Discrete Structure, Differential and Integral Calculus, Operating System, Theory Of Computation, Computer Networks, Data Mining and Knowledge Discovery
Implemented an AI-based software solution to keep track of the startup landscape and to maintain an up-to-date database for startups by using various web crawling and machine learning techniques
Two abstracts were accepted to the Women in Machine Learning (WiML) Workshop 2019, co-located with Neural Information Processing Systems (NeurIPS) conference. Presented the posters during the workshop in Vancouver Convention Centre, Canada on December 9, 2019.
My abstract was accepted to the EEML Summer School 2019. Presented the poster during the poster session in PRECIS Building, Universitatea Politehnica din București, Bucharest, Romania on July 3, 2019.