RESEARCH AND OTHER PROJECTS

Shariq Aftab

• Research Intern @ UNSW, Australia (Aug 2022- Present)

Topic: Improving Online Bot detection Model

Abstract: Working remotely as an intern under Professor Dr. Rahat Masood ( Department of AI and ML) at University of New South Wales, Sydney, Australia. The research topic is Adversarial Bot Detection. It focusses on taking help of adversarial machine learning in detecting the distribution that will aid to classify between automated account and human controlled account.

• Project Intern @ RMIT, Australia (August 2022-Present)

Topic: Recognition and Optimization of IoMT

Abstract: This is a project in collaboration with Dr. Azadeh Alvi from RMIT. The project involves building an approach or improve existing methods in the field of Internet of Medical Things (IoMT).

Jeevansh Gagroo

• Research Intern @ CSIRO’s Data 61 (Aug 2022-Oct 2022)

Topic: Analysing robustness of Deep Neural Networks

Abstract: Working under the supervision of senior research scientists Dr. Kristen Moore, Dr Sharif Abuadbba and Dr. Shuo Wang, his research involves analysing a Deep Neural Network, studying their vulnerability and trying to improve their quality. Study of Generative Adversarial Networks, adversarial sample generations, Variational Auto Encoders (VAEs), Data Drift Detection and plotting is performed.

• Project Intern @ RMIT, Australia (August 2022-Present)

Topic: Recognition and Optimization of IoMT

Abstract: This is a project in collaboration with Dr. Azadeh Alvi from RMIT. The project involves building an approach or improve existing methods in the field of Internet of Medical Things (IoMT).

Unnati Sadh

• Research Intern @ TU Delft, Netherlands (Feb 2022-Aug 2022)

Topic: Compiler Design for Weak Memory Systems

Abstract: Worked under Dr. Soham Chakraborty, where she designed a compiler for Weak Computer Systems using C++ and other functions in Linux Operating System Fency model for compilers was used in the development.

• Research Intern @ UNSW, Australia

Topic: Data visualization using vega software

Abstract: In this we visualise the data into graphic forms by converting the json file in svg files.

Harshit Sharma

• Project Intern @ RMIT, Australia (August 2022-Present)

Topic: Recognition and Optimization of IoMT

Abstract: This is a project in collaboration with Dr. Azadeh Alvi from RMIT. The project involves building an approach or improve existing methods in the field of Internet of Medical Things (IoMT).

Shreyas Raturi

• Research Intern @ UNSW, Australia (May 2022-Present)

Topic: Cancer Tumours Classification

Abstract:His research in UNSW, Sydney, under the supervision of Dr. Sonit Singh involves working on a Pan Cancer Model, where a total of 33 types of cancers will be classified. Deep Learning Algorithms will be applied to find new trends in the classification of the cancer tumours. With the use of classifiers and sci-kit learn Library the goal will be achieved.

• Publication ,IJSER

Topic: Dense Caption Imaging

Abstract:
• Research focuses on the intersection of CV and NLP, specifically generating pictures from captions.
• focus on the lower data regime, using the COCO and CUB data sets which include 200k and 11k picture and caption pairs (respectively).
• A hierarchical GAN architecture was used as a baseline.

A CROSS PLATFORM MOBILE APPLICATION INTERFACE FOR BUS TRANSPORT IN SRMIST

Abstract: To create a cross platform mobile application which provides an interface between the bus commuters (both students and teachers) and bus drivers/conductors. The interface will also be accessible to the Transport Department. The team is looking for fresh talent who can contribute to the project (App Developers and Backend Developers)

Contributors: Jeevansh Gagroo, Gaurvi Vishnoi, Raunak Raj, Harshit Sharma, Shariq Aftab, Shreyas Raturi, C Sreekar, Arpit Triapthi, Ayush Gupta, Devanshu Sinha, Mohd. Shaheer, Samarth Sadana

DEVELOPING A SMART ATTENDANCE CAPTURING MOBILE APP TO BE IMPLEMENTED IN SRMIST CAMPUS (USES REAL TIME LOCATION UPDATES AND FACE DETECTION TO PREVENT PROXY)

Abstract: Developing a Smart Attendance capturing mobile app that makes use of real time location services and biometrics to mark the status of attendance of college students

Contributors: Jeevansh Gagroo, Tanish Khare, Shariq Aftab, Drish, Mohd. Shaheer

FIND MY TEACHER MOBILE APP

Abstract: To develop an interface which helps teachers as well as students to find their respective faculties. Real time location updates of faculties along with their time table status is planned to be integrated in the app.

LOOKING FOR CONTRIBUTORS (App developers, UI Designers, Flutter Developers, Backend Developers)