Aritificial Intelligence in wireless communication•Under guidance of Dr Sandeep Joshi•Interpreted and implemented 5+ research papers to understand various concepts regarding channel estimation.•Understanding the method of channel estimation for IRS by converting the problem statement as denoising problem.•Improving the denoising architecture by 20 percent implementing AI models , neural networks using Pytorch and Tensorflow so as to provide a better measure for channel estimation.

Brain MRI images for brain tumor detection•Under guidance of Dr Raj Kumar Gupta•Worked on methods for feature extraction of 3000 brain tumor MRI scans .Extracted four features using image processing.•Observed and analysed various feature extraction methods using various softwares which led to optimization in feature extraction process.•Developed a machine learning with more than 90% accuracy and Deep learning algorithms with more than 98% accuracy on the given dataset

Some studies on lithium ion-based pseudo supercapacitors for energy storage•Under guidance of Dr Anshuman Dalvi•Devloped electrode and designed circuit for testing properties of supercapacitors which helped to increase batch size and decrease testing time•Prepared electrode for testing purposes and prepared MnO2 graphene flowers using activated carbon•Studied samples created using XRD and FESEM analysis and optimised quality of electrode and reduced raw materials used in it

Classification of Insect species using Acoustic features •Under the guidance Dr Ashutosh Bhatia•Worked on more than 100 sound files containing more than 5 insect sounds for developing and optimizing classification models which aimed in identifying pests.•Observed and analysed the data using graphical representations and acoustic features using various image processing techniques.• Compared accuracies for various machine learning models and created Deep learning model providing more than 95 percent accuracy using Keras,Pytorch and Tensorflow.

Chaos in Nonlinear electronic circuits •Under the guidance of Dr Rakesh Choubisa•Plotting dynamical systems undergoing chaos using given initial conditions.•Studying chaos in electronic circuits using previously implemented research papers.•Discussed and provided detailed analysis on behaviour of chaotic systems under various dynamic condition observed in a system.

AI Inference model which can show vegetation health and predict crop health, CSIR-CEERI•Under guidance of Dr Kaushal Kishore•Studied exiftool and it's Python wrapper to observe RedEdge images to transform raw digital number values into quantitative reflectance•Implemented dataset of research paper to extract the vegetation indices like NDVI,NDWI and MCARI values for analysis of crop health•Working on developing an AI model by training Neural networks to predict crop health for data in format of multispectral images

•Conducted weekly doubt sessions for students to solve their academic doubts

•Managed weekly workout sessions after 3 years with more than 30 participants of various age groups in the campus after 3 years of Covid.•Organised 2 cycling events covering more than 30 km with participation of more 100 cyclists to promote importance of physical activity•Managed a team of more than 10 students in Interhostel events in sports festival of BITS Pilani ,organised stall events in InterBITS tournaments and increased awareness for social causes.

•Led team of 7-8 students to develop posters and other creative aspects for media page of club and encouraged members to develop designing skills•Managed design side of events in OASIS 22, APOGGEE 23 ,recruitments and farewells with the help of various ADOBE softwares•Assisted the club by inceasing its reputation and reach of club to various social media stars and universities .

•Member of a 6 member team in a club of more tha 40 people.•Responsible for providing novel ideas for weekly session spanning across the year.•Assisted in ideating activites for various fests and meetups in the academic year.

•Participated in various activites like debates, presentations and other communication rich games .

Classification of Marine Ambient Noise data using Machine Learning•Under guidance of Dr Williman Fernandes•Engaged with 95 sound files involving sound produced by various aquatic species in river Mandovi and processed on files in in .wav format•Analysed the noise files using graphical methods and extracted 4 features of dataset using various feature extraction algorithms in matlab•Developed a machine learning algorithm for species classification with more than 75% accuracy to recognise the species present in the water body