Brief Profile Information
Sharnil Pandya is an Assistant Professor in the Department of Computer and Information Sciences, Northumbria University. He has done his doctorate in the domain of Internet of Things and Masters in Infomation Technology from Swinburne University, Australia. he has more than 12 years of teaching experience and has served at various institutions as Associate Professor, and Assistant Professor positions.
His research interests include Healthcare Informatics, and Ambient/Smart Sensing. He has a special interest in inter-disciplinary research and projects. He has more than 90 papers published/presented in reputed international conferences and Sci journals to his credit and 6 published patents. He is a winner of prestigious Marie Skłodowska-Curie postdoc Fellowship for the year 2022. He has worked on a couple of national funded projects sponsored by DST and DRDO worth 150k USD and 200k USD. Recently, he has received prestigious Horizon 2020 research project grant of 5 million SEK as a co-Investigator, sponsored by European Union. He is also a reviewer for reputed journals like IEEE Transactions on Industrial Electronics, IEEE Internet of things, Scientific Reports, Nature, IEEE Sensors and many more. He has guided and guiding numerous undergraduate/postgraduate/doctorate students. He has received the “Young Scientist Award” in 2021 in International Scientist Summit 2021, and the “Best Teacher” and “Distinguished Facilitator” Award by Infosys Ltd. Furthermore, he has also worked on three national/international funded projects: Defence Research and Development Organization(DRDO), India, and Department of Science & Technology(DST), NVIDIA GPU Research Centre project, and has published 6 patents.
| Skill | Technologies worked on |
|---|---|
| Programming | Python, C , C++ , Java |
| DataBase | SQL, Sqlite |
| Tools/ IDE | PyCharm, VSCode, Jupyter Notebook |
| Machine Learning | EDA, ML-Algorithms, Execution with python |
| Deep Learning | Neural Networks , Computer Vision, Transfer learning, Execution with Python |
| Natural Language Processing | Neural Network , Transfer learning, Execution with Python |
| Cloud | Basic AWS |
| Operating System | MacOs, Windows |
| Hardware | Tesla T4 from google colab |
| Version control | GIT |
| Skill | Technologies used to work or Known |
|---|---|
| Python | Numpy, Pandas,Spark ,Matplotlib, Seaborn, Plotly, Scikit-Learn, pickle, Keras, Open-cv, Tensorflow, Pytorch |
| Machine Learning | Linear Regression, Logistic Regression, Decision Tree, Support vector machine, Naive Bayes, Ensemble technique, Hyper parameter tunning |
| Deep Learning | Artificial Neural Network, Convolutional Neural Network, Recurrent Neural Network, LeNET, AlexNet, VGG, Resnet, InceptionNet |
| Computer Vision | RCNN family , Yolo family , SSD, Object segmentation(Mask-RCNN) , Object Tracking |
| Natural Language Processing | Encoder-Decoder, Self Attention, Transformer, Transfer Learning models |
For More Details refer my resume click here for resume