I am mainly interested in working in the field of Systems Biology and exploring the mechanism of Tumour Heterogeneity, Cancer Metastasis and Cellular Differentiation. I am driven by the desire to explore the unknowns and learn through practical experience.
Abhay Singh
(+91) 7578952820
abhay18a@iitg.ac.in
ssabhay6@gmail.com
B-Tech in Biotechnology • 2018-2022
Minor in Electronics & Electrical Engineering
Key Courses:
Biotechnology : Bioinformatics, Computational Biology, Biological Data Analysis, Biophysics, Immunology, Genetic Engineering, Microbiology, Cell and Molecular Biology, Biochemistry, Bioengineering, Basic Biotechnology Lab
Mathematics : Linear Algebra, Multivariable Calculus, Partial Differential Equations,
Real Analysis & Complex Analysis
MOOCS : Deep Learning Specialization, AI for Medicine, Inferential Statistics
Computer Science : Introduction to Computing, Computing Lab
Current CGPA : 8.86/10
Class XII (Senior Secondary Examination), ISC board • May 2017
Class XII (ISC): Physics, Chemistry, Mathematics, Computer Science.
Grade: 97.60%
Class X (ICSE): Science, Computer Applications, Mathematics.
Grade: 96.17%
Remote Research Internship, Systems biology lab • January 2021 - Present
Dr Sriram Chandrasekaran, Assistant Professor, Department of Biomedical Engineering, University of Michigan
Bachelor Thesis Project, Viral Immunology Lab • March 2021 - Present
Dr Sachin Kumar, Associate Professor, Department of BSBE, IIT Guwahati
Research Intern, Computational Systems Biology Lab • June 2020 - September 2020
Deep learning approaches for single-cell gene expression data analysisDr. Vinod PK, Assistant Professor, Centre for Computational Natural Sciences, IIIT Hyderabad
Dr. Ajai B. Kunnumakkara, Professor, Dept. of BSBE, IIT Guwahati • Dec 2019 - February 2020
Dr. Ajai B. Kunnumakkara, Professor, Dept. of BSBE, IIT Guwahati • Dec 2019 - March 2020
Classifying diseases on chest x-rays using a neural network. Implementing standard evaluation metrics to see how well a model performs in diagnosing diseases. Implement an appropriate loss function for image segmentation, and apply a pre-trained U-net model to segment tumor regions in 3D brain MRI images.
Image Segmentation, Multi-class classificationCase studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing.
Neural Networks, Hyperparameter Optimization, Transfer LearningLearned about Resnets, Inception network, YOLO. Applications of computer vision in face recognition and object detection
Tensorflow, Image processingUnderstanding how to build and train Recurrent Neural Networks (RNNs), and commonly-used variants such as GRUs and LSTMs. Applying sequence models to natural language problems, including text synthesis and to audio applications, including speech recognition and music synthesis.
Recurrent Neural Network, Long Short-Term Memory (LSTM)If you have any available opportunity for me at your organization then please contact me. Looking forward to connect and learn.