Computer Vision/Machine Learning/AI


Hello Prospective Recruiter/Employer,
I am an MS graduate student in Electrical Engineering and just completed a year working in a healthcare startup developing speech algorithms for detecting ALS among other applications. I have, in addition, 3+ academic years of experience in Digital Signal/Image Processing, Computer Vision and Machine & Deep Learning (ex. NLP, Object detection, tracking, segmentation, Camera calibration).
I am very interested any internship role in Computer VisionML/AI role , hopefully depending on my productivity could potentially convert to a fulltime and love to solve interesting challenges that would eventually contribute to making people's lives easier than it is, especially during this pandemic.
I am experienced with Python, Tensorflow, Pytorch, C++, Linux, Git, AWS, time series forecasting, longitudinal analysis, etc.
I have done projects for object detection and NLP such as Deep Automated Image Captioning using Mask RCNN and BiLSTM, Transfer learning using Deep networks using GPU projects (Satellite Image segmentation, Animal and Spam classification- ( Example datasets: (a) Questions; (Learning question classifiers dataset) (b) Spam; (Enron Spam Dataset) (c) Animals Dataset iNaturalist challenge at FGVC 2017.  Accessed: 2018-04-11. )
In addition, I have done projects related to object tracking in videos through SIFT, SURF, ORB and KLT, Image stitching using SIFT descriptors, Harris corner detection, 3D rendered cube, Grocery object detection, Fabric texture defect segmentation, modelling using camera calibration and object tracking, Sensor fusion using Kalman and Extended Kalman filter for Object tracking, etc
Below is an example of an ML project I am really proud of which combines Speech/Voice processing and ML:
An example for one of the most important ML projects and predictive analysis I am proud of is that I developed a Parkinson's detector through developing features through signal processing and feature selection through Pearson correlation, then further optimizing using a couple of ML binary classifies and thus analyse which gives the best accuracy, in this case, F1 Score as it's an imbalanced dataset, and further analyzing the theoretical reasonings behind them, thus providing an optimum F1 score, and de-black boxing the predictor to make it as interpretable as possible, for say, a clinician would intuitively understand while explaining it to a patient.
I am going to travel from the US tomorrow as my work visa is expiring, to Bahrain just for a couple of days to meet my parents, and in the meanwhile, I am looking for an internship role (which, based only on my performance of course, can hopefully be converted to a full-time) in Computer Vision/ML/AI in India(Bengaluru) (Open to relocation) as I will be moving there indefinitely.


Challenging problems to solve so as to make new/existing products better through Computer Vision, Machine Learning and AI.

Work in India
Employment Preferences
Expected Base Salary

**0,000 INR

Academic Degree

Total Professional Experience

1 year

Startup Experience

1 year

Big-Tech Companies

no experience

Enterprise Experience

1 year
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