I am a 3 years experienced developer, currently pursuing my Master's in Computer Science from Stony Brook University. Passionate about obtaining a position that helps me evolve both in technical and professional front while achieving organizational goals in parallel.
Worked in DevOps PETAP team under OAL (Oracle Application Labs) on Expenses and Travel module, under both Oracle E-Biz and Fusion (Oracle Public Cloud). Implemented and released to production, custom enhancement, to make expense and cash advances submission, approval, audit and payment process efficient for ~138000 Oracle employees.
CSE 114 - Introduction to Java, assisted professor in data logging in reporting system, organized and conducted review session for students and helped in grading exams and homework assignments.
Ongoing project, involves creating VI graph bases model (OpenHab, SmartThings, MUD, IFTTT supported so far). Model detects conflicts/violations, verify it’s correctness and automatically resolved them.
A typical VO pipeline consists of camera calibration, feature detection and extraction, feature matching, outlier removal (RANSAC), motion estimation and local optimisation. All these steps require significant engineering effort and also need fine tuning as per implementation condition. Bypassing this tedious engineering effot, we implemented an end-to-end framework for monocular visual odometry (VO) problem by using the deep RCNNs, using KITTI monocular VO dataset.
Improving baseline tiny image model using bag of SIFT features
Involves KMeans clustering for features, KNN and SVMs model for classification.
Action recognition and classification among 16 classes by analyzing video frames.Pretrained VDD16 was used for feature extraction and action was recognized/classified using both SVM and LSTM RNN network, accuracy 95.77% and 95.59% resp.
A chatbot trained on adapting conversation style of a certain speaker.
Trained on personal chat and character Ross from FRIENDS TV sitcom. GENSIM and GloVe were used for word embedding generation. Model architecture involved BLSTM (Keras), LSTM with attention model (Pytorch).
Algorithm to accelerate the performance of the genome sequence alignment,by using a combination of exact and selective alignment, with a cache
Results prove algorithm is faster than existing KSW2 library
Detects emotion : Happiness, Fear, Sad, Anger, Surprise from face expressions
Cohn-Kanade DB was used for training SVM model, 83% accuracy
Created a user friendly terminal interface (NETMIN)/web interface (WEBMIN) that allows user to perform general tasks like user management , file management , apache server handling, dns server management , port management, both remotely and smoothly
Apart from my technical facet, I am an ultrarunner, a cyclist and an aspiring triathlete. I realized that endurance sports fuel my chi, helping me focus on my immediate goals and being more productive. My enthusiasm towards fitness drove me to be a fitness blogger and mentor people under ‘Couch to 5K’ programme. This way I can inspire people to become better versions of themselves and realize their true potential.