Rohan Bansal

I am a first year Masters student in the department of Computer Science at Stony Brook University. I graduated from IIT Bombay with majors in Electrical Engineering and minors in Computer Science and Engineering. My hobbies include playing football and guitar.

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Part of the Exadata Database Machine Team responsible for the smooth functioning of the Exadata machine and deployment of Exascale on cloud. We use python and shell script to add new features and fix bugs.

Worked on the issues of Field Mapping and Product Classification aimed at reducing the cost and time of External Data Migration and increasing Duty Compliance on International Products

Introduced and implemented a novel approach for anomaly detection in videos by combining the concepts of few shot learning and memory module based prototypical networks.

Woked on a baseline architecture to identify anomalous behaviour in video frames using frame reconstruction .

Studied techniques like weight sharing to increase the efficiency of deep CNNs.

Implemented and compared various robust transformations to counter the effects of various adversarial attacks. We use baseline models for image classification of MNIST and CIFAR10 datasets.

Implemented a method that will take into account several discourse relations while predicting the sentiment of a sentence. Using a lexicon based and an SVM based approach, we showcase the advantage of using these discourse relations over a simple weighted polarity model.

Implemented and compared two popular face recognition algorithms, Fisher faces and Eigen faces on the Yale Face dataset which has sufficient variations in lighting and facial expressions

Implemented Image compression using k-means clustering algorithm. We compare the classification accuracy on the compressed and original image to know about the quality of compression.

Modified various function calls in xv6 and conducted experiments to check the validity of the allocation

Extracted brain waves data using EEG electrodes and filter circuits. Applied machine learning on the final output signals to implement an LED intensity adjuster.

Designed a 16-Bit, 6 stage Pipelined RISC Processor with 8 registers based on Turing-Complete Instruction Set Architecture in VHDL

Constructed an autonomous snake bot using servos, Arduino and IR Sensors.

• Secured All India Rank 122 in JEE(Advanced) among 170,000 candidates (2017)
• Secured All India Rank 155 in JEE(Main) among 1.4 million candidates (2017)
• Qualified for the International Collegiate Programming Contest(ICPC) Regionals (2018)
• Among Top 1% at state level in National Standard Examination of Physics(NSEP) (2017)
• Received an Appreciation Award by Punjab National Bank on clearing JEE(Advanced) (2017)

• Programming Languages : Python, C/C++, Java, Bash, PL/SQL, HTML, VHDL
• Libraries : OpenCV, Keras, Tensorflow, PyTorch, Scikit-learn, NumPy
• Softwares and Databases : MATLAB, MySQL, Oracle Database, Git, Bitbucket, Arduino, Latex, Quartus, Kiel, GNU Plot, AutoCAD, NGSpice