Pankti Gandhi

Boston, MA ***** +1-857-***-**** adem66@r.postjobfree.com Linkedin

EDUCATION

Northeastern University Boston, MA

Candidate for Master of Science in Engineering Management GPA: 3.79/4 Sep’18-Present

• Relevant Courses: Data Mining, Database Management and Designing, Probability and Statistics, Financial Management, Project Management, Economic Decision Making, Deterministic Operational Research, Information Visualization in Data Science Mukesh Patel School of Technology Management and Engineering, NMIMS University Mumbai, India Bachelor of Technology in Electronics and Telecommunication Engineering Jul’14-May’18 TECHNICAL SKILLS

• Python, MATLAB, Java, C, C++ • MS Office, AutoCAD, LUCAS, KEIL, LINGO, JIRA

• SQL, SAS, R, Tableau, GitHub • Mac OSX, Windows

Certifications: Certified Scrum Master, CITI trained, Database Management Foundation Program from Infosys WORK EXPERIENCE

Biogen Inc. Cambridge, MA

Motion Capture Analyst Jul’19- Dec’19

• Evaluated new approaches to measure various objective movement metrics based on pose analysis in both clinic and home settings for use in medical trials by creating a dataset from 4 different cameras and analyzing different human motions

• Developed a low-cost kinematics and pose estimation framework for detecting near falls by fusing commercial depth cameras by increasing the cost efficiency of the system by 96%

• Utilized open pose and tensor flow package in python to detect human movements by generating body key points which were used to develop a 3D human skeleton in Python

• Determined the location of gravity within the base of support for each pose and then converted the pose points in RGB-D image to real-world units and corrected the tilt angle of cameras

• Collected and extracted the features from the data of healthy volunteers using IMU sensors for the Bradykinesia disease

• Practised Agile Scrum work environment using software like JIRA and Kanban Board. Bharti Airtel Limited Mumbai, India

Quality Management Intern May’17- Jul’17

• Conducted research with the Network Team on recent technologies like Voice over IP (VoIP), Voice over Wi-Fi (Vo-WiFi), VoLTE under the mentorship of the head of Quality department and evaluated performance factors such as jitters, latency and packet loss using the Mean Opinion Score metric

ACADEMIC PROJECTS

Classifying videos in something-something dataset Northeastern University, Jun’20- Present

• Building a model which will enable the neural networks to understand subtle difference between basic actions by using TensorFlow.

• Training our dataset of 220k videos on models like VGG-16, 2D-CNN and 3D-CNN with the help of python packages like Keras.

• Building a web framework using Angular and Python-Flask where user can view and test the videos with the predicted text embeddings Auto-Access to Resources to New-Employees Northeastern University, May’20- Jun’20

• Pre-processed a highly imbalanced discrete categorical values data consisting around 52000 samples and 10 features by sampling using SMOTE and encoded the data using one hot encoder and then grouped the entire data by using role tittle and resources.

• Applied machined learning techniques like Naïve Bayes, Logistic Regression, K-NN and Random forest to classify the data into Access granted and Access revoked in Python.

• Compared the accuracies using Confusion Matrix and Precision-Recall to conclude that Naïve Bayes was more accurate and developed a user interface using Flask API.

Law Records Management System Northeastern University, Jan’19- Apr’19

• Developed a consistent database to manage the records of cases registered, victim details and verdict proceedings using MS SQL Server

• Created multiple lookup tables using stored procedures, views, column data encryption, non-clustered index, functions, and triggers that automate all the security needs reducing manual efforts by 80% Sentiment Analysis of Consumer Reviews of Amazon Products Northeastern University, Jan’19- Apr’19

• Performed data cleaning and pre-processed 5000 different amazon consumer reviews data by eliminating capital letters, punctuations, white space and by stemming the words

• Obtained the sentimental values with the help of syuzhet dictionary based on the consumer review texts and the ratings

• Used Logistic Regression and Naïve Bayes to classify the reviews into positive and negative bins in R

• Compared the accuracy using Confusion Matrix and conclude Logistic Regression to be 0.6% more accurate than Naïve Bayes Biometric Security System Using Iris and Speech Recognition NMIMS University, Aug’17- Apr’18

• Implemented segmentation and normalization of iris via Daugman’s method and performed feature extraction using 2D Gabor filters, MFCC

• Utilized Neural Networks for feature matching because of their adaptive-learning, self-organization, and fault-tolerance capabilities

• Created an iris database using macro lens that resulted in a 95% increase in cost-efficiency of the project LEADERSHIP AND VOLUNTEER ACTIVITIES

• Volunteer at Teach for India • NGO volunteer at Spread out Smiles at Anandi

• Vice Chairperson for NMIMS’s Annual Cultural Event • Marketing HOD for NMIMS’s Annual Cultural Event

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