Mohamed Muzamil H

About

Diligent and task-driven engineer with 5yrs 4mos of total IT experience in India, including 4+ yrs in Data Analytics, Machine Learning and 4mos of Data Science internship experience in Canada. I hold a research-based master's degree from Dalhousie University, Canada. Skilled in Python, Data Science, AI/ML/DL, Distributed Computing, AWS Cloud, Relational and No-SQL Databases. Built data quality tools, ETL pipelines, and deployed machine learning models for a multinational financial services company and major banks to facilitate business analytics and data-driven decision-making.
Passionate about building enterprise systems by taking a pragmatic approach to solving complex business problems. I love to code and enjoy learning new skills. Few of the things I like to do outside work are Distance Running, Workout, Hiking, Tennis.

Education

Jul.2022

Dalhousie University Halifax, NS, Canada

Master of Computer Science

Graduate Courses (4/4.3 GPA):

Data Mining and Data Warehousing (CSCI 6405) by Prof Qiang(Chan) Ye
Machine Learning (CSCI 6505) by Prof Sageev Oore
Deep Learning (CSCI 6516) by Prof Sageev Oore
Visual Analytics (CSCI6612) by Prof Fernando Paulovich
Visualization (CSCI 6406 - Course Audited) by Prof Stephen Brooks

Thesis Research:

My master's thesis focused on applying Data Analytics, Machine learning and Visualization techniques on mobile sensing data to identify behavioural patterns that can indicate mental health.
Dataset consisted of millions of smartphone sensor logs from over 1200 participants.
Feature Engineering, Dimensionality Reduction, KNN Classification and novel visual techniques were used to identify patterns in the data that can indicate the mental health of participants under study.
The key achievement was that the techniques used in this research successfully generated visual clusters that separated participants having mental illnesses from healthy participants.

Thesis Report (Dalhousie Library)

Jun.2014

CMR Institute of Technology Bengaluru, KA, India

Bachelor of Engineering, Electronics & Communication
Graduated First Class Honours/Distinction. Scholarship recipient for academic performance.

Experience

Dec.2022 - Present

Data Analyst

Dalhousie University Halifax, NS, Canada

Development of data pipelines, Data Analysis and Machine Learning at Genetic Epidemiology, Community Health and Computer Science lab (GECCO) and PROSIT lab at Dept of Psychiatry.

Sep.2021 - Dec.2021
4mos

Teaching Assistant

Dalhousie University Halifax, NS, Canada

TA for a graduate level Data Science course called Visual Analytics instructed by - Prof Fernando Paulovich with a strength of 55 students.
Designed course assignments, evaluated/graded submitted assignments, and mentored students with course-related technical queries.

May.2021 - Aug.2021
4mos

Summer Intern - Data Science & Machine Learning

Glas Ocean Electric Halifax, NS, Canada

Developed a data integration/preprocessing pipeline and built machine learning and statistical model training framework to forecast fuel consumption and greenhouse gas emissions of boats.
Data consisted of time-series sensor logs from 5 different fishing boats over a period of 1 year.
The key achievement was improving the predictive capability by experimenting with various regression models and hyper parameter tuning.
Deployed the models on AWS cloud and built Flask REST APIs to serve mobile applications.
Presented a detailed report using standard KPIs, charts and data visualizations to company’s CEO and higher management about the research findings.

Aug.2014 - Dec.2019
5yrs 4mos

Analyst for Data Quality - Big Data & Machine Learning

Infosys Bengaluru, KA, India

Built automation tools for data balancing/comparison leading to an increased productivity by over 75% to validate the reliability of financial data duplicated across multiple data centers in hadoop environment using Python, PySpark, Apache Hive & shell scripting.
Deployed machine learning models in development and production settings to detect anomalies in streaming transaction data over a distributed database reducing false alerts by over 5% compared to statistical methods.
Implemented post-deployment monitoring, logging of the model performance metrics using ELK stack and built reporting dashboards using Graphana to assess quality of the models to improve their continual learning capabilities.
Developed ETL pipelines using Informatica and performed data engineering tasks using advanced SQL queries to migrate a legacy system that processed banking data used for business analytics.
Coordinated with large teams following agile development process to brainstorm, plan and executive innovative solutions and to implement systems with high code quality through regular and systematic code reviews.
Lead a team of 3 developers to mentor and supervise tasks that met Jira user stories.

Projects

Visual Analysis of IRIS data: Interactive visual analytics tool developed using D3.js and Flask to visually analyse a IRIS dataset. This tool was an experimental prototype developed as part of my Master's thesis to test the applicability of Visualization and ML techniques to analyse any given dataset.

code • Heroku_Deployment • Video

Visual Analysis of Mobile Sensing data: Interactive visual analytics tool developed using D3.js and Flask. This tool was developed as part of my Master's thesis to analyse mobile sensing data collected using smartphones of 1200+ participants and correlate their mobile usage behaviour with mental wellness.
Master's Thesis Project

code

Change My Pet: Experimental research project developed as part of Deep Learning Course requirement.
This project used generative models (pre-trained BigGAN) and state-of-the-art segmentation models (DeepLabV3 and FCN) for controlled image generation.
In our case, we experimented with swapping the posture of the synthetically generated image of a Dog with a target posture.

code • Research Paper

Deep Learning Projects: Curated list of Colab Notebooks with implementation of Deep Learning projects in NLP, Image Classification, Clustering and Anamoly Detection.

code