About

Welcome to my Portfolio

Profile Picture

I'm a University of Toronto 2022 graduate student specializing in Software Engineering with a minor in Statistics. My passions include learning new technical tools and using them to create practical applications.

Profile

I'm currently seeking a student software engineering/data science position. I'm currently open to relocation. If you think I'm a good fit, please contact me via ben.gavrilov@mail.utoronto.ca.

  • Fullname: Ben Gavrilov
  • Birth Date: November 26, 1999
  • Email: ben.gavrilov@mail.utoronto.ca

Skills

I'm a hard worker with a high tolerance for rapid change both from a technical and non-technical standpoint. I'm especially proficient in the design and analysis of abstract data structures and can apply it on just about any technical platform.

  • 95%
    Python
  • 90%
    C
  • 90%
    Java
  • 90%
    Golang
  • 85%
    SQL (MySQL, PostgreSQL)
  • 85%
    NoSQL(Elasticsearch,MongoDB,DynamoDB)
  • 90%
    React & TypeScript
  • 85%
    AWS
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Resume

More of my credentials.

Here are my work experiences and education.

Work Experience

Software Engineer

May 2021 - August 2021

Relay Financial (Series A Startup)

  • Overlooked and implemented internal tooling components that reduced over 20 hours a week of engineering support for the customer service team by utilizing Node, React, Typescript, and AWS
  • Streamlined internal tooling development processes by setting up robust CircleCI pipelines to schedule unit test automations, configure builds and deployments, and report logs to CloudWatch
  • Saved over $37,000 USD by introducing the first transaction disputing functionality which allows internal users to dispute fraudulent account activity by integrating with QuickBooks, Xero, Finicity, Sardine, Middesk, and Gusto

Software Engineer

September 2020 - December 2020

Sportcred

  • Developed a beta version sports themed social media platform
  • Constructed a web application with React JS on the front-end, Golang on the back-end, Neo4j for data warehousing, and Firebase SDKs to store images in a Google Cloud Storage bucket
  • Introduced a completely modular microservice architecture where all components communicate via REST API
  • Worked with UX designers, product owners, quality assurance analysts, and a scrum master within an agile environment to facilitate deliverables

Technical Systems Engineer

May 2020 - August 2020

Royal Bank of Canada (RBC)

  • Worked within the wealth management team to maintain information systems consisting of market data on the cloud
  • Developed Python applications for automation with Jenkins continuous integration for data processing pipelines
  • Delivered applications utilizing rest API calls from internal microservices that connect to the ELK (Elasticsearch, Logstash, Kibana) stack (NoSQL) through OpenShift (docker, kubernetes) automation
  • Reduced logback processing time by 35% through multithreading with file channel streams and byte buffers
  • Set up a monitoring service for an internal server with agents tracking API calls, resource allocation, and response time aggregation
  • Developed, implemented, and visualized models in Python to aid in predicting failure rates of internal microservices using daily Dynatrace data

Software Engineer

May 2019 - August 2019

Bond Brand Loyalty (BBL)

  • Developed to specifications based on PBIs (Azure DevOps) for abstract applications using the ASP.NET MVC 5 framework
  • Designed, coded, tested, debugged and documented web applications- Desktop and mobile responsive sites
  • Delivered solutions balancing technical and business requirements with the Digital Development team
  • Upheld back-end by maintaining UAT/PROD MS SQL servers, databases, and Web/Rest APIs for Scotiabank Rewards
  • Developed front-end user interface utilizing HTML5, CSS, jQuery, Bootstrap, and Angular infrastructures

Data Analyst

September 2014 - November 2014

Advantex

  • Collected and manipulated over 1200 small business data using Microsoft Excel and Java automation processes
  • Worked closely with business analysts to apply logical analytics to develop solutions for small businesses

Education

Bachelor of Science

September 2017 - April 2022

University of Toronto

  • Completed

Ontario Secondary School Diploma (OSSD)

September 2013 - June 2017

Stephen Lewis Secondary School

  • Completed
Projects
Spotlight Projects
Pathfinding Visualizer
Chatting Platform
Ben's Personal Site
Image Manipulation
Reverse Image Search
Image Database
Image Filters
Compression
Text Compression
School

April 2022

BSc in Computer Science, Mathematics, & Statistics
Software Engineering Specialization
Statistics Minor

Contact

I'd love to connect with you.

Let me get to know more about you.

Where to find me

27 King's College Cir
Toronto, ON
M5S Canada

Email Me At

ben.gavrilov@mail.utoronto.ca

Let's Connect
LinkedIn Profile
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1st Year Courses

CSCA08: Introduction to Computer Science I

Programming in an object-oriented language such as Python. Program structure: elementary data types, statements, control flow, functions, classes, objects, methods. Lists; searching, sorting and complexity. This course is intended for students having a serious interest in higher level computer science courses, or planning to complete a computer science program.

CSCA48: Introduction to Computer Science II

Abstract data types and data structures for implementing them. Linked data structures. Object Oriented Programming. Encapsulation and information-hiding. Testing. Specifications. Analyzing the efficiency of programs. Recursion.

CSCA67: Discrete Mathematics

Introduction to discrete mathematics: Elementary combinatorics; discrete probability including conditional probability and independence; graph theory including trees, planar graphs, searches and traversals, colouring. The course emphasizes topics of relevance to computer science, and exercises problem-solving skills and proof techniques such as well ordering, induction, contradiction, and counterexample.

MATA22: Linear Algebra I for Mathematical Sciences

A conceptual and rigorous approach to introductory linear algebra that focuses on mathematical proofs, the logical development of fundamental structures, and essential computational techniques. This course covers complex numbers, vectors in Euclidean n-space, systems of linear equations, matrices and matrix algebra, Gaussian reduction, structure theorems for solutions of linear systems, dependence and independence, rank equation, linear transformations of Euclidean n-space, determinants, Cramer's rule, eigenvalues and eigenvectors, characteristic polynomial, and diagonalization.

MATA31: Calculus I for Mathematical Sciences

A conceptual introduction to Differential Calculus of algebraic and transcendental functions of one variable; focus on logical reasoning and fundamental notions; first introduction into a rigorous mathematical theory with applications. Course covers: real numbers, set operations, supremum, infimum, limits, continuity, Intermediate Value Theorem, derivative, differentiability, related rates, Fermat's, Extreme Value, Rolle's and Mean Value Theorems, curve sketching, optimization, and antiderivatives.

MATA37: Calculus II for Mathematical Sciences

A rigorous introduction to Integral Calculus of one variable and infinite series; strong emphasis on combining theory and applications; further developing of tools for mathematical analysis. Riemann Sum, definite integral, Fundamental Theorem of Calculus, techniques of integration, improper integrals, numerical integration, sequences and series, absolute and conditional convergence of series, convergence tests for series, Taylor polynomials and series, power series and applications.

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2nd Year Courses

CSCB07: Software Design

An introduction to software design and development concepts, methods, and tools, using a statically-typed object-oriented language such as Java. Topics from: version control, build management, unit testing, refactoring, object oriented design and development, design patterns and advanced IDE usage.

CSCB09: Software Tools and Systems Programming

Software techniques in a Unix-style environment, using scripting languages and a machine-oriented programming language (typically C). What goes on in the system when programs are executed. Core topics: creating and using software tools, pipes and filters, file processing, shell programming, processes, system calls, signals, basic network programming.

CSCB36: Introduction to the Theory of Computation

Mathematical induction with emphasis on applications relevant to computer science. Aspects of mathematical logic, correctness proofs for iterative and recursive algorithms, solutions of linear and divide-and-conquer recurrences, introduction to automata and formal languages.

CSCB58: Computer Organization

Principles of the design and operation of digital computers. Binary data representation and manipulation, Boolean logic, components of computer systems, memory technology, peripherals, structure of a CPU, assembly languages, instruction execution, and addressing techniques. There are a number of laboratory periods in which students conduct experiments with digital logic circuits.

CSCB63: Design and Analysis of Data Structures

Design, analysis, implementation and comparison of efficient data structures for common abstract data types. Priority queues: heaps and mergeable heaps. Dictionaries: balanced binary search trees, B-trees, hashing. Amortization: data structures for managing dynamic tables and disjoint sets. Data structures for representing graphs. Graph searches.

MATB24: Linear Algebra II

Fields, vector spaces over a field, linear transformations; inner product spaces, coordinatization and change of basis; diagonalizability, orthogonal transformations, invariant subspaces, Cayley-Hamilton theorem; hermitian inner product, normal, self-adjoint and unitary operations. Some applications such as the method of least squares and introduction to coding theory.

STAB52: An Introduction to Probability

A mathematical treatment of probability. The topics covered include: the probability model, density and distribution functions, computer generation of random variables, conditional probability, expectation, sampling distributions, weak law of large numbers, central limit theorem, Monte Carlo methods, Markov chains, Poisson processes, simulation, applications. A computer package will be used.

STAB57: An Introduction to Statistics

A mathematical treatment of the theory of statistics. The topics covered include: the statistical model, data collection, descriptive statistics, estimation, confidence intervals and P-values, likelihood inference methods, distribution-free methods, bootstrapping, Bayesian methods, relationship among variables, contingency tables, regression, ANOVA, logistic regression, applications. A computer package will be used.

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3rd Year Courses

MATB41: Techniques of the Calculus of Several Variables I

Partial derivatives, gradient, tangent plane, Jacobian matrix and chain rule, Taylor series; extremal problems, extremal problems with constraints and Lagrange multipliers, multiple integrals, spherical and cylindrical coordinates, law of transformation of variables.

MATB42: Techniques of the Calculus of Several Variables II

Fourier series. Vector fields in Rn, Divergence and curl, curves, parametric representation of curves, path and line integrals, surfaces, parametric representations of surfaces, surface integrals. Green's, Gauss', and Stokes' theorems will also be covered. An introduction to differential forms, total derivative.

CSCC43: Introduction to Databases

Introduction to database management systems. The relational data model. Relational algebra. Querying and updating databases: the SQL query language. Application programming with SQL. Integrity constraints, normal forms, and database design. Elements of database system technology: query processing, transaction management.

CSCC69: Operating Systems

Principles of operating systems. The operating system as a control program and as a resource allocator. The concept of a process and concurrency problem: synchronization, mutual exclusion, deadlock. Additional topics include memory management, file systems, process scheduling, threads, and protection.

CSCC73: Algorithm Design and Analysis

Standard algorithm design techniques: divide-and-conquer, greedy strategies, dynamic programming, linear programming, randomization, and possibly others.

CSCC01: Introduction to Software Engineering

Introduction to software development methodologies with an emphasis on agile development methods appropriate for rapidly-moving projects. Basic software development infrastructure; requirements elicitation and tracking; prototyping; basic project management; basic UML; introduction to software architecture; design patterns; testing.

CSCC24: Principles of Programming Languages

Major topics in the design, definition, analysis, and implementation of modern programming languages. Study of programming paradigms: procedural (e.g., C, Java, Python), functional (e.g., Scheme, ML, Haskell) and logic programming (e.g., Prolog, Mercury).

CSCC37: Introduction to Numerical Algorithms for Computational Mathematics

An introduction to computational methods for solving problems in linear algebra, non-linear equations, approximation and integration. Floating-point arithmetic; numerical algorithms; application of numerical software packages.

CSCC63: Computability and Computational Complexity

Introduction to the theory of computability: Turing machines, Church's thesis, computable and non-computable functions, recursive and recursively enumerable sets, reducibility. Introduction to complexity theory: models of computation, P, NP, polynomial time reducibility, NP-completeness, further topics in complexity theory.

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4th Year Courses

STAC67: Regression Analysis

Orthogonal projections. Univariate normal distribution theory. The linear model and its statistical analysis, residual analysis, influence analysis, collinearity analysis, model selection procedures. Analysis of designs. Random effects. Models for categorical data. Nonlinear models. Instruction in the use of SAS.

STAC62: Stochastic Processes

This course continues the development of probability theory begun in STAB52H3. Topics covered include finite dimensional distributions and the existence theorem, discrete time Markov chains, discrete time martingales, the multivariate normal distribution, Gaussian processes and Brownian motion.

STAD37: Multivariate Analysis

Linear algebra for statistics. Multivariate distributions, the multivariate normal and some associated distribution theory. Multivariate regression analysis. Canonical correlation analysis. Principal components analysis. Factor analysis. Cluster and discriminant analysis. Multidimensional scaling. Instruction in the use of SAS.

CSCD03: Social Impact of Information Technology

The trade-offs between benefits and risks to society of information systems, and related issues in ethics and public policy. Topics will include safety-critical software; invasion of privacy; computer-based crime; the social effects of an always-online life; and professional ethics in the software industry. There will be an emphasis on current events relating to these topics.

CSCD01: Engineering Large Software Systems

An introduction to the theory and practice of large-scale software system design, development, and deployment. Project management; advanced UML; requirements engineering; verification and validation; software architecture; performance modeling and analysis; formal methods in software engineering.

CSCC11: Introduction to Machine Learning and Data Mining

An introduction to methods for automated learning of relationships on the basis of empirical data. Classification and regression using nearest neighbour methods, decision trees, linear and non-linear models, class-conditional models, neural networks, and Bayesian methods. Clustering algorithms and dimensionality reduction. Model selection. Problems of over-fitting and assessing accuracy. Problems with handling large databases.

CSCC46: Social and Information Networks

How networks underlie the social, technological, and natural worlds, with an emphasis on developing intuitions for broadly applicable concepts in network analysis. Topics include: introductions to graph theory, network concepts, and game theory; social networks; information networks; the aggregate behaviour of markets and crowds; network dynamics; information diffusion; popular concepts such as "six degrees of separation", the "friendship paradox", and the "wisdom of crowds".

CSCD84: Artificial Intelligence

A study of the theories and algorithms of Artificial Intelligence. Topics include a subset of: search, game playing, logical representations and reasoning, planning, natural language processing, reasoning and decision making with uncertainty, computational perception, robotics, and applications of Artificial Intelligence. Assignments provide practical experience of the core topics.

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Reverse Image Search

    Nowadays most search engines provide some support for image retrieval, which allows you, for example, to search the web for images that are similar to a given image. If a search engine used a single process to search a large number of images to find the most similar one it would take a very long time to get the results. This project allows users to input an image file and a directory (think of this as the global dataset) to search for the most similar image. The user can then choose to either perform the search using a single process or to use a parallel version that forks new processes and manages communication through various pipes. In reality, determining how similar two images are is a complex problem, which is in fact an active area of research. The project uses a simple metric based on the Euclidean distance between two pixels of different images. The purpose of this project was to demonstrate drastic performance differences between delegating a task to a single process vs a parallel process. (Github Link)
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Image Database (for querying)

    It is important to ease data access so that logs and reports can be completed more effectively. This project consists of an image database that allows for storage and querying of different image files. When entering an image a user must select some attributes associated with the image. These attributes are then used to query. When querying a user must select an array of attributes and the query will return all images with all the given attributes. The user can also perform removal queries where images with the given attributes are deleted. The project also allows for a print command which prints all of the current images in the database. Keep in mind that when querying, images are returned in order of insertion, that is the most recently added images in that query will appear last. (Github Link)
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Image Filters

    Image manipulation seems to be a rather popular feature among many image based platforms (I.e, Instagram, Snapchat). Image manipulation can be achieved rather easily by manipulating the rgb colour spectrum. Images are usually represented by dimensions of pixels, and so we can manipulate each individual pixel. Each pixel for a colour image is encoded by three numbers representing the colour of the pixel. The first number is the red value, the second number is the green value, and the third number is the blue value for that individual pixel. Given this structure we can perform manipulations. For example, suppose we want to make a coloured image black and white. This can be done by averaging the values of all three colour numbers for a pixel and replacing each of those colour numbers with the average. Do this for all pixels and voila! (Github Link)
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Text Compressor

    Compression allows for more practical data storage and transport. It is what allows us to access content at a time effective rate. Think about streaming sites, it would take far too long to transmit the actual file size. Instead it is compressed and decompressed upon transmission to save time but more importantly space! This program allows a user to upload a .txt file and compress it to a form thats on average ~30% smaller in size whilst maintaining its original integrity. Upon usage run the decoder to get the original .txt file. The algorithm uses the huffman coding model to achieve loseless compression. A huffman code is a type of prefix code. The algorithm takes all the unique characters in the .txt file and derives a Huffman tree from the estimated probability or frequency of occurrence of each character for all the common characters. Since we know that a .txt file contains characters and symbols where each character/symbol requires a byte (8 bits) of storage; we can encode this to manipulate file size. Instead we store each character in its encoded binary representation. The idea is that characters/symbols that appear more frequently in the file will be represented by a binary representation smaller than 8 bits in size. Characters that don't appear frequently in the file can take up a greater amount of bits. The net size will always be smaller than the original file. (Github Link)
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My Site

    I've created this personal website to not only showcase my accomplishments but more so to illustrate my web development capabilities (Homepage). I created this site using:
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Pathfinding Visualizer

    Pathfinding algorithms have always been one of the most critical structures for many modern applications. Take a look at google maps for example, when you want to get directions to a location, google maps gives you a route. Now note that this route is the shortest possible path at the current time as it would be too time costly to give an arbitrary path. Factors that determine the shortest path may include traffic and the number of lanes on a road. These are all congestion factors that help find the shortest path. Take a look at another scenario within Uber Pool for example. You are putting a second stop before your final location so the shortest path must consider the shortest path to the second stop and then the shortest path to the final stop. These are all features that have been implemented into this visualizer. You can add checkpoints as well as add obstructions between points and the application will still find the shortest path. Some of the algorithms used include Dijkstra's algorithm, A* Search, Breadth-first Search, and Depth-first Search (this will not always yield the fastest path). Play around with the application to gain a better understanding of Pathfinding algorithms. (Use the App)
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Chatting Platform

    What's the worlds most sought after resource? An uninterrupted medium for communication. Our means of communication is often the most overlooked technological tool. Today we are able to communicate via messaging, emailing, video chatting, audio chatting, as well as in plenty of other forms. It is crazy to think that two people at separate locations on earth can communicate over the internet. Although not as complex as many modern day communication platforms, this chat application hosts a server (a main lobby per say) where individuals can log on with their first and last name and chat with anyone else on the server anywhere around the world. This is in principle how a reddit forum works or perhaps a discord chat operates. The app was made with Node.js, express, and websockets to allow different clients to communicate via the server. The client interface always displays the number of current users on the server as well as notifies them when a user has entered or left the main chat. (Use the App)