Matteo Dall'Olmo

I'm a

About

My name is Matteo Dall'Olmo, and I am a senior at Washington University in St. Louis, majoring in Computer Science with a second major in Italian. I am deeply passionate about computer science and software development. I'm from Los Angeles, California, and speak English, Italian, and a little bit of Spanish ;).

My professional experience includes internships at Wells Fargo, Boondoggle AI, and OpenX, where I gained skills in full-stack development, Blockchain technologies, and AI Systems. I am actively involved in leadership roles, serving as Captain of the university's water polo team and having served as Vice President of Finance of my fraternity.

Outside of my academic and professional life, I enjoy playing jazz guitar, making ceramics, and tending to my many house plants.

Software Engineer candidate

  • Birthday: December 26th, 2003
  • Born: Los Angeles, CA
  • City: San Francisco, CA
  • Age: 21
  • Degree: Bachelor of Science
  • E-mail: matteo.dallolmo1@gmail.com

My Resume

Engineering Coursework

Some courses that I have taken and the methods and concepts that I have learned.

Computer Science

  • CSE 428 Multi-Paradigm Programming in C++
    • Procedural, Functional, Generic, and Object-Oriented Programming Paradigms
    • Deep dive into C++ syntax and libraries
  • CSE 427 Cloud Computing
    • AWS, Google Cloud, Azure
    • Docker, Kubernetes
  • CSE 347 Analysis of Algorithms
    • Algorithm Design
    • Greedy, Divide & Conquer, Dynamic Programming
    • P Vs NP
  • CSE 132 Introduction to Computer Engineering
    • Arduino C
    • Finite State Machine, Information Representation
    • Signal transmission
    • Delta Timing, x86-64 Assembly code
  • CSE 217A Introduction to Data Science
    • Python
    • Packages: numpy, pandas, keras, matplotlib, seaborn, sklearn
    • Implement Linear regression, Logistics regression, nearest neighbors
    • Implement Decision Tree, Random Forest, Neural Network, feature selection
    • Data Science workflow
  • CSE 247 Data Structures and Algorithms
    • Java
    • Big-O notation and asymptotic analysis
    • Recurrence, Master Method
    • Hashmap, hashtable, heap, binary search tree
    • Dijkstra's algorithm, mergesort, Graph Search
  • CSE 332S Object-Oriented Programming Laboratory
    • C++
    • Pointers and References
    • Dynamic Memory Allocation, smart pointers
    • OOP principles, inheritance
    • Copy Control and Design Patterns
    • Labs: multiple card games, Linux file systems simulator,
  • CSE 412 Intro to AI
    • Python
    • BFS, DFS, Greedy Search, A*
    • Minimax, Alpha-Beta, Expectimax, Backtracking
    • Bayesian Networks, Markov Models, Value & Policy Iteration
    • Q-Learning, Entailment, WalkSAT
  • CSE 433 Intro to Computer Security
    • C
    • Network architecture, packet sniffing & spoofing
    • Buffer overflows, race conditions
    • Stream & block ciphers, hash functions
    • Asynch and synchronous cryptography, PKI
    • Software security, fuzzing

Mathematics

  • Math 233: Multivariable Calculus
    • Three space, partial derivatives, multiple integration
    • Surface integrals, vector fields, line integrals
    • Flux surfaces, Green & Stoke's theorems, vector calculus
  • Math 240: Logic & Discrete Mathematics
    • Discrete structures, proof techniques
    • Prepositional & predicate logic, sets, relations, functions and graphs
    • proofs by contradiction, induction and reduction
    • finite state machines and regular languages
  • Math 309: Matrix Algebra
    • Vector spaces, linear independence/dependence
    • Dimensions, nullspace, range, basis
    • Polynomials, linear transformations, determinants, eigenvalues
  • Math 3200: Elementary to Intermediate Statistics and Data Analysis
    • Probability Theorems and Proof, Bayesian Theorem, Combinations and Permutations
    • Discrete probability distributions: Binomial, Geometric, Poisson.
    • Continuous probability distributions: Exponential, Gamma, Normal, Student-T, Chi-Squared, F, etc.
    • Mean, Variance, Co-variance, Joint-distirbution, marginal probability
    • Confidence Interval and Hypothesis Testing