Machine Shop

Alexander Yu

Sayreville NJ, *****

732-***-**** ************@*****.*** linkedin.com/in/alexander-yu-49034a268 Education

Rowan University Sep. 2018 – May 2022

Bachelor of Science in Electrical and Computer Engineering with Bantiviglio Honors Concentration Glassboro, NJ Rutgers University Sep. 2024 – Ongoing

Master of Science in Electrical and Computer Engineering with Specialization in Machine Learning New Brunswick, NJ Experience

Atlantic Casting & Engineering July 2023 – November 2023 IT & Machine Shop Planner Clifton, NJ

• Managed company-wide network’s user access control list; oversaw permissions based on roles, and provided technical support for access issues

• Led efforts to implement an ERP system for Machine Shop purposes by coordinating with teams to optimize usage, and training new employees on how to use the software.

• Oversaw inventory in the machine shop materials and the acquisition process, and led efforts to create a stock forecasting system to prevent future issues.

Projects

Explainable AI in Genomics: TFBS Prediction with Transformers Sep. 2021 – May 2022

• Fine-tuned GPT2 using knowledge distillation to predict transcription factor binding given a DNA sequence using a pre-trained model and the DeepBIND model

• Generated Motifs as visualization of what the model has learned through techniques like GradCAM and ShiftSmooth Face Recognition with kNNs and DCT Nov 2021

• Used Discrete Cosine Transforms and k-nearest neighbor (kNN) algorithms to design a smarter facial recognition platform to solve the accuracy issues currently affecting face identification with the existing methods. J-K Flip Flop Optimization using Logical Effort Dec 2021 – Jan 2022

• Implemented logical effort techniques to achieve size and delay optimization for a J-K Flip Flop.

• Utilized Cadence for schematic and layout construction, ensuring efficient and accurate representation. Noisy Speech Enhancement May 2021

• Implemented a Wiener Filter for cleaning up noisy speech signals, to gain an understanding in noise reduction algorithms, and employed PESQ to evaluate the effectiveness of the Wiener Filter MEMS Microphone Dec 2020

• Designed an embedded system to acquire data from a MEMS microphones and transmit it using an MSP430F5529.

• Implemented a linear data flow, from MEMS microphone connections to ADC conversion and simulated UART transmission.

• Developed MATLAB code to interpret ASCII data from the COM port, convert it to double data type, and visualize AC and DC components in real-time.

Relevant Coursework

• Data Structures

• Cyber Security

• Embedded Systems

• Computer Architecture

• Systems and Controls

• Dig. Signal Processing

Technical Skills

• C++

• Python

• MATLAB

• Breadboards

• Microsoft Office Suite

• Soldering

• Java

• DE10-Lite

Accomplishments

A Comparison of Feature Selection Techniques for First-day Mortality Prediction in the ICU

• Applied classical machine learning techniques to compare sets of signals from patient records, focusing on demographic information, lab values, and vital sign measurements.

• Assisted in finding the feature set that optimally informs first-day mortality predictions. https://jrepifano.github.io/papers/featureselection.pdf

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