
Wireless SoC FW @ Apple
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Apple
Data Scientist
June 28, 2026 – Present
MatMul_SA
February 20, 2025 – February 28, 2025
This project implements a hardware-accelerated matrix multiplication using High-Level Synthesis (HLS). The design is optimized for FPGA implementation and utilizes on-chip BRAM for efficient data storage and processing.
View ProjectTMMA
February 9, 2025 – Present
TMMA: A Tiled Matrix Multiplication Accelerator for Self-Attention Projections in Transformer Models, optimized for edge deployment on Xilinx KV260.
View ProjectEECS_230P_final_project
November 26, 2024 – December 6, 2024
Develop a machine learning model to classify images from the Fashion MNIST dataset into ten categories using deep learning techniques. The project leverages frameworks like TensorFlow or PyTorch to build and train Convolutional Neural Networks (CNNs) for high classification accuracy.
View ProjectFace_detect_AI
November 1, 2021 – February 25, 2025
Detect human faces in real-time video streams and predict gender and age using advanced machine learning and computer vision techniques.
View ProjectIIC_multiclass_classification
October 27, 2021 – October 29, 2021
The goal is to create a Classification Model for Images. The task would be the same as a typical Data Science Project, Data Preprocessing, Feature Engineering, Building a Model, Tuning a Model, and predicting the Image classes on the Test cases.
View ProjectCMPE183_ETH-simulator
October 13, 2021 – October 13, 2021
CMPE183_ETH-simulator — GitHub repository
View ProjectCMPE130_TSP_project
October 13, 2021 – October 13, 2021
CMPE130_TSP_project — GitHub repository
View ProjectMIPS_pipeline_processor
October 8, 2021 – May 18, 2025
5-stage pipelined MIPS CPU with memory-mapped I/O, GPIO, and factorial accelerator on FPGA
View ProjectCMPE-127-82C55_IO_interface
October 8, 2021 – October 8, 2021
CMPE-127-82C55_IO_interface — GitHub repository
View Projectreact_nodeJS_cryptoApp
June 21, 2021 – September 17, 2021
react_nodeJS_cryptoApp — GitHub repository
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards technical and research-oriented tasks, particularly in hardware acceleration and machine learning. The diversity of projects, from MIPS processors to web applications, indicates a broad technical curiosity. However, the lack of team-based projects or detailed descriptions of contributions makes it difficult to assess cultural fit beyond technical alignment. The target role is Data Scientist, and many projects align with this, but the breadth also suggests interests beyond pure data science.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are concise, but there is no information regarding collaboration, problem-solving approaches, or communication style.