AI Systems | End-to-End AI Solutions from Hardware to Software | Focused on Compute Optimization
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
The areas of research I have focused on include optimizing machine learning algorithms for FPGA. Most recently, I have published articles on low numeric precision, sparsity, and evolutionary algorithms.
University of Massachusetts Lowell
Doctor of Philosophy (PhD), Computer Engineering
January 1, 2014 – January 1, 2019
University of Massachusetts Lowell
Master of Science (M.S.), Computer Engineering
January 1, 2013 – January 1, 2014
University of Massachusetts Lowell
Bachelor of Science (B.S.), Electrical Engineering, Robotics, Embedded Systems
January 1, 2009 – January 1, 2012
Emerald AI
Member of Technical Staff
April 1, 2025 – Present
Boston, Massachusetts, United States · Hybrid
AMD
Senior Machine Learning Engineer
August 1, 2023 – April 1, 2025
Boston, Massachusetts, United States · Remote
Groq
Machine Learning Engineer
December 1, 2021 – August 1, 2023
Intel Corporation
Machine Learning and Design Engineer
June 1, 2016 – December 1, 2021
Intel Corporation
PhD Intern
December 1, 2015 – June 1, 2016
Altera
Intern
August 1, 2015 – December 1, 2015
San Jose, California
University of Massachusetts Lowell
Graduate Research Assistant
September 1, 2014 – December 1, 2019
BAE Systems
Software Engineer
September 1, 2014 – August 1, 2015
Nashua
University of Massachusetts Lowell
Teaching Assistant
September 1, 2013 – September 1, 2015
Mr Meds
September 1, 2014 – January 1, 2015
Medication handling in a hospital setting is challenging; if errors are made, patients can suffer threatening side effects that in extreme cases can lead to death. To address this issue, we propose Mr. Meds, a novel mobile robotic platform designed to minimize human errors associated with medication scheduling and dispensing. Using cutting edge technology such as face detection and voice recognition, this system will have the capability to interact with patients and verify their identity. Interfacing through a web application, Mr. Meds will also make the job of a pharmacist more streamlined. Mr. Meds will automate a process that is currently time consuming and prone to human error due to hospitals being extremely busy. Performance evaluations show that the prototype of Mr. Meds can deliver medications to patients in an efficient manner.
Robotic Feeding Arm
January 1, 2012 – January 1, 2015
The Robotic Feeding Arm is an assistive technology device that gives independence to those relying on feeding assistance.
Cultural Fit Analysis
The candidate's experience is heavily skewed towards Machine Learning Engineering, hardware acceleration, and embedded systems, which is a significant mismatch for a 'Data Analyst' target role. While they possess strong technical skills, the specific domain expertise (ML/hardware optimization) does not directly align with typical data analysis responsibilities such as statistical modeling, data visualization, SQL, or business intelligence. The projects, while innovative, also reflect this ML/robotics focus rather than data analysis. This indicates a low cultural fit for the specified target role.
Soft Skills & Operational Fit
The candidate's project descriptions for 'Mr Meds' and 'Robotic Feeding Arm' indicate an ability to identify real-world problems and propose innovative, technology-driven solutions, suggesting problem-solving and innovation skills. The teaching assistant role also implies communication and mentorship abilities. However, the provided data does not offer direct insights into stress handling, team collaboration, or work attitude beyond the general nature of their roles.