Saeed Damadi

AI Researcher

Irvine, California, United States7 yrs 3 mos experience

Most Likely To Switch

Key Highlights

Expert in deep learning and neural network optimization.
Passionate about advancing quantitative trading systems.
Strong academic foundation in mathematics and statistics.

Stackforce AI infers this person is a Machine Learning Researcher with a focus on AI efficiency and quantitative analysis.

Contact

Skills

Core Skills

TeachingMachine LearningDeep LearningLean StartupStatistical Data AnalysisData Analysis

Other Skills

Linear AlgebraPython (Programming Language)LinuxMachine Learning AlgorithmsStatistical ModelingQuantitative ResearchStochastic ProcessesStochastic SimulationStochastic OptimizationLinear ProgrammingNumerical Linear AlgebraGoogle Cloud Platform (GCP)Time Series AnalysisEngineering EconomicsMATLAB

About

I don’t just build AI models—I design systems that make AI work at scale. From compressing large models to optimizing cloud infrastructure, I’ve tackled the challenges of making AI efficient, scalable, and cost-effective. I know what it takes to turn cutting-edge research into products that deliver real value. I know what it takes to turn cutting-edge research into products that deliver real value. I am experienced researcher in deep learning, specializing in neural network designs and compression, time series analysis, and nonlinear sparse optimization. I possess a strong academic foundation in mathematics (Ph.D. candidate), statistics (M.Sc.), and electrical engineering (M.Sc.). My experience is complemented by teaching roles in statistics, linear algebra, and other courses at UMBC and Towson University. I am passionate about advancing quantitative trading with sophisticated deep neural networks and machine learning models, backed by rigorous mathematics and statistics. Moving forward, my goal is to create an automated trading system that identifies and capitalizes on market patterns. There has never been a better time than now, with large language models at your disposal to augment your knowledge and propel you forward. The future is indeed bright!

Experience

7 yrs 3 mos

Total Experience

2 yrs 10 mos

Average Tenure

7 yrs 3 mos

Current Experience

Fda

Researcher

Feb 2026 – Present · 2 mos

National science foundation (nsf)

NSF I-Corps Researcher

Mar 2024 – Jun 2024 · 3 mos

Lean Startup

Towson university

Adjunct Faculty

Sep 2022 – Dec 2023 · 1 yr 3 mos · Towson, Maryland, United States

I taught an undergraduate course in Basic Statistics.

Statistical Data AnalysisStatistical ModelingTeaching

Ifm

Machine Learning Data Analyst Intern

May 2022 – Aug 2022 · 3 mos · Pennsylvania, United States · Remote

Developed machine learning algorithms to automate sensor screening processes for manufacturing quality control.

Python (Programming Language)Machine Learning

University of maryland baltimore county

2 roles

Instructor

Jan 2020 – Present · 6 yrs 3 mos

I taught undergraduate courses in Calculus I, Calculus II, and Linear Algebra.

Linear AlgebraTeaching

Ph.D. Graduate Student in Applied Mathematics

Jan 2019 – Present · 7 yrs 3 mos

As a PhD researcher in machine learning at UMBC, I have been actively engaged in the exploration and application of a wide array of machine learning algorithms. My expertise encompasses a variety of areas including recommendation systems, pattern recognition, data mining, computer vision, and both supervised and unsupervised learning techniques.
My current research delves into the compression of deep neural networks through pruning, aimed at reducing the model's parameter count without sacrificing performance. This involves addressing complex issues such as constrained, stochastic, nonconvex, and non-differentiable optimization problems on a large scale. The outcomes are poised to decrease energy consumption, lessen hardware requirements, and quicken response times.

Python (Programming Language)LinuxDeep LearningMachine LearningMachine Learning Algorithms

Maryland department of information technology

Machine Learning Data Analyst Intern

May 2019 – May 2020 · 1 yr · United States

I have created an ETL (Extract Transform Load) pipeline using Python for cleaning, appending, and storing quarterly crash data including more than half a million crashes registered by the Maryland State Police.
I have created a dashboard using Qlik Sense (analytics) and Python to analyze the polished data to extract information for the other Maryland’s departments.
I have applied K-mean algorithm as an unsupervised learning to the Maryland Property Assessments data including 4.6 million records with 227 features for each record, to create clusters within zip codes in order to find new features characterizing the welfare of each cluster.
I have been cited by the Governor of the state of Maryland (Larry Hogan) for creating visualization dashboards.