Mark Fahim
AI Engineer & ML Specialist
I am an AI engineer and software engineer working at the intersection of machine learning systems, and full-stack development. I hold a Master of Artificial Intelligence, along with graduate certificates in AI Engineering and Natural Language Processing. With a foundation in mobile and backend development and experience building production-level ML pipelines, and LLM-powered systems, I focus on turning complex data into reliable, deployable solutions that drive measurable outcomes.
My Stack
My Journey
Built machine learning models using TensorFlow and Scikit-learn to predict opioid-related deaths, improving accuracy by 15% through feature selection and hyperparameter tuning. Led the Sustainable Energy Marketplace project, analyzing public sentiment data with NLP, identifying correlations between societal support, investment trends, and job creation. Designed web-scraping pipelines using Python (BeautifulSoup, Scrapy) to collect data for an NSF-funded study on gender disparities in bankruptcy. Applied NLP algorithms to analyze over 5 million records, uncovering socioeconomic patterns. Applied statistical modeling and data mining with Pandas and SQL to extract insights, reducing analysis time by 20%.
Gender GAP in Bankruptcy Filings funded by NSF. Utilized PACER datasets to collect and analyze bankruptcy filings, focusing on identifying cases filed for business reasons. Designed a web scraper to extract petitioner names and other pertinent information. Developed a textual analysis-based routine to classify bankruptcy filings by gender. Project implemented using the HPC ROAR computer for efficient processing.
Led software development projects, ensuring timely delivery via daily stand-ups, sprint planning, and sprint reviews. Collaborated closely with the development team, providing guidance throughout the Agile process. Communicated project progress to top management. Developed process automation scripts and dashboards. Managed data integration using RESTful APIs. Preprocessed data from NoSQL sources to SQL management systems.
Used SQL and Python for complex queries against relational databases. Collaborated with cross-functional teams (Data Science, Product, Development, Marketing). Preprocessed datasets for ML models through manipulation, cleaning, and management. Proficient with supervised and unsupervised ML methods. Maintained predictive models to guide Marketing decisions. Visualized data with Tableau, Power BI, and Python (Matplotlib, Plotly, Seaborn).
Collaborated with the software development team throughout the Agile process. Refactored legacy Android application to Kotlin with Coroutines, LiveData, and MVVM. Developed payment gateway solutions integrated with mobile and web apps. Managed Oracle SQL DBs and developed backend API systems using .NET, Entity Framework, stored procedures, triggers, and functions.
Collaborated with cross-functional teams to define, design, and build new app features. Converted Sketch/Figma prototypes into UI code. Proficient in Flutter (Dart) with state management using Provider and MVVM/Redux architectures. Wrote highly maintainable code. Updated application design and workflow for user needs. Enhanced performance and implemented new features.
Academic Background
Achieved 3rd position in engineering innovation at the Fifth Scientific Event of Cairo University. Participated in the Self-Powered Generator competition.
Publications & Research
Using the Fukushima Daiichi nuclear disaster as a natural experiment, we built a Social Readiness Level (SRL) framework powered by large-scale NLP on national news and public discourse. We operationalized Social Readiness Level (SRL) as a quantitative measure of how socially, politically, and institutionally prepared society is to support large-scale technology deployment. Processed large-scale public discourse using NLP, built a sentiment-to-readiness transformation model, anchored thresholds to pre-shock baselines, and integrated SRL into panel regressions with time fixed effects. Core insight: Trust is not merely emotional — it behaves like a measurable risk factor within infrastructure systems.
Extended the SRL + NLP framework to real market outcomes: linking societal readiness to equity trading behavior and volatility in nuclear and traditional energy firms, examining its impact on employment growth in energy-sector labor markets, and using time fixed-effects panel regression to isolate societal effects from macroeconomic shocks. Leveraged the Fukushima accident as a system-wide shock to study structural shifts in risk and employment. Higher societal readiness correlates with lower volatility in energy equities, stronger capital participation, and greater employment expansion in clean and nuclear energy firms.
Featured Projects
Developed a green energy investment model examining the impact of societal acceptance on financial returns and investment decisions, particularly in the post-Fukushima era. By analyzing empirical data with NLP, the project shows that public sentiment significantly influences investment flows, profitability, and job creation. Findings stress the importance of aligning investment strategies with societal values to promote sustainable energy transitions.
Focused on predicting and preventing opioid deaths by analyzing social, economic, and demographic data. Collaborating with Penn State faculty and graduate students, the project uses data-driven AI/ML approaches to identify risk factors and geographic regions with high opioid death rates. Developed a model for targeted interventions using CDC data and computational techniques.
Developed Vocal Bridge, an NLP-powered system that dubs English videos into Turkish, German, Italian, Spanish, or Hungarian with synchronized audio and subtitles. Trained Seq2Seq LSTM models (91.1% accuracy for Turkish) and transformer-based MarianMT models (BLEU scores up to 56.66% for Italian) on datasets of up to 364,199 sentence pairs using Penn State's ROAR HPC.
Honors & Awards
Awarded 3rd place for presenting research on Opioid Epidemic at the Penn State Great Valley Poster Competition. Recognized for innovation, analytical approach, and clarity in communicating research findings.
Selected by Prof. Sorokina and Prof. Ramljak to support the Opioid Epidemic research project through project management, data analytics, and engineering research. Featured by Penn State News.
Achieved third place in the field of engineering innovation at Cairo University's Innovation Competition. Presented a practical and executable idea for a self-powered generator.
Volunteering & Leadership
Directed the Computer Department, mentoring members and overseeing workshops on Android and web development. Fostered technical skill development and knowledge sharing.
Represented Egyptian teams during the ideation camp, contributing to innovative ideas in IoT and artificial intelligence.
Developed two technology-driven applications: The Adventurers App (hobbies, sports, entertainment bookings) and The Business App (sales automation, team/inventory management, analytics). Halted due to COVID-19 pandemic.
Developed and maintained the official website for the summit event held in December 2019. Collaborated on designing and implementing an engaging summit program.
Represented Cairo University and the Faculty of Computers and Artificial Intelligence at the World Youth Forum.
Developed and launched the official TEDxCairoUniversity mobile application on the Google Play Store, enhancing user engagement and accessibility for event information.
What Others Say
It is my pleasure to highly recommend Mark Fahim. Mark has demonstrated exceptional engineering acumen, an outstanding work ethic, and a deep understanding of technical concepts during his academic tenure. Please view the attached letter for full details regarding his academic and professional capabilities.
I am writing to recommend Mark Fahim. He worked with us at IDH as a Software Engineer and reported to me in my position as Project Manager. I have known Mark for two years in IDH and I am still working with him on freelancing projects. During our time working together, Mark demonstrated very strong technical knowledge, combined with leadership skills instrumental in driving successful project outcomes, and was always passionate about learning and self-development. Mark is highly knowledgeable in software engineering, with specific focus on data science, machine learning, and mobile development. His ability to effectively lead software development projects, ensuring timely and high-quality deliverables, was exemplary. I have witnessed Mark's commitment to Agile principles and best practices, which contributed to the overall success of our projects. What sets Mark apart is his exceptional communication skills and ability to collaborate effectively with diverse stakeholders, including cross-functional teams, clients, and top management. He possesses strong problem-solving abilities, enabling him to analyze complex issues and implement appropriate solutions. I have no doubt that Mark would excel in any professional or academic pursuit.