Wafik Aboualim
M.S. thesis student in computer science at the University of Pittsburgh.
I am a Master's thesis student at the University of Pittsburgh specializing in machine learning and reinforcement learning. My work focuses on algorithms that connect theory and practice, especially for real-world decision-making and optimization problems.
I am particularly interested in applied ML/RL, algorithms with predictions, and quantum computing. Alongside research, I have more than two years of industry experience building full stack and mobile applications.
Email: wat29 [at] pitt [dot] edu.
GitHub: Wafik20.
Research Interests
- Machine learning and reinforcement learning
- Algorithms with predictions and decision-making under uncertainty
- Optimization and resource allocation
- Quantum computing
News
- Joined the ReDSCAIP Lab at PittStarted working with Prof. Micheal Colaresi at the ReDSCAIP Lab on forecasting political violence.
- Started Thesis Master at PittBeginning my thesis Master program at the University of Pittsburgh.
- Selected for Qiskit Advocate Program 2.0Selected as part of the Qiskit Advocate Program 2.0, a global initiative recognizing individuals who actively contribute to the open-source Qiskit ecosystem and the broader quantum computing community.
- FoodSocial Mobile App Reached 3000 Downloads!Mobile app reached 3000 downloads milestone in just three months.
- FoodSocial Mobile App LaunchSuccessfully launched the FoodSocial mobile application on both Google Play and Apple App Store.
Selected Projects
- CLCB-DRA-FAIR
Offline CMAB for discrete police patrol allocation with fairness constraints to reduce biased feedback loops.
- List Labeling Array Implementation in C
A C implementation of the List Labeling Array data structure that maintains a sorted array with O(log²n) insertion time and O(log²n) amortized elements moved per insertion.
- FoodSocial
My current workplace, where I helped build a cross-platform social platform empowering food creators and influencers. The app enables users to discover, share, and shop recipes, while fostering authentic connections between creators, their communities, and food brands.