Coded by Sem Ferid
My name is Sem Ferid, a passionate college student studying Computer Science at the University of Pennsylvania. I am an aspiring tech developer who has spent the past few years passionate about the power collaboration and efficiency.
Collaboration, especially through mentorship, plays a crucial role in making each generation better than the previous one. This philosophy is evident in my role as an Engineering Peer Advisor and in my involvement with the National Society of Black Engineers (NSBE), where we benefit from mentors in years above us. Additionally, I am founding a ColorStack chapter at the University of Pennsylvania, an initiative I am really proud and passionate about. In these roles, I share my knowledge to ensure that those younger than me surpass their potential. Ultimately, this approach is the most efficient way for communities to grow.
Leading into my other interest: efficiency. I love learning new things because they bring fresh perspectives. I constantly question and scrutinize the practices of even the largest companies, always seeking areas for improvement. At the beginning of 2024, I joined Neutrino AI as a Software Engineer because their innovation in reducing GPT costs by 95% fascinated me. In the summer of 2024, I continued with Neutrino AI and also started a new role as an Artificial Intelligence Intern at HP. What attracted me to these roles is the potential of AI to create more efficient and user-friendly environments. Uncovering and implementing groundbreaking technology to simplify the lives of workers and users excites me.
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Instagram Lite was a project aimed at recreating the core functionalities of Instagram with a focus on simplicity, speed, and efficiency. This project was an exercise in understanding and implementing social media platform features using modern web technologies.
Took the position of an experimental hybrid team with a roster from some of players the current best players. Created an optimization model for a Valorant ESports team to analyze the team performance to pick the optimal team rosters (players), as well as their optimal game characters (Agents).
Developed a Java-based version of the popular word-guessing game, Wordle, complete with a graphical user interface (GUI). This project involved designing and implementing the game's core mechanics, including word selection, user input handling, and feedback on guesses.
Efficiently find the best flight between two destinations. The project involved using JSoup to webscrape HTML of third-party flight websites and implementing graph objects like Hash Maps to represent the network of airports and flights, facilitating efficient data storage and retrieval. The program applied Dijkstra's and Kosaraju's algorithms to calculate optimal itineraries based on users' travel preferences, such as source, destination, round trip, one-way, and preferred cost. Additionally, a user-friendly Flight Finder GUI was designed and implemented, offering an intuitive interface for users to input their travel preferences and receive optimal flight itineraries.
Developed an algorithm in worst case O(mxn) to find the shortest path in a maze, represented as a 2D-array. The goal is to navigate through obstacles from a starting coordinate (src) to a target coordinate (tgt) and return the ordered list of vertices constituting the shortest path. If no path exists, the algorithm will return an empty list.