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Malek I

- Research Program Mentor

MS at Massachusetts Institute of Technology (MIT)

Expertise

engineering product design and development, upcycling and recycling waste into products, applications of artificial intelligence and robotics in healthcare / public service, AI and mental health, comparative theology / philosophy / interfaith studies

Bio

I'm a mechanical engineer and research scientist by training with degrees from UT Austin (BS, Highest Honors) and MIT (MSc), where I've published patents and authored research spanning nanotechnology, materials science, precision mechatronics, robotics, 3D printing, AI/ML, acoustics, and humanitarian engineering. Specifically, at MIT I wrote my thesis on a molecular self-assembly nanoprinting system based on a technique called atomic force microscopy (AFM). Now, I am a research mentor, scientist, and content creator for the Nushoor Institute, where I work at the intersection of humanitarian development, social innovation, product design, and engineering education. In my free-time, I love spending time with my family, working out, going on nature walks, doing community service, learning languages, and nerding out on YouTube videos about science / math / AI / philosophy. Fun fact: I am ethnically half-Lebanese / half-Chilean, though no one is ever able to guess this based on how I look! 😅

Project ideas

Project ideas are meant to help inspire student thinking about their own project. Students are in the driver seat of their research and are free to use any or none of the ideas shared by their mentors.

1. Turning Plastic Waste into 3D Printer Filament

This project sits at the intersection of materials science and waste management/recycling. Students will explore how waste plastics (like PET bottles - empty soda bottles / water bottles etc.) can be cleaned, cut, and extruded into usable 3D printing filament, learning the basics of polymer properties, extrusion mechanics, and quality control (consistent diameter, no bubbles/brittleness). The research process involves reviewing and replicating existing DIY filament extruder techniques, evaluating the system's performance, and iterating based on print quality results. Depending on the student's interest, the final output can be a short, engaging STEM tutorial video (e.g., TikTok or YouTube Shorts style) documenting the build and testing process, or a more formal write-up suitable for a science fair or publication, depending on the rigor of testing the student wants to pursue.

2. Designing a Low-Tech Solar-Powered Egg Hatchery

This project introduces students to renewable energy applications for agriculture in resource-constrained settings. Students will learn how to design and build a low-cost incubator that uses solar energy (direct or thermal storage) to maintain stable temperature and humidity for hatching eggs, gaining hands-on experience with basic thermodynamics, heat transfer, solar energy capture, and simple passive control/monitoring systems. The research process includes studying incubation temperature/humidity requirements, replicating existing low-tech hatchery designs, building a prototype, and running test cycles to evaluate hatch rates and thermal stability. The expected outcome is a written publication (e.g., a research report or article) documenting the design process, testing methodology, and results, which could be shared with agricultural development or appropriate-tech research communities.

3. AI-Based Air Quality Monitoring for School Sports Locker Rooms

This project lets students explore how machine learning and microcontrollers like Raspberry Pi can be used for practical, everyday environmental health problems. Students will learn how to collect air quality data (e.g., humidity, VOCs, particulate matter) using low-cost sensors, build a dataset, and apply basic AI/machine learning techniques to detect patterns or predict poor air quality conditions (e.g., linked to mold risk, staph, or lingering bacterial odors). The research process includes selecting appropriate sensors, setting up a data collection pipeline, exploring relevant ML models (e.g., simple classification or anomaly detection), and evaluating model performance against real-world readings. The expected outcome is a working prototype system (sensor + basic AI model/dashboard) paired with a short technical write-up or presentation explaining the approach and findings.

4. DIY Solar Parabolic Cooker Build and Evaluation

In this project, students are introduced to concentrated solar power and solar energy applications through a DIY, hands-on, low-cost device. Students will design and construct a parabolic solar cooker from low-cost, accessible materials, learning the basics of solar geometry (angle of incidence, focal point calculations), reflective material selection, and heat transfer principles. The research process involves reviewing existing parabolic cooker designs/approaches, building and refining a prototype based on existing tutorials, and running structured tests to evaluate performance (e.g., time to boil water, max temperature reached, cooking time for different foods) across different conditions like time of day or cloud cover. Depending on the student's interest, the final output can be a demonstration video showing the build process and cooking tests in action, or a written report/publication documenting the design iterations, testing methodology, and performance results.

5. Bio-Inspired Atmospheric Vacuum Pump for Low-Energy Groundwater Extraction

This project lets students explore a biomimicry-inspired approach to a real-world water scarcity problem. Students will investigate how tall trees and plants draw water upward through negative pressure (transpiration pull) and translate that principle into a low-cost, low-tech vacuum pump design for pulling groundwater to the surface, learning fundamentals of atmospheric pressure, fluid dynamics, and pump mechanics along the way. The research process involves studying the biological mechanism behind plant water transport, reviewing existing manual/vacuum-based pump designs, building a prototype from accessible materials based on open-source tutorials, and testing its ability to draw water from varying depths and flow rates. The expected outcome is a working prototype paired with a written report or publication documenting the design rationale, build process, and performance data — with an option to also produce a short explainer video connecting the biomimicry concept to the engineering solution for a broader audience!

Coding skills

Python, MATLAB, Tensorflow / PyTorch / LLM APIs, Google Colab, Javascript, HTML, Vibe Coding (Lovable, Replit, Claude Code), Visual Studio Code, Github, LaTeX, Zotero

Credentials

Work experience

Nushoor Institute (2026 - Current)
Research Mentor
Sunfish Inc. (2022 - 2022)
Software Engineering Intern
Precision Mechatronics Control Lab (UT Austin) (2021 - 2022)
Undergraduate Research Assistant
Applied Research Laboratories (UT Austin) (2020 - 2022)
Student Technician

Education

University of Texas Austin (UT Austin)
BS Bachelor of Science (2022)
Engineering
Massachusetts Institute of Technology (MIT)
MS Master of Science (2024)
Engineering

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