As a high school student interested in AI and ML, you are probably looking for a good way to apply the skills you’ve learned. A great way to do this is by pursuing a passion project. 

By diving into an individual  project, you will get to understand the nitty-gritty of machine learning and contribute to the rapidly growing and relevant research in the field. Pursuing a  project also shows your curiosity and passion for the topic, which will make a great addition to your college application. 

Coming up with an idea can be the hardest part of the process, and is a skill that you will develop over time. For now, we’ve got you covered! Here are some passion project ideas focused on AI and ML which can help inspire your project. Most of these are proposed by our Veritas AI mentors, from universities such as Harvard, MIT, Stanford, Oxford, and more. 

Passion Project Category #1: Computer Vision

With the growth of facial recognition and image classification models, the study of how these systems work is more important than ever. With applications in autonomous vehicles, healthcare, smartphones, and more, computer vision’s impact is felt in various fields. If this sounds interesting to you, you should consider one of the topics below: 

1. Build an image classification model for skin cancer detection. This would require using edge detection and other methods to recognize the development of skin cancer in the early stages. This can help doctors treat it earlyon. 

2. Create image models to predict climate change. You could observe images of the sky or use images of space to perform geospatial data integration and observe the impact of climate change. You could then configure this model to make a prediction based on the data of how climate change might affect a certain area over time.

3. Develop a system that will help robots navigate the environment around them and perform tasks more efficiently. You can do this by building a system that will extract information from a certain area such as a household. You would then feed train data of different images of household items so that the robot knows which items to steer clear of. 

4. Build a computer vision and AI-based solution for enhancing live video feeds in real-time. This would require you to resolve pixelation artifacts and improve edge quality using pre-trained models and training-dependent models. You would then have to optimize them to make sure you output the higher-resolution images efficiently. 

5. Build a model using deep learning to optimize the quality control of industrial packaging. This will help cut down manufacturing costs and time delays. You can use image classification to determine whether a package is intact or damaged. You can train a Convolutional Neural Network (CNN) using edge detection to determine this. 

6. Develop an automated asteroid detection system using techniques like logistic regression, and XGBoost. This system would help determine whether or not an asteroid is dangerous. Train the model to identify certain risk factors in the asteroid, by using edge detection. 

7. Build a model using a CNN (Convolutional Neural Network) to aid individuals with impaired vision to identify crosswalks. You could use a unique dataset of stock images of crosswalks to train the model so that it can identify a crosswalk in an unfamiliar environment, thus helping those with impaired vision.

8. Develop a DeepFake detection algorithm by using face detection and image classification techniques. This system will help combat the spread of fake information and ensure the authenticity of visual media. 

9. Build a system that translates sign language gestures into spoken or written language using computer vision and natural language processing techniques. This would enable those with hearing impairments to communicate more effectively with those who may not be well versed in sign language. 

Passion Project Category #2: Data Analysis

As a potential computer scientist, you must be aware of the fact that data used by computer systems to make interpretations and inferences is of the utmost importance when it comes to machine learning. You will need to use datasets with clear and accurate data to ensure that the inferences you make are correct and admissible. You can find inspiration for a project like this below:

10. Create a model to predict the potential toxicity of new drugs before they reach animal and human trials. You will have to find and analyze large datasets of drug toxicity data, by using regression techniques. 

11. Develop a system to detect academic cheating using ChatGPT. This would mainly involve training the model with a dataset of academic answers that have used ChatGPT and analyzing the text patterns and keywords used in these answers. Using this data, the model should be able to predict whether or not the answer is plagiarized.

12. Analyze Twitter data and investigate public opinion on a political issue of your choice. This could involve trying to determine where on the political spectrum a user would lie based on their tweet. 

13. Analyze the effect of fitness apps such as Strava and Couch to 5K on their users and whether or not they have had a positive effect on public health. You could use data scraping and machine learning tools to understand these apps and their correlation to public health. 

14. Implement a recommendation engine using open-source datasets like Google Local and Amazon reviews. You will need to use NLP techniques to recognize what kind of user likes/dislikes a certain product. 

15. Assess the accuracy of US house price predictions by listing websites. This would involve creating your prediction based on property features using linear regression and comparing it with that listed on the website. This would help users verify the data and assess whether or not the website is a reliable source of information. 

16. Conduct a study exploring how tech company policies influence employee mental health. Create a model that will use logistical regression and neural network techniques to identify which policies and personal factors play the most significant role, which further helps these companies build effective mental health support. 

17. Build an ML model to understand how social interactions influence the spread of diseases, such as COVID-19. Simulate how people’s decisions such as wearing masks, practicing social distancing, and getting vaccinated affect infection rates. 

Passion Project Category #3: Privacy and Security

As AI becomes increasingly integrated into our digital lives, the importance of securing these systems grows exponentially. From protecting sensitive data to preventing cyberattacks, the field of cybersecurity in AI and machine learning is both challenging and crucial. 

18. Explore the vulnerabilities in machine learning systems and their susceptibility to attacks. Test different attack techniques such as evasion attacks, data poisoning attacks, Byzantine attacks, and model extraction, and try to come up with defenses that the model can adopt against these attacks. 

19. Develop a machine learning solution to enhance cybersecurity. One way of doing this is to create a model that  would detect malware and unusual activity on your computer, similar to an antivirus. You could train CNNs with malicious software datasets and then use them to identify malware. 

20. Conduct vulnerability assessments and penetration testing on various chatbot platforms. This would involve exploring the security protocols and privacy policy of these platforms, performing the tests, and then coming up with recommendations to enhance the security of these platforms. 

21. Create solutions to improve the performance of AI models when it comes to processing figurative speech. Often, these models struggle with prompts that include figurative speech, and take the content in a literal sense. Study techniques to remedy this by processing abstract data which would further enable these models to grasp subtleties in human communication. 

Passion Project Category #4: Predictive models

With the growth of generative AI like ChatGPT and Dall-e, machine learning models that incorporate human input and give the desired output are becoming increasingly relevant. Having the right skills to incorporate such a model is a very desirable quality and will make you stand out. If you want to dive into this world, try some of the projects below:

22. Create a tool that predicts the energy consumption of a building by analyzing building details and weather data. You can use a LightGBM model to achieve precise estimations with minimal errors. This tool can be used to reduce energy consumption in buildings that over-consume and helps create energy-efficient solutions. 

23. Develop an educational resource recommendation system using a decision tree classifier algorithm. The recommendations could be based on preferences such as grade, subject, price, and more. 

24. Build a machine learning model to predict the yield of a specific crop more accurately. This could be based on features like bee species and weather conditions, using linear regression and data visualization techniques. 

25. Build a model that will predict NBA game outcomes using neural networks. You can utilize a comprehensive dataset containing player statistics from every NBA game. 

26. Create a model to recognize what key factors affect a music genre’s popularity using linear regression and decision trees. Analyze a dataset containing different genres such as electronic, rap, and jazz, and identify elements such as tempo, chord progression, and duration.

27. Use image generation models to adapt a story in a textual format to a high-quality scene visualization or a motion comic. You can use Dall-e 3 or Midjourney to complete such a project. 

Passion Project Category #5: Reinforcement Learning

Reinforcement learning is the driving force behind intelligent decision-making in AI. It is the method that teaches machines how to learn by doing and adapt to the world by interacting with it. Autonomous robots and AI in gaming are two fields in which it has found the most application, especially in teaching a system how to navigate a new environment. If that sounds interesting to you, check out the options below:

28. Use reinforcement learning techniques to enable real-time interaction between an agent and the Minecraft server to improve navigation and adaptability in the game. 

29. Study the latency implication of reinforcement learning controllers being integrated into robotic systems such as drones and understand if they can safely navigate real-world situations. You can also compare the latency performances of various reinforcement learning algorithms and come up with the ideal algorithm for real-world use. 

Passion Project Category #6: Speech Detection

As voice assistants like Alexa, Siri, and Google are becoming more advanced and accessible, AI speech detection is a growing field of research. The research ranges from emotion recognition to speaker identification and building communication aids for people with disabilities and has room for more. 

30. Use machine learning and computational linguistics to identify features of a language such as confidence in tone and fluency and determine whether or not the speaker is a native speaker or a learner. 

31. Develop a speech recognition system that will help a child learn how to speak by scoring the pronunciation and giving them constructive feedback. You will need to use NLP techniques on a large speech dataset to implement such a model.

32. Create a voice authentication system that verifies the identity of the speaker based on their voice. You will need to use deep learning techniques to identify features in the speaker’s voice such as tone and pitch. 

Passion Project Category #7: AI Ethics

Even though AI and ML have become a lot better over the years, there’s still a lot of room for improvement when it comes to mitigating biases. Ethical principles and morality in AI can relate to the development, use, and impact of systems. Check out some of the topics below if you want to make sure AI doesn’t negatively affect our society:

33. Write a research paper on how the design of AI models can be made more inclusive to accommodate more voices. You could focus on how LLMs like ChatGPT aren’t as accessible to people who speak native languages. 

34. Write a research paper on how bias in LLMs can be decreased while maintaining the accuracy of their outputs. Probability theory, critical thinking, and knowledge about the current socio-political climate would be pivotal to conducting such research. 

35. Build AI models in healthcare that are more interpretable and accessible to patients. Often, these models may end up giving very complex outputs, which may not be accessible to patients. Try providing full transparency about how the diagnosis was made to ensure that the patient is not uncertain about their diagnosis.

Passion Project Category #8: Natural Language Processing (NLP)

If you’re interested in developing systems that enable Human-Computer Interaction (HCI) by having machines understand and generate human language, then NLP is a good project category for you.The potential of NLP ranges from chatbots and language translation to content analysis, creating more ways for us to communicate with machines. Check out some of the topics below for inspiration:

36. Develop a model that turns YouTube videos into concise and professional reports. This can be used to summarize educational material on the platform that often gets overlooked since it isn’t considered professional enough. 

37. Create an AI model that will use NLP to generate poems based on a certain set of prompts such as the theme and type of poem. Use a dataset of various popular poems of different genres and types to implement this. 

38. Build a model that will predict the author of a quote using NLTK in Python. Utilize a dataset of quotes, the emotions of the quotes, and their authors by implementing simple neural networks for training. 

39. Use AI-driven methods to transform natural language into musical melodies. Using MIDI files and NLP models, you could translate the natural language into a structured format for music generation.

40. Develop a system to distinguish between real and fake news on Twitter using a dataset of example tweets. Train a model using text analysis, title evaluation, and source verification techniques to predict the accuracy of news posts. This research will contribute to improving media literacy and prevent the spread of misinformation.

If you’re looking to build unique projects in the field of AI/ML, consider applying to Veritas AI! 

Veritas AI was founded by Harvard graduate students, and through the programs, you get a chance to learn the fundamentals of AI and computer science while collaborating on real-world projects. You can also work 1-1 with mentors from universities like Harvard, Stanford, MIT, and more to create unique, personalized projects. In the past year, we had over 1000 students learn data science and AI with us. You can apply here!

Image Source: Computer Vision Example