In 2023, from June to August, 63 high school students attended the STEM to SHTEM (Science, Humanities, Technology, Engineering and Mathematics) summer Engineering and Mathematics) summer program hosted by Prof. Tsachy Weissman and the Stanford Compression Forum. During this summer program, the high schoolers pursued fun research projects in various domains under the supervision of 34 mentors, where the entire collection of the high schoolers’ reports can be found below.
A YouTube playlist of all of the talks can be found below.
-
Behavior Cloning (BC) of Human Policy via Logged Data
Mentors: Zhengyuan Zhou, Junyao Chen, Dailin Ji, Ni Yan, Ethan Cao By: Aashna Kumar, Evelyn Jin, Hooriya Faisal, Samuel Sosa, Tyler Paik Abstract Human decision policy can be learned by machine learning (ML) models using logged data. Our research aims to train a convolutional neural network (CNN) that can predict the next action of a…
-
Bridging the Gap in Generative A.I. for Audio Generation
Bridging the Gap in Generative A.I. for Audio Generation By: Pranav Battini, Kaley Chung, Navaneeth Dontuboyina, Sude Ozkaya, Kedaar Rentachintala Mentors: Mert Pilanci, Rajarshi Saha, Zachary Shah, Indu Subramanian, Fangzhao Zhang Abstract Generative A.I. has come a long way in recent years, popularized by OpenA.I.’s ChatGPT and DALL-E, with advancements such as diffusion models paving…
-
Designing the Most Efficient Recombination Process by Classical and Quantum Algorithms
By: Aden Lee, Allan Jiang, Kim-Nga Shenoy, Vihaan Kodeboyina Mentors: Junjie Luo, Kepler Boyce Abstract With the development of synthetic biology, to achieve highly specific and accurate control of living organisms, or to construct complex metabolic pathways, it is often desirable to create genetic circuits with multiple genetic elements. Traditional approaches involve docking these genetic…
-
Effectiveness of Virtual Reality in Surgeries, Surgeon Training, and Medical Education
By: Alys Jimenez Peñarrieta, Davyn Paringkoan, Nyali Latz-Torres, Yasmeen Galal, Karen Zhang Mentor: Suyeon Choiv Abstract Augmented Reality (AR) and Virtual Reality (VR) have emerged as transformative perspective tools for medical surgeries. These technologies have the potential to enhance surgical precision, drastically improve patient outcomes, and revolutionize medical training. Furthermore, they can alter the way…
-
Evaluating Location-Dependent Variation in Political Google Search Results: A Case Study in Brazilian Politics
Nguyen Hoang Minh Ngoc, Vania Tucto Mentor: Amy Dunphy Abstract With the rise of the internet and social media, misinformation has driven elections all over the world to become increasingly contentious and polarized. Web search results, while generally understudied as a vector for misinformation and political bias, have been found to have dramatic effects on…
-
Investigating the Viability of Semantic Compression Techniques Relying on Image-to-Text Transformations
By: Adit Chintamaneni, Rini Khandelwal, Kayla Le, Sitara Mitragotri, Jessica Kang Mentors: Lara Arikan, Tsachy Weissman Abstract Data compression is a crucial technique for reducing the storage and transmission costs of data. As the amount of data that is consumed and produced continues to expand, it is essential to explore more efficient compression methodologies. The…
-
On the Detection and Prediction of Seizures using EEG
By: Fatima Ansari and Aren Wang Mentor: Joanna Sands Abstract: Seizures are abrupt, rapid bursts of electrical activity within the brain. Those with epilepsy, a central nervous system disorder, suffer repeated seizures that appear to occur randomly and without warning. Frequent seizures may cause physical injury or even death [2]. A device that can quickly…
-
SaiFETY: An Integration of Audio Protection and Ethical Data Collection Comparisons Within Txt2Vid
By: Lucas Caldentey, Avrick Altmann, Yan Li Xiao, Fenet Geleta Mentors: Arjun Barrett, Laura Gomezjurado, Pulkit Tandon Abstract As a result of globalization and massive technological advancements, multi-media communications have begun running excessively on internet traffic. This reliance on digital connections further increased due to the recent Covid-19 pandemic. From the daily dependence on News…
-
Segmented Image Compression in Healthcare
By: Alex Nava, Cristina Bonilla Bernal, Jayden Tang, Logan Graves Mentors: Ayushman Chakraborty, Qingxi Meng Abstract The crossroads at which medical imaging and data compression intersect has yielded a fascinating, novel area of research, particularly pertaining to the Segment Anything Model (SAM), an AI-based image segmentation model. We researched a plethora of standard medical imaging…
-
Self-Learning AI Model on Limited Biomedical Imaging Data and Labels
By: Niraj Gupta, Saniya Khalil, Jolie Li, Iris Ochoa, Elisa Torres. Mentor: David J. Florez Rodriguez. Abstract This research explores self-learning AI using Google Colab by pre-training a general TensorFlow-coded model on recognizing patterns in limited, unlabeled biomedical image data. This allows the model to understand the basic underlying patterns and structures in the images.…
-
Significance of Entropy in Combating AI-Driven Disinformation
Significance of Entropy in Combating AI-Driven Disinformation By: Henry Widjaja, Shreya Das, GeorgeDaniel Dixon, Farah Basher Mentors: Ann Grimes, Noah Huffman ABSTRACT The proliferation of disinformation presents noteworthy societal challenges, emerging as a multifaceted tool to perpetuate untrue narratives. The prevalence of AI technology has only progressed this phenomenon in the form of false media…
-
Understanding Patient Preferences for Kidney Transplants
By: Omry Bejerano, Yash Chanchani, Eugene Kwek, Anvika Renuprasad Mentor: Itai Ashlagi Abstract Kidney transplantation is the most effective treatment option for end-stage kidney disease. In the United States, Organ procurement organizations (OPOs) are responsible for recovering these organs from deceased donors and offering them to patients that need transplants. However, the current kidney transplant…
-
Unveiling the Orchestra: A Novel System for Audio Separation and Instrument Identification in Musical Recordings
By: Manato Ogawa, Juan Almanza, Brad Ma, Rakshithaa V. Jaiganesh, Danielle Wang Mentors: Quincy Delp, Alan Wong Abstract Audio source separation is a widely applicable field that aims to utilize signal processing techniques to extract separate sources from a piece of audio. While the human brain can easily discern between audio sources, computers require source…