Sam Wang
I'm a computer science student studying AI and Robotics at the University of Pennsylvania, passionate about using AI to address real-world challenge. As a member of the Perception Action & Learning Group of the Penn GRASP Laboratory, I have the privilege of being mentored by Dr. Jason Ma, Prof. Dinesh Jayaraman, and Prof. Osbert Bastani, while collaborating closely with talented peers like Will Liang and Johnny Wang.
I have coauthored two papers on applying foundation models to robot learning, which were presented at CoRL and RSS. My previous research on applying deep learning for rapid cardiac screening earned a Second Grand Prize in Robotics and Intelligent Machines at ISEF 2023.
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Media Coverage:
The Economist: "How AI can make robots fit for a human world"
VentureBeat: "NVIDIA’s DrEureka outperforms humans in training robotics systems"
Fox29 News: "Inside UPenn's new Artificial Intelligence degree program"
Eurekaverse: Environment Curriculum Generation via Large Language Models
William Liang, Sam Wang, Hung-Ju Wang, Osbert Bastani, Dinesh Jayaraman†, Yecheng Jason Ma†
Conference on Robot Learning (CoRL), 2024 (Oral)
Princeton Symposium on Safe Deployment of Foundation Models in Robotics, 2024 (Poster)
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DrEureka: Language Model Guided Sim-To-Real Transfer
Yecheng Jason Ma*, William Liang*, Hung-Ju Wang, Sam Wang, Yuke Zhu, Linxi "Jim" Fan, Osbert Bastani, Dinesh Jayaraman
Robotics: Science and Systems (RSS), 2024 (Oral)
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Deep Learning for Rapid Cardiac Screening
Sam Wang
Regneron International Science and Engineering Fair, 2023
★ Second Grand Prize, ISEF 2023 Robotics and Intelligent Machines Category ★
★ Special Awards from Association for Computing Machinery (ACM) and International Council on Systems Engineering (INCOSE) at ISEF 2023★
★ 1st Place in Computer Science at Delaware Valley Science Fair (DVSF) ★
★ Merck Special Award for Excellence in Drug Discovery and Human Health ★
★ Janssen Cardiovascular and Metabolic Research Award ★
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Machine Learning for Place Detection
Trained models to predict the location of images from only visual features. Experimented with Vision Transformers, in-context learning with vision language models, and segmentation foundation models. Won 2nd place in 200+ student competition.
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Pennstagram Social Media Platform
Built full-stack social media application with profiles, posts, infinite feed, comments, and secure login. Implemented real-time chat using Socket.io, LLM-augmented interest search powered by GPT, YouTube-inspired recommendation algorithm with Apache Spark, and image similarity search with ChromaDB. Deployed to AWS with EC2, Livy, RDS, and S3; utilized Kafka for federated post retrieval.
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Digital Attendance Kiosk
Built kiosk with Raspberry Pi and badge scanner to digitize attendance records for 650+ students and faculty. Developed an object-oriented interface for automated attendance tracking using Python, Tkinter, and gspread.
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Website Management for Local Organizations
Created and maintained brand new websites for School Newspaper, Boy Scout Troop, and community organizations. Created custom plugins for WordPress and ticket sales using PHP.
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Privacy Preserving Contact Tracing with Bluetooth Signals
Developed and tested a Bluetooth Low Energy (BLE)-based system for automated, privacy-preserving COVID-19 contact tracing using Raspberry Pis. Designed experiments to evaluate how factors such as distance, obstacles, and device orientation affect the Received Signal Strength Indicator (RSSI) of Bluetooth signals. Integrated additional data from gyroscope and accelerometer sensors to improve proximity detection accuracy. Built machine learning models using scikit-learn, comparing linear regression with classifiers like Decision Trees, Random Forests, and Naïve Bayes. Results demonstrated that classifiers significantly outperformed linear regression models.
Code • Report2025
CIS 7000 Vision-Based Robot Learning2024
CIS 5800 3D Computer Vision2023
CS285 Deep Reinforcement Learning (UC Berkeley)2022
CS231n: Deep Learning for Computer Vision (Stanford University)I serve as the Vice President of the Penn Engineering Deans' Advisory Board. Together, we organized the inaugural Penn AI conference, which brought together several hundred student and faculty attendees to explore advancements in AI. I'm also leading efforts to improve Penn Engineering's orientation programs and update the undergraduate research guide.
As the Technology Chair for Penn Engineering Council, I've organized multiple seminars and panels on founding startups. I'm also pursuing a minor in Engineering Entrepreneruship to deepen my understanding of bridging technology and business.
I'm an Eagle Scout from Troop 542 in Maple Glen, PA and a two time President’s Volunteer Service Award Gold recipient.
In my free time, I enjoy reading about history and philosophy, cooking, playing basketball, running, and rooting for the Minnesota Vikings.