Maskless Projection Lithography(MPL) is a new lithography process that removes the time-consuming step of producing a mask, allowing our end-user to go straight from design into manufacturing devices. Users can now change designs on the fly at a fraction of the cost and time, with a broad range of applications from microfluidic devices, to integrated circuits and MEMS devices.

Mimmo is pushing the boundaries in self-driving automative radar applications with data fusion and wireless synchronization between independent radars nodes. Our research in cross-radar signals and digital signal processing will give rise to distributed radar networks, which can form wholistic field of views even in complex environments with line of sight obstructions. This technology will greatly reduce the safety risks currently present with self-driving vehicles and give future radar system designers a new sensing platform for innovation.

Hortibeam is a novel lighting system that uses a high-power laser unit, stepper motors, and an optical network to provide the most efficient and desirable light for growing plants. The system’s configurability exploits the benefits of decreased heat accumulation and higher efficiency when compared to traditional LED systems. Open source 3D models with adjustable parameters are available for rapid prototyping.

Extreme Ultraviolet Lithography is an essential step in producing all modern electronic devices and circuits such as the CPU/GPU in your computer and cellphone.

Lithography helps define complex circuit patterns by using optics to focus light onto a photosensitive silicon substrate.

Plasma droplets are vaporized during the lithography process in order to produce the high power EUV light source. 

Our project focuses on using images of the plasma droplets to predict if the EUV light source performance will be satisfactory.

Beehive is an algorithm that manages a fleet of autonomous vehicles for ride sharing service. This algorithm use machine learning to find an optimal way to command vehicles and manages ride prices so that the algorithm maximizes profit while reducing customer wait time. It will also utilize demand prediction and shift vehicle distribution accordingly before actual demand rising in certain areas.

B.A.I. is a cutting-edge optical neural network research aiming at low-energy image classification with light. It uses optical components such as a laser, a digital micromirror device, and a spatial light modulator to encode images and perform calculations in the neural network. Relative to the traditional way of image classification which is implemented exclusively in silicon, the optical setup is able to perform computationally intensive operations and classify images from various datasets with much lower energy consumption.

Waveguides are a nearly century-old technology that transmits electromagnetic waves through metal tubes, resulting in much more efficient transmission than alternative methods, such as coaxial cables. Today, waveguides are used in cutting-edge applications such as radar, sonar, and 5G wireless data. Unfortunately, while the uses for waveguides have advanced significantly since their invention, manufacturing processes used to make them have not. 

Spot On is an implementation of an intelligent parking sensor system powered by image recognition. The key components of Spot On are MAX78000 microcontrollers to facilitate the detection of whether parking space are available or not. The MAX78000 provides Convolutional Neural Network acceleration, which allows a custom ML image recognition model to run in near real time. The system uses LoRa transceivers integrated into each sensor module, and a central gateway will receive and save the data into a database.

Scrapsort is a mechatronic system designed to sort recyclables at the edge. It aims to provide an efficient and inexpensive solution to the growing problem of waste. At the heart of Scrapsort lies an ultra-low-power microcontroller, the MAX78000, which includes a hardware accelerator for convolutional neural networks (CNNs). Scrapsort implements a lean machine learning model that can identify and categorize various recyclable materials, such as glass bottles and aluminum cans, while in motion on a conveyor belt.

Modern vehicles today are beginning to implement smartphone control as an alternative to car keys. However, auto manufacturers have no common standard in implementing smartphone control. Project Portunus creates a secure, plug-and-play implementation of smartphone control using Allthenticate’s suite of hardware and software encryption tools. The project utilizes a minimally based design using a Raspberry Pi to connect to the OBD II port and communicate with the vehicle via the CAN bus.