People :: ECE 445 - Senior Design Laboratory

People

TA Office Hours

Held weekly in the senior design lab (ECEB 2070/2072). NOTE:

There are no office hours during the weeks of board reviews or final demos.

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Summer 2026 Instructors

Name Area
Prof. Arne Fliflet (Instructor)
3056
afliflet@illinois.edu
microwave generation and applications
Prof. Viktor Gruev (Instructor)

vgruev@illinois.edu
Prof. Joohyung Kim (Instructor)

joohyung@illinois.edu
Prof. Rakesh Kumar (Instructor)

rakeshk@illinois.edu
Prof. Michael Oelze (Instructor)
ECEB 2056
oelze@illinois.edu
Biomedical Imaging, Acoustics, Nondestructive Testing
Prof. Craig Shultz (Instructor)
CSL 220
shultz88@illinois.edu
Haptics, Human Computer Interaction, Signals, Audio, HCI, Actuators, Wearables, Interaction
Prof. Cunjiang Yu (Instructor)

cunjiang@illinois.edu
Prof. Yang Zhao (Instructor)

yzhaoui@illinois.edu
Abdullah Alawad (TA)

aalawad2@illinois.edu
Haocheng Bill Yang (TA)

hy38@illinois.edu
Gayatri Chandran (TA)

gpc4@illinois.edu
Super-resolution imaging, force microscopy, nanoscale light-matter interactions
Aniket Chatterjee (TA)

aniketc2@illinois.edu
Shiyuan Duan (TA)

sduan9@illinois.edu
Argyrios Gerogiannis (TA)

ag91@illinois.edu
Reinforcement Learning, Bandits, LLM Reasoning, Theoretical Machine Learning
Gerasimos Gerogiannis (TA)

gg24@illinois.edu
Computer Architecture, High-Performance Computing, Hardware Accelerators, FPGA
Manvi Jha (TA)

manvij2@illinois.edu
Computer Vision; Large Language Models; IoT; High Level Synthesis
Jason Jung (TA)

jasondj2@illinois.edu
Imaging Systems, Circuit design, Signal Processing, Computer Vision
Po-Jen Ko (TA)

pojenko2@illinois.edu
Weijie Liang (TA)

weijiel4@illinois.edu
Wesley Pang (TA)

qpang2@illinois.edu
Zhuchen Shao (TA)

zhuchens@illinois.edu
Yulei Shen (TA)

yuleis2@illinois.edu
Wenjing Song (TA)

ws33@illinois.edu
Eric Tang (TA)

leweit2@illinois.edu
IC, EM, proficient with PCB and soldering
Jiaming Xu (TA)

jx30@illinois.edu
Zhuoer Zhang (TA)

zhuoer3@illinois.edu
Frey Zhao (TA)

yifeiz10@illinois.edu

Other Important People

https://ece.illinois.edu/about/directory/staff

BusPlan

Aashish Kapur, Connor Lake, Scott Liu

BusPlan

Featured Project

# People

Scott Liu - sliu125

Connor Lake - crlake2

Aashish Kapur - askapur2

# Problem

Buses are scheduled inefficiently. Traditionally buses are scheduled in 10-30 minute intervals with no regard the the actual load of people at any given stop at a given time. This results in some buses being packed, and others empty.

# Solution Overview

Introducing the _BusPlan_: A network of smart detectors that actively survey the amount of people waiting at a bus stop to determine the ideal amount of buses at any given time and location.

To technically achieve this, the device will use a wifi chip to listen for probe requests from nearby wifi-devices (we assume to be closely correlated with the number of people). It will use a radio chip to mesh network with other nearby devices at other bus stops. For power the device will use a solar cell and Li-Ion battery.

With the existing mesh network, we also are considering hosting wifi at each deployed location. This might include media, advertisements, localized wifi (restricted to bus stops), weather forecasts, and much more.

# Solution Components

## Wifi Chip

- esp8266 to wake periodically and listen for wifi probe requests.

## Radio chip

- NRF24L01 chip to connect to nearby devices and send/receive data.

## Microcontroller

- Microcontroller (Atmel atmega328) to control the RF chip and the wifi chip. It also manages the caching and sending of data. After further research we may not need this microcontroller. We will attempt to use just the ens86606 chip and if we cannot successfully use the SPI interface, we will use the atmega as a middleman.

## Power Subsystem

- Solar panel that will convert solar power to electrical power

- Power regulator chip in charge of taking the power from the solar panel and charging a small battery with it

- Small Li-Ion battery to act as a buffer for shady moments and rainy days

## Software and Server

- Backend api to receive and store data in mongodb or mysql database

- Data visualization frontend

- Machine learning predictions (using LSTM model)

# Criteria for Success

- Successfully collect an accurate measurement of number of people at bus stops

- Use data to determine optimized bus deployment schedules.

- Use data to provide useful visualizations.

# Ethics and Safety

It is important to take into consideration the privacy aspect of users when collecting unique device tokens. We will make sure to follow the existing ethics guidelines established by IEEE and ACM.

There are several potential issues that might arise under very specific conditions: High temperature and harsh environment factors may make the Li-Ion batteries explode. Rainy or moist environments may lead to short-circuiting of the device.

We plan to address all these issues upon our project proposal.

# Competitors

https://www.accuware.com/products/locate-wifi-devices/

Accuware currently has a device that helps locate wifi devices. However our devices will be tailored for bus stops and the data will be formatted in a the most productive ways from the perspective of bus companies.