Maximilian Drach

• Coordinated sales and solutions between customers and internal product lines impacting over $496mil of potential revenue. • Designed and marketed custom circuit diagram to maximize chip sales on a $360mil automotive camera project. • Planned and presented inductive sensors and high voltage gate drivers demonstrations to automotive OEMs to influence next generation socket selection and favorably position against competitor products.

• Created a physics-based image exposure simulator to improve a 1-bit quanta image sensor color extraction model performance by expanding the size of existing image datasets. • Designed mathematical photodiode and aperture physics models simulating infinite exposure range for a balanced image. • Verified Photodiode model accuracy in Python by reconstructing an HDR image from its simulated LDR sub-images.

• Recognized a crucial requirement for a 5-star NCAP safety rating by 2024 and took the initiative to learn Altium to design a compact driver monitoring camera, closing critical portfolio gap. • Authored an application brief paper to showcase future ADAS camera reference design significance for ti.com and advertise FPD-Link IV product public launch. • Directed future camera reference design specifications from market research ensuring future market competitiveness. • Conducted market research with customers identifying gaps in camera reference design portfolio.

• Provided instruction, homework assistance and miscellaneous student guidance for Electromagnetics (ECE 30411) and Electrical Engineering Fundamentals (ECE 2K2). • Led exam review and Q&A sessions to assist student in mastering course materials.

• Collaborated with Dr. Song Zhang to engineer an object detection system in Python utilizing point-cloud data from a LiDAR module to localize regions of interest for high-resolution 3D scans. • Updated the Ros 2 LiDAR distance program for wireless processing of LiDAR scans permitting the Turtle-bot to be mobile. • Presented a live MATLAB visualization to showcase how the algorithm focuses on localized regions.

• Collaborated with Professor Joseph M. Cychosz to detect consumer patterns on the NanoHUB website to track users more accurately on the web-apps platform. • Designed Python algorithms to connect induvial and aggregate users to their web-traffic, which directly contributed to the new site-wide recommendation engine. • Employed SQL to analyze the connections between YouTube and Google external links with tool usage on the website to provide actionable insight into consumer behavior on NanoHUB.org. • Validated the differences between the NanoHUB Database and Google Scholar to confirm the accuracy of the citations in the database. Ensured NanoHUB accurately accounted for the citations on the website to measure the h-index for both the website and its users.