Alexander U. Adler
On the side
I've worked on a few projects for the lab and in the classroom
Top and bottom clamp pieces
1 - 1
High-temperature thin film sample holder
Completed Fall 2011
When measuring the conductivity of thin films, a van der Pauw contact geometry is ideal. The old stainless-steel body thin film holder had three primary drawbacks:
1. Sample size and geometry was limited by the apparatus.
2. When mounting the sample, placement of thermocouple beads proved difficult and sample breakage would easily occur.
3. Stainless steel is both electrically conductive and chemically unstable at very high temperatures (above 550ºC).
The new, electrically insulating and thermally stable all-alumina clamp system can accommodate virtually any sample shape or size. Notches in the top piece of the clamp help keep placement of the bead contacts consistent.
Ready, Set, Go: A course in strategic communication for scientific minds
Status: In progress
While graduate school is all about learning how to 'do' good science, I've found it to be just as much about learning how to 'talk' good science. Not everyone emphasizes this last part. I want to do something to help graduate students from all backgrounds (from archaeology to physics) engage any audience and effectively explain what they do and why they do it.
Recently, I was an author for a grant to fund a quarter-long workshop series to help graduate students communicate effectively by helping them communicate more strategically. The course will enhance their confidence 'on stage,' help them understand what their audience wants to know, and learn how to connect to their audience by tailoring their message and methods for their target audience. I'm very excited to be involved with it.
Currently, I serve as a consultant and guest trainer for the program as well as web administrator for the course website, rsg.northwestern.edu.
Science and Engineering Research and Teaching Synthesis Workshop:
Transparent Oxide Semiconductor Research
Materials in Modern Society (MSE 101) is a course that teaches materials science to non-science and engineering majors. The course favors demonstrations and concepts over rigorous mathematics in order to inform students from all backgrounds.
As part of the course, the university's SERTS program teams students up with graduate student mentors to learn as much as they can about what goes on in a university lab in a short workshop (three two-hour sessions over three weeks) and even do lab work with their mentors to get a flavor for materials science.
Development of workshops for this purpose involves identifying key take-away points from brief interactions which cover publications, the publication process, research funding, and, of course, the mentor's own work among other aspects of the research process.
First Principles-Assisted Structure Solution (FPASS) process figure
Completed Summer 2011
This figure appears in my colleague's publication in Nature Materials (A hybrid computational–experimental approach for automated crystal structure solution, 2013). As is typically the case, the visual display of information and processes can be of great value in presentations and publications alike. Summarizing an idea or a page of text into a figure can mean the difference between memory and oblivion.
Kaggle: AXA Telematics Competition
Status: Completed, March 2015
Skills: R Programming, Machine Learning, Agile development model
I’m proud to say I was part of the NYCDSA Bootcamp Team, Vivi’s Angels, for the AXA Telematics Kaggle competition. Now that the competition is over and the scores have been tallied, we are all learning so much from those who have started to share their approaches to solving the problem of identifying the primary owner of a car merely from the x-y data of the trip he or she took.
While we didn't walk away with the $30,000 grand prize, we did manage to earn a top 10% ranking among a set of fierce competitors. Our team worked with in the Agile development model and within the R programming language to develop relevant features in order to train and test unsupervised learning methods.
Hearthstone Deck Analysis
Status: Completed, April 2015
Skills: R Programming, MySQL, Machine Learning, Data Visualization
Exploratory Analysis: Blog, GitHub, RPub
I love computer games. When I started to see big gaming companies releasing APIs for their games so that others could produce data-driven products, I knew I had to try a project using similar data.
Sadly, Hearthstone: Heroes of Warcraft has no API; but, thankfully, the webmaster at arenamastery.com granted me access to a SQL dump of de-personalized, self-reported player data from the popular electronic card game. In this project, I wanted to explore the numbers behind various aspects of the game, ultimately trying to predict a player's success with a list of the cards they had in their deck. It was a difficult task, but I learned a lot about the game (and R).
High-temperature thin film van der Pauw holder
Ready, Set, Go: A course in strategic communication
FPASS Schematic Figure
Kaggle: AXA Telematics
Services & Curricula
Data Science & Analysis