A reflection written by Women’s Center staff member, MJ Jalloh Jamboria

Beyoncé’s newest hit, “Formation” has been the topic of conversation everywhere. If you missed the video, here it is!

Since her Super Bowl performance on February 7th, Beyoncé has received mountains of praise and criticism for her performance and newest video. (Also, take a second to watch the Super Bowl performance here if you haven’t already. Ready? OK!)

While surfing Twitter during the Super Bowl performance (obviously not as Bey was singing), I came across a tweet that angered me to my very core. In efforts to find the original tweet, I came up empty handed, so instead I’ll summarize. The author of the tweet expressed anger at the hairstyle Beyoncé chose to rock for her Super Bowl performance, specifically the color and texture of her weave.

Credit: Getty Images

Their ire was grounded in the fact that Beyoncé’s weave wasn’t aligned with the pro-blackness and importance of self-identity portrayed within her video.

Trying to isolate my frustration with the tweet, I found myself asking (and later dissecting) the following questions:

• Why are people focusing on her hair style?
• Why is wavy, blonde hair considered anti-black and indicative of self-hate?? 

First of all, weaves are not always indicative of hatred of one’s own natural hair! Beyoncé, and black women everywhere, are entitled to having and wearing the hairstyles that express themselves or the person they choose to personify. Seemingly, the choice to wear her hair long, blonde and wavy (as opposed to in an afro, like her performers) was a PERSONAL CHOICE (or between herself and her stylist). It seemed as if the author of the tweet thought Beyonce’s lack of afro or other natural hairstyle was a rejection of blackness. The idea that Black women should stick to a limited number of styles to be considered beautiful or “black enough” is ridiculous! Second, long blonde hair does not belong to one racial or ethnic group.

At first, I was upset that people weren’t paying attention to the positive messages in her song, video and performance. For example, her section of the Super Bowl performance paid homage to Malcolm X, the Black Panther Party and Michael Jackson. Similarly, the “Formation” video recreates and depicts the aftermath of Hurricane Katrina and begins to challenge and shed light on larger systems of police brutality and anti-blackness.

Perhaps I was even upset that people were attacking my beloved queen.

Me @ the mere mention of Beyonce

But again, I realized I needed to think more critically about black hair politics. Too often have I heard the ways in which artificial relaxers and perms kits ruined the naturally bodacious curl patterns and beautifully kinky hair of young girls and women alike. In fact, I lived it. I lived through hot combs and suffered the consequences of rocking baby hairs before they were a trend. I vividly remember crying every time my hair was subjected to being plaited into neat cornrows, through tears asking my mom why my hair couldn’t be straight like the other pretty (white) girls at school.

Without fully knowing it, at an early age I understood the ways in which hair was racially coded and tied to constricting beauty standards for women. Looking back, I was beginning to see the possible reasons as to why the author of the tweet may have felt betrayed by Beyoncé’s selection of hairstyle.

I wanted to continue to reflect on the policing of Black women’s hair and beauty standards and I remembered the recent controversy over military bans on specific hairstyles. Initial restrictions banned many types of hairstyles (including locs and two-strand twists) but restrictions were later dialed back to allow two-strand twists as a permissible style. The thought of an institution banning something as arbitrary as hair seemed bizarre but I understood this was just another way of constricting black and female autonomy and categorizing good versus bad, acceptable versus rejected, manageable versus kinky.

However, the “Formation” video, the Super Bowl performance, and Beyoncé’s lyrics highlight some amazing things as well. One of the lines from “Formation” is “I like my baby hair with baby hair and afro’s.”

Remember that time there was a petition to have Blue’s parents change her hair? No? Revisit that awful moment in history HERE.

Not only did Beyoncé feature her daughter in the video, she acknowledged the texture of Blue Ivy’s hair, and featured her beside two other beautiful children with similarly curly hair. Her video also features women of different hairstyles and Beyoncé herself switches between a plethora of hairstyles. Her video highlights just a few of the ways in which black hair is versatile and beautiful.

In a society where women, specifically black women, aren’t always taught to value their features and beauty, but instead alter and damage their natural beauty, I feel Beyoncé, her video, and her performance continued to allow for necessary and important discourse on black hair.

Learning from High-Dimensional Data via Transformations

Dr. Hossein Mobahi, MIT

12:00pm Monday 29, February 2016, ITE325b

High-dimensional data is ubiquitous in the modern world, arising in images, movies, biomedical measurements, documents, and many other contexts. The “curse of dimensionality” tells us that learning in such regimes is generally intractable. However, practical problems often exhibit special simplifying structures which, when identified and exploited, can render learning in high dimensions tractable. This is a great prospect however, but how to get there in not trivial. In this talk, I will address two challenges associated with high-dimensional learning and discuss my proposed solution.

First, parsimony (sparsity, low rank, etc.) is one of the most prevalent structures in high-dimensional learning applications. However, its presence is often implicit and it reveals itself only after a transformation of the data. Studying the space of such transformations and the associated algorithms for their inference constitute an important class of problems in high-dimensional learning. I will present some of my work in this direction related to image segmentation. I will show how low-rank structures become abundant in images when certain spatial and geometric transformations are considered. This work resulted in a state of the art algorithm for segmentation of natural images.

Second, important scenarios such as deep learning involve high-dimensional nonconvex optimization. Such optimization is generally intractable. However, I show how some properties in the optimization landscape, such as smoothness and stability, can be exploited to transform the objective function to simpler subproblems and allow obtaining reasonable solutions efficiently. The theory is derived by combining the notion of convex envelopes with differential equations. This results in algorithms involving high-dimensional convolution with the Gaussian kernel, which I show has a closed form in many practical scenarios. I will present applications of this work in image alignment, image matching, and deep learning. Furthermore, I will discuss how this theory justifies heuristics currently used in deep learning and suggests new training algorithms that offer a significant speedup.

Hossein Mobahi is a postdoctoral researcher in the Computer Science and Artificial Intelligence Lab at the Massachusetts Institute of Technology. His research interests include machine learning, computer vision, optimization, and especially the intersection of the three. He obtained his PhD from the University of Illinois at Urbana-Champaign in Dec 2012. He is the recipient of Computational Science & Engineering Fellowship, Cognitive Science & AI Award, and Mavis Memorial Scholarship. His recent work on machine learning and optimization have been covered by the MIT news.

The UMBC Cyber Defense Lab presents

Mini-MAC: Raising the Bar for Vehicular Security with a
Lightweight Message Authentication Protocol

Jackson Schmandt, CSEE, UMBC
11:15am-12:30pm Friday, 26 February 2016, ITE 237

We propose Mini-MAC, a new message authentication protocol that works in existing automotive computer networks without delaying any message or increasing network traffic. Deployed in many vehicles, the CAN bus is a low-speed network connecting electronic control units, including those that control critical functionality such as braking and acceleration. The CAN bus is extremely vulnerable to malicious actors with bus access, including wireless access. Traditionally, Message Authentication Codes (MACs) help authenticate the sender of a message, and variants prevent message replay attacks; however, standard MACs are unsuitable for use on the CAN bus because of small payload sizes. Restrictions of the CAN bus, including the need not to delay messages or increase bus traffic, severely limit how well this network can be protected.

Mini-MAC is based on a counter-seeded keyed-Hash MAC (HMAC), augmented with message history and truncated to fit available message space. It does not increase bus traffic and incurs a very small performance penalty relative to the provably secure HMAC. It is the first proposal to combine these two tenets for vehicle networks. The message history feature protects against all transient attackers, even if they know the keys. Though the CAN bus cannot be properly secured against a dedicated attacker, Mini-MAC meaningfully raises the bar of vehicular security, enhancing the safety of drivers and others.

Jackson Schmandt is a MS student in Computer Engineering in the Mobile Pervasive Sensor System Lab. Joint work with Alan Sherman and Nilanjan Banerjee.

Host: Alan T. Sherman, Sorry, you need javascript to view this email address.

Establishment of Trust and Integrity in Modern Supply Chains

Ujjwal Guin, University of Connecticut

11:30 Thursday, 25 February 2016, ITE325b

With the advent of globalization and resulting horizontal integration, modern supply chain becomes extremely complex and requires immediate solutions for eliminating counterfeit integrated circuits (ICs), which pose a serious threat to the safety and security of our day-to-day lives. The reliability of such ICs could be questionable as they may have many defects and might not go through as much of a rigorous test process as their authentic counterparts. An adversary can also create a backdoor to bypass the security modules in these ICs. In this research, I have systematically addressed the aforementioned issues by risk analysis and assessment of test methods, and by proposing different Design-for-Anti-Counterfeit (DfAC) measures. As a part of risk analysis, I have developed taxonomies for counterfeit IC types, counterfeit defects, and test methods. Based on these taxonomies, I have introduced novel test metrics and developed a comprehensive framework for assessing a set of test methods to maximize test coverage. In the DfAC domain, I have proposed a suite of solutions to detect counterfeit ICs without performing conventional tests. A set of lightweight negative-bias temperature instability (NBTI)-aware ring oscillators have been developed for combating die and IC recycling. In addition, I have developed a comprehensive solution for preventing intellectual property piracy and IC overproduction by assuring forward trust between all entities involved in the system-on-chip design and fabrication process.

Ujjwal Guin is a PhD candidate at the Electrical and Computer Engineering department of University of Connecticut, where he has been working with Dr. Mark M. Tehranipoor. His current research interests include Hardware Security and Trust, Supply Chain Security, Cybersecurity, and VLSI Design and Test. He has developed several on-chip structures and techniques to improve the security, trustworthiness, and reliability of integrated circuits. He has co-authored a book entitled “Counterfeit Integrated Circuits – Detection and Avoidance”. He has published several journal articles and refereed conference papers. He received Best Student Paper Award from the IEEE North Atlantic Test Workshop (NATW’2013). He is an active participant in the SAE International’s G-19A Test Laboratory Standards Development Committee. Mr. Guin received his B.E. degree from the Department of Electronics and Telecommunication Engineering of Bengal Engineering and Science University, Howrah, India in 2004 and the M.Sc. degree from the Department of Electrical and Computer Engineering of Temple University, Philadelphia, PA, USA in 2010.

Host: Chintan Patel