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Showing posts with the label UT Austin

One year later...

In the first week of August 2020, I was back home from the famous cancer hospital in Houston, MD Anderson, in which I received a brutal chemotherapy to control my lymphoma.  How the lymphoma ran away is a separate story of poor decision making by a junior doctor at MD Anderson, and me not dumping him two months earlier and starting on Acalabrutinib that has kept me alive until today.  Because of the rather sloppy administration of the support IVs, over four days they pumped into me a net 10 kilograms of liquids, and I was swollen like an elephant. How do I know this?  Because I weighed myself each day and at the peak I gained 10 kilograms. The doctor who burst in for a 5 minute visit, disputed my finding, arguing that it did not agree with the nurse's notes about my urine production. More about notes soon. I asked him quietly if mass conservation did not hold in medicine?  He was somewhat embarrassed, but then again, he was busy running from one patient to another, a...

The Future of Engineering Education - Part III

In Part I and Part II of this series, I told you how desperately public universities play the U.S. News & World Report rankings game. Public academia appears to be unable to grasp the fact that school rankings are an elaborate scam set up to boost private schools and provide them with steady income and prestige.  This obsession with rankings also plays to the recurrent thinking in the U.S. that unless you are rich or an already highly-educated, ready-to-use immigrant like me, you are not worthy of a decent life and it is your own fault.  Yeah, shame on you, why aren't you rich or well-educated? In Part I and Part II, I also suggested that in undergraduate education public universities would never win or place high in the current rankings scam.  Simply put, the rankings carrot is dangled from much too high for the public universities to bite, no matter how hard they try to jump. Since I spent 18 years as a faculty of the University of California at Berkeley, a...

Why Good Engineering Education and Research Are Inseparable? Part II - Research and Technology

Has anyone heard of foreigners clamoring to emulate the U.S. K-12 school system?  I certainly haven't.  I do receive, however, foreign delegations that want to learn how we organize academic research and graduate programs at UT Austin.  This happens at least once a month.  People around the world correctly perceive that most Tier 1 academic institutions in the U.S. are second to none and worthy of emulation. And how about premier U.S. corporations?  Do they come to UT Austin or to the local community colleges to hire their top engineers and scientists?  Do they set up research campuses and incubators around UT or the Austin Community College?  (Please do not get me wrong, ACC is a very fine and vastly underfunded institution, which treats the most difficult cases of acute high-schoolitis and online-learnatis .  My youngest daughter, a BS graduate in premed from UC Santa Cruz, is a nursing student at ACC, and I am pleased with the quality of her ...

Why Good Engineering Education and Research Are Inseparable? Part I - Teaching

Here are two other questions related to the title: What unique benefits are given to students at all levels - from freshmen to PhD candidates - by a good engineer and scientist, who also happens to be a decent teacher?  How are these benefits different from those delivered by a credentialed, but scientifically incompetent teacher? We keep on hearing the loud and stubborn voices that call for a strict separation of teaching from engineering practice and research. I think that these voices are tragically mistaken. By the way, when I say "tragically," I am thinking of Euripides , Aeschylus , Sophocles , and Shakespeare. In a good Greek tragedy the audience knows the inevitable fatal outcome, but the protagonists don't. For 22 years, I have been a teacher at two top public universities in the U.S.: UC Berkeley and UT Austin. Over time, I have taught some pretty large classes, so my statistical sample is sufficiently broad to justify the statements I shall make next. ...