musings on music and life

August 17, 2016

The next Theranos

Filed under: Internet craziness — sankirnam @ 11:22 am

I’m calling it right now: Biocellection is going to be the next Theranos.

The “depolymerization” of polymers is a massive, unsolved problem in chemistry, because it essentially involves the reversal of thermodynamics; for instance, “depolymerizing” polyethylene involves converting strong C-C sigma bonds to C-C pi bonds. This is a problem that many millions of man-hours have been spent on by some of the smartest people on the planet, with little luck. I’m highly skeptical that two girls just out of college with little experience doing serious scientific research would be able to solve this long-standing challenge.

In any case, breaking down plastics into carbon dioxide (as shown in the TED talk on Biocellection’s website where they talk about bacteria backing down phthalates into CO2 via aerobic respiration) by conventional methods is not difficult.

The comments at Chemjobber are particularly enlightening, and I had the idea for this being the “next Theranos” before that commenter did!


August 14, 2016

Microsoft DAT210x

Filed under: Data Science, education — sankirnam @ 12:15 pm

I recently completed the course Microsoft DAT210x: Programming with Python for Data Science on Edx, so I’ll just take a moment to review it here. I’m still taking the Data Science bootcamp by Logit, and took this as a supplement to get additional exercises with Python, Pandas, Scikit-Learn, and other Data Science-related packages.

The course was just introduced by Microsoft last month as part of their “Online Data Science Degree Program“. As such, I took the course from July-August, and this was the first iteration (the course just ended last Friday). That being said, 6 weeks is not much time to teach something as broad as “Data Science”. The course starts with an introduction to the subjects of Data Science and Machine Learning, and then progresses into an introduction to Pandas, which is a Python package for the manipulation of DataFrames, similar to what you do in R. After also covering a brief survey of 2-D and 3-D visualizations with Pandas and matplotlib, the course then covers data transformations and dimensionality reduction, namely PCA and Isomap (for non-linear dimensionality reduction). After that, the course covers several important algorithms used in supervised and unsupervised Machine Learning, including K-means clustering, K-Nearest Neighbors classification, Ordinary Linear Regression and Multiple Linear Regression, Support Vector Machines, Decision Trees, Random Forest Classifiers, and a final rush through confusion matrices, cross-validation, pipelining, and tuning parameters with GridSearchCV.

Given that this was the first iteration of the course, my experience was pretty good. The course could use a little more polish, both in the presentation of the online materials, quizzes, and programming assignments. There were minor typos all over the place (though they didn’t really impede understanding of the material), and the quiz questions were rather ambiguous from time to time, much to my consternation. The explanations of the concepts themselves were a little wishy-washy, but when you’re trying to address a general audience there’s little else you can do. Links to the literature, textbooks, and further explanations are included, and should be read as well in order to gain a complete understanding of the subject matter.

The programming assignments were great, however. They were quite challenging, and I think I spent more than the recommended 4-8 hrs/week on the assignments. They were all really interesting, and challenging enough where I didn’t get completely frustrated and give up. We used PCA and Isomap to project 3-D images into 2-D space, K-Means to identify people’s residences based on anonymized geolocation data from their cellphones (!), linear regression to reconstruct audio samples (sort of like what they do on TV shows!), SVC to analyze whether or not someone has Parkinson’s based on collected speech quality, and other interesting examples.

I would recommend people taking this course do as I did, and use it as a supplement for other courses. There’s no way you can learn everything there is to learn about a subject as broad as “Data Science” from one course, and it is good to take multiple courses because some of them explain certain concepts better than others. For example, this course covers Isomap, which is something that most other courses do not.

If you’re curious about the programming assignments, I’m posting them in my github.

July 31, 2016

Birthday reflections

Filed under: Philosophy — sankirnam @ 2:12 pm

No, I’m not dead.

I have been on the receiving end of an intellectual beatdown for the last 7 weeks, and that will only end on Sep 2. So until then, communication will be sparse.

Before I get started, I just wanted to share some not-so-noteworthy news: I’ve finally crossed some milestones on Quora. I’ve been reading and contributing to the community there for the past year or so, and in the last few weeks, crossed 100,000 views on my answers and became a “Most Viewed Writer” on the topic of Organic Chemistry. Why am I doing this? Because in this day and age, it’s important to have an “online presence”; not having one can count against you (people might see you as either a luddite or that you have something to hide), and as can be seen from the infographic below, networking online is becoming an increasingly common way to get a job. Contributing to Quora and writing this blog are both attempts to build up my own “online presence”.


In any case, two days ago I just crossed another milestone in my life – I just turned 30. I’ve always known that this day would eventually come, but now it has come and passed, and I’m still coming to terms with it. When I was younger, I would feel an impending sense of doom at the thought of getting older; I did have a bucket list of things I wanted to do before this age (the most prominent one being performing in the Madras Music Academy), but sadly they have all gone unfulfilled. My 20’s have disappeared and I feel like I do not have much to show for it. I’m behind all my friends in accomplishing the usual things by this stage of life: getting a full-time job, getting married (or being in a long-term relationship), getting a house… “settling down”, if you will. I’m 30 and I’ve never had a full-time job. That realization is a bit frightening and I sincerely hope it doesn’t result in being unemployed for the rest of my life.

I have pretty much been in school my whole life, and my feelings about that are similar to what Chembark describes. Thanks to the largesse of my parents and taxpayers, I have been able to receive an education without crippling debt. That being said, even though I got my PhD funded by taxpayer money, I am more than likely not going to be employed in the area that I got my PhD in…. which means all that taxpayer money was, ultimately, wasted. This represents a colossal market failure, and I know that I am not alone in this regard.

Like Chembark, if I were to drop dead today, there is no doubt that my net impact on society is still negative. I have published a few papers which represent a minute drop in the ocean of scientific publications and may be lost in the deluge, to be cited only a handful of times or not at all. This is the culmination of thousands of man-hours of work which may, or more likely, may not be useful to other people in the future. These anxieties of mine could be dismissed as the cost of scientific progress or of growing up in general, but the question is: is it worth it? A lot of scientists will argue that research is “incremental”, where one person adds a little to the progress of those before him/her. My experience has shown that for 99.999999% of people that is true, but real progress is accomplished by geniuses who come only a handful of times every generation and make startling breakthroughs, drastically pushing the frontiers outward. And no, I am not in the 0.000001%.

Even if I factor in music, I still haven’t accomplished quite as much as some of my peers in India or in the Bay Area. If you don’t do music full time, it is incredibly difficult to practice as much as you would like to or work on improving your teaching methodologies.

Fortunately, I haven’t had the urge (yet) to do anything crazy at this point in my life, as this paper would suggest, so…..there’s that.

June 28, 2016

Next concert, 7/10/2016

Filed under: Carnatic Music — sankirnam @ 12:14 pm


June 21, 2016

Statistics? Statistics?

Filed under: Philosophy — sankirnam @ 12:20 pm

Statistics? Statistics? Statistics mean nothing, newbie. As doctors, we know that people diagnosed with pancreatic cancer have an 85% death rate within five years, whereas people having an appendectomy have a 95% survival rating, but we both know pancreatic cancer sufferers who are still alive and appendicitis patients who didn’t make it. Statistics mean nothing to the individual. Not a damn thing.” -Dr. Cox, Scrubs

June 20, 2016

This week in The Economist, 6/18/2016

Filed under: The Economist — sankirnam @ 5:17 pm

I’ve neglected this for a while – I’ve been busy with other stuff. But this week’s issue has a LOT of good articles that caught my attention. It’s the story of my life; everything always gets lumped together, rather than being spaced out in regular intervals.

  1. An article about computing bootcamps! This is especially relevant for me, since I’m taking a bootcamp right now, and bootcamps are the hot new thing in the US for people wanting to transition to software/web development and “data science”. The article doesn’t really take a stance, but describes the overall picture.
  2. It’s interesting to see the “manosphere” getting some attention here; I wrote a little about it a long time ago. I used to read Chateau Heartiste (one of the main blogs) religiously, but stopped following it closely due to time and the decline in the quality of positings there.
  3. The big issue of this week is Brexit. On the 23rd, British citizens will vote on a referendum to decide whether or not their country will stay in the European Union. Even though England does not use the euro, this decision has massive economic and political ramifications.
  4. A roaring trade“: this article describes how Chinese parents are moving to the US to take of their college-going children, and in doing so, buying properties in the US, driving up real-estate prices in some locations. Irvine gets a shoutout in this article, and this sentence really struck me: ““If you want to make money in real estate,” says Steven Lawson, the CEO of Windham Realty Group, “buy where the Chinese are buying, because they perpetuate the price increase.”
  5. Yes, for the love of God, please ban female genital mutilation. As always, whenever this topic is bought up, the related topic of male circumcision is raised, even though it is not the same thing – circumcision is mainly for aesthetic purposes, and the organ is still functional. It’s not really mutilation, even though some groups (like the manosphere), might like to claim otherwise. Neonatal male circumcision is the legacy of Mr. Kellogg, the same person of Corn Flakes fame (think about that next time you eat a bowl of cereal!).
  6. I sincerely hope that the recent shootings in the US (Orlando and UCLA) cause the population of the US to reflect and introspect about gun laws. The UCLA shooting is unfortunately not covered in this article, but the outcome is the same; people are dead, and we are left wondering…why? Donald Trump immediately tweeted this response after the shooting, which is just incredibly distasteful and unprofessional.

June 17, 2016

Python Pandas

Filed under: Data Science — sankirnam @ 3:56 pm

Now that I’m learning how to use the Pandas package in Python, all I can think of is this:


June 9, 2016

Mixed messages

Filed under: Chemistry Jobs — sankirnam @ 12:56 pm

I mentioned before my reasons for not wanting to do a postdoc after completing my PhD. I will freely admit that when I started as a young, naive, doe-eyed first-year graduate student, I initially wanted to go into academics – I was even told multiple times by people from within and outside my department that I had the “mentality” and “intelligence” for academia. After having my soul properly crushed a few years into the program, my goals readjusted to something more realistic – that is, getting an industry job, a goal that was considered by many “selling out”, “settling”, or “selling yourself short”. I didn’t do a postdoc because I wanted to get an industry job, but now it appears that a postdoc is necessary – and this is information that I only found out after graduating.

Now, the problem is that there’s no clear-cut advice as to what PhD’s should do in order to get industry jobs these days. As far as academia is concerned, a postdoc or two is mandatory in order to broaden your knowledge base, make your CV more competitive, and get additional network contacts and letters of recommendation. However, if industry is the goal, then you will hear things from all over the spectrum, such as “doing a postdoc lowers your eligibility for industry positions since it means you’re too focused on academics”, to “we throw the resumes of applicants without postdocs in the trash”, to illustrate the two extremes.

SeeArrOh wrote about this situation a month ago, but it is still valid, and I think the situation is going to get worse with time, as the saturation of scientists at the PhD level keeps increasing year after year. My experience tracks with SeeArrOh’s observations. I think that my inability to get job after completing my PhD could be attributed in part to not doing a postdoc after graduating. That being said, doing a postdoc does not guarantee getting a job either! It’s still a very risky gamble.

One big problem is that these employment issues are very opaque to graduate students, and it is only recently, thanks to the efforts of truth-tellers like Chemjobber, that these issues are coming out into the open, and students/postdocs are able to read about employment and unemployment in the chemistry job market (largely anecdotal, but these are better than no information at all). It also works to the advantage of PI’s to keep their students in the dark regarding employment after graduation; PI’s can promise the (nonexistent) big payoff in order to keep their students working hard 80-90 hours a week, sacrificing their lives at the altar of science.

Unfortunately, the issue “do you need a postdoc if you want to get an industry job?” has not been resolved, and this is something that incoming students need to be aware of. If the answer is yes (a postdoc is necessary), then you need to be prepared for the long haul; an additional 7-10 years in school after undergrad (PhD + postdoc) in order to get a job. That’s why I tell people science is a lousy career path these days. People used to criticize medicine for taking too much training before being able to start one’s career, but I think science has safely beaten that now. According to the 2014 NSF Survey of Earned Doctorates, the mean time to PhD in the physical sciences is 6.5 years (5.7 years in chemistry), and is slowly increasing every year. The question of “how long is the average postdoc?” is more difficult to answer, but SeeArrOh did a back-of-the-envelope calculation for chemistry, and the mean postdoctoral stay (for those who went to academia) was 3.7 years. 5.7 + 3.7 = 9.4 years in school. Granted, these numbers were only derived from those going to academia, but they at least give some sense of the situation. Compare this with medicine, which is strictly 4 + 4 (8 years, 4 for medical school, 4 for residency – or 3+4 in some universities!). Suddenly, medicine seems like a smart choice, when one factors in the opportunity cost of time, the fact that residents on average get paid more than postdocs (for similar hours of work), and the fat doctor salaries at the end (the big payoff!) thanks to the AMA.

Finally, and this is something that will hit most people the hardest: Unfortunately, society sends PhD students mixed messages. On one hand, there are people who say “wow, doing a PhD is great, you’ll be able to change the world!”. But once you graduate, you see the real value of the degree, which is…less than toilet paper, due to insane market saturation in both academia and industry. Another issue is that it is very difficult to find employment statistics of graduates of PhD programs – this data is crucial to being able to assess the relative strength of a program, because after all, you get a degree in order to get a job and make money, right? But most universities do not care about what happens to their graduates after getting a PhD, which is very unfortunate.

This needs to change. If departments properly tracked career outcomes of their graduates, then maybe the equilibrium salary of PhD scientists would properly reflect the amount of training involved, rather than being depressed due to an artificial flooding of the market.

June 1, 2016

Classics in Organic Chemistry, Part V

Filed under: Classics in Organic Chemistry — sankirnam @ 3:59 pm

Wow, we’re on our fifth post in this series!

This next paper is a classic by E. J. Corey that all serious students of organic chemistry should have read at least once. It’s not terribly complicated, but at the same time is iconic enough that it is worth mentioning in this context.

A key concept when doing total synthesis (or almost any type of organic synthesis) is “functional group protection”. During the course of a synthesis, you may want to conduct a reaction to change one part of the molecule, but the reaction conditions employed for that transformation may affect other sensitive groups in other parts of the molecule. Thus, you will need to “protect” the vulnerable functional group(s) in the molecule so that they are not unnecessarily changed by the reaction.

When I was younger, I used to joke that a lot of total synthesis was basically “protection, coupling, deprotection”, making it like sex. If you do use this dirty chemistry joke later, remember to credit me (or not…do I really want to be associated with such hopeless humor?).

Anyway, a particularly sensitive functional group in organic chemistry is the hydroxyl (-OH) group. The hydroxyl group is what makes compounds alcohols. Ethanol, the alcohol we all know and love, is simply an ethyl group with an -OH.

Alcohols can also be thought of as organic derivatives of water. Water’s formula is H2O, and so alcohols can be thought of as water molecules with one of the hydrogen atoms replaced by an organic group (giving rise to the generic formula R-OH, where R represents any organic structure). Alcohols also undergo reactions on their own, and as such, are sensitive to acidic and basic reaction conditions. In basic media, the hydroxyl can be deprotonated, making it a stronger nucleophile (R-O vs. R-OH), and in acidic media, E1 and E2 eliminations are possible, depending on the structure of the carbon backbone. Therefore, if you want to do a reaction on a molecule containing hydroxyl groups, you have to be aware of the reaction conditions, and if the alcohol proves to be reactive, it may be necessary to temporarily “protect” it or “mask” it. A common way of doing so is by converting it to an ether, such as a THP (tetrahydropyranyl) ether.

Another alternative is the use of a silyl ether (-OSiR3) as a protecting group. Silyl ethers are easily synthesized by adding a chlorosilane and a weak base (to mop up the HCl produced) to an alcohol. As with everything in chemistry, while the concept is simple, the situation is much more nuanced than might seem on the surface. Standard TMS (trimethylsilyl) ethers are not useful, because as mentioned in Corey’s paper, “Trimethylsilyl ethers are too susceptible to solvolysis in protic media (either in the presence of acid or base) to be broadly useful in synthesis“. One solution is to increase the steric bulk of the groups attached to the silicon atom. Replacing one of the methyl groups with an isopropyl, while promising, still did not give the stability desired, especially in “Grignard reagent formation, Wittig reaction, or Jones (CrO3) oxidation”. Thus, Corey decided to increase the steric bulk further, opting for a tert-butyl group on the silicon. This is called the “t-butyl dimethylsilyl” group, and is abbreviated -TBS or -TBDMS.

However, another roadblock ensued – TBSCl proved to be too unreactive with most alcohols under conventional or even forcing conditions, “for example, with excess silyl chloride, excess dry pyridine in tetrahydrofuran at temperatures from 20 to 60° for many hours”. This was solved by the discovery that the use of TBSCl with catalytic imidazole in DMF turned out to be appropriate conditions for the activation of TBSCl. These conditions quickly became known as Corey’s classic conditions for TBS protection. Even though a detailed experimental section is not included in this communication, Corey demonstrates the versatility of this method in the total synthesis of several prostaglandins. The TBS group is much more stable to hydrolysis than less bulky silyl ethers, and as such became widely used in synthesis. Like all silyl groups, it can be quantitatively removed by the use of fluoride (either a solution of KF or TBAF (tetra n-butyl ammonium fluoride)).

This begs the question – how does this method of activation work? My guess is that imidazole is able to initially bond to the silicon, forming a hypervalent pentavalent species, which is then transferred to the hydroxyl oxygen atom. Unfortunately, I cannot find the source right now, but imidazole is known to be able to activate silicon groups too, although not as strongly as fluoride does. DMF is also known to be able to activate silicon compounds such as TMSCN and TMSCF3.

More in the next. I need to get some coffee!

EDIT (7/28/2016): Prof. Andrei Yudin has a very nice discussion about this reaction on his blog.

May 31, 2016

Next concert, 6/12/2016

Filed under: Carnatic Music — sankirnam @ 1:09 pm


As always, if you are in town, please do come! All are welcome.

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