All posts by mbaxaac2

Learnings From My Third Year Project: Part 1

If I had been asked at the start of my first year, how do I envision myself in my final year, working with graphene would have been the furthest thing on my mind. Yet, here I am, spending most of my time in the labs of the Nanoengineering and Storage Technologies group and loving every moment of it. 

In my previous posts, I have only alluded to my third year project and described it briefly, but now i’m going to talk about it in a lot more detail…

This post aims to not only highlight the vast range of opportunities on offer at the University (if one knows where to look for them) but also help me catalogue important lessons and habits that I have picked up that have helped me become more effective as a researcher. 

My project relates to Parkinson’s Disease, but to understand why, we must first understand the underlying cause of Parkinson’s Disease, which is the loss of dopamine producing cells in the human brain (why these cells die themselves is still unknown, however the effects of that death are very well known). Motor movement in humans can be viewed as a set of two actions, one, preventing unwanted movement and two, allowing precise movement. These two actions are co-ordinated by a part of the brain called the motor cortex. The motor cortex can be viewed as the last stop in a series of complex interactions occurring in a region called the basal ganglia. 

It’s at the first stop, substantia nigra, where the problems start and then cascade all the way along! When the dopamine producing cells in the substantia nigra start dying, the dopamine receptors in the striatum no longer receive adequate input. This lack of input prevents the striatum from regulating the thalamus, which ultimately cannot influence the motor cortex enough so that it carries out the two actions as intended.

Eye blinking, like other motor actions, is co-ordinated by the same region and hence is affected as the result of this. Surprisingly, using eye blink as a marker hasn’t been explored extensively, despite the link being known. This has primarily been due to the fact that tremors and other symptoms (changes in voice) might offer better clues. Yet, for a third year project, this represents a low hanging fruit. One where I can build on existing literature and contribute something to what we currently know about the progression of Parkinson’s Disease. While this is all hunky dory, an important question is raised. 

How does one measure eye blink? 

To build a useful sensor, some considerations must be taken into account. The obvious one is that the sensor must actually detect the intended signal. The less obvious ones are, it must be unobtrusive and shouldn’t, in any manner, affect the existing behaviour of the person wearing the sensor. Given these constraints, we have to design our sensor carefully. Before I settled on the graphene one, there were three others that I had contemplated/discussed with Professor Simon Harper.

The first two were camera based. You could either have a camera (a miniature one, of course) looking at your eye at all times and then use image processing to identify blinks, or use your smartphone’s camera to remotely track your blinks and detect differences over time. The third one was using an infrared beam directed across the eye. I was unsure about the first two since they either didn’t offer continuous monitoring and/or required bulky apparatus. The third one was intriguing and some friends (Mihnea Savu, Rifad Lafir and Hendrik Mölder) and I built it at HackTheBurgh to win the top honours. While that was a fun hackathon project, it too had some real practical issues, such as requiring constant calibration and lack of effectiveness when looking downwards. Now these are all solid scientific reasons for why I chose to do it the way I did, nonetheless, there is no denying that……working with graphene is REALLY. FRIGGING. COOL.

The team showing off the product and the incorporated company logo.

A good way to imagine graphene is to take a slab of graphite (yes, the one found in pencils) and then polish it down to a thickness so fine, that all you have is a single layer of carbon atoms (this was actually a precursor to the scotch tape technique if I remember my history right). It isn’t much to look at, it’s mostly transparent. But this single layer’s properties make it incredibly useful for bio-mechanical sensing. For one, it’s electrically conductive, with an extremely low resistance (and this is the property I am trying to exploit). It is also relatively flexible. In fact, its flexibility combined with its resistivity makes it an excellent sensing material. This isn’t a monumental leap of faith, these properties have been known and used for quite some time in literature (for those keen on the references, check the project proposal linked underneath) to build sensors and it was one of these techniques I wanted to adapt and improve to accomplish my project’s goals. 

Blinking in humans is the function of 3 muscles. One of these muscles is called the orbicularis oculi. To identify where this muscle is located, lift your index finger and place it close to the junction of your eyelids on the side of your head. Now blink twice. You must have felt a slight twitch under the skin. This is the very twitch that graphene would be picking up. 

Blinking in Parkinson’s (taken from my lightning talk)

If you have followed so far, this must have sounded simple enough. And that was my initial reaction too. I mean, how hard it can be, just slap on some graphene on the side of your head, pass a current through it and pick up the change in resistance on a small micro-controller. Ha. Ha. Ha.

Building the sensor

Patterned graphene for my sensor under an optical microscope at 100x zoom

The sensor by itself isn’t very useful. The data it collects needs to be analysed, stored and visualised to be useful to physicians. In a nutshell, I have to go right from a single atomic layer, all the way up to the cloud. Funnily enough, this serves as a useful analogy while I do my graphene work in the labs on the ground floor of the IT Building and discuss the cloud platform on the second floor of the Kilburn building. 

The IT Building is home to the Centre for Mesoscience and Nanotechnology (CMN). It was here that they were able extract graphene using scotch tape and carry out electrical measurements on it, work which later led to the 2010 Noble Prize in Physics. At the CMN, under Prof. Thomas Thomson’s supervision and Dr. Gregory Auton’s guidance, I commenced my attempts to build my eye blink sensor. 

One of our first working sensors

Soon enough, the humbling lessons started. My first lesson was about recreating results from papers. I had, wrongly assumed, that a paper is like a recipe. My naïve (less so now, but still quite) self thought that I could follow the methodology section down to the dot and in about a few weeks, I would have the results I hoped for. It’s been 7 months since I started and I am still struggling to build the right type of sensor. Lesson learnt, papers aren’t like a collection of recipes, they are more like far apart placed signboards on a road that has many potential detours. 

One of the earlier designs that later failed

The next lesson that followed on from this was that of patience. As CS students, I think there are few avenues for us to develop that skill (unless you are a machine learning researcher). We live in an age where the output of our work can be seen instantaneously, when it works and when it doesn’t and this has spoilt us. In the natural sciences, this process is a lot more subtle. It can be a few days before I can see the result of my work, assuming that the procedure was carried out meticulously. In case it wasn’t, that’s a few days of effort wasted, unless…

(Lesson 3) you use every failure to learn something new about The Problem. As of last count, I have burnt, broken and botched 20 graphene samples and that has taught me 15 lessons (I am a slow learner, it took me 5 samples to come to grips with reality). These lessons have spawned ideas ranging from using an oven to make the process quicker to building a Lego testing apparatus. 

My synthetic blink creator!

Lesson 4 obviously has to be about collaboration and discussion. Several ideas that I utilised came from talking about my research with other people (both willing and unwilling participants). Sometimes, by explaining things to someone who doesn’t know the details, you are able to challenge your own assumptions and examine them closely to either modify them, discard them or relax them. This leads to insights that can help you take a few more steps forward. Closely related to this is, feedback, either positive or negative, is still useful. I say this because good feedback motivates you and negative feedback highlights questions in your research that you should be answering but probably haven’t. Recently, I had the honour of having my research questioned by Sir Andre Geim at a weekly conference where my supervisor was presenting the lab’s work. The question Sir Geim asked was whether graphene was truly a good/novel choice to build this sensor? The answer to that question is, probably not, but it’s a decent compromise between usability and sensitivity. Anyhow, had it not been for that question, I wouldn’t have spent a few days trying to absorb information on all other ways one could possibly do this, which itself was an essential exercise. 

I have spoken about my project quite extensively above and I am just getting started. If I keep going, the post would become much much longer than it already is, hence, I am going to stop here. In the next one, I’ll probably talk about other lessons I learnt, some mundane, yet fulfilling experiences and the way forward for my project. That would probably be my last post on the topic before I move onto writing about Exploring Europe: One Hackathon at a Time.

Original project proposal (there were several revisions and corrections to this, so this isn’t the latest version)

Summer in the City and Starting a Third Year Project

It’s been a while since I last wrote. Primarily, this was because there wasn’t much to write about apart from the usual routine. However, with the summer finally here and a collection of experiences to boot, it was the perfect opportunity to write a new post.

For most second year students, this summer is used for starting their internships and year long placements. For me though, the summer was the perfect opportunity to get started on my third year project. Getting this head start was imperative since I had a lot of ground to cover, in graphene, physics, chemistry and nanotechnology.

The third year project is a piece of extensive academic work that all undergraduates must submit in the School of Computer Science in their final year. One can propose their own topic or choose a topic from those that have been proposed by the faculty members. The topics proposed by the faculty members span a huge number of sub-fields of computer science and some offer the opportunity to work on cutting edge technology, like the SpiNNaker project.

My project, on the other hand, isn’t heavily focussed on pushing the boundaries of a CS field, which some of the other projects in the past have done. What I intend to do is build a sensor which is about as wide as one’s fingertip and use that to monitor eye blinking. Now one might wonder what can something as mundane as eye blinking tell us. Surprisingly, a lot. Primarily, it can tell you if you have developed a neurodegenerative disease and that is what I am interested in finding out. To do that, I am going to use a single layer of graphene, which is about as tall as 2D materials are and about as wide as the tip of one’s finger, stick it onto some medical tape and pass an electrical current through it. Given the nifty properties of this wonderful material, it should detect a blink, when mounted on a small muscle close to one’s eyebrow. This blink would be represented as a change in resistance, which hopefully, should be read by a small Arduino board on one’s spectacles. That’s the idea, at least. And that’s how my summer started, straight out of the exam room and into the research lab. The moment to relax a little came on the weekend, at a hackathon in Amsterdam.

The Amsterdam hackathon was organised by adidas as part of a series of hackathons over Europe and 8 of us from Manchester attended, partly thanks to the generous support of the Student Activities Fund. The objective of the hackathon was to help ‘Personalise the next generation shopping experience’, which I think was a very vague topic! The hackathon itself was very well organised, it was at an excellent roof top venue with lovely food. All in all, the hackers were very well taken care of, as they should be, at a corporate hackathon. The 8 of us from Manchester formed two teams, my team worked on creating a facial recognition based system that provides in house sales assistants with personalised information about the clients in store, whereas the other team built a machine learning driven service that finds you similar products as the one you see on social networks. Though we didn’t win, we learnt a great deal about React and Vue.js. In addition to that, we were also able to take some time off hacking and explore the city on bikes.

On returning from Amsterdam, I was back in the lab, refreshed and raring to go. The entire experience in the lab deserves its own post, so I shall speak more about that at the end of the summer. Before I end, I am going to talk about the other highlight of the summer, moving to a self-catered hall.

In my last post, I had mentioned that I had moved into a heritage hall called Ashburne. Since Ashburne is only open for term time, I had to pack up and move into one of the summer accommodations that the university offers. Given a choice between the legendary Oak House and Whitworth Park, I ended up choosing Whitworth Park. Whitworth Park has quite a few things going for it. It is conveniently situated very close to the university, is really close to the famous concert venue at Manchester Academy, has a pub on site and the Turing Tap right outside. Moreover, the hall has a well equipped gym and the kitchen is an absolute dream to cook in. In essence, you can cook to your delight in the huge kitchen, after purchasing some really good ingredients from the supermarket outside your front door, grab a pint and not feel guilty about piling on the calories since the gym awaits you to sweat it out.

That wraps up a quick summary of my summer so far. I’ll talk more about my 3rd year project and the experience of working in a nanotechnology lab in the next post. Until then!

CERN, bus to France and other semester 2 (mis)adventures

This post has been in the works for quite some time now. The past semester has been full of interesting experiences that could be posts in their own right. However, I seldom have had the patience or energy during term to sit down and write them. Now that the Christmas break has started and I have finally managed to soak in some of the warm Indian sunshine, it’s time to revisit all those anecdotes and put together a cohesive summary.

Ashburne Hall

I started the academic year by moving back into university’s accommodation. My choices during the application were Dalton Ellis (catering on the weekend), Ashburne (quiet and quaint) and Woolton (No good reason, I guess it was another catered hall).

Ashburne Hall

I found out that I was assigned Ashburne Hall before I went home for the summer, but it was only on moving in that the charm of the place took effect. Long corridors with high ceilings, a large and ancient library with huge windows looking out on the lawn and a rich history dating back to the early 1900s surely add to its aura. With all the other modern creature comforts thrown in, it is no surprise that this is one of the best halls here at the University.

Alas, before I could settle in and perhaps attend one of the traditional formal dinners, I ended up bumbling my way to CERN in Geneva, Switzerland for a 4 day hackathon.


When one mentions CERN, the first thing that comes to mind is a humongous machine that only exists to cause a particle pileup on the quantum highway, so that some really smart people can tell us how the universe came into being!

The Atlas Control Room where Higgs Boson was first observed
CERN Grounds

The Large Hadron Collider, whose function I paraphrased above is not the only thing CERN does though. With so many talented minds around, it would be a waste to not solve other pressing issues and therefore, some of the people who work there decided to do an annual hackathon. They provided us with CERN’s superb resources, be it research excellence, incredible mentors from CERN/EPFL, cranes (the 60 feet kind) and contacts in the industry to take the project forward. They then let 6 multidisciplinary teams loose on various problems for 4 days and it finally culminated in a presentation before an esteemed group who could provide support to take the projects out into the real world. In fact, the ideas that were thrown around ended up inspiring my 3rd year project.

The lab where we worked had eclectic workspaces
You must have a couple of Nobel prizes to have a street named after you here

It was all quite exciting and a rare opportunity, although I came really really close to missing it. The trouble is, as a non-European passport holder, travelling is not always hunky dory. When I want to travel I need to navigate a maze of processes that seem to have been devised by Daedalus and Icarus themselves! And in my case, my application was forwarded to the with great reluctance because of all the fun that entails when you mention a “HACK”-athon. This is not to say that the Embassy didn’t understand what a hackathon meant, on the other hand, the application breezed through once it got to them. However, I couldn’t even have the last laugh, when the visa came back, the purpose of visit was listed down as ‘Other Motives’.

Despite all of this I was able to safely board my flight to Switzerland, and it was in Geneva that I also happened to board the bus, strangely to France. Little did I know that the bus that says ‘CERN’ on it when collecting  at the airport first crosses the border into France, then comes and heads to CERN back in Switzerland, in the opposite direction!

Nonetheless, these (mis) adventures wouldn’t have been possible without the help of the Student Activities Fund here at the School of Computer Science. The fund exists to financially enable students to undertake opportunities that can be of great value as an undergraduate student. It was due to this fund that I was able to cover the cost of visa, plane tickets and insurance to visit Geneva and Barcelona (it was on the weekend after Geneva) for hackathons.


Our “hackathon venue”


HackUPC was one of the first MLH hackathons of this season and it was organised at a time when the weather in Barcelona is quite the respite from the sultry Manchester rain. As I had mentioned in a previous post, I intend to maximise the fun and learning when at a hackathon, both for my team and myself. At Barcelona, this is exactly what we did.

Starting Friday, we slugged through the night hacking a DSLR and Raspberry Pi to create a Photo Booth. By Saturday afternoon, the voice control and DSLR was mostly working but the Raspberry Pi was acting up over the network. So, we took the sane decision of hitting the beach and gulping down some gelatos. After a 5 hour jaunt walking the streets of Barcelona, swimming in the Mediterranean and humming Ed Sheeran and George Ezra’s songs, we returned, refreshed and raring to go.

An oddly symmetrical building in Barcelona
Oddly colourful building on the streets of Barcelona

By early Sunday morning, we not only managed to have all the components working, we also put together a nice case of cardboard around it, emblazoned it as if it were an F1 Car with sponsor stickers and sent a shoutout to people to come try it out.

Maybe it was the fact that our photos spammed the Twitter page of the hackathon and participants and judges alike came to take pictures with their team that did it for us, but we ended up winning Bloomberg’s prize for our very hacky, hackathon’s HackerBooth.


Computer Networks

Computer Networks is a course unit that every second year loves talking about, for various reasons. I personally found this to be the most interesting unit I took this semester, trumping even the machine learning unit, which I would have sworn by at one point.

This course is demanding, no doubt about that. The labs are quite involved, the marking tough and the course material overwhelming. In spite of that, the course is the most comprehensive introduction to the functioning of the internet, going right from the movement of packets along a link to the functioning of a global streaming service, like Netflix.

Whatever everyone else might say, I’d highly recommend taking it.


Since February 2017, I have also had the opportunity to work under Dr. Simon Harper and Julio Vega, a doctoral student here in the Interaction Analysis and Modelling Lab. Researching as an undergraduate offers a very valuable experience and exposes one to the many struggles and triumphs of academia, which does shape one’s perspective of delving into this field post their undergraduate degree.

My work was focussed on developing a plugin for an open source Android library called AWARE that lets an Android phone collect data from an IoT sensor over bluetooth and store this in a cloud database to be used for later analysis. After a lot of back and forth, I finally managed to finish the task around October. This was a great learning experience in terms of software skills, since I had never worked with Android or Java before in a project like this. It also afforded a perspective on things one often takes for granted about the users as a developer. Furthermore, it gave me a taste of the larger academic environment which was an interesting contrast to the industrial environment I had already grown accustomed to. Come next semester, I am already looking forward to undertaking more work, some of which might support future projects in the lab including my own project in the next academic year.

That more or less winds up my recap of the semester. Time to return to some revision now. Until next time!

Experimenting with a Convolutional Neural Net

Its 11:00 PM at night and I have grown bored of revising for the upcoming exams. To alleviate my boredom, I think I am going to spend the next 12 hours or so hacking and blogging.

For a long time, I have been wanting to get my hands dirty with training a convolutional neural network on a GPU instance to recognise breast cell clusters and classify them to be benign or malignant. With the forthcoming days seeming to be terribly occupied with all sorts of revision frenzy, this seems the best time to dive in and see how far I can get with it. Before I dive into the code and setup, I must point out that this is my first attempt at setting up a neural network. A lot of what I will write here would be what I learn as I go along. I am not going to delve into the theoretical details and the math behind making convolutional neural nets work in this blog, I’d like to keep my focus narrowed on the implementation details.

Without further ado, lets get started.

23:34 – Got an Amazon EC2 GPU instance running. I tried installing the CS231N AMI, but I didn’t have GPU instance permissions there, so I reverted to the Oregon region and used the ami-dfb13ebf AMI for having pre installed deep learning frameworks like Tensorflow, Torch, Caffe, Theano, Keras, CNTK amongst others. As I write this, I am also installing Anaconda on the instance so I can put all of my code in a Jupyter notebook and access that remotely from my laptop. I found this guide quite useful on getting the Jupyter notebook up and running on a remote instance –

00:27 – GitHub Repository – Check, Packages Installed – Check, Data Transferred to EC2 Instance – Check.  The dataset I’ll be using today consists of ~45 histopathological images. The dataset is available at Now, 45 images are no where near enough for training and testing a model. That’s why I’ll rely on Keras’ image augmentation features to generate synthetic training data. This would include create images that are flipped, blurred and rotated. To give an example of what the images look like, here are two from the original dataset.Screen Shot 2017-06-06 at 09.08.34 Histopathological Image Sample 1

When I first looked at these images, two conflicting feelings engulfed me. On one hand, I found these images quite fascinating; one of the smallest components of our body, undergoing mitosis. On the other hand, it was terrifying, a peek at a disease that is, as Harold Varmus put it, a distorted version of our normal selves.

01:54 – Managed to read the images into my notebook successfully and create the training arrays. Seems like all those all nighters at hackathons have made it easier for me to work well into the night without feeling particularly drowsy. Going to generate about 2500 new images per class.example

02:08 – Running into errors with generating new images. For some reason, its trying to find JPEG files, whereas my files are TIF. Managed to solve it, the error was arising due to an incorrectly specified path argument for the directory where the images were supposed to be saved. But now, I have a mix of TIF and JPEGs, not sure if that will be alright. Guess I’ll find out. With the augmented image generation done, I now have 5045 images in total. I used an 80:20 split on this.

02:50 – Transforming the images and labels was easy. Finally, after 4 hours of data processing, I can finally start training a model. For this, I’ll use an architecture with an input layer followed by convolution, maxpooling, convolution, convolution, max_pooling and fully connected layers. At this point, I’ll also add dropout to prevent over-fitting and then connect it to a fully connected layer that predicts one of the two classes. Will also use the ADAM optimiser and the loss function would be binary_crossentropy. I was predisposed to this architecture because it performed relatively well on the CIFAR-10 database. Enough talk now, time to train it.


03:39 –  The model has started training. The validation accuracy initially was looking quite encouraging, however, it remains to be seen how well it performs on the test set.evaluation training

03:46 – 87% accuracy on the test set. Not bad for a baseline model. Still, when I look at the training and validation loss, it seems the model started overfitting. I might have to play around with the parameters/model layers to see if I can make it fit better. However, going to do all that after the exams. This will require a lot of trial and error. Below are some examples that confounded the model.

Here’s an image that was predicted to be benign but is actually malignant.


On the other hand, this one was predicted to be malignant but is actually benign:


The confusion matrix for the model was:

[[415  93]
[ 31 470]]

Giving this confusion matrix was important since the accuracy of the model by itself doesn’t tell us much. A better metric to use is precision and recall. Precision of a model refers to the percentage of true positives guessed, which in this case happens to be 93.04% ( Malignant Predicted and Malignant True / All Malignant Predicted). The recall percentage of the model comes out to 81.7%, which implies that the model was successful in finding the images with malignant tumours roughly 82 times out of 100.

Like I said earlier, this was primarily a learning experience for me. Spending the few hours wrangling with these images taught me:

  1. About the effectiveness of CNNs in image recognition tasks due to their ability to extract features without explicitly being given any.
  2. A few details about evaluating model performance using the training, validation and testing accuracy.
  3. How to leverage openCV and Keras to work with image data.
  4. Intuitive details about convolution, max pooling and activation functions.

Now I must call it a day on that and get back to revision, after getting some shut-eye! In the next blog post, I am going to talk about leveraging the Raspberry Pi and a few external components to turn it into a personal assistant device.

Until next time then!

A lot of code was adopted from

Understanding Convolutional Neural Networks

Further reading – Spanhol, Fabio Alexandre, Luiz S. Oliveira, Caroline Petitjean, and Laurent Heutte. “Breast Cancer Histopathological Image Classification Using Convolutional Neural Networks.” 2016 International Joint Conference on Neural Networks (IJCNN) (2016): n. pag. Web.

Code –

Studying, Living and Working in Manchester

Over the past few weeks, a couple of Indian students wanting to study Computer Science/Engineering at Manchester got in touch with me to ask me about what it’s like to study, live and work here. Therefore, I decided on writing a (hopefully) comprehensive, guide, to answer most of the queries these students couldn’t find answers to on the University website. I hope to cover quality of education, finances, trade-offs one faces when they get here, tips on managing living costs, employment (in light of my 6 months of experience) and, of course, the weather!

But before I begin, I must point out that my ‘advice’ should only be used as a reference point. Also, my views about the education here only apply to the School of Computer Science.

Quality of Education:

In comparison to the education back home, I definitely think Manchester outclasses several domestic universities. The courses offered here are vast, often taught by people who are really passionate about their field. There are tremendous resources available for exclusive student use, be it well stocked libraries, computer clusters, support systems or sporting facilities. With the largest student body in the UK, the diversity is pretty high too.

The Alan Turing Building
The Alan Turing Building

However, I know, as an International student, the argument is seldom about the number of Nobel Prize winners in the Faculty, or the number of books in the library. Being a student who pays more than double the amount of a British/EU student, it does boil down to one important consideration, return on investment (ROI).

If you do decide to come and study here, then you should make the most of the university’s resources! Write to Faculty academic staff to try and engage in cutting edge research, devour the knowledge contained in the libraries, network through the university’s events and make the most of what’s on offer. The international student fee is high, but you can very well get the most out of it.


There are two major costs associated with studying here, tuition fees and accommodation fees. The university allows you to pay them in instalments, which can be quite convenient. But, also keep an eye out on the exchange rate, a favourable exchange rate might just make it easier to pay the fees in a lump sum.

Once you get here, you can work upto 20 hours a week during term time and full time during holidays to contribute towards your living costs (more on this later). You can read about the Tier-4 visa University work policy here.


  1. Accommodation

With so many choices for accommodation, it does become a little bit overwhelming when deciding what is the best option. The way I dealt with this dilemma was looking at it in terms of implicit and explicit costs.

Before I go on, please be aware that these costs are estimated living costs for 2016/17 academic entry.

Catered accommodation means that you get 2 meals on the weekdays and fend for yourself on the weekends and during the holidays. In terms of explicit costs, you can get catered accommodation from £93 (Twin room accommodation @ Dalton Ellis) to £175 (Ensuite @ Ashburne Hall). In terms of implicit costs, this means that you have to adhere to the timings, 7:30 – 9:30 in the morning for breakfast and 17:30 – 19:15 for dinner. Then there is the cost of eating the same breakfast every day, and dinner on a 5 week rotation. On the bright side though, your food is generally healthy.

Ashburne Hall
Ashburne Hall

Self-catered on the other hand means that you can cook whenever you want, eat whatever you want and socialise over cooking with your flat mates. In terms of explicit costs the range is nearly the same. In addition to that, there are the costs of purchasing your ingredients. This can be between £20-£50 depending upon your tastes. It’s not the explicit costs that make it a tough decision, but the implicit costs. By cooking your own food, you are effectively spending time purchasing your ingredients and cooking them. While it might be an enticing idea, you should take into account your other commitments which will take a larger amount of time, such as classes and part time work. Also, more often than not, in order to save time, I have seen a lot of my friends just binge eating on processed and junk food day in, day out.

The university has a good mix of both self-catered and catered options. Some of the good catered halls are Dalton Ellis, Hulme Hall and Ashburne (this is the furthest away though from the main university campus). Similarly, some of the good self-catered halls are Denmark Road, Burkhardt House and Wright Robinson.

Denmark Road - Uncatered, swanky, close to the city, expensive
Denmark Road – Uncatered, swanky, close to the city, expensive

Then there is also the dilemma of going for private accommodation. This is another feasible choice and the university has great help available on this and all the types of accommodation on their website. 

  1. Travel

For travel within Manchester, you have plenty of options. You can walk, bike, take the bus or hail a taxi.

Stagecoach is one of the bus operators here and they offer an annual bus pass for £595 which allows unlimited travel on their buses. If you are an infrequent bus traveller and don’t want to buy a pass, a ticket for bus rides along Oxford Road cost between £1 (First) – £3.70 (Stagecoach).

I personally prefer cycling or walking though. Most of Manchester’s major roads have dedicated bike lanes. Buying a bike at one of the sales organised by the Students Union is way cheaper than investing in a bus pass, plus you can use the bike throughout your time here. Again, there is another alternative here. If you are new to biking in the city and don’t want to put money into a bike right away, you can rent one for £1/week from the Student Union’s Biko Bike project. That way, you can get your feet wet (in the Manchester rain) without burning a hole in your pocket.

One of the bikes at Biko
One of the bikes at Biko

Intercity travel in the UK is quite affordable if you book early enough. As a student, you might want to keep a look out for the Virgin Trains Seat Sale, when you can snap up a ticket for as low as £10 or the Mega Bus, which has outrageously low ticket prices at times. Apart from that, the 16-25 rail card from the National Rail gets you 1/3rd off your ticket, making it a good investment if you intend to travel and explore the country frequently.

A ride to London on one these can be as low as £10 if you make use of the sales
A ride to London on one these can be as low as £10 if you make use of the seat sale

Money Saving Tips

I already mentioned a few of these above, however, here are some more, I might update this list if I come across more:

  1. Haircuts are cheaper on the Curry Mile, in Rusholme (£6 upwards)
  2. There are two huge grocery stores on the Curry Mile as well which sell most of the things we take for granted back home. Do check out Manchester Super Store and Worldwide.
  3. Aldi is cheaper compared to Tesco
  4. Greenhouseand Vasio Cafe are probably the healthiest and most reasonable food outlets on the university campus.
  5. You can get student discounts at a bunch of stores and restaurants across the UK.
  6. There is a Gurudwara in Cheadle-Hulme that does a communal meal (Langar) at least every Sunday and on Indian religious holidays.


This is probably the elephant in the room when it comes to us Indian students and whatever I write in the next few paragraphs is only restricted to STEM degrees.

The short and simple answer to the great employment question is, if you have the skills, you will get hired, be it in the UK, in the EU or in the States.

The longer one is, you need to take initiative and put yourself out there. After all, there is no such thing as a free dinner. One of the reasons why students don’t get the right job is because they start too late, be it at cultivating their skills or searching for positions. I would recommend to undertake work that genuinely excites you and the rest will tend to fall in place.

The UK government allows for 20hrs of paid work per week during term time and full time work during the vacations. There are several places one can work part time, including the university, for instance, you can become a Student Ambassador for the School. Again, when it comes to jobs, its imperative that the notion of any job being beneath you should be left behind. Though I’d recommend that you first seek jobs relevant to your degree and once you have exhausted your options, only then move to jobs in retail/marketing.

I used a slightly different path in my job hunt though. Since I was keen on supplementing my CS education, I thought of sending speculative emails to tech startup founders in Manchester, so I could work as a developer at their companies, a few months into my ‘formal CS education’. Perhaps it was the audacity or a tool box slightly different from the others that clicked, but I got 3 offers, out of which one led to my current job.

Art in the Northern Quarter - Manchester's Art, Leisure and startup hub.
Art in the Northern Quarter – Manchester’s Art, Leisure and Startup hub.

All in all, there is a plethora of opportunities in Manchester, if you know where to look. Also, the additional money eases several of the international student costs.


“O Mancunion Weather, thou art a wundor” 

Having coming from a place where the weather is mostly sunny, the drastic weather changes in Manchester never ceases to amaze me..

A snowy Manchester morning - probably the only snow this year
A snowy Manchester morning – probably the only snow this year

There have been days when I have stepped out into bright, gleaming sunshine, only to return in a gentle snowfall. There have also been days when I have stepped into absolutely torrential rain and it has all cleared by the time I was done with classes.

A glorious, bright day in Manchester @ The Museum of Science and Industry
A glorious, bright day in Manchester @ The Museum of Science and Industry

Then there have been days when I have cursed my choice of studying in England, as I pedal furiously against a vile wind and rain duo hell bent on making me miserable!

Nonetheless, the variety definitely keeps it interesting!

On that bombshell, it’s time to end, I hope my rant + informative piece has made it easier for you to pick your university and has allayed some of the fears you may have about moving to Manchester or the UK. If there is something that you feel wasn’t covered, feel free to leave a comment below and I’ll do my best to answer!

Speak to you again soon,


The n00b’s survival guide to hackathons

When I first started writing this post, I had only been to two hackathons. But now, with 7 hackathons under my belt, several fond memories and great friendships created, I think I can provide a more well-rounded view of attending hackathons. Despite that, I am still not getting rid of the n00b in the title. Even though my team and I built some really good stuff, it still doesn’t compare to the creative and technical brilliance one can see at some hackathons.

My main motivation behind talking about hackathons is to encourage current and incoming first years to put aside their misguided notions of being incompetent and dive head first into this crazy, energetic world of red bull and sugar driven development.

Without any further ado, here are seven things I have learnt from seven of my experiences

  1. Never go into a hackathon with a must win mindset

True, the Amazon Alexa and various drones make your mouth drool, nonetheless, hackathons are not about that! The way I see it now, it is about building cool hogwash (this was the closest substitute I could find for a certain four letter swear word starting with S), literally and figuratively. You create a product that (hopefully) works, which is cool, but your code is mostly spaghetti, spaghetti enough that TAs on COMP161 will give you zero for layout and code quality.

Out of the seven hackathons I attended, my worst two were the ones where we were only gunning for the prize and in the process, forgetting to have fun.  (More on this later)

2. Your first priority must be learning, learning fast 

Hackathons teach you a lot of things standard CS curriculums don’t. So you must see this as an opportunity to pick up frameworks, language paradigms, tools that you will probably never be formally taught. And the pace is dizzying. You have to learn things on the fly.

Some of the hackathon buzzwords
Some of the hackathon buzzwords

3. If you are the smartest person on the team, leave the team

This borrows from point 2. You are a first year student! You won’t learn unless someone pulls you out of your comfort zone and I believe that only happens when there is someone smart enough on the team to challenge you and your decisions.

4. Interact. Socialise. Network. 

There are ~300 people at a hackathon! Just imagine the amount of things you could learn and the experiences you could share if you spoke to them. People at hackathons are always keen to talk about what they are building, and that always serves as a great conversation starter, from there on, making friends is a cakewalk.

The attendees at HackCambridge (Courtesy: Major League Hacking)
The attendees at HackCambridge (Courtesy: Major League Hacking)

Apart from the hackers, also talk to the sponsors. Ask them about the work they do, the challenges they have brought, what have been their most memorable hacks and what free goodies are they offering today ;).

Some of the more interesting swag (Courtesy: Major League Hacking)
Some of the more interesting swag (Courtesy: Major League Hacking)

All of this not only helps build great rapport with them, but can also be useful to land you an internship when the time comes.

5. Don’t quit

Often, your code won’t be working as intended. For the first few hackathons, this is going to happen really often. But you must not get fazed by it! It’s part of the process. Sometimes, getting up and taking a stroll, talking to other hackers about their project works really well.

Another thing I would like to add over here is, don’t be afraid to pivot. Sometimes, what you might be trying to achieve is not possible in the given time frame (been there, done that, apparently, 50 epochs takes a long time). At one hackathon, my team came up with an idea about toilets at 1 A.M in the morning! And we ended up winning because of that.

6. Demo

At my first hackathon, I had created an Alexa skill that did nothing but looked for a word like funny, sad, boring in a sentence and told you something that would swing your mood the other way. All in all, it was a pretty basic thing. Compared to what my fellow hackers had made, my hack was a Commodore 64 compared to their Titans. Nonetheless, I demoed.

My team and I demoing are toilet hack. Yes, you can be happy and laugh after close to 30 hours of no sleep. (Courtesy: Major League Hacking)
My team and I demoing our toilet hack. Yes, you can be happy and laugh after close to 30 hours of no sleep. (Courtesy: Major League Hacking)

Since then, demoing has become my favourite part of the hackathon, it helps build character, especially when something doesn’t work as intended. Plus you get really cool hexagonal stickers that make a cool honeycomb on your laptop.

7. Have fun!

The jubilant HackSoc Manchester team at HackKings (Courtesy: Major League Hacking)
The jubilant HackSoc team at HackKings (Courtesy: Major League Hacking)

As a first year student, with practically no programming experience, hackathons can indeed seem really daunting. In all the frenzy surrounding the features to create, frameworks to learn, food to gobble, swag to pick up, one actually forgets about having fun. My fondest memories of hackathons have been where I have not been too serious, engaging in banter with my other hackers, getting Alexa to play Tunak Tunak at 12 in the morning or going out for impromptu walks in an amazing new city.

Panorama of Glasgow from the Necropolis
Panorama of Glasgow from the Necropolis


With all that said, stop reading this!!! Go sign up for your first hackathon on (they really didn’t pay me to write this). A world of Node.js, Alexas, Red Bull, Sponsor Memorabilia and infinite fun awaits you! 😉

Happy Hacking.

Namaste, Manchester.

I hate clichés, I prefer to avoid them like the plague. However, I do not want to treat starting a blog as an NP complete problem and that’s why, I chose to resort to a known solution.

>> print (“Hello, world!”)

Slightly relevant XKCD comic

With that out of the way, here are a few bytes about me:

“All my details can be found here ->

(How I wish I could achieve that sort of memory optimisation for a few of my course units!)

Anyway, on to the more important things…

Firstly, how and why I ended up here in Manchester.

Truth be told, Manchester wasn’t actually my top choice at first, but when the list was whittled down to three, Manchester United certainly helped swing the gauntlet!


Moreover, its a university with a rich heritage, it has an entire degree programme option dedicated to the study of Artificial Intelligence and a lot of exciting research being undertaken. The city isn’t overwhelming (looking at you, London!) and has a lot of startup energy. Also the student community here in the CS school is very inclusive, hacker types who know how to have great fun.

The second important thing to tell you is what I intend to use this blog for.

  1. By letting me write this, I obviously owe the university some gratitude and naturally, I’ll be writing about things such as what it’s like to study here and what it’s like to be an international student at Manchester. I’ll also be honest about the things that I think could be better.
  2. Chronicling my time here – when I first got here, I thought about maintaining a journal, and I even got a fancy notebook for it! Alas, I couldn’t stick to it, however, this blog should drill some discipline into me on that front.
  3. Occasional discussion about studying in the UK given the economic and political situation. As an international student, it was one of my primary concerns about coming here and now I can hopefully impart some information about why it’s not such a bad idea after all!
  4. Data science projects. Every week, I try to take a dataset and derive some compelling insight from it. Now I have a platform to share some really good ones.
  5. Hackathons. Hackathons are my default weekend setting. Plus it’s a great way to travel the country, meet new people and build cool stuff (more on this next time).

Now, I must get back to my team (you guessed it, at a hackathon 😉 ) who have been giving me the glare as I have been yanking away at my keyboard and not writing anything that compiles to machine code.

Until next time!