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First Day at FiveAI

less than 1 minute read

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The building is so cool! And so are all the people. So I begin my first internship at a tech company here in Cambridge working with the computer vision research team. Getting familiar with their code base, and working on a simple issue on my own, I begin a new page in my life. Read more

How I learnt a bit of Machine Learning

2 minute read

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Machine Learning (ML) is something really hot these days and thousands are learning it. Day by day it’s becoming easier to run implementations using APIs with little knowledge. Learning ML includes three things: understanding the mathematics behind algorithms & optimizations, coding out simple, efficient implementations, and getting familiar with the most common ML libraries and platforms. I started off following the Machine Learning MOOC by Andrew Ng on Coursera. This gives a good introduction to machine learning (https://www.coursera.org/learn/machine-learning/home/welcome). This doesn’t really require a lot of mathematical knowledge. It is a beginner’s course. It uses MATLAB. I suggest running through this course as fast as you can. Just get an overall understanding about the stuff. Try to apply these in some projects you’re working on. At the same time, I set up Python with Spyder (my favourite IDE on Windows) along with Tensorflow, Keras, and a few other ML libraries (this can be time-consuming if you’re not familiar). However, I started off running most of the algorithms I learnt using Numpy in Python (so I had to code everything from scratch). This gives a good grasp over the basic concepts. I also looked at a few implementations on this site: http://deeplearning.net/tutorial/. I tried implementing them from scratch (mostly non-deep learning algorithms: the traditional ML ones). Afterwards I looked at the Deep Learning Specialization on Coursera offered by the same Professor (https://www.coursera.org/specializations/deep-learning). This explores Deep Learning, which is one of the hottest areas in ML these days. It gives you a good understanding of how to implement the work you do in both Numpy, and Tensorflow.  This will take some time, and you should definitely begin a project on your own while doing this where you will apply these things. Also I read up on a bit of Linear Algebra: about Eigen Values, Matrix Decompositions, Subspaces, etc. This helps us get a good understanding of some of the concepts behind these areas. You will need to decide what you want to work on: pure research or innovating applications. For pure ML research, a strong mathematical understanding of concepts will be essential. Even for applications, this will be useful, but familiarity with implementations and optimizations will be a lot more useful.  Also, after you’re familiar with ML, you can spend some time every week reading a few top research papers in the area. Read more

Privilege

less than 1 minute read

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Early dawn watches one little girl from her cottage flee,
The morning birds chirping with her as she dances in glee,
Flowers every colour to that merry tune dance beside,
Flowers, flowers smiling to her she plucks in every stride.


Little mind of faith unscrupulous,
Embrace all colours so fabulous,
Red and white and purple and blue,
With her flowers to the shrine she flew.


Old flowers forgotten she clears away,
But the old and wise to her they say,
“Only white flowers so noble and pure”,
The rest in her pocket she hides secure.

<div class="MsoNormal">The little girl in stealth with a smile slowly steps inside,
A flower of each colour beneath the white she does hide,
The other coloured skinned flowers with her she takes outside,
With stretched arms those crushed flowers she lifts up to the skies,
As the winds devour those broken petals a little tear she cries. 
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Lost in Love

less than 1 minute read

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A world so bright with colours so vivid,
And winds of scent that never stay placid,
To a world fresh filled with much delight,
A butterfly young begins its graceful flight.

The glorious, majestic, and glamorous sun,
He falls for none but that fierce one,
His wings do feel those scorching rays of hers,
But love is madness, one deceiving curse.

And of course a wade through pools of moonlight,
Amidst the soothing air she brings with night,
Wash away those burns leaving little behind,
Yet unseen is the moon to his lost mind.

The butterfly too begins to roam in despair,
Soon amused by flowers, fleeting yet so fair,
The moon he misses, so soothing and kind,
But she’s no sun, he must leave both behind,
The flowers it is, he makes up his mind,
Drunk on their nectar he lives happy but blind. 
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Glory of Lies

less than 1 minute read

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Legend upon legend so courageous, brave and bold,
Adorn those books of history, their names are written in gold,
Henry the Conqueror and the valiant Alexander,
Oh glamorous warriors! Could it get any better?

The trumpets blow in all majesty and galore,
Handsome men in red march straight to the fore,
Poet and bard alike weave history from their homes,
Ah glamorous war! Who really began these norms?

Brother murdering brother and guns slaughtering hundreds,
Even those warriors with swords slayed their own kindreds,
The names of glorious warriors were writ not in shining gold,
Those letters were drawn from blood of men who passed untold.

Time to admire the glamour of war many great men had found,
Of glorious slaughter houses though no one spoke out aloud,
The killing fields see men being murdered in worse a way,
But what of all that glory? Alas! There never was such a day.

Cruel, callous and evil is all there is to war,
Innocent men dying for others’ problems is all the world saw,
Someone’s petty greed or hatred always begins it all,
And nothing good that came of war does anyone ever recall. 
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The Birdling

1 minute read

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Winds of morn ruffle all leaves around,
The nest awakes by that shuffling sound,
Spears of sunlight tear apart the green,
Endless skies around so much they mean.
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Chasing the Light

1 minute read

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Walking down one empty lonely lane,
Smiling up at that desolate lovely dame,
Who in all her pride and glamour,
Glimmers from above oh magical stunner,
Alone yet queen of heavens above,
Make mine the moon forever I vow.

But in that dark and lonely lane,
Lies just misery and none to gain,
The glimmer above sometimes adds light,
Helps relieve and keep up that weary fight,
Or so I think as I walk in the dark,
Always that lane as gloomy do I mark.

Through shadows of trees the fireflies' glint,
Blinking at me but alas they are so faint,
I smile at one ah the gorgeous creature,
Flies to me but seems too miniature,
Yet those giant trees sway in delight,
Adorned in jewels those fireflies' light.

The chill of night the strong winds bring,
The leaves around a happy tune they sing,
The lissom fields of paddy all dance along,
Puppets of wind they swing to its song,
Amused by all I begin to ponder in the darkness of night,
Is it only the paddy that swings with the wind's might.
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New Year

less than 1 minute read

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Another year is gone with many a merry,
Days and nights embedded deep in memory,
Colourful days with many an amazing friend,
All good things must come to an end,
Yet what’s gone’s not to fret and cry,
But to learn your faults to stand up high.

Another year is gone but another comes ahead,

Filled with mystery and days unknown instead,
May be joy may be pains the coming year,
Be made of, but it’s not for us to fear,
All one needs is friends in life to love and cheer,
Let me wish you and all have a  happy new year! Read more

Acta est Fabula, Plaudite!

1 minute read

Published:

Even the glamour of gold with time begins to fade away, 
Its splendour and gleam diminishes sadly day by day,
The golden treasure of opulence and majesty that we define,
As College, the heart of our lives that is to us so divine,
Has the worst of all adversities on it reclining,
Like all other, College too in many ways is declining.

Standing against an eternal truth: this descent inevitable,
Lies almost outside the realms that we know as possible,
Yet there is one unique force striving to accomplish,
The noble task of preserving College; that coveted wish,
The Council of esteem that guards with care this glory and pride,
Day and night to achieve this worthy goal takes many a stride.

An year of striving to give life to the traditions that may have been,
Lost if not for the onerous efforts, commitment, dedication so keen,
That they portrayed in all their work to the highest vertex,
Sacrifices they made in the name of College pile up to an apex,
A strenuous but worthwhile year of panache and flamboyance,
Has come to an end revealing Royal spirit’s true essence.

Wonders and magic have been performed within one year,
The success is evident in each magnificent endeavour,
Uplifting the honour of college in every single avenue,
The dying lore from bygone times they knew to renew;
And even for the plain student the pillar of strength stood still,
Sheltering from every problem, the pupils with joy they did fill.

All good times must meet their ends someday and so must all of this,
Ends now an year of wondrous memories that to College was indeed bliss,
The Council with all their lives the legacy of College secured undiminished,
The heart of College for us to guard and protect they have relinquished,
Gratitude for the fame and glory they brought in our hearts are indelibly written,
The debts they repaid and the honour they rebuild shall never be forgotten.

Farewell to them, the great men who led this legacy for yet another year,
The treasure bestowed on us shall be guarded with life and blood, do not fear.


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Let it live on

1 minute read

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Legend upon legend born within her halls,
A legacy lies beneath those ancient walls,
A journey through time of glory and pride,
A home like no other those golden walls hide.

The school that nurtured youths to be fair men,
Men of virtue, men of success time and time again,
Taught of not just books to make dull pedants,
But of all one needs to make apt students,
To think to speak to play to win to lose,
To command to rise and to live by life’s rules.

The college so great for many a year did last,
Not a scar in its prowess just growth so vast,
Only stood thus with the care of its sons,
Its glory preserved by endless dedicated ones,
Who laid down all in the name of College,                                  
Died a hundred times to guard her esteemed prestige.

The precious treasure has been bestowed on us today,
Take all from her and grow and rise we may,
But give her back to make her live another day,
The great school for years more with not a loss must stay.

Her history is writ in gold but the future we must write,
The duty lies on each to take her to a greater height,
And unless it’s fulfilled to the best college may slowly fall apart,
Its traditions its nurturing its spirit shall soon from us depart.

The least any and all should always strive to do,
Is put discipline and good manner to the very fore,
The worthy gentleman is of much more honour,
For no good is the corrupt man void of manner.

And of course excellence in everything we do,
Will always keep high the flag of gold and blue,
To win with honour to shine college’s name,
Is the best to do to guard that pride and fame,
Never the mediocre but perfect in every possible way,
Do live up to the golden words Disce aut Discede.
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Bueno Santa Marta

2 minute read

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Uno, dos, tres……

Counting in Spanish for the first time in my life was perhaps the least significant happening during my tour in Latin American Colombia for IMO 2013. Over one day of flights all the way to the other end of the world left our team of seven (with deputy leader) totally exhausted. We were staying at a lovely beach resort. Despite the exhaustion we had explored half the resort in a couple of hours.

The first few days were quite intense as we kept thinking of the exam whilst doing those last minute preparations. Nothing that significant happened apart from some vain attempts to communicate with the hotel staff who had miserable English.

It was finally day one. My first time at an IMO. I managed to get through the first question pretty fast. The second turned out to be difficult. I didn’t really try the third after finding it completely out of my bounds. I got back to the second and spent the remaining time trying to figure out what I could. Although I was quite passionate about mathematics I was a beginner and I realized what little knowledge I had after discussing the paper with others around.

Day two was bad. I was stuck in the first question. After an hour or so I switched over to the second. No clue there either. The third was pretty much the same; or even worse. I went back to the first and kept working on it to get through somewhere. At last time was up. I walked off feeling neither happy nor sad.

Soon the fun element of our tour to this Caribbean beach resort kicked off. Some crazy out of the world adventures we had and some unique individuals we met are memories I still cherish. Pushing each other into the pool early morning and trying out those funny looking dishes for lunch (turned out to be super tasty) and beach volleyball and dancing along the sand all evening were indeed joyful.

Soon the last day arrived and the time for the award ceremony came up. Our team mate winning a bronze medal was the highlight of the evening for us. I was delighted to discover that I had been placed among the top 300 in the world. It was definitely one delightful day for everyone.

As the say all good things must meet their ends. The tour wrapped up as we headed for the airport grumbling a bit as the thought of the over 24 hours of flying time before us crossed our minds. But it was difficult to keep that laughter of gaiety off for long. Thus we bid farewell to that memorable city of wonders, each of us taking home memories that were to last a lifetime.

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portfolio

Action Recognition in Videos

The project focused on researching on action recognition in videos. We explored individual contribution of static and motion domain information for action recognition and succeeded in establishing the presence of optimal contribution ratios. Using Cholesky transformations based control of correlation to parents of fused feature vectors, we managed to experimentally validate our findings. Additionally, we explored the role of underlying temporal trends of video sub-events in recognizing compound actions. Tasked with modelling that temporal trend, individually I experimented with recurrent neural networks (RNNs) considering their greater representation capacity, and established their optimality over traditional techniques for our use case of modelling temporally evolving feature vectors. This work resulted in two peer-reviewed publications at DICTA 2017 and TCSVT 2019. Code for the RNN component of this system is available here. Read more

Automated Plant Leaf Disease Detection

Designing a plant disease detection system aimed at helping small-scale cultivators and home gardeners. In collaboration with a plant virus indexing centre, we were able to tested our product closely with a number of selected cultivators. We focussed on utilizing multi-spectral image feeds (NIR/RGB spectra) and implementing transfer learning based training of CNNs on small datasets of domain-specific images. The product was deployed using a mobile app with edge inference and recognized as a Top Initiative at National Tech Awards. Initial versions of the product were also developed as a raspberry-pi based system and later an FPGA based system. Code for the raspberry-pi based system is hosted here.

im01 im02 im03
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Multi Object Tracking

Research on combining Siamese Trackers and recurrent neural networks (LSTM) to simultaneously exploit appearance and spatial information for multi-object tracking, developing unique approach for occlusion aware object tracking, and analyzing effectiveness of BEV space projections for spatial tracking. Code for the this project is available here. An initial outline of the work done is present on arxiv here.


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Panoptic Segmentation

Research on panoptic segmentation using conditional random fields. Worked on development of a novel information fusion layer, for optimum combination of semantic and instance segmentation network outputs. Bipartite Conditional Random Fields (BCRF) uses an energy function containing cross-potential terms between the outputs of two parallel deep neural network heads to produce an optimal panoptic segmentaion condition on the original image. The BCRF layer uses a cross compatibility function between each pair of thing and stuff classes, which is completely learned using the data distribution. Our work was able to achieving state-of-the-art performance on selected popular datasets. The novel layer is also more interpretable and is inline with our intuition about compatibility between classes. Code for our work is hosted here. Our BMVC publication and oral presentation can be found here.


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publications

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post. Read more

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post. Read more