-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathUntitled
1542 lines (1386 loc) · 67.2 KB
/
Untitled
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
<!DOCTYPE HTML>
<html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<title>Ayaan Haque</title>
<meta name="author" content="Ayaan Haque">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta property="og:image" content="images/2022_circle_cropped_pfp.png" />
<link rel="stylesheet" type="text/css" href="stylesheet.css">
<link rel="stylesheet" type="text/css" href="alt.css">
<link rel="icon" type="image/png" href="images/2022_circle_cropped_pfp.png">
<script src="https://kit.fontawesome.com/dc4da0b3ff.js" crossorigin="anonymous"></script>
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/4.7.0/css/font-awesome.min.css">
<link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/jpswalsh/academicons@1/css/academicons.min.css">
<link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/devicons/devicon@v2.11.0/devicon.min.css">
<script src="https://code.iconify.design/1/1.0.7/iconify.min.js"></script>
</head>
<body id="home">
<!-- <header>
<nav>
<ul class="nav__links" style="list-style-type:none">
<li><a href="#home">Home</a></li>
<li><a href="#research">Research</a></li>
<li><a href="#service">Community Service</a></li>
<li><a href="#experience">Experience</a></li>
<li><a href="#activities">Activities</a></li>
<li><a href="#talks">Talks</a></li>
<li><a href="#projects">Projects</a></li>
<li><a href="#awards">Awards</a></li>
<li><a href="#writing">Writing</a></li>
<li><a href="#skills">Skills</a></li>
<li><a href="#socials">Socials</a></li>
</ul>
</nav>
</header> -->
<table style="width:100%;max-width:1000px;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;"><tbody>
<tr style="padding:0px">
<td style="padding:0px">
<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;"><tbody>
<tr style="padding:0px">
<td style="padding:2.5%;width:70%;vertical-align:middle">
<p style="text-align:center">
<name>Ayaan Haque</name>
</p>
<p>
Hi! I'm Ayaan Haque, a 20 y/o research scientist at <a href="https://lumalabs.ai/">Luma AI</a>. I'm also a student at <a href="https://eecs.berkeley.edu/">UC Berkeley</a> studying EECS, where I'm advised by <a href="https://people.eecs.berkeley.edu/~kanazawa/">Angjoo Kanazawa</a>.
I'm currently interested in training generative models. Recently, I worked on <a href="https://lumalabs.ai/genie">Genie</a>,
Luma's text to 3D foundation model which can generate high-fidelty 3D objects in seconds.
</p>
In the past, I've worked on self-supervised and unsupervised representation learning. I've previously interned at <a href="https://www.samsungsds.com/us/index.html">Samsung SDSA</a>, and got my research career jumpstarted back in high school with <a href="https://med.stanford.edu/wanggroup.html">Wang Group</a> at <a href="https://med.stanford.edu/rsl.html">Stanford</a>.
At Berkeley, I'm a part of <a href="https://ml.berkeley.edu/">Machine Learning @ Berkeley</a> and the <a href="https://docs.nerf.studio/">Nerfstudio</a> team.
</p>
<p>
In a past life, I was a builder and hacker (I'm a <a href="https://top.mlh.io/2021/profiles/ayaan-haque">MLH Top-50 Hacker!</a>), and now I'm exploring deep-tech startups. Other than that, I enjoy writing, watching/playing sports, eating out with friends,
and just having a good time. My ongoing goal and dream:
</p>
<p style="text-align:center">
<img src='images/inspirational-tweet.png' width="400">
</p>
<p style="text-align:center">
<a href="https://twitter.com/ayaanzhaque">Twitter</a>  / 
<a href="mailto:ayaanzhaque@berkeley.edu">Email</a>  / 
<a href="https://scholar.google.com/citations?user=OWDai70AAAAJ&hl=en">Google Scholar</a>  / 
<a href="https://github.com/ayaanzhaque/">Github</a>  / 
<!-- <a href="data/ayaan_haque_resume1_2023.pdf">Resume</a>  /  -->
<!-- <a href="https://ayaanzhaque.medium.com/">Medium</a>  /  -->
<!-- <a href="https://devpost.com/ayaanzhaque">Devpost</a>  /  -->
<a href="https://www.linkedin.com/in/ayaan-haque/">LinkedIn</a>
</p>
</td>
<td style="padding:2.5%;width:70%;max-width:70%">
<img style="width:100%;max-width:100%" alt="profile photo" src="images/2022_circle_cropped_pfp.png" class="hoverZoomLink">
<div style="text-align:center">
<i style="text-align:center">Learning about learning 💯</i>
</div>
</td>
</tr>
</tbody></table>
<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;" id="updates"><tbody>
<tr>
<td style="padding:20px;width:100%;vertical-align:middle">
<heading>Updates</heading>
<p>
<ul>
<li>
<b>[Jan 2024]</b> Joining <a href="https://lumalabs.ai/">Luma</a> (now a <a href="https://lumalabs.ai/series-b">Series B</a> company) full-time!
</li>
<li>
<b>[October 2023]</b> Gave <a href="https://youtu.be/4AOqcjH5_3U">oral talk</a> on Instruct-NeRF2NeRF at ICCV in Paris!
</li>
<li>
<b>[July 2023]</b> Instruct-NeRF2NeRF accepted to ICCV 2023 (Oral)!
</li>
<li>
<b>[May 2023]</b> Joining <a href="https://lumalabs.ai/">Luma AI</a>, a Series A startup building the future of 3D!
</li>
<li>
<b>[Mar 2023]</b> Released new pre-print <a href="https://instruct-nerf2nerf.github.io/">Instruct-NeRF2NeRF</a>!
</li>
<li>
<b>[August 2022]</b> Starting my undergrad at <a href="https://eecs.berkeley.edu/">UC Berkeley</a> to study EECS!
</li>
<!-- <li>
<b>[Nov 2022]</b> <a href="https://arxiv.org/abs/2208.04278">SSL-MeshCNN</a> accepted to <a href="https://aaai.org/Conferences/AAAI-23/">AAAI 2023</a>!
</li>
<li>
<b>[Sep 2022]</b> Joined <a href="https://ml.berkeley.edu/">Machine Learning @ Berkeley</a>!
</li>
<li>
<b>[Aug 2022]</b> Released new <a href="https://arxiv.org/abs/2208.04278">preprint</a> with Samsung on contrastive learning for mesh segmentation
</li>
<li>
<b>[June 2022]</b> Joining <a href="https://www.samsungsds.com/us/index.html">Samsung SDSA</a> as a Research Intern
</li>
<li>
<b>[April 2022]</b> Committed to <a href="https://eecs.berkeley.edu/">UC Berkeley</a> to study EECS! (First update)
</li> -->
</ul>
</p>
</td>
</tr>
</tbody></table>
<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;" id="research"><tbody>
<tr>
<td style="padding:20px;width:100%;vertical-align:middle">
<heading>Research</heading>
<p>
Since I've worked on a wide variety of topics (and am still exploring new topics), I've split my publications into currently relevant works and previous works.
<b>Only relevant works are listed below.</b> For a full list (and chronological list) of my papers,
visit my <a href="https://scholar.google.com/citations?user=OWDai70AAAAJ&hl=en">Google Scholar</a>.
</p>
</td>
</tr>
</tbody></table>
<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;"><tbody>
<tr onmouseout="nerfie_stop()" onmouseover="nerfie_start()">
<td style="padding:20px;width:30%;vertical-align:middle">
<div class="one">
<div class="two"><video width=220 muted autoplay loop>
<source src="images/in2n_animation.mp4" class='thumbnail' type="video/mp4">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://instruct-nerf2nerf.github.io/">
<papertitle>Instruct-NeRF2NeRF: Editing 3D Scenes with Instructions</papertitle>
</a>
<br>
<strong>Ayaan Haque</strong>,
<a href="https://www.matthewtancik.com/">Matthew Tancik</a>,
<a href="https://people.eecs.berkeley.edu/~efros/">Alexei A. Efros</a>,
<a href="https://holynski.org/">Aleksander Holynski</a>,
<a href="https://people.eecs.berkeley.edu/~kanazawa/">Angjoo Kanazawa</a>
<br>
UC Berkeley
<br>
<em><a href="https://iccv2023.thecvf.com/">ICCV</a></em>, 2023 <span style="color:red">(Oral Presentation)</span>
<br>
<a href="https://instruct-nerf2nerf.github.io/">Project Page</a> /
<a href="https://arxiv.org/abs/2303.12789">ArXiv</a> /
<a href="https://youtu.be/4AOqcjH5_3U">Oral</a> /
<a href="https://github.com/ayaanzhaque/instruct-nerf2nerf">Code</a>
<p></p>
<p>We propose a method for editing NeRF scenes with text-instructions. Given a NeRF of a scene and the collection
of images used to reconstruct it, our method uses an image-conditioned diffusion model (InstructPix2Pix) to
iteratively edit the input images while optimizing the underlying scene, resulting in an optimized 3D scene that
respects the edit instruction.
</p>
</td>
</tr>
<tr onmouseout="nerfie_stop()" onmouseover="nerfie_start()">
<td style="padding:20px;width:30%;vertical-align:middle">
<div class="one">
<img src='images/ssl-meshcnn.png' class = "thumbnail" width="220">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://arxiv.org/abs/2208.04278">
<papertitle>Self-Supervised Contrastive Representation Learning for 3D Mesh Segmentation</papertitle>
</a>
<br>
<strong>Ayaan Haque</strong>,
<a href="https://www.linkedin.com/in/hankyu-moon-b678b910">Hankyu Moon</a>,
<a href="https://www.linkedin.com/in/heng-hao-36a5b997">Heng Hao</a>,
<a href="https://scholar.google.com/citations?user=e7JYe3cAAAAJ&hl=en">Sima Didari</a>,
<a href="https://sites.google.com/site/jaeohwoo/">Jae Oh Woo</a>,
<a href="https://scholar.google.com/citations?hl=en&user=tpa6iwkAAAAJ&view_op=list_works">Patrick Bangert</a>
<br>
Samsung SDS Research America
<br>
<em><a href = "https://aaai.org/Conferences/AAAI-23/">AAAI</a></em>, 2023
<br>
<a href="https://arxiv.org/abs/2208.04278">ArXiv</a> /
<a href="data/SSL_MeshCNN_Poster.pdf">Poster</a>
<p></p>
<p>We introduce self-supervised MeshCNN, or SSL-MeshCNN, a novel mesh-specialized contrastive learning method to
perform downstream segmentation with limited-labeled data. We create an augmentation policy tailored for meshes,
enabling the network to learn efficient visual representations through contrastive pre-training.
</p>
</td>
</tr>
<tr onmouseout="nerfie_stop()" onmouseover="nerfie_start()">
<td style="padding:20px;width:30%;vertical-align:middle">
<div class="one">
<img src='images/sdcnl.png' class = "thumbnail" width="220">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://ayaanzhaque.github.io/SDCNL/">
<papertitle>Deep Learning for Suicide and Depression Identification with Unsupervised Label Correction</papertitle>
</a>
<br>
<strong>Ayaan Haque*</strong><sup>1</sup>,
<a href="https://github.com/viraajreddi">Viraaj Reddi</a>*<sup>1</sup>,
<a href="https://tylergiallanza.github.io/">Tyler Giallanza</a><sup>2</sup>
<br>
Saratoga High School<sup>1</sup>, Princeton University<sup>2</sup>
<br>
<em><a href = "https://e-nns.org/icann2021/">ICANN</a></em>, 2021
<br>
<a href="https://ayaanzhaque.github.io/SDCNL/">Project Page</a> /
<a href="https://arxiv.org/abs/2102.09427">ArXiv</a> /
<a href="https://www.youtube.com/watch?v=-JVbne534sQ">Teaser Video</a> /
<a href="data/SDCNL Poster.pdf">Poster</a> /
<a href="https://github.com/ayaanzhaque/SDCNL">Code</a> /
<a href="https://towardsdatascience.com/nlp-for-suicide-and-depression-identification-with-noisy-labels-98d7bb98f3e8?sk=43d9806e0975695c08e6b19ad36b3a9f">Blog</a>
<p></p>
<p>We propose SDCNL to address the unexplored problem of classifying between depression and more severe suicidal
tendencies using web-scraped data. Our method introduces a novel label correction
method to remove inherent noise in web-scraped data using unsupervised learning combined with a deep-learning classifier
based on pre-trained transformers.
</p>
</td>
</tr>
<tr onmouseout="nerfie_stop()" onmouseover="nerfie_start()">
<td style="padding:20px;width:30%;vertical-align:middle">
<div class="one">
<img src='images/multimix_diagram.png' class = "thumbnail" width="220">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://ayaanzhaque.github.io/MultiMix/">
<papertitle>MultiMix: Sparingly Supervised, Extreme Multitask Learning From Medical Images</papertitle>
</a>
<br>
<strong>Ayaan Haque*</strong><sup>1</sup>,
<a href="https://aaz-imran.github.io/">Abdullah-Al-Zubaer Imran</a>*<sup>2,3</sup>,
<a href="https://profiles.stanford.edu/adamwang">Adam Wang</a><sup>2</sup>,
<a href="http://web.cs.ucla.edu/~dt/">Demetri Terzopoulos</a><sup>3,4</sup>
<br>
Saratoga High School<sup>1</sup>, Stanford University<sup>2</sup>, University of California, Los Angeles<sup>3</sup>, VoxelCloud Inc.<sup>4</sup>
<br>
<em><a href = "https://biomedicalimaging.org/2021/">IEEE ISBI</a></em>, 2021
<br>
<a href="https://ayaanzhaque.github.io/MultiMix/">Project Page</a> /
<a href="https://arxiv.org/abs/2010.14731">ArXiv</a> /
<a href="data/ISBI2021_Poster.pdf">Poster</a> /
<a href="data/MultiMix Stanford Template.pptx.pdf">Presentation</a> /
<a href="https://github.com/ayaanzhaque/MultiMix">Code</a> /
<a href="https://towardsdatascience.com/consistent-semi-supervised-explainable-multi-tasking-for-medical-imaging-aa96abbb3b07?sk=b8f60f02ef17f098dff8d96fa1ce3096">Blog</a>
<p></p>
<p>We introduce MultiMix, a joint semi-supervised classification and segmentation model
employing a confidence-based augmentation strategy for semi-supervised classification
along with a novel saliency bridge module that guides segmentation and provides explainability
for the joint tasks.
</p>
</td>
</tr>
<tr onmouseout="nerfie_stop()" onmouseover="nerfie_start()">
<td style="padding:20px;width:30%;vertical-align:middle">
<div class="one">
<img src='images/ECGAN.png' class = "thumbnail" width="220">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://ayaanzhaque.github.io/EC-GAN/">
<papertitle>EC-GAN: Low-Sample Classification using Semi-Supervised Algorithms and GANs</papertitle>
</a>
<br>
<strong>Ayaan Haque</strong>
<br>
Saratoga High School
<br>
<em><a href = "https://aaai.org/Conferences/AAAI-2">AAAI</a></em>, 2021 <span style="color:red">(Best Student Abstract Finalist, Oral Presentation)</span>
<br>
<a href="https://ayaanzhaque.github.io/EC-GAN/">Project Page</a> /
<a href="https://arxiv.org/abs/2012.15864">ArXiv</a> /
<a href="https://slideslive.com/38951242/ecgan-lowsample-classification-using-semisupervised-algorithms-and-gans?ref=account-83491-history">Oral</a> /
<a href="data/ec_gan_poster.pdf">Poster</a> /
<a href="data/ec_gan_presentation.pdf">Presentation</a> /
<a href="https://github.com/ayaanzhaque/EC-GAN">Code</a> /
<a href="https://towardsdatascience.com/artificial-data-for-image-classification-5b2ede40640f?sk=173ee5ca1849a81af7f4a58b4dd91c99">Blog</a>
<p></p>
<p>We propose EC-GAN, which combines a Generative Adversarial Network with a classifier to leverage artifical GAN
generations to increase the size of restricted, fully-supervised datasets using semi-supervised algorithms.
Mentored by Microsoft Postdoc and Princeton University PhD <a href = "http://www.jordantash.com/">Jordan T. Ash.</a>
</p>
</td>
</tr>
</tbody></table>
<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;" id="future-research"><tbody>
<tr>
<td style="padding:20px;width:100%;vertical-align:middle">
<subheading>Previous Research</subheading>
</td>
</tr>
</tbody></table>
<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;"><tbody>
<tr onmouseout="nerfie_stop()" onmouseover="nerfie_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/sspwam.jpg' class = "thumbnail" width="220">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://ayaanzhaque.github.io/Noise2Quality/">
<papertitle>Noise2Quality: Non-Reference, Pixel-Wise Assessment of Low Dose CT Image Quality</papertitle>
</a>
<br>
<strong>Ayaan Haque</strong><sup>1, 2</sup>,
<a href="https://profiles.stanford.edu/adamwang">Adam Wang</a><sup>2</sup>,
<a href="https://aaz-imran.github.io/">Abdullah-Al-Zubaer Imran</a><sup>2</sup>
<br>
Saratoga High School<sup>1</sup>, Stanford University<sup>2</sup>
<br>
<em><a href = "https://spie.org/conferences-and-exhibitions/medical-imaging">SPIE Medical Imaging (SPIE)</a>, 2022</em>
<br>
<a href="https://ayaanzhaque.github.io/Noise2Quality/">Project Page</a> /
<a href="https://spie.org/medical-imaging/presentation/Noise2Quality--non-Reference-pixel-wise-assessment-of-low-dose/12035-55?SSO=1">Paper</a> /
<a href="/data/SPIE Teaser Presentation.pptx.pdf">Presentation</a> /
<a href="/data/SPIE Poster.pptx.pdf">Poster</a> /
<a href="https://github.com/ayaanzhaque/Noise2Quality">Code</a>
<p></p>
<p>We propose Noise2Quality (N2Q), a novel, self-supervised IQA model which predicts SSIM Image Quality maps from
low-dose CT. We propose a self-supervised regularization task of dose-level estimation creating a
multi-tasking framework to improve performance.
</p>
</td>
</tr>
<tr onmouseout="nerfie_stop()" onmouseover="nerfie_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/sswl-idn.png' class = "thumbnail" width="220">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://ayaanzhaque.github.io/SSWL-IDN/">
<papertitle>Window Level is a Strong Denoising Surrogate</papertitle>
</a>
<br>
<strong>Ayaan Haque</strong><sup>1, 2</sup>,
<a href="https://profiles.stanford.edu/adamwang">Adam Wang</a><sup>2</sup>,
<a href="https://aaz-imran.github.io/">Abdullah-Al-Zubaer Imran</a><sup>2</sup>
<br>
Saratoga High School<sup>1</sup>, Stanford University<sup>2</sup>
<br>
<em><a href = "https://miccai2021.org/">MICCAI MLMI</a>, 2021</em>
<br>
<a href="https://ayaanzhaque.github.io/SSWL-IDN/">Project Page</a> /
<a href="https://arxiv.org/abs/2105.07153">ArXiv</a> /
<a href="data/MLMI Poster Final.pptx.pdf">Poster</a> /
<a href="https://github.com/ayaanzhaque/SSWL-IDN">Code</a> /
<a href="https://towardsdatascience.com/sswl-idn-self-supervised-ct-denoising-208fde94583e?sk=b450af4d2a8ee8c4eeed9f42041f9b0f">Blog</a>
<p></p>
<p>We introduce SSWL-IDN, a novel self-supervised CT denoising window-level prediction surrogate task. Our method is task-relevant
and related to the downstream task, yielding improved performance over recent methods.
</p>
</td>
</tr>
<tr onmouseout="nerfie_stop()" onmouseover="nerfie_start()">
<td style="padding:20px;width:30%;vertical-align:middle">
<div class="one">
<img src='images/multimix_journal_diagram.jpg' class = "thumbnail" width="220">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://ayaanzhaque.github.io/MultiMix/">
<papertitle>Generalized Multi-Task Learning from Substantially Unlabeled Multi-Source Medical Image Data</papertitle>
</a>
<br>
<strong>Ayaan Haque</strong><sup>1, 2</sup>,
<a href="https://aaz-imran.github.io/">Abdullah-Al-Zubaer Imran</a><sup>2,3</sup>,
<a href="https://profiles.stanford.edu/adamwang">Adam Wang</a><sup>2</sup>,
<a href="http://web.cs.ucla.edu/~dt/">Demetri Terzopoulos</a><sup>3,4</sup>
<br>
Saratoga High School<sup>1</sup>, Stanford University<sup>2</sup>, University of California, Los Angeles<sup>3</sup>, VoxelCloud Inc.<sup>4</sup>
<br>
<em><a href = "https://www.melba-journal.org/">MELBA</a></em>, 2021
<br>
<a href="https://ayaanzhaque.github.io/MultiMix/">Project Page</a> /
<a href="https://www.melba-journal.org/papers/2021:011.html">Journal Page</a> /
<a href="https://arxiv.org/abs/2110.13185">Paper</a> /
<a href="https://github.com/ayaanzhaque/MultiMix">Code</a>
<p></p>
<p>We expand upon MultiMix (in ISBI 2021). Our extended manuscript contains a detailed
explanation of the methods, saliency map visualizations from multiple datasets, and
quantitative (performance metrics tables) and qualitative (mask predictions, Bland
Altman plots, ROC curves, consistency plots).
</p>
</td>
</tr>
<!-- <tr onmouseout="nerfie_stop()" onmouseover="nerfie_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/3N-GAN.jpg' class = "thumbnail" width="220">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://arxiv.org/abs/2109.13862">
<papertitle>3N-GAN: Semi-Supervised Classification of X-Ray Images with a 3-Player Adversarial Framework</papertitle>
</a>
<br>
Shafin Haque*,
<strong>Ayaan Haque*</strong>
<br>
Saratoga High School
<br>
<em><a href = "">ArXiv</a></em>, 2021
<br>
<a href="https://arxiv.org/abs/2109.13862">ArXiv</a> /
<a href="https://github.com/ayaanzhaque/3N-GAN">Code</a>
<p></p>
<p>We propose 3N-GAN, or 3 Network Generative Adversarial Networks, to perform semi-supervised
classification of medical images in fully-supervised settings. We incorporate a classifier
into the adversarial relationship such that the generator trains adversarially against both
the classifier and discriminator. <b>(Authors contributed equally)</b>
</a>
</p>
</td>
</tr>
<tr onmouseout="nerfie_stop()" onmouseover="nerfie_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/convolutionalnets.png' class = "thumbnail" width="220">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://arxiv.org/abs/2108.04358">
<papertitle>Convolutional Nets for Diabetic Retinopathy Screening in Bangladeshi Patients</papertitle>
</a>
<br>
<strong>Ayaan Haque</strong><sup>1,2</sup>
<a href="">Ipsita Sutradhar</a><sup>2</sup>,
<a href="">Mahziba Rahman</a><sup>2</sup>,
<a href="">Mehedi Hasan</a><sup>2</sup>,
<a href="">Malabika Sarker</a><sup>2</sup>
<br>
Saratoga High School<sup>1</sup>,
BRAC University School of Public Health<sup>2</sup>
<br>
<em><a href = "https://arxiv.org/abs/2108.04358">ArXiv</a></em>, 2021
<br>
<a href="https://arxiv.org/abs/2108.04358">ArXiv</a> /
<a href="https://github.com/Drishti-BD/Drishti-CNN">Code</a> /
<a href="https://github.com/Drishti-BD/Drishti-CAD">CAD Designs</a> /
<a href="https://drishtiai.org/">Application (Drishti)</a>
<p></p>
<p>This paper presents specifications on the deep learning model implemented in <a href="https://drishtiai.org/">Drishti</a>. The paper outlines the process
of performing deep learning classication of diabetic retinopathy and contains extensive evaluation of the method
on real fundus images collected from the Bangladesh Eye Hospital and BRAC University.
</p>
</td>
</tr> -->
<!-- <tr onmouseout="nerfie_stop()" onmouseover="nerfie_start()">
<td style="padding:20px;width:30%;vertical-align:middle">
<div class="one">
<img src='images/roboticspaper.png' class = "thumbnail" width="220">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://ayaanzhaque.github.io/FCE-NN">
<papertitle>Simulated Data Generation Through Algorithmic Force Coefficient Estimation for AI-Based Robotic Projectile Launch Modeling</papertitle>
</a>
<br>
<a href="http://sajivshah.me/">Sajiv Shah</a>*<sup>1</sup>,
<strong>Ayaan Haque*</strong><sup>1</sup>,
<a href="https://www.ucsdarclab.com/people">Fei Liu</a><sup>2</sup>
<br>
Saratoga High School<sup>1</sup>, University of California, San Diego<sup>2</sup>
<br>
<em><a href = "http://www.acirs.org/">IEEE ACIRS</a></em>, 2021 <span style="color:red">(Best Presentation, Oral Presentation)</span>
<br>
<a href="https://ayaanzhaque.github.io/FCE-NN">Project Page</a> /
<a href="https://arxiv.org/abs/2105.12833">ArXiv</a> /
<a href="https://youtu.be/rkAp8RS7gqc">Oral</a> /
<a href="data/FCE-NN Presentation.pdf">Presentation</a> /
<a href="data/FCE-NN Poster.pdf">Poster</a> /
<a href="https://github.com/ayaanzhaque/FCE-NN">Code</a> /
<a href="https://towardsdatascience.com/deep-learning-for-projectile-trajectory-modeling-fb6380e06b8f?sk=e61aa8399c1fd64dcb9b7bc6591ef5d8">Blog</a>
<p></p>
<p>We propose FCE-NN, a novel method of modeling robotic launching of non-rigid objects using neural networks which are trained
with supplemental simulated data, generated from algorithmic force coefficient estimation.
</p>
</td>
</tr> -->
</tbody></table>
<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;" id="experience"><tbody>
<tr>
<td style="padding:20px;width:100%;vertical-align:middle">
<heading>Experience</heading>
</td>
</tr>
</tbody></table>
<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;"><tbody>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/luma.jpeg' class = "thumbnail" width="180">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://lumalabs.ai/">
<papertitle>Research Scientist at Luma AI</papertitle>
</a>
<br>
<span id="left">Palo Alto, CA</span>
<span id="right">May 2023 - Present</span>
<br>
<p>
<ul>
<li>Generative AI startup building the future of visual AI, raised <a href="https://lumalabs.ai/series-b">$43 million Series B</a></li>
<li>Released <a href="https://lumalabs.ai/genie">Genie</a>, a text to 3D foundation model which can generate high-fidelty 3D objects in seconds</li>
</ul>
</p>
</td>
</tr>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/bair.png' class = "thumbnail" width="180">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://people.eecs.berkeley.edu/~kanazawa/">
<papertitle>Research Intern at Berkeley AI Research (BAIR)</papertitle>
</a>
<br>
<span id="left">Kanazawa AI Lab (KAIR), Berkeley, CA</span>
<span id="right">Dec 2022 - Present</span>
<br>
<p>
<ul>
<li>Working on NeRFs and diffusion models</li>
</ul>
</p>
</td>
</tr>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/samsung.jpeg' class = "thumbnail" width="180">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://www.samsungsds.com/us/index.html">
<papertitle>Research Intern at Samsung SDSA</papertitle>
</a>
<br>
<span id="left">AI Research Group, San Jose, CA</span>
<span id="right">June 2022 - September 2022</span>
<br>
<p>
<ul>
<li>Proposed "SSL-MeshCNN", a novel self-supervised algorithm for segmenting non-uniform, irregular 3D meshes</li>
<li>Introduced new SimCLR-inspired stochastic augmentation policy for mesh-specialized contrastive learning</li>
<li>Matched accuracy of fully-supervised training (90.50%) with just 67% of labels on benchmark datasets</li>
<li>Wrote paper accepted to <a href="https://aaai.org/Conferences/AAAI-23/">AAAI 2023</a>, available on <a href="https://arxiv.org/abs/2208.04278">ArXiv</a></li>
</ul>
</p>
</td>
</tr>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/wanggroup.png' class = "thumbnail" width="180">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://med.stanford.edu/wanggroup/people.html">
<papertitle>Research Intern at Stanford</papertitle>
</a>
<br>
<span id="left">Wang Group in RSL, Stanford, CA</span>
<span id="right">July 2020 - June 2022</span>
<br>
<p>
<ul>
<li>Worked on learning from limited labeled data for clinical imaging tasks using unsupervised, self-supervised, and semi-supervised techniques</li>
<li>Developed research skills by running hundreds of experiments, writing papers, preparing supplementals, and writing rebuttals</li>
</ul>
</p>
</td>
</tr>
<!-- <tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/reu.png' class = "thumbnail" width="180">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://med.stanford.edu/wanggroup/people.html">
<papertitle>Research Intern in REU Program at Stanford's RSL</papertitle>
</a>
<br>
<span id="left">RSL @ Stanford, Stanford, CA</span>
<span id="right">June 2021 - August 2021</span>
<br>
<p>
<ul>
<li>Participated in Stanford's Radiological Sciences Lab Research Experience for Undergraduates (REU) summer program</li>
<li>Attended talks and lectures with fellow undergraduate researchers, only high schooler in the program</li>
<li>Attended group meetings with Wang Group</li>
</ul>
</p>
</td>
</tr> -->
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/ow.jpg' class = "thumbnail" width="180">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://openwater.vc/">
<papertitle>Software Engineering Intern at Openwater Accelerator</papertitle>
</a>
<br>
<span id="left">Internal SWE Team, Menlo Park, CA</span>
<span id="right">August 2020 - December 2020</span>
<br>
<p>
<ul>
<li>Accelerator providing early-stage startups with software and human capital instead of direct funding (closed as of late 2021)</li>
<li>Developing a Waitlist API which is to be sold to porfolio companies in the program, where companies can establish
waitlists for their products to build a market</li>
<li>Using React.js, MongoDB, Flask and other web dev/backend tech, integrating Stripe payment features and referral features, writing documentation</li>
</ul>
</p>
</td>
</tr>
<!-- <tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/tdslogo.jpeg' class = "thumbnail" width="180">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://ayaanzhaque.medium.com/">
<papertitle>Content Writer for Towards Data Science</papertitle>
</a>
<br>
<span id="left">Medium</span>
<span id="right">June 2020 - Present</span>
<br>
<p>
<ul>
<li> Writer on Medium for multiple publications: <a href="https://towardsdatascience.com/">Towards Data Science</a> (Primary, 577k, top publication), <a href="https://betterprogramming.pub/">Better Programming</a>
(154k), <a href="https://codeburst.io/">Codeburst</a> (100k), <a href="https://pub.towardsai.net/">TowardsAI</a> (22k), and more</li>
<li>4x Editor’s Pick on TDS, chosen for Hands on Tutorial and Thoughts and Theory Column, Featured on Medium home page twice, 21.6k+ total
views, 3800+ likes</li>
<li>Wrote articles about AI/CS topics, activities and projects, and tips and advice</li>
</ul>
</p>
</td>
</tr> -->
</tbody></table>
<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;" id="activities"><tbody>
<tr>
<td style="padding:20px;width:100%;vertical-align:middle">
<heading>Activities</heading>
<p>
Outside of research, I enjoy building practical applications in both competitive and casual formats.
</p>
</td>
</tr>
</tbody></table>
<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;"><tbody>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/hacksquad.png' class = "thumbnail" width="180">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://github.com/ayaanzhaque/">
<papertitle>Hackathons</papertitle>
</a>
<br>
<span id="left">Team Captain</span>
<span id="right">May 2019 - June 2022</span>
<br>
<p>
<ul>
<li>Team Captain of 5 total members (shoutout Viraaj, Adithya, Ishaan, and Sajiv)</li>
<li>Created numerous projects (listed in <a href="#projects">Projects</a> section)</li>
<li>🏆 33x Award Winner, 9x First Place, 22x Top 3, $10,000+ in earnings</li>
<li>Chosen for <a href="https://top.mlh.io/2021/profiles/ayaan-haque">MLH Top 50 Hackers Class of 2021</a>, one of five high schoolers</li>
</ul>
</p>
</td>
</tr>
<tr>
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/mset.png' class = "thumbnail" width="180">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://msetfish.weebly.com/">
<papertitle>MSET Robotics Team 649</papertitle>
</a>
<br>
<span id="left">Software Team</span>
<span id="right">August 2018 - April 2021</span>
<br>
<p>
<ul>
<li>FRC Robotics Software Team, ML-Specialist (FTC Captain 9th Grade)</li>
<li>Worked with AI/ML for in-game object detection and using predictive models for shot selection, work on shooter
trajectory modeling, write documentation</li>
<li>🏆 2021 Skills Competition Finalist in Carbon Group 🏆 2021 Engineering Excellence Award 🏆 CalGames 2019 Finalist 🏆 ChezyChamps 2019 Semi-Finalist</li>
</ul>
</p>
</td>
</tr>
</tbody></table>
<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;" id="projects"><tbody>
<tr>
<td style="padding:20px;width:100%;vertical-align:middle">
<heading>Projects</heading>
<p>
I've just listed a few of my favorite projects, and the remaining are available on my <a href="https://github.com/ayaanzhaque">Github</a>. On Github, I have 500+ commits and ~300 stars across all my repositories.
Check out this cool commit <a href="https://skyline.github.com/ayaanzhaque/2021">graph</a>, and check this out for my Github <a href="https://github.com/ayaanzhaque/ayaanzhaque">stats</a>.
</p>
</td>
</tr>
</tbody></table>
<table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;"><tbody>
<tr onmouseout="nerfie_stop()" onmouseover="nerfie_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/nerfstudio-logo.jpeg' class = "thumbnail" width="180">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://docs.nerf.studio/en/latest/">
<papertitle>Nerfstudio</papertitle>
</a>
<br>
<i>A collaboration friendly studio for NeRFs</i>
<br>
Jan 2023 - Present
<br>
<a href="https://docs.nerf.studio/">Website</a> /
<a href="https://github.com/nerfstudio-project/nerfstudio">Github</a>
<p></p>
<p>Contribute (in small parts) to large-scale open-source project. Helped implement research methods (Instruct-NeRF2NeRF, CLIP-based NeRF)
into main repository.
</p>
<p>
<b>Stack</b>: Python, PyTorch
</p>
</td>
</tr>
<tr onmouseout="nerfie_stop()" onmouseover="nerfie_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/suisense.png' class = "thumbnail" width="180">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://suisense.space/">
<papertitle>SuiSense</papertitle>
</a>
<br>
<i>Using Artificial Intelligence to distinguish between suicidal and depressive messages</i>
<br>
June 2020 - Dec 2020
<br>
<a href="https://suisense.space/">Website</a> /
<a href="https://www.youtube.com/watch?v=QHpKJBVObhA">Demo</a> /
<a href="https://github.com/ayaanzhaque/SuiSense">Github</a> /
<a href="https://devpost.com/software/suisense-i2cnrd">Devpost</a> /
<a href="https://codeburst.io/suisense-an-innovative-approach-to-suicide-prevention-19cbdf150575?sk=bc16527363f641d1009754e0e77a5891">Medium Article</a> /
<a href="https://ayaanzhaque.github.io/SDCNL/">Research Paper (SDCNL)</a>
<p></p>
<p>SuiSense is a progressive web application that uses Artificial Intelligence (AI) and Natural Language Processing
(NLP) to distinguish between depressive and suicidal phrases and help concerned friends and family determine whether
their struggling loved one is on the path to suicide. SuiSense uses an implementation of <a href="https://ayaanzhaque.github.io/SDCNL/"></a>SDCNL.
</p>
<p>
🏆 4th Place Congressional App Challenge 2020 🏆 2nd Place @ GeomHacks 2020 🏆 HM @ MLH Summer League SHDH 2020
</p>
<!-- <p>
In order to continue expanding our project and implementing it, we are currently working with two therapists, Dr. Paul Marcille
and Dr. Marilee Ruebsamen, who act as our advisors and consultants. With their help, we have begun an implementation process in our local community.
</p> -->
<p>
<b>Stack</b>: Python, HTML, CSS, JavaScript, Tensorflow, PyTorch, BERT, Flask, PythonAnywhere, Pandas, Sci-Kit Learn
</p>
</td>
</tr>
<tr onmouseout="nerfie_stop()" onmouseover="nerfie_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/drishti-rig.jpeg' class = "thumbnail" width="180">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://drishtiai.org/docs.html">
<papertitle>Drishti Smartphone Retinal Camera System</papertitle>
</a>
<br>
<i>CAD Files and Implementation Drishti's Retinal Camera System Prototype</i>
<br>
June 2021 - Sep 2021
<br>
<a href="https://github.com/Drishti-BD/Drishti-CAD">Github (CAD Files)</a> /
<a href="https://youtu.be/K8nVQCHWzno">Assembly Guide</a> /
<a href="https://youtu.be/1zDsNmXHbFA">Instructional Guide</a> /
<a href="https://drishtiai.org/docs.html">Documentation</a> /
<a href="https://towardsdatascience.com/smartphone-based-retinal-camera-rig-for-ai-screening-4f7944d5a513?sk=af361f4e77c16059a887aa5592bc67c9">Technical Blog</a> /
<a href="https://drishtiai.org/">Drishti Website</a>
<p></p>
<p>This mobile, on-the-go system is designed for clinics in Bangladesh to screen patients for
Diabetic Retinopathy (DR) using a smartphone camera with a retinal attachment. The purpose
of this rig is to allow precise positioning of the smartphone to any patient's left and right
eye such that the images can be efficiently fed into Drishti's AI algorithms for DR diagnosis.
The system is completely adjustable for all head sizes. It is made of readily available
components that can be purchased at many local hardware stores, and is designed for low-cost
fabrication. All assembly tools are common household tools or easily purchasable/rentable
from a local hardware store. The 3D-printed components can be printed on low-end machines
and with cheap PLA filament. We designed this system to be completely collapsable, such that
it can fit into a standard size backpack.
</p>
<p>
<b>Stack</b>: SolidWorks, Hardware Materials
</p>
</td>
</tr>
<tr onmouseout="nerfie_stop()" onmouseover="nerfie_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/tickbird.png' class = "thumbnail" width="180">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://tickbird.netlify.app/">
<papertitle>Tickbird</papertitle>
</a>
<br>
<i>Streamlined prescription analysis for visually impaired patients</i> <span style="color:blue">(Available on the App Store)</span>
<br>
September 2019 - June 2020
<br>
<a href="https://tickbird.netlify.app/">Website</a> /
<a href="https://apps.apple.com/us/app/tickbird-co/id1508006830?ls=1">App Store</a> /
<a href="https://www.youtube.com/watch?v=7230378jFNk">Demo</a> /
<a href="https://github.com/rvignav/Tickbird">Github</a> /
<a href="https://docs.google.com/presentation/d/1dY442wAG3Hk91HyDZDluQm-OmfDMlNpH95d_u01IWZA/edit?usp=sharing">Slides</a> /
<a href="https://devpost.com/software/tickbird">Devpost</a>
<p></p>
<p>Tickbird is an advanced Swift mobile app based on the TesseractOCR neural network framework allowing visually impaired patients
to aurally understand their prescriptions or the labels on their pill bottles in order to gain independence and avoid
the prospect of lethal miscommunication regarding necessary medicines from their doctors. Moreover, the app's smart
profiling feature not only finds the nearest pharmacy containing the user's prescription, but it also uses AI/ML
algorithms to detect and set notifications for the times the user has to take or refill their medicine.
</p>
<p>
🏆 2x Award Winner @ OmniHacks 2019 🏆 App Store April 2020, 1000+ Impresions
</p>
<p>
<b>Stack</b>: Swift, Xcode, IOS, Firebase, TesseractOCR, Ruby
</p>
</td>
</tr>
<!-- <tr onmouseout="nerfie_stop()" onmouseover="nerfie_start()">
<td style="padding:20px;width:25%;vertical-align:middle">
<div class="one">
<img src='images/tecconect.png' class = "thumbnail" width="180">
</div>
</td>
<td style="padding:20px;width:75%;vertical-align:middle">
<a href="https://tecconnect.tech/">
<papertitle>TecConnect</papertitle>
</a>
<br>
<i>Connecting schools to donate or request devices to aid COVID Learning</i>
<br>
April 2020 - June 2020
<br>
<a href="https://tecconnect.tech/">Website</a> /
<a href="https://youtu.be/eep9ySXg_vA">Demo</a> /
<a href="https://github.com/ayaanzhaque/TecConnect">Github</a> /
<a href="https://drive.google.com/open?id=1Ee47YBi950PiapqS32xQgjRajwDxdv41Z-_5aRPkN6Y">Proposal</a> /
<a href="https://drive.google.com/open?id=1YfTJ62Jyqvhz7gQOhnRn55-TWZL59RQJpBskmdQ0BCw">Executive Summary</a> /
<a href="https://devpost.com/software/tecconnect">Devpost</a> /
<a href="https://medium.com/illumination/tecconnect-the-greatest-covid-education-proposal-that-ever-failed-6ebea230259e?sk=92622e4e52fd1836b107a8421d4fc1d0">Medium Article</a>
<p></p>
<p>TecConnect is a unique PWA that allows impoverished and wealthy schools to easily connect and transfer devices
from those who have them to ones who don’t. Due to the COVID crisis, low-income students don't have access to
devices, and as a result, are falling behind in their education. However, many schools have surpluses of devices
that are currently being wasted.Thus, we developed TecConnect to allow struggling schools to request devices from
schools with excess devices. We developed an application specifically for schools and the state government. We plan
to implement our software as part of a statewide plan to promote device sharing in all schools.
</p>
<p>
🏆 1st Place Grand Prize Winner @ AI4ALL CreAItivity Challenge 2020
🏆 1st Place Grand Prize Winner @ Saratoga Congressional Hackathon 2020
🏆 Sponsor Prize Winner @ MLH Summer League RH 2020
</p>
<p>
<b>Stack</b>: HTML, Javascript, CSS, Firebase, MongoDB, Radar.io, Google Cloud
</p>