1 00:00:01,350 --> 00:00:04,950 So can you just start by saying your name and what your current position is? 2 00:00:05,520 --> 00:00:12,090 I'm Agent Wong and currently I'm a research scientist at the University of Oxford. 3 00:00:12,120 --> 00:00:20,870 I'm a student and I am also employee and Perspective, which is the founder who fund me to do my Ph.D. 4 00:00:20,880 --> 00:00:25,730 And yeah, I am a research scientist and innovation team right now. 5 00:00:26,120 --> 00:00:30,650 All right. So I'm going back to how you first got interested in science. 6 00:00:30,660 --> 00:00:38,550 Can you just talk me through the stages of your education and career up to the point where you first came to us? 7 00:00:38,580 --> 00:00:41,730 Oh, wow. Okay. Even before I came to. 8 00:00:41,910 --> 00:00:46,770 Oh, yes. Yes. From right. How did you first decide you were going to do a science degree? 9 00:00:47,050 --> 00:00:50,970 Right. That is that's that's a very good that's a good question. 10 00:00:51,120 --> 00:00:57,689 Yeah, I, I think since I was young, I was always interested in the subject line math. 11 00:00:57,690 --> 00:01:00,599 And then I really like to know how things work. 12 00:01:00,600 --> 00:01:08,339 And specifically when I approach when I approach a new object, I will I will ask about how so how does that make sense? 13 00:01:08,340 --> 00:01:17,309 How does that come into play? And yeah, through throughout my educational journey, I like a lot of hands on type of experience. 14 00:01:17,310 --> 00:01:22,139 So I like, I like chemistry, I like math, I like experiment. 15 00:01:22,140 --> 00:01:28,830 And yeah, that's pretty much I knew that I would I would do a science degree, science based degree. 16 00:01:28,830 --> 00:01:39,000 And so yeah, I, I chose to do, to be really specialised in medical imaging and radiology science from my undergrad in when I was back in Taiwan. 17 00:01:39,480 --> 00:01:48,180 And that was, that was at that time a I wasn't really sure about the decision at that time because I, 18 00:01:48,420 --> 00:01:54,570 but I knew very well I want to do in the medicine related type of sciences, either radiology. 19 00:01:54,900 --> 00:01:58,350 I applied to pharmacology as well. 20 00:01:59,160 --> 00:02:08,160 There's another called, I think it's biochemistry, and I applied for a medicine degree, but obviously I didn't get it. 21 00:02:08,370 --> 00:02:11,900 Yeah, at that time you can apply to six when I was back in time. 22 00:02:11,910 --> 00:02:21,930 One choosing to do a degree in in medical science and I got full scholarship for the for the radiology science degree. 23 00:02:21,930 --> 00:02:23,490 And so I got so I chose that. 24 00:02:26,160 --> 00:02:35,780 So yeah, that was, that was a three year very hardcore science course and then the very practical, very practical oriented. 25 00:02:35,790 --> 00:02:41,819 So the, the fourth year is very practical because we do internship actually at sites in hospitals. 26 00:02:41,820 --> 00:02:48,390 So at that time I was at the National Time University Hospital for the fourth year of my undergrad. 27 00:02:48,780 --> 00:02:54,749 And yeah, we, I basically shadow our Radiographers onsite and we, 28 00:02:54,750 --> 00:03:02,910 I was running through various departments of the Mini in diagnostic radiology and another one is nuclear medicine and another one is 29 00:03:03,210 --> 00:03:12,690 our radiation therapy disability and the treatment side and the others that bits and pieces like ultrasound and then dental X-ray in, 30 00:03:13,290 --> 00:03:15,600 so doing X-ray and MRI and. 31 00:03:15,890 --> 00:03:25,020 Yeah, so that's, that's one of the things that's really I found a really interesting back in Taiwan we do various modality so I can run, 32 00:03:25,020 --> 00:03:34,800 I can run ultrasound, I can run CT, I can run X-ray, dental, X-ray, MRI, and this therapy size, the lenient accelerator. 33 00:03:35,010 --> 00:03:38,800 Yeah. This is like high, high energy machine. Yeah. 34 00:03:38,820 --> 00:03:50,370 So that's a that's an interesting bit. I was in, I believe here in the UK people probably choose to be specialised to a specific type of modality. 35 00:03:50,730 --> 00:03:53,250 Yeah. Yeah. Radiological signs. 36 00:03:54,270 --> 00:04:08,190 And then when I was, when I graduated from, I finished my clinical training and get back I got the national exam which is basically you, 37 00:04:08,190 --> 00:04:14,160 you qualify to be a radiographer to be able to work as a radiographer. 38 00:04:14,310 --> 00:04:16,500 Um, yeah, that's the national exam. 39 00:04:16,500 --> 00:04:24,030 So I finished exam and, and started thinking about I actually really wasn't sure that I wanted to start working clinically. 40 00:04:25,650 --> 00:04:30,160 So I decided to apply to various universities and, 41 00:04:30,180 --> 00:04:37,980 and at that time I was really interested in radiotherapy in the treatment side specifically that comes out from a radiology degree. 42 00:04:39,270 --> 00:04:44,190 So I applied to six universities in the UK to do a master's degree. 43 00:04:44,580 --> 00:04:55,830 And yeah, at that time I didn't, I really wasn't pretty much hope into like with I'll get into to Oxford and I would just since I'm preparing myself, 44 00:04:55,840 --> 00:04:59,880 just submit an application to Oxford and then in. 45 00:04:59,990 --> 00:05:05,450 And I accept it and I was interested in the time was actually a lunar New Year. 46 00:05:05,720 --> 00:05:13,340 I got the information saying that, Hey, you're accepted to do a massive program in in, in Oxford. 47 00:05:14,120 --> 00:05:19,849 And like, I was in a car with my parents or just like, shouting in the car or so. 48 00:05:19,850 --> 00:05:24,050 Happy. Yeah. Yeah. So I decided to study a little bit more. 49 00:05:24,680 --> 00:05:30,620 So I came to Oxford in 2018. And that was a degree in radiation biology. 50 00:05:30,800 --> 00:05:42,860 So it's, it's, it's far more, I would say, niche and specialised because you kind of look at a combination of biological science and physics together. 51 00:05:43,430 --> 00:05:46,700 And yeah, and that in the program itself, 52 00:05:47,030 --> 00:05:56,599 I could also feel was a very multidisciplinary team and multidisciplinary cohort and I was the only Asian 53 00:05:56,600 --> 00:06:03,650 student within a cohort and all the elbows had like they were either European or an American student. 54 00:06:04,730 --> 00:06:13,040 And my understanding at that point of time, that specific program was also like very, you know, like there were very few Asian student before. 55 00:06:13,480 --> 00:06:22,220 Um, yeah. So I joined and most people, most other people do biology and I did like more like physics and math type of degree as undergrad. 56 00:06:22,250 --> 00:06:25,549 So people came with a different background. It was six of us. 57 00:06:25,550 --> 00:06:29,360 We were super, super tied. We worked together. We travel together. 58 00:06:29,900 --> 00:06:37,100 Yeah. And I yeah, that's, that's my, that's, that's at that time I, I really enjoyed my master's, 59 00:06:37,140 --> 00:06:41,070 you know, So was that was mostly a taught program or did you do some research. 60 00:06:41,090 --> 00:06:44,270 Yeah. So it was a 13 month program. 61 00:06:44,270 --> 00:06:48,470 So you, we get taught for the first two terms and then the last ten. 62 00:06:48,560 --> 00:06:55,880 I mean, then second half of the second term. In a last term we did a short project and research project. 63 00:06:56,180 --> 00:07:04,220 So at that time I was really lucky to be to be part of the medical physics group in, in the oncology department. 64 00:07:04,850 --> 00:07:09,440 And I was I was supervisor was Franklin the it was Belgium. 65 00:07:09,860 --> 00:07:14,570 He left Oxford after after I graduated from my master's degree. 66 00:07:14,840 --> 00:07:27,140 So I did did a research project with them, specifically looking at a type of technical, stereotactic sterile, static radiotherapy. 67 00:07:27,440 --> 00:07:32,659 Yeah. Yeah. It was roughly like a six months period of time. 68 00:07:32,660 --> 00:07:38,000 And we, we will write up our thesis, our dissertation, and then do a viva. 69 00:07:38,300 --> 00:07:47,960 Yeah. So it's very compact our a really stressful degree actually, I have to say it was, it was very intense but also fun. 70 00:07:47,970 --> 00:07:51,590 It was probably the best year of my life here in Oxford. 71 00:07:52,300 --> 00:08:03,620 Yeah, Yeah. So that's about me. And then after I graduated from my master's degree, I wasn't I wasn't really sure what to do. 72 00:08:05,150 --> 00:08:13,550 I was lost. I was the definition of lost. Most of also like in the cohort most of my other peers, 73 00:08:14,390 --> 00:08:20,810 they went back to the US to start their medical degree medicine degree, which is interesting to know actually. 74 00:08:20,810 --> 00:08:21,629 Yeah, they, they, 75 00:08:21,630 --> 00:08:32,780 they have a first degree and then to do a medicine degree and then the other two had all got like Ph.D. position lined up before they even graduated. 76 00:08:33,200 --> 00:08:36,769 So I was the only one who left with like no job. 77 00:08:36,770 --> 00:08:41,120 No, no for the plan. I was really, really, really lost. 78 00:08:43,070 --> 00:08:46,760 And did you go home at that point? I went home, yeah. 79 00:08:46,760 --> 00:08:55,819 I went home. And during a junction when I was when I was when I submitted my dissertation and waiting for my viva. 80 00:08:55,820 --> 00:09:00,110 So I came back for my viva. So then towards the end of 2019. 81 00:09:00,140 --> 00:09:03,620 Towards the end of 2019, yes. Yeah. At that time. 82 00:09:04,880 --> 00:09:11,210 Yeah. I finished my Viva in September and then, and then I went back home and came back for the graduation in November. 83 00:09:11,390 --> 00:09:15,140 Right. Yeah. So it was very end of 2019. Yeah. 84 00:09:15,140 --> 00:09:22,640 And they came back for the graduation and that time my visa sort of allow me to stay all the way into March 2020. 85 00:09:22,790 --> 00:09:31,790 So there was a grace period and so I utilised those period to just start to find jobs, find an internship, find a new life opportunities. 86 00:09:32,990 --> 00:09:40,850 Yeah. And then I came in contact with perspective. I approach perspective and I ask them if I can do internship with them. 87 00:09:41,300 --> 00:09:46,540 And yeah, they, they saw, they saw my background was like, okay, you can come and do internship this. 88 00:09:46,760 --> 00:09:52,820 Yeah. So, so you were just I think I think what Pancho told me was that you, you were planning to do a piece. 89 00:09:52,880 --> 00:09:59,750 I was planning, yeah. So I was fine in finding, like, either internship as a. 90 00:09:59,980 --> 00:10:10,800 It is like an interim option. But I also was like trying to apply to like many different Ph.D. positions I got into to the oncology Ph.D. in oncology. 91 00:10:10,810 --> 00:10:14,140 Yeah, I did so, but then there was no funding. 92 00:10:14,920 --> 00:10:21,330 I'd say I didn't carry on an internship was became indigent, became available. 93 00:10:21,340 --> 00:10:28,510 And so I decided, okay, that's also a good opportunity for me to gain some industry experience and really try to like, 94 00:10:28,750 --> 00:10:33,940 do busy life work work, you know, as opposed to just study. 95 00:10:34,060 --> 00:10:42,610 Mm hmm. Yeah. Yeah. And so I think we've got so we've got and that was going to take you through to March, was it? 96 00:10:42,760 --> 00:10:45,790 Yeah. Yes. Through to March. Take me through to March. 97 00:10:45,850 --> 00:10:58,240 But then of course, as we all know. So can you remember when you first heard that there was a nasty respiratory infection spreading in China? 98 00:10:58,420 --> 00:11:01,960 Yeah. We came to realise that was going to have a bit of an impact on your life. 99 00:11:02,200 --> 00:11:16,240 It was. I was. I really wasn't sure how to respond at that time because so I just started my internship and I started to get to know about like my, 100 00:11:16,450 --> 00:11:27,309 my colleagues and then my manager here and perspective and, and there were so many things to learn when you first join an organisation. 101 00:11:27,310 --> 00:11:36,220 There also are lots of policies to read. And yeah, so it was a very like I was trying to absorb as much as I can. 102 00:11:37,480 --> 00:11:47,080 And when I first heard about the outbreak, I was, I was really not sure how to respond. 103 00:11:49,000 --> 00:11:51,730 I didn't necessarily worry about that, honestly. 104 00:11:51,770 --> 00:12:00,969 I was just really focusing on like starting off properly for my for my for my career at that point of time. 105 00:12:00,970 --> 00:12:05,260 So I really didn't think that much when I first hear about Outbreak. 106 00:12:05,650 --> 00:12:14,650 And it was things started to became really, really weird in March 2020, I believe in March 2020. 107 00:12:14,650 --> 00:12:20,140 And we had a company meeting where Banjo, which is our CEO, 108 00:12:20,920 --> 00:12:30,879 he just brought us to the to the to the boardroom and then tell everybody the next day on a Wednesday, everybody go home. 109 00:12:30,880 --> 00:12:36,160 Everybody work from home. And everybody didn't know how to respond. 110 00:12:36,160 --> 00:12:40,960 The team like some of the team, because I was a very like hands on involved team. 111 00:12:41,020 --> 00:12:50,920 Like we we had physical equipment where we store on here on onsite in the lab and we need to like physically come in to transport them. 112 00:12:51,280 --> 00:12:56,560 And at that time everybody was like scramble trying to find a way to make things work. 113 00:12:57,130 --> 00:13:00,280 And I was I was I was the intern at that time. 114 00:13:00,280 --> 00:13:05,200 There was still a lot of operational procedures that I didn't know, so I was really freaked out. 115 00:13:05,230 --> 00:13:12,450 I was pretty much just being blank and then trying to see like, what I can do, what, how I can help, so I can help. 116 00:13:12,490 --> 00:13:16,860 I start I here a little bit there A little bit, Yeah. 117 00:13:17,850 --> 00:13:23,559 Um, it wasn't pretty frightening at that time, but the hope is that was going to run out at the end of March. 118 00:13:23,560 --> 00:13:27,560 Is that right? Yes, yes, yes. 119 00:13:27,560 --> 00:13:37,690 He was going it was about to run out. But luckily at that time I was able to like to extend with a different relative visa, which is quality of life. 120 00:13:37,690 --> 00:13:42,790 And that's specifically for an internship for people to do an internship here in the UK. 121 00:13:43,150 --> 00:13:52,240 Yeah. So that that got extended. So it was, yeah, I was very lucky in that sense to be able to, to do that. 122 00:13:53,290 --> 00:13:57,970 And I was really grateful that perspective at that time helped me out to do that. 123 00:13:58,210 --> 00:14:06,490 Yeah, because I mean, would you have been able to go back to Taiwan at that stage or was it there had flights going? 124 00:14:06,730 --> 00:14:19,180 Yeah, At that time when I was monitoring, I've seen I've certainly found it impossible to go back on many because the the the the cost of the 125 00:14:19,180 --> 00:14:25,989 flight is just so much it's really not like some affordable for someone who's just started their career, 126 00:14:25,990 --> 00:14:30,639 barely have any saving earning an individual salary will be able to afford. 127 00:14:30,640 --> 00:14:40,060 So that's that's really unreasonable. And another thing in my mind about time, I knew that I just started I just started my career. 128 00:14:40,330 --> 00:14:50,060 Do I throw away my career? Potentially, because you never know how how long the pandemic, how long and as as now is. 129 00:14:50,080 --> 00:14:58,870 Now that I know it was a really extended impact. And at that time, if I was really thinking, do I throw my career away? 130 00:14:59,860 --> 00:15:04,840 Or do I do I chose to stay on the safe side. 131 00:15:05,380 --> 00:15:12,160 So, like, I was worried about that. Like my career would just stop my career here and you can just stop. 132 00:15:13,450 --> 00:15:20,259 And also, I was I was like, financially not possible to I do I came from from the U.K. So it was kind of it 133 00:15:20,260 --> 00:15:24,970 was kind of like a in a way of an easier decision that I just chose to stay. 134 00:15:25,570 --> 00:15:30,600 Yeah, I didn't I didn't second guess to that or whether should I go now, that type of thing. 135 00:15:30,610 --> 00:15:35,860 I was also really worried about my future at that point of time. 136 00:15:37,090 --> 00:15:40,510 Yeah. So the internship was extended. 137 00:15:40,870 --> 00:15:42,610 Was extended. Yeah. Yeah. 138 00:15:42,650 --> 00:15:49,700 And you must have begun to feel more comfortable around the company and read all the operating procedures and all the rest of it. 139 00:15:49,720 --> 00:15:52,930 I did. And, and I. And I was. And where did you find your niche? 140 00:15:52,930 --> 00:15:59,560 In the company. I really. I wouldn't say I have a niche in and company. 141 00:15:59,620 --> 00:16:12,430 Not necessarily, but things started to change at the point, I believe in May 2020 or like maybe mid April, early May 2020, 142 00:16:13,570 --> 00:16:21,380 at a time perspective and start to set up a study called the Call, the scan, which is now called the the long COVID study. 143 00:16:21,400 --> 00:16:28,389 And at that time we want to see like the organ impairment through the effect of COVID. 144 00:16:28,390 --> 00:16:32,200 So we basically scan do an MRI scan. 145 00:16:32,470 --> 00:16:42,220 The extent is protocol for for supposedly COVID COVID cases at that time. 146 00:16:43,210 --> 00:16:50,530 So, yeah, that study was set up and it was it was a Pacific funded study and we decided to do that. 147 00:16:51,100 --> 00:17:02,890 And it was it was a it was a type of a project where nobody really knew how the long term plan is going to be. 148 00:17:03,370 --> 00:17:11,740 Um, but we did it anyway. We thought that like, hey, we are, as it were, medical technology company, we can do something to help. 149 00:17:11,950 --> 00:17:18,460 And we had the capacity, had the skillset to be able to support this type of research. 150 00:17:18,790 --> 00:17:27,160 So that study got set up really quickly and I was, I had a radiographer qualification back in Taiwan. 151 00:17:27,340 --> 00:17:38,350 And so at that time, apart from just my internship like original role in it as a intern and the imaging applications team, 152 00:17:39,310 --> 00:17:49,420 I was brought up to the study team to support the scanning of the patient and it came in almost to me had like, 153 00:17:49,690 --> 00:17:56,590 I just feel like this is like a flashback and like it was an opportunity for me to really support 154 00:17:57,220 --> 00:18:04,990 and support as in the general population with a skill set that I that I had acquired prior, 155 00:18:04,990 --> 00:18:09,970 before I came to Oxford and I, and it was at the point where I had like this, 156 00:18:10,420 --> 00:18:17,920 this phase of my phase of my life, where I was so unsure about where I'm going to go next in terms of career. 157 00:18:18,670 --> 00:18:30,010 And so that study almost came in, almost came into like, I feel like you saved my life to, to, to save me from having to make a really hard decision. 158 00:18:30,610 --> 00:18:34,750 Yeah. And so I joined a team and then I just started to scan patients non-stop. 159 00:18:35,260 --> 00:18:43,930 So talk me through how that happened. So did you did was the diagnostic centre that there is here now in the spectrum offices. 160 00:18:44,380 --> 00:18:47,920 Not that that hadn't been set up with. No, that hasn't been set up at that. 161 00:18:47,920 --> 00:18:52,030 So where were you doing the scanning. Yeah. So it was, it was really interesting. 162 00:18:52,030 --> 00:18:58,870 So the scanning was, was done by there is a truck basically contain a big magnet, 163 00:18:58,870 --> 00:19:08,410 an image scanner within a truck that is put into the to the, to the car park of the building at the back of the building. 164 00:19:08,800 --> 00:19:18,190 And we had that scan as well. We just sit there and people and then we design, we sort of work around the building. 165 00:19:18,190 --> 00:19:24,339 We design a route where people will be coming in from one direction and going out from the other direction. 166 00:19:24,340 --> 00:19:29,410 And it was really lucky for us because the ground floor, it was pretty much empty at that time. 167 00:19:29,770 --> 00:19:39,819 And so we can we can at people from the front and then look them out from the back and come into the truck where they did the scan and go out 168 00:19:39,820 --> 00:19:49,030 from the other side of the truck towards the other direction and then come into the building to take their blood and then exit the building. 169 00:19:49,390 --> 00:19:55,450 And so there's this almost a one in, one out that we sort of utilise what we had at that time. 170 00:19:55,780 --> 00:19:59,710 And these were people who had recovered from COVID. 171 00:20:00,100 --> 00:20:06,220 Yeah. So they have ongoing symptoms or were you just looking at anybody who'd who had recovered from COVID? 172 00:20:06,240 --> 00:20:10,090 Yeah, So it was a very early stage at that time in 2020. 173 00:20:10,090 --> 00:20:20,230 So we before there was there's like specific test or like quick antigen testing coming in. 174 00:20:20,260 --> 00:20:26,530 Yeah, it was about the, the GP, like the doctors, they, they will assign the symptoms, 175 00:20:26,530 --> 00:20:33,520 they will so will look at symptoms and at the time we, we, we qualified. 176 00:20:33,550 --> 00:20:41,410 I wouldn't say qualified, we include patients where they had like proper How does it like GP diagnosis say okay this is likely, 177 00:20:41,680 --> 00:20:45,819 this person's a likely a COVID case. 178 00:20:45,820 --> 00:20:53,469 Yeah. And then they, they are brought into the inclusion, they can be included to the study at that time. 179 00:20:53,470 --> 00:20:59,770 But then they had, they were over the acute phase by the time they came to see, you know, so we actually, 180 00:21:00,010 --> 00:21:09,190 we actually scanned quite a lot of people who are who they, they still had difficulty breathing, have difficulty walking this. 181 00:21:09,190 --> 00:21:14,530 This is because it was actually quite big. They had to walk along the way to to complete the whole study. 182 00:21:16,600 --> 00:21:20,259 We actually scanned quite a few patients. They would describe their symptoms. 183 00:21:20,260 --> 00:21:27,430 And it was it was just really painful to to to see them had to go through go through that. 184 00:21:28,120 --> 00:21:32,769 But the antigen tests come coming into play. And then we were able to, like, use test results. 185 00:21:32,770 --> 00:21:39,729 So we did a protocol amendment on the cover scan study and therefore we we will be was 186 00:21:39,730 --> 00:21:45,040 able to be confident that all the patients we all scanned were all COVID patients. 187 00:21:47,110 --> 00:21:51,849 But this is this doesn't say that what we did before was was not truly right. 188 00:21:51,850 --> 00:21:58,060 It but it was because we didn't have like tangible measure to do the best you could do. 189 00:21:58,090 --> 00:22:02,139 It was the best that we could do. Yeah, yeah, yeah. 190 00:22:02,140 --> 00:22:14,080 So, so that was we pretty much scanned COVID patients and with a very extensive protocol and, and you were the the main patient facing person also. 191 00:22:14,080 --> 00:22:18,760 They are so the the study team they were it consists of quite, quite a few different people. 192 00:22:18,760 --> 00:22:26,589 We had met the research nurse and we also had radiographer was also like the receptionist, the administrative side. 193 00:22:26,590 --> 00:22:35,649 So the team, the whole core team were patient facing and now I'm just part of them and I'm actually like the junior side of, of, of part of them. 194 00:22:35,650 --> 00:22:39,309 They were very experienced at that time. So I was lucky. 195 00:22:39,310 --> 00:22:48,129 I was able to, to learn how to, how to properly receive patients, check their safety check if they are eligible. 196 00:22:48,130 --> 00:22:52,960 Make sure they are they're safe on the scanner and make sure they are safe on the road to a different station. 197 00:22:53,890 --> 00:23:01,660 It was an amazing experience to to be able to learn, but also scary and tiring and that at the same time. 198 00:23:01,930 --> 00:23:05,319 Yeah. So how long a day were you doing? 199 00:23:05,320 --> 00:23:22,660 Yeah. So the the scan started all from of the earliest was six was in the earliest was before 8:00 and then we usually finished until sometime late. 200 00:23:22,660 --> 00:23:25,930 Is 730 in the evening. Yeah. 201 00:23:25,930 --> 00:23:30,310 And you every, every day we would need to, we would need to shut up, 202 00:23:30,700 --> 00:23:42,940 shut down the scanners without as takes quite a bit of time to read and then sub and the most tricky part to run a COVID study for to, 203 00:23:43,000 --> 00:23:49,600 to run a scan for COVID patient is that you have to clean like very thoroughly during each visit. 204 00:23:50,020 --> 00:23:51,520 And it was really tricky. 205 00:23:51,790 --> 00:24:01,030 And so we need to find specific equipment that wouldn't wouldn't now wouldn't interfere with the magnetic field that comes out from the MRI scanner. 206 00:24:01,810 --> 00:24:05,380 And we need to use this equipment that really clean in water. 207 00:24:05,980 --> 00:24:09,130 So it was it was a bit hilarious. Now, looking back. 208 00:24:10,000 --> 00:24:14,350 Yeah, but hard work and just like a kind of machine. Yeah, yeah, yeah, yeah. 209 00:24:14,350 --> 00:24:19,329 So you, you, you rotate cases like one one at a time. 210 00:24:19,330 --> 00:24:25,270 And the most we can do was a patient at that time for one day because he was, 211 00:24:25,270 --> 00:24:34,630 it was a 40 minute scan and depending on how well the how will the patients feel about like being been in the scanner in the set up. 212 00:24:35,350 --> 00:24:38,620 So it is actually quite, quite time consuming. 213 00:24:39,220 --> 00:24:42,100 So the most we could do was probably eight people, 214 00:24:43,510 --> 00:24:51,820 some for occasionally we will we will extend to till late in night to help finish the, the, the demand. 215 00:24:53,350 --> 00:24:58,030 But Yeah. Mm. Yeah. It was like that we had, we had. 216 00:24:59,830 --> 00:25:08,200 We have three radio, two radio before they started off, which was my most senior colleagues at that time. 217 00:25:08,230 --> 00:25:14,380 They started off and then I joined and then we brought up a few other people to help support the demand. 218 00:25:15,110 --> 00:25:19,620 Yeah. Mm hmm. And just to go over it again, I mean, I did talk to them about this, 219 00:25:19,630 --> 00:25:29,320 but the the point about the cover scan technology was that you were essentially scanning the whole patients, 220 00:25:29,320 --> 00:25:31,600 basically the whole so, you know, the whole torso. 221 00:25:31,600 --> 00:25:42,100 So we as we scan from the from the how to so you can see from the neck all the way down to almost covering their knee. 222 00:25:42,460 --> 00:25:48,070 So basically the whole torso like the abdominal and and chest region of the patient. 223 00:25:48,310 --> 00:25:54,250 Yeah. And then the software part of it was was looking at six organs. 224 00:25:54,290 --> 00:25:58,300 Yeah. Yeah. So we have heart measurement. We have heart metrics. 225 00:25:59,080 --> 00:26:09,340 At that time long was was relatively new that that's also like a new method of really to start ramped up pancreas, liver and kidney kidneys. 226 00:26:09,370 --> 00:26:12,909 Yes, yes, yes, yes. 227 00:26:12,910 --> 00:26:17,290 These five yeah yeah, yeah. 228 00:26:17,320 --> 00:26:22,059 Perspective started off as a like a very specialised name in liver. 229 00:26:22,060 --> 00:26:26,830 Yes. Technology. But the at the R&D side of prospecting, 230 00:26:26,830 --> 00:26:31,750 we always have people from their life from various different background who they used 231 00:26:31,750 --> 00:26:37,630 to look at either cardiac like the heart or they used to look at kidney disease. 232 00:26:38,140 --> 00:26:48,910 And so at that time people was being really creative to support new support, new metric, new analysis that came in during the cold, wet time. 233 00:26:49,600 --> 00:26:57,360 Yeah, it was a stressful period for the whole organisation and people were people were really helping each other out. 234 00:26:57,880 --> 00:27:05,260 Yeah. So as well as collecting data that hadn't been collected before, the, the software itself was evolving, it was involving. 235 00:27:05,260 --> 00:27:19,510 Yeah. And yeah. And to a degree really it really just sort of let us know how much we could do as an organisation and to extend. 236 00:27:23,070 --> 00:27:26,280 They also like, creates lots of innovation. Yeah. 237 00:27:26,610 --> 00:27:31,020 And also like because the way people work let everybody work remotely. 238 00:27:31,500 --> 00:27:38,740 It also creates new, new a new type of collaborative procedure. 239 00:27:38,760 --> 00:27:43,740 Yeah. Among the group. Yeah. It wasn't it was actually at some point very productive. 240 00:27:45,300 --> 00:27:48,460 We would everybody was working from home at that time. 241 00:27:48,990 --> 00:27:54,630 Yeah. The. Oh yes. Okay. So the I mean, you were obviously here with the truck. 242 00:27:54,660 --> 00:27:58,610 I was here with the truck. It only all your. Yeah. The rest of the team. 243 00:27:59,030 --> 00:28:04,860 Yeah they were, they were away. Yeah. So how often did you link up with them on a virtually. 244 00:28:06,150 --> 00:28:14,960 Yeah. So we have, we have weekly meet weekly and then we will update each other on the, on the issues on site and the coordinators, 245 00:28:14,970 --> 00:28:18,990 there will be coordination sites who actually we receive patients information, 246 00:28:18,990 --> 00:28:23,130 screen them and give them information on like when to arrive at the site. 247 00:28:23,970 --> 00:28:32,400 Yeah. So we will have like weekly meetings with them and have an update about each like specific area on the on the study. 248 00:28:32,580 --> 00:28:40,559 Mm hmm. Yeah. And the analysis side of the cover scan study, that happens in parallel as well. 249 00:28:40,560 --> 00:28:45,870 But but they have their study, which I wasn't necessarily been part of. 250 00:28:46,080 --> 00:28:50,100 Yeah. Mm hmm. And how long did this intense period last? 251 00:28:51,490 --> 00:29:00,580 Oh, I can't remember. Intense period. 252 00:29:01,090 --> 00:29:07,050 It had always been quite intense. Okay. I mean, did it go over into 2021 or was it just. 253 00:29:07,060 --> 00:29:16,510 Yeah, it was it did go over into time. So the conversation started formally finished at the very close to the end of 2021. 254 00:29:16,540 --> 00:29:17,439 Oh, right. Yeah. 255 00:29:17,440 --> 00:29:24,970 Very close to the end of 2021 to, to, to basically make sure that okay we, so we set out by the number of patients that they would need to, 256 00:29:25,510 --> 00:29:30,070 to make it, to make it statistically power enough for us to make judgement. 257 00:29:30,700 --> 00:29:44,530 So like the whole recruitment and finalising analysis was probably done in late 2021 and the intent period was, was probably throughout 2020. 258 00:29:45,340 --> 00:29:49,750 Through all 2020 was the whole, the whole period was very intense. 259 00:29:51,300 --> 00:29:55,660 And so once the study was was completed, what was your next move? 260 00:29:56,350 --> 00:29:59,620 What was our next move? Yeah. 261 00:29:59,620 --> 00:30:05,889 End of 20. Well I was really hoping to, to start my PhD. So alongside running is called the scan. 262 00:30:05,890 --> 00:30:14,380 I was applying to Ph.D. position and I got into the engineering for the engineering department from Oxford. 263 00:30:14,830 --> 00:30:19,900 And but then in 2020, 2021, I couldn't start at that time. 264 00:30:20,470 --> 00:30:25,600 So I kind of just pushed that aside, which, which it honestly was. 265 00:30:25,630 --> 00:30:30,850 I was really lucky because in, in Oxford they allow you to do that for a year. 266 00:30:31,480 --> 00:30:38,650 So I was, I was able to do that. And then, then I just focussed on supporting like the existing work, 267 00:30:38,650 --> 00:30:46,900 like the backlog actually type of responsibility imposed by the original team, which was image implications team. 268 00:30:47,620 --> 00:30:55,060 Yeah. So at that time I was supporting and writing up documentations and these documentations are, 269 00:30:55,600 --> 00:31:01,700 and specific protocols that's set up on a trial case is only trial. 270 00:31:02,410 --> 00:31:05,290 When, when I say trial it means that clinical trials. Yeah. 271 00:31:05,320 --> 00:31:12,010 And so each of these clinical trials they want a set of guidelines, a set of protocol, a set of image and acquisition instructions. 272 00:31:12,010 --> 00:31:16,660 So I would, I will be tailoring those instructions based on the trial requirement. 273 00:31:17,830 --> 00:31:23,830 Yeah. So that was like the technical writing side of, of my, of my role at that time. 274 00:31:25,420 --> 00:31:33,220 Yeah. And it was, it was honestly also a very valuable skill to have, which I didn't necessarily get taught back at school. 275 00:31:34,180 --> 00:31:38,470 And so that was very hands on and very real world experience. 276 00:31:38,770 --> 00:31:48,460 Yeah. To be able to support and technical documentation and with so many different variations across trials, 277 00:31:49,090 --> 00:31:52,840 we kind of need to be very creative with the way that we write documentation. 278 00:31:52,840 --> 00:31:58,890 So we adopt new software and actually learn different type of structuring techniques. 279 00:31:59,290 --> 00:32:04,809 So it was a very like software based technical and then knowing understand 280 00:32:04,810 --> 00:32:10,690 how to utilise databases in that case and also do proper version control of, 281 00:32:10,810 --> 00:32:15,280 of the documentation. So that was, that was relatively new to me at that time. 282 00:32:15,460 --> 00:32:16,450 Yeah. Yeah. 283 00:32:16,450 --> 00:32:26,380 So I basically the whole year of 2021 to 2020 and 2020, I was focusing on supporting the technical documentations for the image applications team. 284 00:32:26,980 --> 00:32:30,870 Yeah. And so you got a place to do a PhD. 285 00:32:31,060 --> 00:32:38,560 Yeah. In engineering. So had you changed your thinking because I mean, when you were originally going to go for one, an oncology in oncology, 286 00:32:38,560 --> 00:32:42,639 what was the I had you already sketched out what you thought the problem you were going to 287 00:32:42,640 --> 00:32:49,910 investigate was and did that change feel that the engineering place or was it like the, 288 00:32:49,910 --> 00:32:54,069 the, the question of like this study, the topic of the research? 289 00:32:54,070 --> 00:32:59,380 Yes. Yeah, it did change along the way. And it wasn't necessarily just about like insurance. 290 00:32:59,480 --> 00:33:08,980 The change of interest on my, my. And I was also like considering the fact that like my supervisor would, who I, who I was was a doing my master's. 291 00:33:09,160 --> 00:33:21,129 He left Oxford. Yes. And I and I thought about and I and I had like advice from the senior scientist and also my supervisor here in perspective. 292 00:33:21,130 --> 00:33:26,620 And I sort of asked them, like, what would be the good research topic to do further down the line? 293 00:33:26,680 --> 00:33:30,010 And so they kind of shape my research interest in a bit. 294 00:33:31,180 --> 00:33:44,380 Yeah, yeah. Um, but what made me chose to apply to engineering it was because I was specifically really interested in in this man, this person's work, 295 00:33:44,440 --> 00:33:51,040 which my current supervisor, Daniel Botha in IBM, the Institute of Biomedical Engineering, 296 00:33:52,210 --> 00:33:55,660 I was really interested in his research, so I so I approached him. 297 00:33:55,660 --> 00:33:59,050 I wrote my proposal, had a few. Discussions with him. 298 00:33:59,530 --> 00:34:03,760 And we continue to do that almost through our 2021 to 2022. 299 00:34:04,240 --> 00:34:12,220 Yeah. And and yet he was he was also a very supportive person who sort of like carried me, 300 00:34:13,240 --> 00:34:22,980 carry me through the the last bit of pandemic and also like carry me where I was probably second year into my career, 301 00:34:22,990 --> 00:34:27,370 wasn't really sure what I was supposed to do in terms of being a scientist. 302 00:34:27,430 --> 00:34:31,440 So like, he he gave me a bit of guidance along with all the colleagues here. 303 00:34:32,560 --> 00:34:36,910 Yeah. And of course, I mean, perspective has quite strong links with the engineering department. 304 00:34:36,910 --> 00:34:40,030 It does. Yeah, it does. It does. It really does. 305 00:34:40,030 --> 00:34:45,040 And then, and then that's probably why it's become and became into. 306 00:34:45,220 --> 00:34:49,990 So what, what is your thesis topic or to what. Yeah. So currently. 307 00:34:49,990 --> 00:35:01,090 Yeah. So my, my thesis topic is hopefully using Bayesian network to support the decision making on liver cancer primary liver cancer. 308 00:35:01,600 --> 00:35:10,450 And now in first year in the the research focus is gearing towards the treatment selection side. 309 00:35:11,350 --> 00:35:16,790 So yeah. Can you explain that to someone who doesn't have a background in statistics? 310 00:35:16,820 --> 00:35:19,940 Yeah. Yeah. So in in liver cancer. 311 00:35:20,540 --> 00:35:24,890 So the treatment, there are many different options for treating liver cancer, primary liver cancer. 312 00:35:25,580 --> 00:35:30,920 You can do you can do surgery, you can do transplant. 313 00:35:31,100 --> 00:35:42,410 You can also do something called ablation, which is sticking a rod into and then basically burn the tumour cells out. 314 00:35:42,500 --> 00:35:45,260 Ablation and some other thing called embolisation. 315 00:35:45,260 --> 00:35:58,970 So you sort of like use like this little adenoma beads to block out the, the vascular, the other vascular structures for, for the tumour. 316 00:36:00,560 --> 00:36:06,980 And there's also radiotherapy which is using radiation to treat the tumour. 317 00:36:06,980 --> 00:36:20,870 So it's, so the, the, the field and the practice of liver cancer treatment is very, very, is very non standardised across the world. 318 00:36:21,200 --> 00:36:34,040 And for these treatments specific for this disease we had guidelines in American has their own guideline, Europe has their own guideline. 319 00:36:34,160 --> 00:36:39,730 Asia has a set of guidelines and within Asia they're also different countries has law, it has their own guideline. 320 00:36:39,740 --> 00:36:42,860 So it's a very wide spread field. 321 00:36:43,790 --> 00:36:50,990 And the tricky part is there's no way to properly compare which one is more effective than the other. 322 00:36:52,160 --> 00:37:00,440 And when it comes to treatment, there are many other options that came into play in maybe other factors that came into play. 323 00:37:00,740 --> 00:37:06,380 Then just the then just the how to say the patients diagnosed it results. 324 00:37:06,830 --> 00:37:12,110 So be also comes with like if if they if they will respond well to the treatment. 325 00:37:12,110 --> 00:37:19,040 If these patients has like enough financial support to support them to be able to go through the treatment. 326 00:37:20,870 --> 00:37:24,740 Yeah. Or that complications that might come in to come into play. 327 00:37:25,070 --> 00:37:28,160 And so it's very it's very messy as a result. 328 00:37:28,520 --> 00:37:38,810 And so my my research really is about using patient to be able to make these type of comparisons more tangible, more effective. 329 00:37:39,170 --> 00:37:45,350 So you're collecting data from health systems across from health and not necessarily across the world, 330 00:37:45,350 --> 00:37:51,040 but like currently, we currently we have quite a few data. 331 00:37:51,050 --> 00:37:57,110 So that is isn't in perspective and that's collaboration with like across the UK. 332 00:37:57,110 --> 00:38:00,110 And there's some data, some in Singapore, some in the US, 333 00:38:00,590 --> 00:38:08,150 but I wouldn't say it's very widely covered like all over the world, but it's a good coverage is a good starting point. 334 00:38:08,990 --> 00:38:14,910 So it's essentially a, it's a data analysis. Yeah, it is a very data analysis intensity. 335 00:38:15,200 --> 00:38:19,670 Yes. And they let you slide over they Bayesian networks. 336 00:38:21,770 --> 00:38:25,669 Yes. I've already asked somebody to explain what making approaches approach yourself. 337 00:38:25,670 --> 00:38:29,330 But it's it's it's to do with probability. 338 00:38:29,390 --> 00:38:33,560 Yeah. It's to do with probability. Yes. Exactly. That's that's a good way to put it. 339 00:38:33,560 --> 00:38:39,650 Yeah. That's the core actually the core of, of Bayesian is all about probability. 340 00:38:39,680 --> 00:38:42,690 It's a particular way of looking at probability. Yeah. Yeah. 341 00:38:42,700 --> 00:38:47,600 A different way than what people usually do to look at statistics. 342 00:38:47,840 --> 00:38:51,050 Yeah. It's a very distinct type of approach. 343 00:38:51,590 --> 00:38:59,149 Yeah. And what you hope will come out of this is some kind of clearer idea of the treatment approach. 344 00:38:59,150 --> 00:39:03,800 Is that what happens with particular kinds of patients. Oh yes, that's, Yeah. 345 00:39:03,880 --> 00:39:07,010 Yeah. So that's, that's the goal. That's a goal. 346 00:39:07,010 --> 00:39:15,650 And I, and I and I have good level of support from a senior position and uh, who utilise that technique. 347 00:39:15,980 --> 00:39:23,730 And I had good support from, from like my current supervisor and also had good support in terms of data here and perspective. 348 00:39:24,080 --> 00:39:33,140 So hopefully we can come up with something that can really make the treatment selection site very personalised, 349 00:39:33,650 --> 00:39:37,610 geared towards the patient and currently really, 350 00:39:38,210 --> 00:39:47,720 really what I think will be the immediate next step is to hope that there will be some collaborating doctors actually in the clinic. 351 00:39:47,850 --> 00:39:55,380 They are, they're happy to like help me, you know, really validate the technology, you know. 352 00:39:57,170 --> 00:40:00,440 Um, and, but you're still working here. 353 00:40:00,440 --> 00:40:03,829 It's the spectrum. How do you manage your time? 354 00:40:03,830 --> 00:40:08,239 Are you doing that the full time or are you doing it as a part time? 355 00:40:08,240 --> 00:40:11,900 So I'm doing it full time, but like, since I'm in the. 356 00:40:12,540 --> 00:40:16,650 Team, which is a very research scientist type role. 357 00:40:17,220 --> 00:40:20,640 And so that it didn't necessarily go over. 358 00:40:20,640 --> 00:40:21,810 I mean, I mean, 359 00:40:21,810 --> 00:40:33,930 the the the wide I guess doing a research unit person is that you can you can just read so much re really broad try and test things out as much 360 00:40:33,930 --> 00:40:45,390 as you can and he in perspective the innovation team obviously we have objectives but like it's also very hard to say like it's very liberal. 361 00:40:45,630 --> 00:40:49,270 Yeah I think it's quite academic environment. 362 00:40:49,320 --> 00:40:59,220 Yeah yeah yeah yeah So, so yeah if you had fit in well so far and for the in terms of like how I manage my time, 363 00:40:59,340 --> 00:41:04,360 I really don't know, I really don't know and still learning and probably the, 364 00:41:04,380 --> 00:41:11,370 the Yeah, I wouldn't say I have a, I have a strategy to properly manage my time, 365 00:41:11,370 --> 00:41:17,910 but I found if I schedule more things to do more of the various type of things to do, I get more productive. 366 00:41:18,510 --> 00:41:21,660 Yeah. So that's, that's my approach. 367 00:41:23,550 --> 00:41:26,760 Yeah. Mhm. Yes it is a lot of energy for that. 368 00:41:28,680 --> 00:41:34,980 So just I'm just going back to how the the pandemic impacted on you run smoothly movie. 369 00:41:36,270 --> 00:41:41,490 How did you feel about it as a disease? Did you feel personally threatened by the possibility that you might be infected? 370 00:41:41,640 --> 00:41:50,370 Have you in fact had it? I did. I did get an infection and actually was so I get infected and it was 20 I think was 2022. 371 00:41:50,970 --> 00:41:57,780 So you boys had a vaccine by then? I had yeah. I had like two or three doses of the vaccine at that time already. 372 00:41:58,170 --> 00:42:04,350 And, and so I probably caught the strain, the Omicron variant at that time. 373 00:42:04,350 --> 00:42:14,429 Yeah. I had the, I had the infection at that time but I before, before I even had my first vaccination, 374 00:42:14,430 --> 00:42:22,950 first dose of the vaccination, I, I was, I wasn't afraid about the disease. 375 00:42:22,950 --> 00:42:32,069 Honestly, my mind was not about my mind was not about making sure that I was safe. 376 00:42:32,070 --> 00:42:36,780 I knew that I had the I knew that I had way to protect myself. 377 00:42:36,780 --> 00:42:40,049 I wash my hands or like, never touch your faces. 378 00:42:40,050 --> 00:42:44,520 And when we come in here to do cover scan, we get like proper scrub. 379 00:42:44,520 --> 00:42:53,730 We're like, we were all covered, and I clean everything before I head back to head back to the house. 380 00:42:54,120 --> 00:42:59,590 Um. And in my mind, I really wasn't afraid of the disease. 381 00:43:00,100 --> 00:43:07,700 Yeah. Did you encounter and this might be a slightly difficult question, but I interviewed another East Asian Oxford researcher. 382 00:43:07,720 --> 00:43:14,950 Right. And she encountered hostility early on in the pandemic from ordinary people in the street, 383 00:43:15,250 --> 00:43:18,910 simply because of her East Asian looks and because she was wearing a mask. 384 00:43:19,030 --> 00:43:25,089 Right. And I think there was a certain amount of prejudice early and early on that 385 00:43:25,090 --> 00:43:28,540 people just automatically assume that if you looked as if you were Far East, 386 00:43:28,810 --> 00:43:32,820 you must have COVID. Right. Did you encounter anything? I Oh, wait, actually. 387 00:43:32,830 --> 00:43:41,680 So now I did. I did had had a bit of fear in terms of there were there were a lot of hatred and negativity 388 00:43:41,680 --> 00:43:50,700 against the Asian looking Asian looking person wearing a mask in in the in society in general. 389 00:43:50,710 --> 00:43:58,750 So I was I was quite wary of that. But, um, but I have to say in Oxford at that time. 390 00:44:00,850 --> 00:44:04,960 Oxley itself is a very unique place you never really find. 391 00:44:04,980 --> 00:44:18,850 And I think I think discrimination is very not tolerable in Oxley itself, or so I feel safe in a sense of being being Asian as a baseline. 392 00:44:19,600 --> 00:44:27,489 And I was, I was also like just fully focussed on like trying to scan patients. 393 00:44:27,490 --> 00:44:36,490 So I wasn't really quite wary of that, but say if I have some time that I, that I actually check about the news. 394 00:44:36,640 --> 00:44:45,250 I was worried that I hey, so if I go outside of it, I will get discriminated, I might get hurt, I may, I might get stabbed somehow. 395 00:44:45,730 --> 00:44:51,250 Yeah, but it was it was really just concern in the back of my mind. 396 00:44:51,490 --> 00:44:55,150 Not necessarily I had experience in any of that. 397 00:44:55,720 --> 00:45:00,370 So I didn't I didn't experience any of those hatred or racial discrimination. 398 00:45:02,140 --> 00:45:09,400 So it was lucky. Actually, I was really lucky at that time. And also, was it hard being a long way from your family when this was going on? 399 00:45:09,400 --> 00:45:14,050 It was hard, yeah, it was. I think Taiwan managed the pandemic. 400 00:45:14,500 --> 00:45:19,030 It was it was majority Well, yeah, it was managing really well. 401 00:45:19,030 --> 00:45:24,669 So in, in Taiwan, ah, wearing a mask is a necessary something that is just for disease, you know, 402 00:45:24,670 --> 00:45:31,360 it's not like you, you wear a mask because you had a cold and you catch a flu or something. 403 00:45:31,360 --> 00:45:36,310 No. Wearing a mask is fashionable, is who is cool to do. 404 00:45:36,460 --> 00:45:42,310 And it helps to let block out some sunlight to like keep you like keep your skin a 405 00:45:42,310 --> 00:45:47,320 little bit better or like make us make your face look smaller so it's fashionable, 406 00:45:47,350 --> 00:45:54,130 like, and it's really, really acceptable. So yeah, you wouldn't worry about wearing a mask there at time one. 407 00:45:54,460 --> 00:46:02,140 And that's probably why it's actually so, so easy to to control to control the disease back in time one. 408 00:46:02,140 --> 00:46:12,610 And then another thing is we we didn't really get vaccine early on and the whole country understand that like it will probably be really challenging 409 00:46:12,970 --> 00:46:24,610 for Taiwan to get vaccines production and manufactured being available to administer across to across the whole country just because of some, 410 00:46:24,610 --> 00:46:29,049 you know, like global, you know, political geopolitical issues. 411 00:46:29,050 --> 00:46:37,360 Yeah. So the so the CDC was was very, very aware of that and therefore that therefore like these type of policies in terms of 412 00:46:37,360 --> 00:46:44,560 like being social distancing was pretty much just like obeyed by the citizens itself. 413 00:46:45,700 --> 00:46:50,230 So you too worried about your family? I wasn't really worried about my family. 414 00:46:51,940 --> 00:46:56,380 I wasn't really worried about my family because I knew that they they would they will control it properly. 415 00:46:56,680 --> 00:47:02,290 Uh, at that point in time. Yeah. Oh, yeah. 416 00:47:02,290 --> 00:47:15,610 They didn't get I know that. I recall they have had like four doses of vaccine until they actually get COVID. 417 00:47:16,840 --> 00:47:24,130 Yeah. Yeah. So they had, they were reluctant to, to, to that extent. 418 00:47:24,850 --> 00:47:28,569 Yeah. It was hard to be, to be away with, with family. 419 00:47:28,570 --> 00:47:37,149 I was, but also because I had experienced things they very early on I was able to 420 00:47:37,150 --> 00:47:43,330 explain to them of like oh how what how people respond in terms of symptoms and. 421 00:47:45,370 --> 00:47:52,990 So it was it was in a way, it was in a way it like nice as a topic to talk about, you know what I mean? 422 00:47:53,710 --> 00:47:57,010 Like communicable medicine expertise. I had some expertise. 423 00:47:57,540 --> 00:48:04,719 Yeah. Yeah. I became I became popular within my family group in comes when it comes to COVID. 424 00:48:04,720 --> 00:48:10,870 Yeah. Otherwise the whole thing, it was just like the only thing we talk about is just about food. 425 00:48:11,800 --> 00:48:15,430 There's finally another topic we can talk about. Yeah. Mhm. 426 00:48:16,180 --> 00:48:22,030 And, um. And what was your I mean what was your living situation and. 427 00:48:22,420 --> 00:48:25,960 Yeah, but were you in a shared house. So were you by yourself or. 428 00:48:26,260 --> 00:48:30,190 Yeah, I was, I was at the beginning. 429 00:48:30,190 --> 00:48:36,430 I was live living in with the, with, with just one other person and I was my landlord and, and I, 430 00:48:36,460 --> 00:48:45,640 and then I decided that like no I need to move houses because it's not really, not really nice to be living in that situation. 431 00:48:46,330 --> 00:48:50,040 So I moved moved to further down the road and, 432 00:48:50,040 --> 00:48:56,440 and having a house with another four people and that was also just happened to be what I could afford at the time. 433 00:48:57,040 --> 00:49:03,189 So yeah, I moved, moved into that house and I would and I made this and I made them aware that I hey, 434 00:49:03,190 --> 00:49:08,259 I'm, I'm part of this college study and they were okay with it. 435 00:49:08,260 --> 00:49:16,120 And in fact, another person of of mine, another housemate of mine, she was the vaccine researcher at that time. 436 00:49:16,450 --> 00:49:21,660 And so, yeah, it turned out to be a turn out to be really, really nice. 437 00:49:21,670 --> 00:49:32,380 And uh, that I joined that house and it was, it was also a really good decision because it during the period of a very isolated time in COVID, 438 00:49:33,640 --> 00:49:37,300 we as we as a house were very supportive towards each other. 439 00:49:38,410 --> 00:49:42,910 One of the house my he, he worked at the Board Game cafe. 440 00:49:43,480 --> 00:49:46,570 So we will have the opportunity to play board games at home. 441 00:49:47,380 --> 00:49:50,590 So it was a very good social support at that time. 442 00:49:50,920 --> 00:49:59,530 Um, yeah. So living situation was okay. I was, I was careful most of the time just trying to clean up before before I get back home. 443 00:49:59,590 --> 00:50:00,400 Yeah. Yeah. 444 00:50:00,610 --> 00:50:09,909 And they were really consider the considerate um, I was really lucky that, that, I mean the work itself you said was intense and and quite stressful. 445 00:50:09,910 --> 00:50:13,389 Yeah. Yeah. Do you think the fact that you were working on something that was important, 446 00:50:13,390 --> 00:50:18,640 that was contributing to our understanding of this disease helped to support your own well-being? 447 00:50:18,760 --> 00:50:22,630 Yeah. Yeah, certainly. I think. I think that was a special thing to do. 448 00:50:23,350 --> 00:50:26,710 I think that was very important to do. Yeah. 449 00:50:26,950 --> 00:50:33,460 And. And I knew it. Not everybody will be part of the, we'll be part of this experience. 450 00:50:34,070 --> 00:50:42,810 Um, I was in a, in a way now, looking back, really proud that I had made a decision to, to stay honestly. 451 00:50:43,000 --> 00:50:48,040 Mhm. Yeah. So I think we're nearly at the end of the time. 452 00:50:48,340 --> 00:50:57,790 Um, has your experience of working through the pandemic changed your attitude or your approach to your work and your plans for the future? 453 00:51:00,590 --> 00:51:03,770 Um, probably yes and no. 454 00:51:03,770 --> 00:51:06,950 I think I'm consciously did changed the way that I work. 455 00:51:06,960 --> 00:51:11,060 I became really flexible and became okay with things going wrong. 456 00:51:13,550 --> 00:51:21,110 But no, but no, because I really was in early on in my in my career, I knew that there will be changes. 457 00:51:21,740 --> 00:51:26,860 So, yeah, I guess it is a yes or no together. 458 00:51:27,180 --> 00:51:32,630 Yeah. Mhm. Yeah. But I have to say regardless it was a it was a good experience to have, 459 00:51:33,080 --> 00:51:41,720 although like it's a it's a huge part of my twenties gone socially but like it's, it's, it's good to. 460 00:51:42,500 --> 00:51:47,090 For my early career I would say so and I said I should last this before you've 461 00:51:47,090 --> 00:51:50,140 now had an experience of what it's like working in a commercial company. 462 00:51:50,150 --> 00:51:53,390 Yeah, but also in an academic environment. Yeah. 463 00:51:53,840 --> 00:51:57,260 Which way do you think your career will go in the future? 464 00:51:57,260 --> 00:52:07,580 Will go in the future? Um, I'm, I'm leaning more towards at a corporate setting and in an industry setting. 465 00:52:08,600 --> 00:52:12,060 Um. Mhm. 466 00:52:12,780 --> 00:52:18,630 Yeah. I'm more leaning towards that. And actually this is not necessarily because uh. 467 00:52:19,050 --> 00:52:21,090 It's not necessarily because. 468 00:52:22,230 --> 00:52:33,420 Because my experience in in perspective and changed the way that I think it's probably because that's just my nature is when I Yeah. 469 00:52:33,430 --> 00:52:39,500 Growing up because I knew I am someone who really like to get engaged. 470 00:52:39,550 --> 00:52:49,080 People talk about like big stuff, talk of all the impactful stuff and had the opportunity to really make things like come into play. 471 00:52:49,800 --> 00:52:56,640 Uh, yeah, that's just, that's just probably based on me, personality wise and strength wise. 472 00:52:56,760 --> 00:53:00,450 I think industry will be a good fit for me. Yeah. 473 00:53:01,020 --> 00:53:03,837 Right. Yeah, I very much. Thank you.