WEBVTT 1 00:00:00.240 --> 00:00:02.399 Oh hey, it's your co worker that you had a 2 00:00:02.480 --> 00:00:05.120 dream about, who you will never tell what the dream 3 00:00:05.200 --> 00:00:09.199 was about. Allie ward back Ologies. This is an ology 4 00:00:09.240 --> 00:00:12.080 you've likely never even heard of. It was invented just 5 00:00:12.199 --> 00:00:15.560 around the turn of the century when y two K 6 00:00:15.679 --> 00:00:19.679 fears were big eyebrows were within systems biology. It's only 7 00:00:19.679 --> 00:00:23.039 been around about twenty years in name, and the National 8 00:00:23.079 --> 00:00:26.559 Institutes of Health says that different labs define it differently, 9 00:00:26.600 --> 00:00:29.359 but at its core, you ready for this here it is. 10 00:00:29.600 --> 00:00:33.359 It's an approach in biomedical research to understanding the larger picture, 11 00:00:33.840 --> 00:00:36.280 be it at the level of an organism, tissue, or cell, 12 00:00:36.640 --> 00:00:39.960 by putting its pieces together. It's like detective work, but 13 00:00:40.079 --> 00:00:42.920 with math and computers and graphs and stuff. And I'd 14 00:00:42.920 --> 00:00:45.320 put money on at least one of you who have 15 00:00:45.439 --> 00:00:48.479 never heard of it before falling in love with it 16 00:00:48.560 --> 00:00:51.119 and becoming this type of ologist in the future. But 17 00:00:51.200 --> 00:00:54.759 before that, gamble, Let's thank everyone at patreon dot com 18 00:00:54.799 --> 00:00:59.000 slash ologies for supporting the show. It costs one cool 19 00:00:59.119 --> 00:01:03.759 American dollar a month to join and you can submit questions. Also, 20 00:01:03.799 --> 00:01:07.599 thanks Spotify for having us as your number one science 21 00:01:07.640 --> 00:01:11.760 podcast on there. Hot dang. Whoever thought not me. We 22 00:01:11.799 --> 00:01:14.200 stay up in the charts thanks to every kind soul 23 00:01:14.239 --> 00:01:17.840 who leaves us ratings and reviews like this one from 24 00:01:18.200 --> 00:01:21.239 Will Gollahue on Apple Podcasts, who wrote, this show is 25 00:01:21.280 --> 00:01:24.719 like a red carpet premiere with scientists instead of celebrities, 26 00:01:24.719 --> 00:01:27.200 and I just can't get enough. I'm glad you can't, 27 00:01:27.359 --> 00:01:29.680 because we have more for you in this episode. Will 28 00:01:29.719 --> 00:01:31.879 value you. Okay, So this ologist and I we met 29 00:01:31.920 --> 00:01:34.920 via Twitter last year. She wrote some really thought provoking 30 00:01:35.000 --> 00:01:38.560 articles on the robotics scene in Pittsburgh and how errant 31 00:01:38.959 --> 00:01:42.480 delivery rovers cause a lot of problems for wheelchair users 32 00:01:42.599 --> 00:01:46.959 like herself, and she has written extensively about accessibility in STEM. 33 00:01:47.359 --> 00:01:51.519 She has a PhD and chemical engineering, where she used 34 00:01:51.599 --> 00:01:54.840 data and math and modeling to figure out what the 35 00:01:54.879 --> 00:01:57.680 fuck happens in the body when we're infected with a 36 00:01:57.760 --> 00:02:01.239 virus like the flu, and what drugs might work best 37 00:02:01.239 --> 00:02:03.719 for whom. We recorded this while she was still in 38 00:02:03.760 --> 00:02:07.840 the throes of finishing her dissertation. But now this doc 39 00:02:08.000 --> 00:02:10.360 is off to Cambridge to start postdoc work at a 40 00:02:10.400 --> 00:02:14.199 little place called Harvard Medical School and it's the Systems 41 00:02:14.199 --> 00:02:18.639 biology department there. She is smart, kind, funny, brilliant, not 42 00:02:18.759 --> 00:02:21.759 at all a slacker. More on that later, So count 43 00:02:21.879 --> 00:02:27.080 your lucky stars. You're about to learn about mathematics, computational science, excel, curses, 44 00:02:27.360 --> 00:02:34.919 career pivots, accessibility, identity, genomics, crisper soapboxes, science, and more 45 00:02:35.080 --> 00:02:40.680 with Advocate, Scholar and systems biologist doctor Emily Ackerman. 46 00:03:00.039 --> 00:03:01.719 Emily Ackerman her. 47 00:03:01.639 --> 00:03:07.159 Pronouns, she her cool. And now you are a systems biologist, 48 00:03:07.280 --> 00:03:08.479 correct I am? 49 00:03:09.080 --> 00:03:13.560 I mean by my own definition, I'm a chemical engineer 50 00:03:13.560 --> 00:03:16.879 by training, but most chemical engineers don't want to do 51 00:03:17.000 --> 00:03:21.000 chemical engineering, so we do other stuff. And my other 52 00:03:21.120 --> 00:03:24.120 stuff of choice is biology. 53 00:03:24.159 --> 00:03:27.680 When you say chemical engineering, what exactly does that encompass? 54 00:03:27.840 --> 00:03:31.280 Chemical engineering is very broad. We always think of it 55 00:03:31.319 --> 00:03:35.319 as the movement of heat, mass, and energy. It's been 56 00:03:35.360 --> 00:03:41.520 around forever and it hasn't changed in forever. So like 57 00:03:41.599 --> 00:03:45.919 the core curriculum that you learn is like transport, and 58 00:03:46.039 --> 00:03:49.280 they're more dynamics, and that hasn't changed in like one 59 00:03:49.400 --> 00:03:54.919 hundred years. So I'm in the more biological area. There's 60 00:03:54.960 --> 00:04:00.840 also the energy area where people do alternatives of energies 61 00:04:00.879 --> 00:04:04.759 and fuels batteries, and then they also do things like 62 00:04:05.360 --> 00:04:07.960 solar or biofuels and things. 63 00:04:08.599 --> 00:04:12.759 So her chemical engineering department focused on petroleum and fuels, 64 00:04:12.800 --> 00:04:15.840 but she didn't work with petroleum. Her work involved more 65 00:04:16.079 --> 00:04:21.600 living things. But you've always loved biology too, Yeah, yeah. 66 00:04:21.759 --> 00:04:28.959 Yeah, I love It's so cool. It's such a mystifying place, 67 00:04:29.720 --> 00:04:31.000 at least to me. 68 00:04:32.600 --> 00:04:35.560 Where did that start? Was it bird watching or was 69 00:04:35.600 --> 00:04:41.439 it documentaries about bugs? Or where did you start? You know, 70 00:04:41.600 --> 00:04:43.279 did you have a microscope growing up? Where did you 71 00:04:43.319 --> 00:04:45.519 start to get really interested in the natural world. 72 00:04:45.920 --> 00:04:51.639 So, being disabled and having like medical conditions, I've always 73 00:04:51.639 --> 00:04:56.079 found the body very interesting and kind of understanding the 74 00:04:56.120 --> 00:04:59.720 ways that line is different has led me to kind 75 00:04:59.720 --> 00:05:04.560 of for a lot of biology from like a younger age. 76 00:05:04.560 --> 00:05:08.160 I think once I got to kind of high school, 77 00:05:08.160 --> 00:05:12.399 when you really start learning and deciding what you want 78 00:05:12.439 --> 00:05:16.600 to do, I guess we force sixteen year olds to 79 00:05:16.680 --> 00:05:20.759 decide to do it the lot. It was like a 80 00:05:20.879 --> 00:05:26.680 very interesting thing to me, But the definitions of types 81 00:05:26.680 --> 00:05:30.399 of engineerings were like a real mystery to me and 82 00:05:30.439 --> 00:05:34.279 I think for most people. So I chose chemical based 83 00:05:34.279 --> 00:05:38.439 on the fact that I liked chemistry, but I didn't 84 00:05:38.519 --> 00:05:42.600 want to do like lab science, and so I thought, okay, 85 00:05:42.600 --> 00:05:43.240 I'll do more. 86 00:05:43.120 --> 00:05:47.199 Math, she says. At sixteen, she thought, hey, math sounds 87 00:05:47.199 --> 00:05:49.839 like a good thing to commit to. Math will always 88 00:05:49.839 --> 00:05:52.800 be there for you, and math is in everything. It's 89 00:05:52.839 --> 00:05:56.399 all around us, like ghosts who make sense and have 90 00:05:56.519 --> 00:05:56.959 our back. 91 00:05:57.439 --> 00:06:02.040 So I went into chemical engineering and slowly migrated more 92 00:06:02.079 --> 00:06:06.360 toward biology when I realized it was way more interesting. 93 00:06:07.560 --> 00:06:11.040 And you in order to be a biologist, and in 94 00:06:11.040 --> 00:06:15.120 the biological sciences, there's a ton of patterns and math 95 00:06:15.279 --> 00:06:20.560 and chemistry that needs understanding, right for sure. I mean 96 00:06:20.600 --> 00:06:23.360 my type of biology is like I sat on a 97 00:06:23.399 --> 00:06:25.959 bench and I drew a picture of a mushroom, because 98 00:06:26.040 --> 00:06:31.639 I'm not very gifted in the other way. But there 99 00:06:31.680 --> 00:06:34.399 need to be people like you who also can do 100 00:06:34.560 --> 00:06:38.439 applied topology and a lot of words I don't understand, 101 00:06:38.519 --> 00:06:40.680 which I understand is on your CV, and I don't 102 00:06:40.680 --> 00:06:44.040 even under know what topology is. But like, so, how 103 00:06:44.160 --> 00:06:47.879 is how does like math and systems and patterns? How 104 00:06:48.040 --> 00:06:51.839 do you get to apply that to the natural world? 105 00:06:52.959 --> 00:06:56.360 Yeah, it's really I think a lot about I mean 106 00:06:56.399 --> 00:07:02.959 the body, specifically the human body, and I specifically work 107 00:07:03.000 --> 00:07:08.360 with the immune system, something that like the rest of 108 00:07:08.399 --> 00:07:13.399 your body is in a very kind of precarious balance 109 00:07:13.600 --> 00:07:17.759 at all times, and the only time you really notice 110 00:07:17.800 --> 00:07:21.439 it is when it's out of whack. You're sick and 111 00:07:21.560 --> 00:07:25.600 your body is trying to compensate, so it starts giving 112 00:07:25.639 --> 00:07:29.959 you a fever and you start trying to cough anddo 113 00:07:30.040 --> 00:07:32.759 all kinds of things to get rid of it. That's 114 00:07:32.800 --> 00:07:37.000 really the definitive example for me of kind of how 115 00:07:37.079 --> 00:07:41.000 much we rely on maths to exist, but we don't 116 00:07:41.000 --> 00:07:45.079 think about it. So what's happening is that, really your 117 00:07:45.160 --> 00:07:49.839 body is the math is this few like things are 118 00:07:49.879 --> 00:07:53.920 out of balance. There's too much of something, or too 119 00:07:53.959 --> 00:07:58.160 little of something, or even it showed up six hours 120 00:07:58.199 --> 00:08:04.360 too late, whether it's your your T cells or something 121 00:08:04.360 --> 00:08:07.120 that you need to fight an infection, or even that 122 00:08:07.160 --> 00:08:09.920 a gene doesn't get turned on. It's really an interesting 123 00:08:10.040 --> 00:08:14.720 kind of view of math, and we can use math 124 00:08:14.839 --> 00:08:20.040 to describe all of the relationships within ourselves and all 125 00:08:20.079 --> 00:08:23.240 of the interactions happening that kind of keep us alive, 126 00:08:24.360 --> 00:08:26.600 which is really really cool. 127 00:08:27.879 --> 00:08:32.720 I heartily agree on that staying alive is on my 128 00:08:32.960 --> 00:08:41.720 coolst And if someone isn't sure what systems biology is 129 00:08:41.759 --> 00:08:44.279 and you have to describe it to them, how do 130 00:08:44.320 --> 00:08:46.320 you put such a big thing in such a small nutshell. 131 00:08:46.720 --> 00:08:54.080 Yeah, systems biology is I like to think of systems 132 00:08:54.080 --> 00:09:00.519 biology as the Frankenstein of biology. It's the very young, 133 00:09:01.039 --> 00:09:05.759 most definitions you would probably see like popping up twenty 134 00:09:05.919 --> 00:09:10.679 thirty years ago. It's really the result of having huge 135 00:09:10.799 --> 00:09:15.840 amounts of data and needing to process it and trying 136 00:09:15.879 --> 00:09:18.519 to do it in a way that you get a 137 00:09:18.559 --> 00:09:24.440 better system view. So, for example, you can invent algorithms 138 00:09:24.559 --> 00:09:29.120 to understand it, you can make models of it, and 139 00:09:29.159 --> 00:09:33.320 the goal is that you get kind of this picture 140 00:09:33.399 --> 00:09:36.600 that you wouldn't get from just doing an experiment. So 141 00:09:36.960 --> 00:09:40.320 if I want to understand the immune response, which just 142 00:09:40.320 --> 00:09:44.639 what I do. I take data from real mice and 143 00:09:45.120 --> 00:09:51.039 I try to represent it with math or to work backwards. 144 00:09:51.080 --> 00:09:55.559 If I don't understand really what's biologically happening, maybe I 145 00:09:55.600 --> 00:09:59.679 can find some math that fits it, and I'd say, oh, well, 146 00:09:59.679 --> 00:10:03.720 then the must be what's happening. It must be these 147 00:10:03.759 --> 00:10:09.480 two things interacting causing us. And well. The great things 148 00:10:09.519 --> 00:10:12.879 about what we do is that there's so much data 149 00:10:13.480 --> 00:10:17.759 out just in the world. But if you have questions, 150 00:10:18.200 --> 00:10:22.559 you can sometimes just find data to help you answer them. 151 00:10:22.559 --> 00:10:25.279 And that's kind of what you see happening with COVID. 152 00:10:25.639 --> 00:10:30.759 There's this really huge effetsis on making data publicly available 153 00:10:30.919 --> 00:10:35.240 and easy to use, which is a great that's a 154 00:10:35.240 --> 00:10:39.120 great effect on the kind of scientific endeavor that I love. 155 00:10:39.559 --> 00:10:44.600 So doctor Ackerman had analyzed infectious disease and influenza strains, 156 00:10:44.840 --> 00:10:47.519 but while getting her PhD at the University of Pittsburgh, 157 00:10:47.639 --> 00:10:50.879 she did a little pivot to a different virus. You 158 00:10:51.000 --> 00:10:53.639 probably have not heard a lot about. It's called SARS. 159 00:10:53.720 --> 00:10:56.559 COVID too, just an intro to it. 160 00:10:56.879 --> 00:10:57.159 JK. 161 00:10:57.799 --> 00:11:01.200 So I was eating fistfuls of sour dough all through 162 00:11:01.200 --> 00:11:04.960 twenty twenty and watching people make out on Outlander, but 163 00:11:05.039 --> 00:11:08.320 she was spending the pandemic trying to help us understand 164 00:11:08.440 --> 00:11:10.919 the pandemic while getting a PhD. 165 00:11:11.480 --> 00:11:13.639 I used to work only with the flu. Now I 166 00:11:13.720 --> 00:11:16.480 work with COVID nineteen. 167 00:11:16.960 --> 00:11:18.519 Heard of it, heard of it making headlines? 168 00:11:18.600 --> 00:11:22.559 Yeah, I've seen that. And so basically my group deals 169 00:11:22.600 --> 00:11:27.159 with viol respiratory infection. For the most part. I have 170 00:11:27.399 --> 00:11:33.240 kind of to major kind of projects. The first is 171 00:11:33.320 --> 00:11:38.320 trying to identify important proteins that we could use as 172 00:11:38.399 --> 00:11:41.759 drug targets and to do that I use network topology 173 00:11:42.679 --> 00:11:48.039 and analysis, which is a very large scale like zoomed 174 00:11:48.039 --> 00:11:51.879 out view of a cell. And then my other project 175 00:11:52.519 --> 00:11:57.000 is a very specific zoomed in view where I write 176 00:11:58.000 --> 00:12:03.519 kind of mathematic equations to try to understand the dynamics 177 00:12:03.559 --> 00:12:08.279 of the AMAT response, so the timing and the kind 178 00:12:08.320 --> 00:12:12.960 of magnitude of response, and how that differs between say, 179 00:12:13.159 --> 00:12:18.159 strains of the flu, or between males and females, or 180 00:12:18.200 --> 00:12:22.960 any kind of relationship, in hopes of better treatment strategies, 181 00:12:23.840 --> 00:12:27.759 better understanding of disease as a whole, because I think 182 00:12:27.799 --> 00:12:29.840 we we don't have a great idea what's going on, 183 00:12:31.399 --> 00:12:35.320 and just kind of better understanding so that we can 184 00:12:35.440 --> 00:12:37.200 better address the infection. 185 00:12:38.600 --> 00:12:41.320 How was that pivot? How much of you had to 186 00:12:41.360 --> 00:12:44.600 pivot your research to COVID, which, by the way, that's 187 00:12:44.759 --> 00:12:49.039 amazing that you're working on it. Thank you, yeah, thank 188 00:12:49.080 --> 00:12:51.279 you for doing that on behalf of like me and 189 00:12:51.720 --> 00:12:55.200 literally the world. What was that pivot like for you? 190 00:12:55.279 --> 00:12:58.000 Was it exciting? Was it daunting? Was it really different 191 00:12:58.000 --> 00:13:00.159 from the flu? 192 00:13:01.000 --> 00:13:04.120 A lot? At once? When it hit I realized that 193 00:13:04.240 --> 00:13:09.039 I could very easily apply the network study methods to 194 00:13:09.840 --> 00:13:14.039 sarrus CO two. I did it, and it was just 195 00:13:13.600 --> 00:13:17.240 this giant whirlwind of like trying to get things, so 196 00:13:17.440 --> 00:13:22.240 it was it's it's very stressful to be working under 197 00:13:22.279 --> 00:13:25.600 that kind of clime restream, kind of a magnitude of 198 00:13:25.639 --> 00:13:32.519 these problems. It's kind of overwhelming, but it's really exciting 199 00:13:32.600 --> 00:13:35.159 at the same time to be able to help and 200 00:13:35.240 --> 00:13:38.639 contribute in the best way I know how. And it's 201 00:13:38.639 --> 00:13:42.279 been a really interesting make lemons out of lemonade opportunity. 202 00:13:43.440 --> 00:13:46.039 That's not even the phrase, what is it make lemonade 203 00:13:46.039 --> 00:13:47.440 out of lemon I was give the. 204 00:13:47.519 --> 00:13:52.639 Lemons tomato tomato when life throws tomatoes at you, make salsa. 205 00:13:52.759 --> 00:13:57.159 Science is just all about confronting setbacks head on, piecing 206 00:13:57.159 --> 00:13:59.919 things together with the info. We do have an adapting 207 00:14:00.080 --> 00:14:04.159 to new circumstances. That's why it's high drama behind the 208 00:14:04.240 --> 00:14:05.919 scenes and we love it. 209 00:14:06.039 --> 00:14:12.840 The problem when such a novel virus, we don't even 210 00:14:12.879 --> 00:14:17.600 know what it looks like, and it's different for every virus. 211 00:14:18.519 --> 00:14:23.799 They'll have kind of different evasion mechanisms or ways that 212 00:14:23.840 --> 00:14:25.320 they try to hide themselves. 213 00:14:25.519 --> 00:14:29.360 And what does your work look like like? If you 214 00:14:29.399 --> 00:14:34.120 were to say, like take your ologies host to work day, 215 00:14:34.200 --> 00:14:36.679 what is it is? It like I picture, Okay, tell 216 00:14:36.759 --> 00:14:41.000 me if I'm wrong. I picture that you have like 217 00:14:41.840 --> 00:14:45.279 six computer monitors, and it's like when you walk into 218 00:14:45.320 --> 00:14:48.519 like the control room at NASA and it's all spreadsheets 219 00:14:48.519 --> 00:14:52.720 and like minority report, like and you have maybe several 220 00:14:52.840 --> 00:14:57.000 different input devices like mouses or keyboards or lasers, and 221 00:14:57.039 --> 00:14:59.440 it's just numbers flying by. And if I were there, 222 00:14:59.519 --> 00:15:01.679 I would just be trembling in a corner, being like, 223 00:15:01.840 --> 00:15:04.200 how do you keep track of all the numbers? Is 224 00:15:04.240 --> 00:15:05.080 that correct? 225 00:15:05.559 --> 00:15:12.879 To a certain extent, I've got to monitors, okay, very 226 00:15:12.919 --> 00:15:16.279 high up in the world. To a lot of the 227 00:15:16.320 --> 00:15:22.120 raise five cups of coffee and two keyboys because I 228 00:15:22.159 --> 00:15:25.200 spilled a full cup of coffee on my laptop last year, 229 00:15:26.879 --> 00:15:32.320 so that's sound great. But yeah, I get told a 230 00:15:32.320 --> 00:15:36.360 lot that it looks very scary because I have I 231 00:15:36.440 --> 00:15:40.159 learned to code from like an old man who's been 232 00:15:40.200 --> 00:15:44.480 coding since cody existed, and so I code like in 233 00:15:44.519 --> 00:15:48.039 the terminal and like the worst visual way, and it 234 00:15:48.120 --> 00:15:50.919 looks very scary, and people tell me all the time 235 00:15:51.279 --> 00:15:56.159 that it looks horrifying, But yeah, it's you're not too 236 00:15:56.240 --> 00:16:03.559 far off, except it's it's less less funded. I knew it, okay, 237 00:16:03.919 --> 00:16:07.200 just like one hundred thousand dollars. 238 00:16:09.960 --> 00:16:12.679 Takes some funding away. Who was the Who was the 239 00:16:12.720 --> 00:16:14.480 old man that taught you to code? I picture like 240 00:16:14.480 --> 00:16:16.559 an old sailor in a park with a with an 241 00:16:16.600 --> 00:16:17.360 ancient laptop. 242 00:16:17.840 --> 00:16:25.039 Didn't He's very much like the daddest dad that ever? 243 00:16:25.159 --> 00:16:29.320 Did you? 244 00:16:29.519 --> 00:16:29.960 Just Doug? 245 00:16:30.440 --> 00:16:34.279 You know, if anyone out there knows a very paternal 246 00:16:34.360 --> 00:16:36.679 guy named Doug who has taught people to code, tell 247 00:16:36.720 --> 00:16:41.000 him I love him? Am I exaggerating? I love him? 248 00:16:41.120 --> 00:16:42.559 Yeah? I miss him. 249 00:16:42.759 --> 00:16:44.240 Do you dream in code at all? 250 00:16:45.720 --> 00:16:48.519 No? But I have dreamed about COVID, and I've dreamed 251 00:16:48.559 --> 00:16:54.600 about like just school things in general. It's a terrible experience. 252 00:16:54.919 --> 00:16:59.519 Oh no, let's move on from nightmares to flim flam 253 00:17:00.000 --> 00:17:01.200 stems biology style. 254 00:17:01.720 --> 00:17:14.039 Oh. I guess like that we spend all of our time, 255 00:17:15.240 --> 00:17:20.440 like actively coding is like the biggest thing. I spend 256 00:17:20.519 --> 00:17:24.880 most of my time either waiting the code to them 257 00:17:25.160 --> 00:17:31.480 to take like days, or googling the same error code 258 00:17:32.400 --> 00:17:38.720 in different ways, or downloading Excel files of data and 259 00:17:38.759 --> 00:17:43.680 then searching for the one gene that is the same 260 00:17:43.720 --> 00:17:47.759 as a date, so Excel like converts it to a 261 00:17:47.880 --> 00:17:50.440 date and then you end up with like errors in 262 00:17:50.480 --> 00:17:55.319 your in your code, because yeah, stept four is my 263 00:17:55.519 --> 00:17:56.240 mortal enemy. 264 00:17:58.720 --> 00:18:00.559 Side note, of course I had to look this up, 265 00:18:00.720 --> 00:18:03.880 but Sept four means sept in four and it's a 266 00:18:03.920 --> 00:18:07.480 protein that in humans is encoded by the sept four gene, 267 00:18:07.759 --> 00:18:11.000 which also reminded me of the meme, which is a 268 00:18:11.119 --> 00:18:16.480 Venn diagram of excel and in cells, both incorrectly. Assuming 269 00:18:16.559 --> 00:18:17.799 everything is a date. 270 00:18:19.160 --> 00:18:22.640 It hurts so good, but the amount of time I 271 00:18:22.680 --> 00:18:27.400 spent actually writing going is very embarrassing. 272 00:18:28.160 --> 00:18:31.240 Are there moments where you run data or run an 273 00:18:31.279 --> 00:18:36.480 algorithm or applied something computational to see if it fits 274 00:18:36.559 --> 00:18:39.680 with data and it works? Like does your screen light 275 00:18:39.799 --> 00:18:42.680 up like a gold glitter? Like what happens when that's 276 00:18:43.599 --> 00:18:44.440 when it works? 277 00:18:47.000 --> 00:18:54.519 I stop crying. Yeah, I mean there's a problem in systems, biology, 278 00:18:55.359 --> 00:19:01.559 more computational fields where you don't always have validation for 279 00:19:01.640 --> 00:19:06.240 your answer. Maybe you need more data to prove that 280 00:19:06.319 --> 00:19:11.240 it's correct, or you have to very carefully design training 281 00:19:11.319 --> 00:19:16.519 sets and things to prove that you have actually done something. 282 00:19:17.519 --> 00:19:23.680 So I can feel a little unrewarding, but sometimes it's 283 00:19:23.759 --> 00:19:27.039 the other way I'm around. You're fitting to data that 284 00:19:27.160 --> 00:19:30.319 ivy exists or you have a way to validate it. 285 00:19:30.799 --> 00:19:33.799 So sometimes it just points you down the path, but 286 00:19:33.880 --> 00:19:36.519 you're not quite to the destination yet. But at least 287 00:19:36.519 --> 00:19:39.160 you know that your work isn't a mess. Are you 288 00:19:39.240 --> 00:19:44.720 a person that is super organized and analytical in the 289 00:19:44.720 --> 00:19:46.920 rest of your life? Are you like a person like 290 00:19:47.240 --> 00:19:50.640 friends go to with computational questions, or are you like 291 00:19:50.720 --> 00:19:53.279 I save that for work and I let the rest 292 00:19:53.279 --> 00:19:54.440 of my life be loosey goosey. 293 00:19:55.000 --> 00:19:59.759 I'm a little bit of a unorganized I'm a very 294 00:20:00.039 --> 00:20:05.440 stectful person. I love having a schedule, I love having 295 00:20:05.519 --> 00:20:14.720 rules to follow. Always rules me. Yeah, but I'm also 296 00:20:15.799 --> 00:20:19.640 known as like not in a serious way, but like 297 00:20:20.079 --> 00:20:22.759 the one who does not for a living, but is 298 00:20:22.759 --> 00:20:28.039 a very little bit what like, I'm always doubting. 299 00:20:27.720 --> 00:20:32.240 My Do people ever tell you to stop doubting your 300 00:20:32.240 --> 00:20:34.599 ability to do math because you're probably so much better 301 00:20:34.640 --> 00:20:35.759 at it than other people. 302 00:20:37.480 --> 00:20:42.400 Yeah, I need like constant reminders. I got this one. 303 00:20:42.839 --> 00:20:46.240 You mentioned something too about about disability and STEM and 304 00:20:46.640 --> 00:20:49.680 I'm wondering, is there anything that you you wish you 305 00:20:49.839 --> 00:20:52.400 do kind of coming up that you you wish other 306 00:20:52.480 --> 00:20:57.400 people in STEM with Maybe any kind of disabilities new Oh. 307 00:20:57.240 --> 00:21:03.359 Yeah, so many things. I think, what do I want 308 00:21:03.400 --> 00:21:03.759 them to know? 309 00:21:04.799 --> 00:21:05.839 Sorry, that's a big question. 310 00:21:06.319 --> 00:21:10.839 No, I mean it's this is what I really am, 311 00:21:10.880 --> 00:21:15.359 like so so practicous. I think when I was when 312 00:21:15.359 --> 00:21:21.000 I went to college, I was very unsure. Like most, 313 00:21:21.400 --> 00:21:25.359 I think college students are what they want to do 314 00:21:25.519 --> 00:21:29.480 or what they care about. I think one thing that 315 00:21:29.680 --> 00:21:38.839 is them particular is the fear that you that like 316 00:21:38.960 --> 00:21:41.480 STEM isn't made for you in a very physical way, 317 00:21:42.000 --> 00:21:46.759 but also in a there's this emphasis on working long hours, 318 00:21:47.440 --> 00:21:52.640 on kind of devoting yourself and therefore your body to 319 00:21:53.039 --> 00:21:58.559 the cause, whatever it's the cause you've chosen. And I 320 00:21:58.559 --> 00:22:02.640 guess what I would tell people is that's unhealthy and false. 321 00:22:04.240 --> 00:22:09.240 There's so much of a push to be a scientist 322 00:22:09.319 --> 00:22:13.359 or an engineer and to devote your whole self and 323 00:22:13.400 --> 00:22:16.640 it should be first. And I think what we know 324 00:22:16.920 --> 00:22:21.400 in the disability community is that our bodies, that our 325 00:22:21.440 --> 00:22:23.720 minds have to come first. And you can't do the 326 00:22:23.759 --> 00:22:28.119 science if your body's not there. Right so, and if 327 00:22:28.160 --> 00:22:30.559 you really want to be there, there has to be 328 00:22:30.599 --> 00:22:34.359 a way. So if you need to change your schedule, 329 00:22:34.400 --> 00:22:39.000 if you need to ask for accommodations and things because 330 00:22:39.039 --> 00:22:43.440 you want to be there. That's you are so in 331 00:22:43.480 --> 00:22:45.920 the right to do that, and there's always a way 332 00:22:46.079 --> 00:22:49.400 that you can get to it. When I the reason 333 00:22:49.440 --> 00:22:54.359 I do computational work is that I am very weak. 334 00:22:54.519 --> 00:22:58.079 I'm very small. I weigh like fifty pounds. I can 335 00:22:58.720 --> 00:23:01.839 lift like half a pound to a pound on a 336 00:23:01.839 --> 00:23:05.000 good day, and a lab is just not made for 337 00:23:05.160 --> 00:23:10.359 me in any way. It just will never work. And 338 00:23:10.920 --> 00:23:13.960 I knew that, and it's part of why I chose engineering. 339 00:23:15.000 --> 00:23:19.000 And when I got to college, I was just by 340 00:23:19.160 --> 00:23:24.160 chance kind of complaining to a professor about how I 341 00:23:24.319 --> 00:23:28.799 was a little bit upset that I felt that there 342 00:23:28.880 --> 00:23:32.599 was no opportunities for me to do research because it 343 00:23:32.680 --> 00:23:37.079 felt like my peers were doing research that was going 344 00:23:37.079 --> 00:23:40.759 to get them a grad school or a job, and 345 00:23:40.759 --> 00:23:45.640 that I wasn't able to do it. And he was like, well, 346 00:23:45.799 --> 00:23:51.119 don't you know anything about computational work, and I was like, nope, 347 00:23:52.000 --> 00:23:56.279 no way. He told me about that and he was like, oh, oh, 348 00:23:56.359 --> 00:23:58.480 you got to meet this guy un where I met 349 00:23:59.000 --> 00:24:03.400 my undergrad advisor, doctor Kirk Brenman, who does computational chemistry, 350 00:24:04.160 --> 00:24:07.519 and it was nothing like anything i'd ever learned. But 351 00:24:07.599 --> 00:24:11.759 I could do it anywhere, any time of day. You 352 00:24:11.839 --> 00:24:17.039 didn't involve lifting anything except my computer. And it was 353 00:24:17.079 --> 00:24:21.279 such an opportunity that I didn't know existed. And so 354 00:24:22.640 --> 00:24:27.160 I didn't know anyone else that was disabled, students or faculty, 355 00:24:28.160 --> 00:24:30.680 and so I really just had no idea that there's 356 00:24:30.720 --> 00:24:34.559 this whole world out there what I consider way more 357 00:24:34.559 --> 00:24:38.400 excessive to science. And so one tip I would definitely 358 00:24:38.400 --> 00:24:44.599 say is to explore computational science. It's such a cool area, 359 00:24:44.880 --> 00:24:48.000 and it's so much more accessible with the timing and 360 00:24:48.079 --> 00:24:55.359 the physical demands of it, and it's super cool and 361 00:24:55.440 --> 00:24:56.559 I want everyone to do it. 362 00:24:58.400 --> 00:25:02.359 That's so wonderful that just someone suggesting something like that 363 00:25:02.640 --> 00:25:05.039 can Yeah. You know, it's so funny that those moments 364 00:25:05.079 --> 00:25:06.880 in our lives are like, wait, I could do but 365 00:25:07.039 --> 00:25:07.640 I could do that? 366 00:25:08.160 --> 00:25:13.200 Do that? Yeah, And if I knew someone who was disabled, 367 00:25:14.079 --> 00:25:15.880 it probably would have been way more queer to me. 368 00:25:16.720 --> 00:25:19.599 At least I would have had some kind of hope 369 00:25:20.039 --> 00:25:23.279 that I could I could do it in the same 370 00:25:23.319 --> 00:25:27.519 way that life peers were just going up and asking 371 00:25:27.559 --> 00:25:32.559 for la positions. I am really passionate about not only 372 00:25:32.799 --> 00:25:37.440 like getting more people into STEM, but making it a 373 00:25:37.480 --> 00:25:42.200 place they can stay and foster the next generation of 374 00:25:43.160 --> 00:25:47.359 kids like I was, who had no idea what it 375 00:25:47.440 --> 00:25:50.200 what the future could even look like. I guess yes, 376 00:25:50.480 --> 00:25:55.279 it's so important that we make it equitable, because right 377 00:25:55.319 --> 00:25:56.440 now it's. 378 00:25:56.720 --> 00:26:01.799 About, Yeah, anything that would make it more equable, any 379 00:26:01.920 --> 00:26:05.119 kind of moves that others could make or that you 380 00:26:05.160 --> 00:26:07.200 would love to see made. 381 00:26:07.440 --> 00:26:13.799 Yeah, one big thing is just generally thinking about your 382 00:26:13.880 --> 00:26:21.720 lab space or your lab policies or leaving your classroom 383 00:26:21.799 --> 00:26:25.359 policies can be designed in a way that make it 384 00:26:25.400 --> 00:26:32.440 easier for disabled students and researchers to exist in your space. So, 385 00:26:32.559 --> 00:26:38.559 for example, if you're teaching class and your qualicy in 386 00:26:38.599 --> 00:26:43.960 this strange pandemic time is that you have to always 387 00:26:43.960 --> 00:26:46.960 have your video on and you have to show up 388 00:26:47.000 --> 00:26:50.119 to every zoom or you drop a lot of grade. Right, 389 00:26:51.319 --> 00:26:54.200 it's really difficult for a lot of us to attend 390 00:26:54.240 --> 00:26:58.680 every lecture on time when there's no difference between watching 391 00:26:58.680 --> 00:27:03.240 a recording of it and at any time. Or if 392 00:27:03.240 --> 00:27:08.960 your lab space. Most lab spaces aren't disgustingly inaccessible, but 393 00:27:09.039 --> 00:27:12.799 what can you do? You can not load all of 394 00:27:12.839 --> 00:27:17.400 your piet boxes and glub boxes and everything right inside 395 00:27:17.400 --> 00:27:19.759 the door, so that like I can't even enter a. 396 00:27:19.799 --> 00:27:23.519 Lab right And just a quick side note on identity 397 00:27:23.519 --> 00:27:27.400 and disability, so doctor Ackerman says she prefers identity first 398 00:27:27.640 --> 00:27:31.400 language she is a disabled person, rather than saying a 399 00:27:31.480 --> 00:27:34.359 person with a disability. And this discussion comes up in 400 00:27:34.400 --> 00:27:38.000 the disability community a lot. Many autistic folks prefer identity 401 00:27:38.039 --> 00:27:43.000