Alberto Stolfi, PhD
School of Biological Sciences
Georgia institute of Technology | LIVESTREAM

The adaptive radiation of our vertebrate ancestors likely depended on an increase in the complexity of their brains and motor units. Our research is focused on the molecular basis of neuromuscular development and function in our closest non-vertebrate relatives, the tunicates. Most tunicates live a “biphasic” life cycle that alternates between a swimming larva and a sessile, filter-feeding adult. We have revealed some of the gene regulatory networks that specify different larval motor and sensory neuron subtypes, some of which are proposed homologs of neurons found in vertebrate nervous systems. We have also identified specific cell types required to trigger larval settlement and metamorphosis in response to environmental cues, as well as neural stem cells that give rise to post-metamorphic neurons, after the pre-programmed elimination of the larval nervous system. Finally, we also show that the formation of multinucleated muscles specifically in adult tunicates requires post-metamorphic activation of the conserved muscle fusion factor Myomaker, indicating that this important gene arose in the last common ancestor of tunicates and vertebrates. Our findings have not only refined prevailing models of chordate and vertebrate evolution, but have also provided insights into basic principles of chordate neuromuscular development.

 

Host By: Dr. Greg Gibson

Event Details

Vanessa Sperandio, PhD

Robert Turell Professor of Medical Microbiology and Immunology And Department Chair

University of Wisconsin | LIVESTREAM

Gut-microbiota membership is associated with diverse neuropsychological-diseases, including substance use disorders (SUDs). Unravelling mechanistic interactions between gut microbes and the host during psychostimulant use remains challenging. Here we show that cocaine exposure increases intestinal levels of norepinephrine, sensed through the bacterial adrenergic receptor QseC to promote virulence and intestinal colonization of C. rodentium (a murine pathogen used as a surrogate animal model for EHEC), as well as intestinal colonization of commensal g-Proteobacteria. This shift in microbiota-composition depletes the neuroactive metabolite glycine (used as a nitrogen source by C. rodentium and/or g-Proteobacteria) in the gut and cerebrospinal fluid, enhancing host cocaine-induced behaviors. Glycine repletion reversed this response, and intestinal colonization by g-Proteobacteria unable to uptake glycine did not alter the host response to cocaine. Transcriptomic profiling indicates a role of microbiota modulated glycine levels in cocaine induced transcriptional plasticity in the nucleus accumbens through the glutamatergic transmission. Altogether, we introduce a mechanism by which intestinal bacteria alter the host’s brain responses to cocaine that could be exploited to modulate reward-related brain circuits that contribute to SUDs.

 

Host: Dr. Marvin Whiteley

Event Details

N/A

Event Details

The third class of Brook Byers Institute for Sustainable Systems (BBISS) Graduate Fellows has been selected.

The BBISS Graduate Fellows Program provides graduate students with enhanced training in sustainability, team science, and leadership in addition to their usual programs of study. Each 2-year fellowship is funded by a generous gift from Brook and Shawn Byers and is additionally guided by a Faculty Advisory Board. The students apply their skills and talents, working directly with their peers, faculty, and external partners on long-term, large team, sustainability relevant projects. They are also afforded opportunities to organize and host seminar series, develop their professional networks, publish papers, draft proposals, and develop additional skills critical to their professional success and future careers leading research teams.

The 2023 class of Brook Byers Institute for Sustainable Systems Graduate Fellows are:

  • Aminat A. Ambelorun - Ph.D. student, School of Earth and Atmospheric Sciences, College of Sciences, Advisor: Alex Robel
  • Min-kyeong (Min) Cha - Ph.D. student, School of Public Policy, Ivan Allen College of Liberal Arts, Advisor: Daniel Matisoff
  • Allannah Duffy - Ph.D. student, George W. Woodruff School of Mechanical Engineering, College of Engineering, Advisor: Srinivas Garimella
  • Eric Greenlee - Ph.D. student, School of Computer Science, College of Computing, Advisor: Ellen Zagura
  • Spenser Wipperfurth - Ph.D. student, Ocean Science and Engineering, organized by the Schools of Biology, Civil and Environmental Engineering, and Earth and Atmospheric Sciences, MBA, Scheller College of Business, Advisor: Kevin Haas

Additional information about the BBISS Graduate Fellows Program, and about the first class of BBISS Graduate Fellows is available at https://research.gatech.edu/sustainability/grad-fellows-program.

William Ratcliff, PhD
School of Biological Sciences
Georgia institute of Technology

LIVESTREAM

 

The origin of multicellularity was one of the most significant innovations in the history of life. Our understanding of the evolutionary processes underlying this transition remains limited, however, mainly because extant multicellular lineages are ancient and most transitional forms have been lost to extinction. We bridge this knowledge gap by evolving novel multicellularity in the lab, using the 'snowflake yeast' model system. In this talk, I'll focus on our ongoing Multicellular Long-Term Evolution Experiment (MuLTEE), in which we've put snowflake yeast through ~5,000 generations of selection for larger size and faster growth. We will examine key steps in the evolution of multicellularity, namely how multicellular traits arise and become heritable, how simple multicellular bodies evolve to become radically stronger and tougher, and how cells divide labor through differentiation. Overall, our approach allows us to examine how simple groups of cells can evolve to become increasingly integrated and organismal, providing novel insight into this major evolutionary transition. 

 

Host: Dr Greg Gibson

 

Event Details

It is valuable and rare to have someone care to invest their time and invest in you early in your career. Breanna Shi, a Ph.D. student in bioinformatics, was lucky to have had many inspiring mentors throughout her college career. Shi’s experience with mentors inspired her to pursue mentorship.  

“Being a mentor is my favorite part of my work,” said Shi. “I have learned so much about student psychology and my own psychology. As scientists, we can neglect the human experience it takes for us all to collaborate. I love thinking of new ways to improve the effectiveness of our communication so we all feel welcomed and valued in our scientific communities.”  

In 2022, Shi started a mentorship group, FishStalkers, which grew from five to 20 members in just one semester. Shi’s mentees have been offered competitive co-ops and internships, awarded prestigious fellowships, presented at research symposiums, and more.  

Shi provides her techniques for cultivating a positive and productive mentor-mentee connection. 

Instill confidence in your mentees. “Student researchers have a lot of helpful ideas,” said Shi. “They attend courses where they learn about the newest software and theories while you are held up in the lab. You need to try and access this information, but it’s not going to happen if you do not instill the confidence in them that their idea is worth your time, and that it’s okay if the idea doesn’t work out because the contribution is valuable.”  

  • Shi’s tips for instilling confidence include:  
    • Refer to mentees as “researcher” or “student researcher” to dissipate internal separations between undergraduates, master’s, and Ph.D. students working in the lab. 
    • Tell your mentees when they have taught you something new and when their work has gone above and beyond. 
    • Support mentees in pursuing their own goals to recognize their personhood. 

Lower the standards you set for yourself. “Most Ph.D. students are perfectionists, and they will put a lot of pressure on themselves in terms of responsibility to a mentee,” said Shi. “You don’t need to be perfect. In fact, if you are perfect around your mentees, you will probably just intimidate them.” 

According to Shi, this pressure can deter Ph.D. students from pursuing mentorship.  

“A lot of people will place barriers on themselves that they do not know enough, or they don’t have enough ‘good work’ for a mentee,” said Shi. “You will make mistakes as a mentor. You and your mentees as people will solve these miscommunications or issues. This is normal and healthy.”  

Humanize yourself. “Mentees often have an idealized perception of what a Ph.D. student is,” said Shi. “I will point out mistakes I have made in my work to students and encourage them to correct me if they have better information. I do not want to feel smart. I want to do good work and that requires criticism from other parties, including my mentees. Our goal is to increase the comfortability of the mentee while maintaining the professional boundary required of your role.”  

Facilitate situations where the mentee is empowered. “The important thing I focus on with my students is cross-training,” said Shi. “If one mentee has studied a software, they now become responsible for training other mentees and me. It helps to be intentional in teaching your mentees that knowledge can come from anyone. I think putting knowledge into a hierarchy is overblown and only serves to preserve the status of people at the top rather than allowing for new ideas.”  

Align mentor and mentee goals. “Goals should not conflict with one another, but this can happen if the mentor does not plan strategically,” said Shi. “The mentor needs to be transparent with what work the mentee needs to complete and the timeline. The mentor should inform the mentee of the amount of time the mentor has to assist the mentee and the appropriate method for contacting you when you need help. It is always best practice to be as specific with what you want rather than assume some ‘should know’ something.” 

Shi has created a mentorship document that outlines her expectations for all new student researchers.  

Communicate expectations. “We should communicate with each other the experience that we want from the relationship and work towards that goal,” said Shi. “You should align your students’ projects such that they are working towards something that advances your work. Sometimes, you will have motivated students who want to go off and do their own idea. That shows initiative in the student, but you should be direct with them that straying off into projects unrelated to your current research goals will mean that they will receive less oversight/feedback from you.” 

Provide positive feedback. “A lot of us analytical types may forget that we should point out tasks that are proceeding well along with the things that are going up in flames,” said Shi. “Recognizing quality mentee work is vital to them reproducing that quality of work again. They need to know when they have met your standards.” 

Provide critical feedback. “You will need to provide critical feedback to the mentee both on work and logistical miscommunications,” said Shi. “Do not shy away from this. If you are uncomfortable with discussing concerns on performance, this is normal, but by ignoring the issue you will deny the mentee from improving in this respect.” 

Shi’s procedure for handling performance issues involves gathering the facts, detangling your emotions, defining the solution, and sending them a message.  

For logistical, non-research issues, Shi recommends keeping records.  

“There is a lot of front-loaded work in creating documentation of expectations, but it really pays off in terms of not dealing with day-to-day logistical questions.” 

Understand the student researcher’s mindset. “Student researchers often feel insecure in navigating the lab equipment,” said Shi. “Sometimes, their perfectionism will cause them to ask you a lot of questions because they really want to impress you and do things correctly.”  

In these situations, Shi advises mentors to protect their own time while reassuring the mentee in their work. Let them know that you appreciate their effort to do things correctly, but part of research is independence, or let them know that you are unavailable to answer their question and provide a timeline for when they can expect to hear from you.  

Take the Tech to Teaching program and try your best! “I highly recommend this [Tech to Teaching] program to any Ph.D. student who has long-term goals of becoming a professor,” said Shi. “I want to emphasize something: you do not need formal training to be a mentor. If you are on the fence, try your best. You will learn the most about being a mentor by being a mentor. Listen to your mentee, balance your commitments, prioritize your time and goals, and you will be fine. There is the perception some people have that you need to mentor in a specific way. I do not agree with this mentality. I believe the scope of mentorship should be negotiated by the mentor and the mentee based on an alignment of goals.”  

It is valuable and rare to have someone care to invest their time and invest in you early in your career. Breanna Shi, a Ph.D. student in bioinformatics, was lucky to have had many inspiring mentors throughout her college career. Shi’s experience with mentors inspired her to pursue mentorship.  

“Being a mentor is my favorite part of my work,” said Shi. “I have learned so much about student psychology and my own psychology. As scientists, we can neglect the human experience it takes for us all to collaborate. I love thinking of new ways to improve the effectiveness of our communication so we all feel welcomed and valued in our scientific communities.”  

In 2022, Shi started a mentorship group, FishStalkers, which grew from five to 20 members in just one semester. Shi’s mentees have been offered competitive co-ops and internships, awarded prestigious fellowships, presented at research symposiums, and more.  

Shi provides her techniques for cultivating a positive and productive mentor-mentee connection. 

Instill confidence in your mentees. “Student researchers have a lot of helpful ideas,” said Shi. “They attend courses where they learn about the newest software and theories while you are held up in the lab. You need to try and access this information, but it’s not going to happen if you do not instill the confidence in them that their idea is worth your time, and that it’s okay if the idea doesn’t work out because the contribution is valuable.”  

  • Shi’s tips for instilling confidence include:  
    • Refer to mentees as “researcher” or “student researcher” to dissipate internal separations between undergraduates, master’s, and Ph.D. students working in the lab. 
    • Tell your mentees when they have taught you something new and when their work has gone above and beyond. 
    • Support mentees in pursuing their own goals to recognize their personhood. 

Lower the standards you set for yourself. “Most Ph.D. students are perfectionists, and they will put a lot of pressure on themselves in terms of responsibility to a mentee,” said Shi. “You don’t need to be perfect. In fact, if you are perfect around your mentees, you will probably just intimidate them.” 

According to Shi, this pressure can deter Ph.D. students from pursuing mentorship.  

“A lot of people will place barriers on themselves that they do not know enough, or they don’t have enough ‘good work’ for a mentee,” said Shi. “You will make mistakes as a mentor. You and your mentees as people will solve these miscommunications or issues. This is normal and healthy.”  

Humanize yourself. “Mentees often have an idealized perception of what a Ph.D. student is,” said Shi. “I will point out mistakes I have made in my work to students and encourage them to correct me if they have better information. I do not want to feel smart. I want to do good work and that requires criticism from other parties, including my mentees. Our goal is to increase the comfortability of the mentee while maintaining the professional boundary required of your role.”  

Facilitate situations where the mentee is empowered. “The important thing I focus on with my students is cross-training,” said Shi. “If one mentee has studied a software, they now become responsible for training other mentees and me. It helps to be intentional in teaching your mentees that knowledge can come from anyone. I think putting knowledge into a hierarchy is overblown and only serves to preserve the status of people at the top rather than allowing for new ideas.”  

Align mentor and mentee goals. “Goals should not conflict with one another, but this can happen if the mentor does not plan strategically,” said Shi. “The mentor needs to be transparent with what work the mentee needs to complete and the timeline. The mentor should inform the mentee of the amount of time the mentor has to assist the mentee and the appropriate method for contacting you when you need help. It is always best practice to be as specific with what you want rather than assume some ‘should know’ something.” 

Shi has created a mentorship document that outlines her expectations for all new student researchers.  

Communicate expectations. “We should communicate with each other the experience that we want from the relationship and work towards that goal,” said Shi. “You should align your students’ projects such that they are working towards something that advances your work. Sometimes, you will have motivated students who want to go off and do their own idea. That shows initiative in the student, but you should be direct with them that straying off into projects unrelated to your current research goals will mean that they will receive less oversight/feedback from you.” 

Provide positive feedback. “A lot of us analytical types may forget that we should point out tasks that are proceeding well along with the things that are going up in flames,” said Shi. “Recognizing quality mentee work is vital to them reproducing that quality of work again. They need to know when they have met your standards.” 

Provide critical feedback. “You will need to provide critical feedback to the mentee both on work and logistical miscommunications,” said Shi. “Do not shy away from this. If you are uncomfortable with discussing concerns on performance, this is normal, but by ignoring the issue you will deny the mentee from improving in this respect.” 

Shi’s procedure for handling performance issues involves gathering the facts, detangling your emotions, defining the solution, and sending them a message.  

For logistical, non-research issues, Shi recommends keeping records.  

“There is a lot of front-loaded work in creating documentation of expectations, but it really pays off in terms of not dealing with day-to-day logistical questions.” 

Understand the student researcher’s mindset. “Student researchers often feel insecure in navigating the lab equipment,” said Shi. “Sometimes, their perfectionism will cause them to ask you a lot of questions because they really want to impress you and do things correctly.”  

In these situations, Shi advises mentors to protect their own time while reassuring the mentee in their work. Let them know that you appreciate their effort to do things correctly, but part of research is independence, or let them know that you are unavailable to answer their question and provide a timeline for when they can expect to hear from you.  

Take the Tech to Teaching program and try your best! “I highly recommend this [Tech to Teaching] program to any Ph.D. student who has long-term goals of becoming a professor,” said Shi. “I want to emphasize something: you do not need formal training to be a mentor. If you are on the fence, try your best. You will learn the most about being a mentor by being a mentor. Listen to your mentee, balance your commitments, prioritize your time and goals, and you will be fine. There is the perception some people have that you need to mentor in a specific way. I do not agree with this mentality. I believe the scope of mentorship should be negotiated by the mentor and the mentee based on an alignment of goals.”  

Today, machine learning, artificial intelligence, and algorithmic advancements made by research scientists and engineers are driving more targeted medical therapies through the power of prediction. The ability to rapidly analyze large amounts of complex data has clinicians closer to providing individualized treatments for patients, with an aim to create better outcomes through more proactive, personalized medicine and care. 

“In medicine, we need to be able to make predictions,” said John F. McDonald, professor in the School of Biological Sciences and director of the Integrated Cancer Research Center in the Petit Institute for Bioengineering and Bioscience at the Georgia Institute of Technology. One way is through understanding cause and reflect relationships, like a cancer patient’s response to drugs, he explained. The other way is through correlation. 

“In analyzing complex datasets in cancer biology, we can use machine learning, which is simply a sophisticated way to look for correlations. The advantage is that computers can look for these correlations in extremely large and complex data sets.”

Now, McDonald’s team and the Ovarian Cancer Institute are using ensemble-based machine learning algorithms to predict how patients will respond to cancer-fighting drugs with high accuracy rates. The results of their most recent work have been published in the Journal of Oncology Research .  

For the study, McDonald and his colleagues developed predictive machine learning-based models for 15 distinct cancer types, using data from 499 independent cell lines provided by the National Cancer Institute. Those models were then validated against a clinical dataset containing seven chemotherapeutic drugs, administered either singularly or in combination, to 23 ovarian cancer patients. The researchers found an overall predictive accuracy of 91%.

“While additional validation will need to be carried out using larger numbers of patients with multiple types of cancer,” McDonald noted, “our preliminary finding of 90% accuracy in the prediction of drug responses in ovarian cancer patients is extremely promising and gives me hope that the days of being able to accurately predict optimal cancer drug therapies for individual patients is in sight."

The study was conducted in collaboration with the Ovarian Cancer Institute (OCI) in Atlanta, where McDonald serves as chief research officer. Other authors are Benedict Benigno, MD (OCI founder and chief executive officer, as well as an obstetrician-gynecologist, surgeon, and oncologist); Nick Housley, a postdoctoral researcher in McDonald’s Georgia Tech lab; and the paper’s lead author, Jai Lanka, an intern with OCI. 

The challenges in predicting cancer treatments

The complex nature of cancer makes it a challenging problem when it comes to predicting drug responses, McDonald said. Patients with the same type of cancer will often respond differently to the same therapeutic treatment. 

“Part of the problem is that the cancer cell is a highly integrated network of pathways and patient tumors that display the same characteristics clinically may be quite different on the molecular level,” he explained. 

A major goal of personalized cancer medicine is to accurately predict likely responses to drug treatments based upon genomic profiles of individual patient tumors. 

“In our approach, we utilize an ensemble of machine learning methods to build predictive algorithms — based on correlations between gene expression profiles of cancer cell lines or patient tumors with previously observed responses — to a variety of cancer drugs. The future goal is that gene expression profiles of tumor biopsies can be fed into the algorithms, and likely patient responses to different drug therapies can be predicted with high accuracy,” said McDonald.   

Machine learning is already being applied to the data coming from the genomic profiles of tumor biopsies, but prior to the researchers’ work, these methods have typically involved a single algorithmic approach. 

McDonald and his team decided to combine several algorithm approaches that use multiple ways to analyze complex data; one even uses a three-dimensional approach. They found using this ensemble-based approach significantly boosted predictive accuracy.

The algorithms the team used have names like Support Vector Machines (SVM), Random Forest classifier (RF), K-Nearest Neighbor classifier (KNN), and Logistic Regression classifier (LR). 

“They’re all fairly technical, and they’re all different computational mathematical approaches, and all of them are looking for correlations,” said McDonald. “It’s just a question of which one to use, and for different data sets, we find that one model might work better than another.”

However, more patient datasets that combine genomic profiles with responses to cancer drugs are needed to advance the research.  

“If we want to have a clinical impact, we must validate our models using data from a large number of patients,” said McDonald, who added that many datasets are held by pharmaceutical companies who use them in drug development. That data is typically considered proprietary, private information. And although a significant amount of genomic data of cancer patients is generally available, it’s not typically correlated with patient responses to drugs.

McDonald is currently talking with medical insurance companies about access to relevant datasets, as well. “It costs insurance companies a significant amount of money to pay for drug treatments that don’t work,” he noted. Time, medical fees, and ultimately, many lives could be saved by providing researchers with these types of information. 

“Right now, a percentage of patients will not respond to a drug, but we don’t know that until after six weeks of chemotherapy,” said McDonald. “What we hope is that we will soon have tools that can accurately predict the probability of a patient responding to first line therapies — and if they don’t respond, to be able to make accurate predictions as to the next drug to be tried.”

Citation: Lanka J, Housley SN, Benigno BB, McDonald JF. “ELAFT: An Ensemble-based Machine-learning Algorithm that Predicts Anti-cancer Drug Responses with High Accuracy.” Journal of Oncology Research. ISSN: 2637-6148.

Funding for this research provided by the Ovarian Cancer Institute, Atlanta, Georgia; Northside Hospital (Atlanta); and The Deborah Nash Endowment Fund. John F. McDonald serves as chief research officer of the Ovarian Cancer Institute (OCI) in Atlanta.

About Georgia Tech

The Georgia Institute of Technology, or Georgia Tech, is a top 10 public research university developing leaders who advance technology and improve the human condition. The Institute offers business, computing, design, engineering, liberal arts, and sciences degrees. Its nearly 40,000 students, representing 50 states and 149 countries, study at the main campus in Atlanta, at campuses in France and China, and through distance and online learning. As a leading technological university, Georgia Tech is an engine of economic development for Georgia, the Southeast, and the nation, conducting more than $1 billion in research annually for government, industry, and society.

This story first appeared in Georgia Tech Alumni Magazine.
 
Kristen Marhaver, Bio 04
Associate Scientist | CARMABI Foundation
Georgia Tech 40 Under 40: Class of 2021
 
Kristen Marhaver speaks for the corals. The scuba diver, underwater photographer, and world-renowned expert in coral breeding has racked up more than 2.3 million views of her engaging TED talks, in which she shares her ground-breaking innovations and heartfelt passion for preserving these little-understood and greatly undervalued marine creatures.

“Corals are so distant from us evolutionarily, so foreign and alien, that you really have to be creative in thinking about what their life is like and what they need to survive,” she says.

In her research lab at CARMABI (Caribbean Research and Management of Biodiversity) on the island of Curaçao, Marhaver and her team have made great strides in aiding coral survival by inventing methods for coral breeding, baby coral propagation, and coral gene banking.

“It’s like running an IVF clinic, a neonatal intensive care unit, and a daycare all at once for an endangered species,” she says.

Through hundreds of night dives, she and her colleagues pinpointed the timing for the spawning of numerous Caribbean coral species. Their spawning charts are now used by dozens of research teams to collect and preserve coral sperm and eggs. Marhaver was also the first person in the world to raise baby pillar corals, a nearly extinct Caribbean coral species. Juvenile corals supercharge reefs; they spawn more prolifically and adapt more readily to changing environments.

“Raising young corals today boosts the reproduction on future coral reefs for centuries,” she says.

Her lab’s Genome Resource Bank takes an even longer view. Its 500 billion (and counting) cryopreserved coral sperm can survive indefinitely, serving as the ocean equivalent of a seed bank that endures whatever disease outbreaks or thermal events arise.

She is always eager to speak for the corals: about their critical role in shoreline protection, their value to is land economies, their tremendous potential as a source of future medications and, well, just how cool they are. “There’s lots of reasons to keep corals around, for sure,” she says.

She’s grateful and thrilled to be part of the global community devoted to that very cause. “Collaborators, awesome students, and mentors have been so critical in all the progress we’ve made,” she says. Her father, Carl Marhaver, was her first mentor, who first took her scuba diving at age 15. “He was in charge of all the logistics, and I was in charge of all the small animal encounters,” she says with a laugh.

She credits Tech for providing her with the invaluable combination of lab research skills and field ecology experience that she draws on daily. As a first-year student, she pleaded her way into the lab of Terry Snell. He first let her observe his work on coral stress genomics before promoting her through the ranks as a lab assistant—and helping set her course toward her celebrated career.

In gratitude, Marhaver now sponsors a first-year biology researcher each year at Tech through the FastTrack Research Program. “That’s how it all began for me,” she says. “It means a ton to be able to pay it forward to support someone who is in my shoes 20 years later."

It’s Homecoming week at Georgia Tech, but with Halloween coming this weekend, there are other ways to get into the spirit of the season.

If you’re looking for Halloween fun or just a way to unwind, stop by one of these campus events this week.

 

SCPC Homecoming Carnival

Tuesday, Oct. 26

Noon – 3 p.m.

Tech Green

Enjoy food, activities, and fun, including fall carnival treats like apple cider, caramel apples, fried Oreos, and popcorn! There will be inflatable games and the event is free.

 

HSOC Society Presents: HCON 2021

Tuesday, Oct. 26

5 p.m.

Old Civil Engineering Building Patio

The History and Sociology Society hosts its annual HCON historical costume event. Stop by for fun, costumes, and free food from the Halal Guys. RSVP is requested to account for food: visit gatech.campuslabs.com/engage/event/7513210.

 

Halloween Holla 5K

Oct. 27 – 31

At the Campus Recreation Center and Online

Though advanced registration is sold out, participants can still don a costume and participate virtually all week long. The course will run along the newly-refurbished Tyler Brown Pi Mile trail on campus.

 

Neuroscience Paint and Sip

Wednesday, Oct. 27

6 – 7 p.m.

Room 098, Weber SST III

The Neuroscience Club hosts a brain-themed paint and sip event. Attendees will paint a neuro-themed piece of art and enjoy “brain juice.” RSVP to attend.

 

Kwaidan Film Screening

Wednesday, Oct. 27

6 – 8 p.m.

Room 115, Swann Building

The Japanese program in the School of Modern Languages will celebrate Halloween with a showing of Kwaidan, a horror anthology based on four well-known Japanese ghost stories. Two stories from the anthology (about an hour and a half) will be shown. There will also be a trivia contest on the movie and general Japanese horror trivia following the film. The winner will receive a box of Japanese candy.

 

Crafting With the Women’s Resource Center

Thursday, Oct. 28

11 am. – 3 p.m.

LGBTQIA Resource Center

The Women’s and LGBTQIA Resource Centers host a crafting event and Harry Potter movie marathon all day on Thursday.

 

Wicked Design and Pumpkin Ramble

Thursday, Oct. 28

6 – 8:30 p.m.

West Architecture Courtyard

Design a mask or costume or carve a pumpkin at this event from the School of Industrial Design.

 

SCPC Presents: Scratches, Scars, and Scabs!

Thursday, Oct. 28

7:30 – 11 p.m.

Midtown V, Exhibition Hall

Take a dive into Halloween makeup and special effects. All supplies will be provided, but attendees must register for a ticket at bit.ly/campustickets. Wearing your spooky costume is encouraged.

 

TV Marathon

Friday, Oct. 29

9 a.m. – 4 p.m.

LGBTQIA Resource Center

The LGBTQIA Resource Center will show Stranger Things (or another spooky TV show) all day on Friday. Stop by the center in the Smithgall Student Services (Flag) Building.

 

Trick or Tree Tour

Sunday, Oct 31

1 – 2 p.m.

Einstein Statue at Tech Green

Trailblazers hosts a Halloween-themed walk around campus to learn about the beautiful trees in our own backyard. RSVP on Engage.

 

Night at the Haunted Mansion

Sunday, Oct. 31

7 p.m.

The Historic Academy of Medicine

Join SCPC at the Historic Academy of Medicine for a night of frights. Come in your best Halloween costume and be spooked in the haunted maze and escape rooms, go trick-or-treating, and participate in a costume contest. Tickets are free but required; reserve a ticket at bit.ly/campustickets.

 

Pumpkin Drop

Friday, Nov. 5

3 – 4 p.m.

Howey Physics Building (and streamed online at twitch.tv/gatechsps)

The Society of Physics Students (SPS) hosts its annual Pumpkin Drop, where pumpkins are dunked in liquid nitrogen and dropped off the top of the Howey Physics Building. The event is free and no RSVP is required — drop by the outside of Howey to see frozen and glitter-filled pumpkins explode and learn about the science and physics behind the drops.

You can also purchase a pumpkin to be decorated, carved, and frozen in liquid nitrogen or frozen fruit. All pumpkin sales support SPS programming and activities.

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