- Gradstudents - mailman.cs.vt.edu

The Trade Desk: Recruiter Info Session TONIGHT!!
by Watson, Joan 03 Sep '25

03 Sep '25

Hey, CS Majors, Minors, and Grad Students! Ever wonder how ads reach you at the right time and place? Are you interested in making advertising more effective - collaborating with your favorite brands to drive advertising initiatives? You can do this and much more with The Trade Desk<https://protect-us.mimecast.com/s/z9QfCpYqZXUAKBL0T2b1ur?domain=thetradedes…>, a media buying company impacting how brands deliver data-driven programmatic advertising to their audiences. (See the attached flyers for more details.) Connect with University Recruiter, Chris Gooding, on Wednesday, September 3rd @ 5:30PM EST (via Zoom) to learn a bit more about the company, the interview process, and how you can stand out to our engineers. This would be a great opportunity to ask questions before the career fair – giving more time to dig deeper on our tech, projects, and growth potential from our experts in attendance. Zoom: https://thetradedesk.zoom.us/j/96494197898?from=addon Additionally, we will be hosting a 2nd session (with a few special guests) at Torgersen Hall Room 2150 on Monday, September 8th @ 6PM. Hope to see you there! If you are interested in connecting further, expediting your application, interviewing and/or remaining up to date on opportunities with us, please be sure to connect using this form<https://forms.office.com/pages/responsepage.aspx?id=rsoyA0cdEk28TcOajE_SgP3…>. The Trade Desk has a unique mission - to create a better, more open internet for everyone through principled, intelligent, data-driven advertising. Handling over 1 trillion queries per day, our platform operates at an unprecedented scale. We have also built something even stronger and more valuable: an award-winning culture based on trust, ownership, empathy, and collaboration. The Trade Desk is offering internship opportunities within our research and development teams including: * Internships * Software Engineering * Data Science * Product Management Students interested in technical summer internship opportunities would be graduating between Fall 2026 – Spring 2027 and pursuing tech-related majors/minors (ie. Computer Science, Data Science, Mathematics, etc). We look forward to meeting you virtually and during career fair week! *************** Joan Monahan Watson, Ph.D. Director of Assessment and Strategy Department of Computer Science Faculty Affiliate Center for Educational Networks and Impacts (CENI) Virginia Tech 3160 Torgersen Hall 620 Drillfield Drive Blacksburg, VA 24061 Phone: 540.231.8874 Email: jmwatson(a)vt.edu<mailto:jmwatson@vt.edu> [cid:image001.png@01DC0078.85E20550] Author of Learning with AI: The K-12 Teacher’s Guide to a New Era of Human Learning<https://www.press.jhu.edu/books/title/54027/learning-ai?srsltid=AfmBOooALyy…>

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You Are Invited to the CS Grad Council Meetings!
by Madabushi, Sindhuja 02 Sep '25

02 Sep '25

Hello All, CS Grad Council invites all graduate students in CS@VT to join our biweekly meetings, held every other Thursday at 11 AM in Gilbert (Room 3002). Our next meeting is on September 4, 2025. In this meeting, we will discuss the upcoming back-to-school pizza party, plans for this semester, and anything else you would like to share. For those unable to join in-person, a Zoom option is available here: https://virginiatech.zoom.us/j/87397593679 Looking forward to seeing you there! Best regards, Sindhuja Secretary, CSGC 2025-26

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Help Shape the Future of Virtual AI Assistants – Participate in a VR Research Study!
by Ilo, Cory 30 Aug '25

30 Aug '25

Hi there! Are you interested in virtual reality (VR) and curious about how cutting-edge technology is shaping our digital experiences? The 3D Interaction (3DI) Group at Virginia Tech is currently seeking participants for a research study exploring how a virtual privacy assistant influences user privacy awareness and overall experience in VR environments. Your participation will contribute directly to the design and development of more intuitive, user-centered virtual assistants. Participants will be paid $10 for their participation in the study. Who Can Participate? We're looking for individuals who meet the following criteria: * Age 18 or older * Proficient in reading and writing in English * Have normal or corrected-to-normal vision (glasses or contact lenses are fine) This is a unique opportunity to experience advanced VR technology firsthand while playing a valuable role in shaping the future of digital privacy tools. Interested? For more information or to schedule a session, please contact Cory Ilo at ciilo(a)vt.edu. This study is supervised by Dr. Doug A. Bowman in the Department of Computer Science. It has been approved by the Virginia Tech Institutional Review Board under protocol number 25-589. Thank you for considering this opportunity—we hope to see you in VR soon! Best regards, The 3DI Research Team Virginia Tech Cory Ike[chukwu] Ilo, M.S. PhD Student Researcher 3D Interaction Group<https://wordpress.cs.vt.edu/3digroup/people/>, Virginia Tech, CS Dept. "Dreams without goals are just dreams. And ultimately, they fuel disappointment. On the road, to achieving your dreams, you must apply discipline but more importantly, consistency because without commitment you'll never start, but without consistency, you'll never finish." - Denzel Washington

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Nure Tasnina's doctoral defence at 3pm on September 5, 2025
by T. M. Murali 29 Aug '25

29 Aug '25

Dear colleagues and students, I welcome you to join us for Nure Tasnina's doctoral defence at 3pm on September 5, 2025. The details are below. Murali *Design and Evaluation of Network Algorithms and Deep Learning Models in Systems Biology and Biomedicine* Nure Tasnina 3pm-5pm, September 5, 2025 D&DS 450 https://virginiatech.zoom.us/my/tmmurali *Thesis committee* T. M. Murali, Chair Mark Crovella (Boston University) Hoda Eldardiry Lenwood S. Heath Liqing Zhang Cells function through a complex web of interactions among genes, proteins, and other molecules. A central goal of modern biology is to understand how these interactions shape health and disease. To study them, researchers often use a network representation, where molecules are depicted as nodes and their interactions as edges. These networks can then be analyzed using both traditional algorithms and machine learning models to reveal patterns of cellular behavior. In the first part of this thesis, we focus on protein-protein interaction (PPI) networks that represent how proteins connect and work together. We develop a method to explain the predictions of a widely used algorithm: network diffusion. Making these predictions interpretable is critical for building confidence in their use for biomedical research. Recognizing that the effectiveness of network-based methods depends on the quality of the input networks, we further design a deep learning model to integrate PPI networks generated from multiple experimental sources. The integrated network provides richer biological information and outperforms individual source networks in predicting protein function. Building on this foundation, our next two projects addressed a key biomedical application: combination therapy. Combination therapies are a cornerstone of cancer treatment, offering improved efficacy at lower doses and helping to overcome drug resistance. However, experimentally testing the vast space of drug combinations is prohibitively expensive and time-consuming, making computational prediction indispensable. We conduct a large-scale evaluation of existing computational models for drug synergy prediction and demonstrate that many approaches rely on statistical shortcuts in the data rather than capturing true biological mechanisms. This result underscores the need for more robust and trustworthy predictors. To support the development of such stronger models, we build a pipeline powered by large language models to extract and organize information about the mechanisms, the “why” behind effective drug combinations in cancer treatment. Together, these contributions provide new methods and guidelines for making biological predictions more transparent, reliable, and useful for guiding experiments and therapeutic development. -- Director, NSF COMPASS Center <https://compass-pipp.org/> Director, Pandemic Prediction and Prevention Destination Area <https://wordpress.cs.vt.edu/pandemicpredictionandprevention/> Associate Department Head for Research Department of Computer Science Virginia Tech http://bioinformatics.cs.vt.edu/~murali/

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Recruiting for a Research Study on Using Gestures for Learning
by Bruen, Jacqueline 29 Aug '25

29 Aug '25

Hi everyone, I know this may be a long shot, but I’m recruiting participants for my research study who either 1) can’t program without help or 2) haven’t taken a semester long computer science class The information about the study is below in blue. Thank you for your help! ~~~~~~~~ The Mind Music Machine Lab at Virginia Tech is seeking individuals to participate in a study to determine how gestures can improve the acquisition of algorithmic interpretation skills. During this study, participants will: -Complete a demographic survey. -Learn an algorithmic language either with or without accompanying hand gestures over the course of three 30 minute sessions. -Take two tests in a fourth 30 minute session which assesses your acquisition of various algorithmic interpretation skills. -Take a short 10 minute semi-structured interview. You’re eligible for our study if you: -Are >= 18 years old -Have normal hearing, vision (or correct-to-normal vision), and fine motor skills -Have never taken a computer science course OR cannot program without help. The study will take a total of approximately two hours over the course of four 30 minute sessions. Each participant will receive compensation of $10/hour. Total compensation for time and effort for the whole study will be $20 in cash, distributed to the participant at the end of the fourth session. You are free to discontinue participation at any point if you feel uneasy or uncomfortable. Interested individuals can reach out to Jacqueline Bruen at jacquelineb(a)vt.edu. The research protocol for this experiment has been reviewed by the Virginia Tech Institutional Review Board (IRB #24-942). ~~~~~~~~ Kindly, Jacqueline Elise Bruen Ph.D. Candidate | Mind Music Machine Lab Department of Computer Science Virginia Tech "Are you in earnest? Seize this very minute: What you can do, or dream you can, begin it; Boldness has genius, power, and magic in it. Only engage and then the mind grows heated; Begin and then the work will be completed." -Goethe

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Participant Recruitment for Eye-Tracking Study
by Ramirez, Nikki 29 Aug '25

29 Aug '25

Sharing from Dr. David-John’s lab, they are recruiting for a user study: Greetings, everyone. The Private-Eye lab is looking for participants for a user study selection techniques in VR. To participate, you need to * Be 18 years or older * Have normal vision, or corrected vision using contact lenses * Have conversational proficiency in spoken and written English * Can perform basic arithmetic operations The study will take up to 75 minutes to complete and the you will be paid $20 usd for participation. If you want to participate, please complete the form at https://docs.google.com/forms/d/e/1FAIpQLSelLdQl3a-nYV9UlXQZVZtsq00kzJxxUoy… and schedule the experiment using the link in the form If you have any questions don't hesitate to get in touch with Anish Narkar(anishnarkar(a)vt.edu). The study is in person and will take place in Gilbert 3216. Participation in this study is entirely voluntary. This study was approved by the Virginia Tech Institutional Review Board (IRB #23-501). Anish Narkar Ph.D. Candidate, PrivateEye Lab Department of Computer Science Virginia Tech anishnarkar(a)vt.edu<mailto:anishnarkar@vt.edu> --- G. NIKKI RAMIREZ she, her, hers Ph.D. student, Department of Computer Science Virginia Tech

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Pouyan's Ph.D. defense
by Sharath Raghvendra 28 Aug '25

28 Aug '25

Dear Faculty and Students, You are cordially invited to attend the PhD thesis defense of *Pouyan Shirzadian*. The defense will be held in person, and all are welcome to join. *Date:* Friday, August 29, 2025 *Time:* 2:00 PM – 3:00 PM (EST) *Title:* *Overcoming Computational Complexity Barriers for Optimal Transport in Discrete and Semi-Discrete Settings* *Location:* Gilbert Place, 4001 *Abstract: *Measuring the similarity of two probability distributions is a fundamental task in many machine learning applications. Optimal Transport (OT) captures this similarity as the minimum cost required to transport mass between distributions and has found numerous applications in computer science due to its ability to define meaningful distances. OT has been studied in various settings. For instance, when one distribution is continuous and the other discrete, the problem is called semi-discrete OT. In many real-world scenarios, a distribution is represented as an empirical distribution using finite samples drawn from the underlying distribution. When both distributions are empirical, OT is equivalent to the minimum-cost bipartite matching problem. Other variants of interest are the partial transport (ignoring a fraction of mass) and robust transport (regularizing with other distances). This thesis presents (i) new approximation algorithms for semi-discrete OT, (ii) a characterization of optimal solutions to semi-discrete robust OT along with a novel combinatorial algorithm, (iii) a faster algorithm for Euclidean bipartite matching with provably improved performance on stochastic point sets, and (iv) an exact algorithm for the offline k-server problem via reduction to partial bipartite matching.

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CS Grad Student Mentoring Program
by Moussad, Bernard 28 Aug '25

28 Aug '25

Hey folks, For new students, welcome to Virginia Tech! And to everyone else, welcome back! I hope everyone is settling into their first week of classes! I'm Bernie Moussad, your CS Grad Council President for this academic year. I just have a few things I want to share with you so you can start to think about ways to get plugged in here and meet each other. 1. We are looking for new PhD students who want help in general navigating life in the CS department (finding labs, finding buildings, finding great students to get to know). 2. We are looking for older PhD students who want to help new folks find their way around our department. If either of the above sounds like you, we'd love for you to fill out this survey<https://forms.gle/JNz9kh1cKp9cGEUc9>! If you're a Masters (not MEng) student looking for mentorship, reach out to @Sirles, Andrea<mailto:asirles@vt.edu> to get connected! With that, we are planning to host a type of round table discussion for new students to get the opportunity to ask older students any questions they may have! This is tentatively planned for September 17th at 12 pm! Be on the lookout for more info on this in the coming weeks. This will be open to all grad students (not just PhDs)! We'll also be starting up Grad Council meetings next week so keep an eye on your email for when and where those will be! It's a great way to get an idea of how our department works and have your voice be heard. That's all I have for now, but if you have any questions, feel free to reach out to me or any of our other council members! Wishing all the best, Bernard Moussad PhD student CS@VT Phone: 256-668-7571<tel:256-668-7571> Website: Bernym12.github.io<https://Bernym12.github.io>

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Visit of Dr. Simone Silvestri, September 19, 2025
by Wang, Xuan 28 Aug '25

28 Aug '25

Dear colleagues and students, We are pleased to host Dr. Simone Silvestri (University of Kentucky) on Friday, September 19, 2025. Dr. Silvestri will be giving two talks during his visit: * Morning Seminar Talk: Towards the Internet of Agricultural Things: Optimization, AI, and Communication Solutions for Modern Farming * Graduate Seminar: The PhD Journey: Essential Strategies for a Successful PhD Journey Flyers for both talks are attached for more details. We have also prepared a sign-up sheet for meetings or breakfast/lunch/dinner with Dr. Silvestri. Please add your name to an available time slot if you would like to meet with him: [cid:0caf88f5-b62a-4474-b91f-4bcf8c67e81c]Simone Silvestri_Seminar Talk_9.19.25.xlsx<https://virginiatech-my.sharepoint.com/:x:/g/personal/debzi5_vt_edu/EbJ2HNw…> This will be a great opportunity to learn about Dr. Silvestri’s research and engage in discussions. We encourage faculty and students to attend. Best regards, Xuan -------- Assistant Professor Department of Computer Science Sanghani Center for AI and Data Analytics Virginia Tech

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Participate in 45-Minutes User Study
by Ubur, Sunday 28 Aug '25

28 Aug '25

We invite you to participate in a research study focused on evaluating real-time captioning systems enhanced with emotional cues, such as emojis, and tags. This study is part of a broader project titled: "Design Guidelines for Emotive Captioning Systems: Cultural Differences in XR." What’s This About? This stage of the study examines how individuals perceive and interpret emotions embedded in captions when using Augmented Reality (AR) headsets. We are specifically exploring cultural differences in understanding nonverbal emotional cues in AR-based captioning systems. What Will You Do? * Wear an AR headset and interact with real-time captioning prototypes (20 mins) * Experience various captioning styles (e.g., symbolic vs. explicit cues) * Complete a post-interaction survey about your experience (25 mins) Who Can Join? * Adults (18+) * Experience using captioning systems (e.g., in classrooms, meetings, videos) * Comfortable using wearable devices like AR/VR headsets When and Where? * In-person at DVE Lab at Virginia Tech, – 220 Gilbert St, Room 3213, Blacksburg, VA. * Duration: ~45 minutes total Why Participate? * Contribute to accessibility innovation for diverse cultural communities * Help researchers design inclusive AR-based communication systems * Paid research study — in appreciation of your time, we will provide a $20 Amazon Gift Card If you're interested, please complete the brief sign-up form here: https://forms.office.com/r/mdXKtVsFaq We hope you’ll consider lending your insights to help build more inclusive technologies. Sincerely, Sunday Ubur, DVE Lab, Virginia Tech, Department of Computer Science

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