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Virginia Tech’s virtual university commencement will livestream tonight, Friday, May 14, at 6:15 p.m., and degrees will be conferred at this time.

“We are extremely proud of our graduates who achieved their goals despite more than a year of a pandemic that upended much of their lives,” said Naren Ramakrishnan, the Thomas L. Phillips Professor of Engineering in the Department of Computer Science at Virginia Tech and director of the Sanghani Center for Artificial Intelligence and Data Analytics. “When everything went virtual, they continued to attend classes, meet with their advisors, conduct research, present papers at conferences, and work at internships — all testament to their perseverance and a good barometer of their future success .”

Following is a list of Sanghani Center graduates:

Ph.D.

Prashant Chandrasekar, advised by  Edward Fox, is receiving a Ph.D. in computer science. His research interest lies in digital libraries. The title of his dissertation is “Continuously Extensible Information Systems: Extending the 5S Framework by Integrating UX and Workflows.” Chandrasekar will join the University of Mary Washington as an assistant professor in computer science.

Kaiqun Fu, advised by Chang-Tien Lu, is receiving a Ph.D. in computer science. His research interests lie in spatial data mining, machine learning, and graph neural networks, with a focus on social media analysis in intelligent transportation systems and smart cities. The title of his dissertation is “Spatiotemporal Event Forecasting and Analysis with Ubiquitous Urban Sensors.” Fu will join South Dakota State University as assistant professor in August 2021.

Yen-Cheng Lu, advised by Chang-Tien Lu, is receiving a Ph.D. in computer science. His research interests lie in anomaly detection and probabilistic modeling. The title of his dissertation is “Relational Anomaly Detection: Techniques and Applications.” Lu will be continuing his career as a software engineer at Amazon Alexa AI.

Sneha Mehta, advised by Naren Ramakrishnan, is receiving a Ph.D. in computer science. Her research interests are data mining and deep learning, especially for natural language processing applications. The title of  her dissertation is “New Methods for Event Detection and Extraction from News Articles.” Mehta will join Twitter as a machine learning researcher in July.

Sathappan Muthiah, advised by Naren Ramakrishnan, is receiving a Ph.D. in computer science. His areas of interest include forecasting, machine learning, information retrieval, and topic detection and tracking (TDT). The title of his dissertation is “Design and Maintenance of Event Forecasting Systems”.  Muthiah has joined eBay as an applied researcher.

Reza Sepasdar, advised by Anuj Karpatne, is receiving a simultaneous master’s degree in computer science and Ph.D. in civil engineering. (His master’s co-advisor is Maryam Shakiba). His research interests lie in the intersection of AI and computational mechanics. Sepasdar’s master’s thesis is entitled “A Deep Learning Approach to Predict Full-Field Stress Distribution in Composite Materials.” He will defend his Ph.D. dissertation, “Micro-mechanical Behavior of Fiber-reinforced Composites using Finite Element Simulation and Deep Learning,” this summer.

Sirui Yao, advised by Bert Huang, is receiving a Ph.D. in computer science. Her research interests include machine learning, recommender systems, and fairness. The title of her dissertation is “Evaluating, Understanding, and Mitigating Unfairness in Recommender Systems.” Yao will join Google in June 2021 as a machine learning engineer.

Master’s degree

John Aromando, advised by Edward Fox, is receiving a (coursework only) master’s degree in computer science. His research interests include natural language processing and information retrieval, particularly analyzing design specs written in natural language and synthesizing a machine-understood language via relevant descriptions.

Mohi Beyki, advised by Edward Fox, is receiving a master’s degree in computer science. His research interests are in deep learning, health care, and software engineering. The title of his thesis is “Synthetic Electronic Medical Record Generation using Generative Adversarial Networks.”  Beyki will be joining Google as a software engineer this summer.

Yi-Chun Chang, advised by Chang-Tien Lu, is receiving a master’s degree in computer science. His research interest is in using social media analytics to detect threats. The title of his thesis is “RISECURE: Metro Incidents And Disruptions Detection Using Social Media And Graph Convolution.”  He will join Walmart Global Tech as a software engineer in July.

Po-Han Chen, advised by Chang-Tien Lu, is receiving a master’s degree in computer science. His research focuses on using data from social media to help solve real-world problems. The title of his dissertation is “Metro Security Incidents And Threat Detection Using Social Media.” He will be joining Bloomberg as a software engineer this summer.

Yi Huang, advised by Jia-Bin Huang, is receiving a masters of engineering degree. His research interests lie in computer vision and machine learning. The title of his master’s project is “Cross-Domain Context-aware 3D Hand Pose Estimation.” Huang will join Qualcomm as a computer vision research engineer.

Kulendra Kumar Kaushal, advised by  Naren Ramakrishnan, is receiving a master’s degree in computer science. His research interests lie in the field of natural language processing and information extraction. The title of his thesis is “Information Extraction of Technical Details From Scholarly Articles.” Kaushal will be joining Bloomberg as a software developer.

Prathamesh Kalyan Mandke, advised by Anuj Karpatne, is receiving a masters of engineering degree. His research interests lie in machine learning and computer vision. The title of his master’s project is “Fluorescent Image Reconstruction in Shape Controlled Cell Migration using Deep Learning.”  Mandke will join Qualcomm AI Research as a machine learning software engineer in July.

Ashkan Nazari, advised by Lenwood Heath, is receiving a master’s degree in computer science. His research interests lie in artificial intelligence, deep learning, and cloud-based intelligence systems analysis. Nazari has also worked toward a Ph.D. in mechanical engineering. He will join the Silicon Valley-based luxury electric vehicle start-up Lucid Motors as a senior data scientist, working on developing intelligent battery initiatives.

Ioannis Papakis, co-advised by Anuj Karpatne and Abhijit Sarkar, is receiving a master’s degree in computer science. His research interests lie in machine learning, computer vision, robotics, and signal processing. The title of his thesis is “A Graph Convolutional Neural Network Based Approach for Object Tracking Using Augmented Detections With Optical Flow.”  Papakis also won first place in the 2021 Paul E. Torgersen Graduate Student Research Excellence Awards MS poster presentation category. Starting in July, he will be employed by Bertrandt US, Inc., working at Audi in Santa Clara, California, as an advanced driver-assistance systems engineer.

Arya Shahdi, co-advised by Anuj Karpatne and Bahareh Nojabaei, is receiving a master’s degree in computer science. His research interests lie in forecasting and geospatial modeling and analysis. The title of his thesis is “Physics-guided Machine Learning Approaches for Applications in Geothermal Energy Prediction.” Shahdi is a supply chain data scientist at Lowe’s Companies, Inc. 

Aarohi Sumant, advised by Edward Fox, is receiving a master’s degree in computer science. Her research focuses on deep learning and machine learning application, specifically in natural language processing. The title of her thesis is “Improving Deposition Summarization using Enhanced Generation and Extraction of Entities and Keywords.” Sumant will join Amazon as a software development engineer in July.

Omer Zulfiqar, advised by Chang-Tien Lu, is receiving a master’s degree in computer science. His research interests lie in social media event detection and natural language processing. The title of his thesis is “Detecting Public Transit Service Disruptions Using Social Media Mining and Graph Convolution.” He will join Walmart Labs as a software engineer in June.

Sneha Mehta, a Ph.D. student in computer science at the Discovery Analytics Center, was in New York City this week to present “Simplify-then-Translate: Automatic Preprocessing for Black-Box Translation” in a talk and poster presentation at the main AAAI Conference on Artificial Intelligence.

The paper represents her work on novel methods to improve machine translation for subtitles while an intern at Netflix for two consecutive summers.

In fact, last summer was a busy one for Mehta, who is advised by Naren Ramakrishnan. In addition to an internship at Neflix headquarters in Los Gatos, California, she was also selected to attend the Deep Learning and Reinforcement Learning Summer School (DLRLSS), in Edmonton, Alberta, Canada.

“I applied to the Summer School because both deep learning and reinforcement learning are very relevant to my work both at DAC and the work I was doing at Netflix,” Mehta said. “Hearing directly from some of the pioneers in the field was a great – and invaluable – experience.”

As an undergraduate, Mehta did a couple of internships where she was introduced to data mining and deep learning. “As a result, I decided I wanted to study these areas in more depth,” Mehta said.

Mehta earned a bachelor’s degree in computer science and a master’s degree in mathematics from BITS Pilani University in India.

“I was attracted to Virginia Tech and DAC to pursue a Ph.D. because of the faculty who are doing cutting edge research in the fields of data science and machine learning,” Mehta said.  “What I like best about being a DAC student is the opportunity it provides for interdisciplinary collaborations.”

Last May, Mehta presented a poster of her collaborative work at DAC, “Event Detection using Hierarchical Multi-Aspect Attention,” at The Web Conference.

Recently, Mehta was named a 2020 Twitch Research Fellow, one of five students across the country to receive the $10,000 award to support her academic research and an offer to connect with a team at Twitch for a full-time paid internship at Twitch HQ.

Mehta has presented a successful preliminary of her dissertation on new frameworks for event detection and extraction and is projected to receive her Ph.D. in Fall 2020. After graduation, she would like to have a research role in industry.

Sneha Mehta has been selected to attend the Deep Learning and Reinforcement Learning Summer School (DLRLSS), from July 24 to August 2, in Edmonton, Alberta, Canada.

Mehta is a Ph.D. student in computer science at the Discovery Analytics Center, advised by Naren Ramakrishnan. In May, she began a summer internship as a data scientist at Netflix headquarters in Los Gatos, California, where she is researching novel methods to improve machine translation for subtitles.

“I applied to the Summer School because deep learning and reinforcement learning are very relevant to my work at problem solving both at DAC and at Netflix,” said Mehta. “Hearing directly from some of the pioneers in the field will be a great – and invaluable – experience.”

The 2019 DRLSS is hosted by the Canadian Institute For Advanced Research (CIFAR) and the Alberta Machine Intelligence Institute (Amii), with participation and support from the Vector Institute and the Institut québécois d’intelligence artificielle (Mila).

The program brings graduate students, post-docs, and professionals together to cover the foundational research, new developments, and real-world applications of deep learning and reinforcement learning.

Mehta will present a poster of her collaborative work at DAC, Event Detection using Hierarchical Multi-Aspect Attention which she presented at The Web Conference in May.

“The Summer School also provides a great opportunity to network with Ph.D. students, postdocs and industry professionals from all over the world who apply these technologies to a variety of fields, including recommendation systems, physics, 3D printing, marine biology, natural language processing, computer graphics, medical image analysis, neuroscience, epidemics, computer vision, and drug discovery,” Mehta said.

At the conclusion of the program, Mehta will continue her internship at Netflix until August 14, and then return to Virginia Tech for the Fall semester.

 

A number of graduate students at the Discovery Analytics Center have opted for internships and jobs at companies and national laboratories across the country this summer as a way of both benefiting their own research and gaining real world experience.

Following is a list of where they are for the next few months:

Aman Ahuja, a Ph.D. student in computer science, is an applied scientist intern at Amazon in Palo Alto, California. He is on the Amazon Search Team, researching product search techniques. His advisor is Chandan Reddy.

Tyler Chang, a Ph.D. student in computer science, has begun a six-month appointment at Argonne National Laboratory in Chicago, Illinois. He is one of 70 graduate students who received an appointment from the U.S. Department of Energy (DOE) Office of Science Graduate Student Research (SCGSR) to work on his thesis. The goal is to produce a portable multi-objective optimization software which Argonne could utilize in the future. Chang’s advisor is Layne Watson.

Jinwoo Choi, a Ph.D. student in electrical and computer engineering, is a research intern at NEC Labs America, San Jose, California, working on domain adaptation for video. Choi’s advisor is  Jia-Bin Huang.

Chen Gao, a Ph.D. student in electrical and computer engineering, is a research intern on a video completion project at Facebook in Seattle, Washington. He is working on an algorithm that synthesizes missing regions of videos. His advisor is Jia-Bin Huang.

Liuqing Li, a Ph.D. student in computer science, is on the Content Science team at Yahoo! Research in Sunnyvale, California, working on document recommendation through reinforcement learning. His advisor is Edward Fox.

Sneha Mehta, a Ph.D. student in computer science, is a data science intern at the Netflix headquarters in Los Gatos, California. She is researching novel methods to improve machine translation for subtitles. Her advisor is Naren Ramakrishnan.

Shruti Phadke, a Ph.D. student in computer science, is an intern at the Oak Ridge National Laboratory in Oak Ridge, Tennessee. She is working on developing scalable machine learning and Natural Language Processing (NLP) algorithms to detect public sentiment in news and social media. Her advisor is Tanushree Mitra.

Esther Robb, a master’s degree student in electrical and computer engineering, is a research intern at Google in Mountainview, California, where she is working on facial recognition. Her advisor is Jia-Bin Huang.

Alexander Rodriguez, a Ph.D. student in computer science, is a research intern at WalmartLabs in Sunnyvale, California. His advisor is B. Aditya Prakash.

Dhruv Sharma, a master’s student in computer science, is working at Kitware, Inc., in Carborro, North Carolina. As a research and development intern, Sharma’s work includes some medical image processing/machine learning tasks; mining EHR data for prediction of risk, procedure outcome, or other events; and analyzing training needs of healthcare providers. He is advised by Chandan Reddy.

Tian Shi, a Ph.D. student in computer science, is an intern at Pacific Northwest National Laboratory in Richland, Washington, where he is working on machine comprehension and question-answering on clinical notes in the healthcare domain. His advisor is Chandan Reddy.

Shih-Yang Su, a Ph.D. student in electrical and computer engineering, is a research intern at Borealis AI in Vancouver, Canada, working on graph convolution for structural prediction. His advisor is Jia-Bin Huang.

Deepika Rama Subramanian, a master’s student in computer science, is a mobility intern at Lam Research, Fremont, California, working on designing and developing an end-to-end mobile application for field engineers at Lam Research. Her advisor is Tanushree Mitra.

Anika Tabassum, a Ph.D. student in computer science, is a research intern at the Oak Ridge National Laboratory in Oak Ridge, Tennessee, where she will be applying data mining and visualization skills in two U.S. Department of Energy (DOE) projects: “Reynolds Landing Research” and “North American Energy Resilience Model.” Her advisor is B. Aditya Prakash.

Sai Sindhura Tipirneni, a master’s student in computer science, is working in the Quantum Computing Lab at Oak Ridge National Laboratory in Oak Ridge, Tennessee. Her advisor is Chandan Reddy.

Ping Wang, a Ph.D. student in computer science, is an intern at Pacific Northwest National Laboratory in Richland, Washington, where she is working on question answering on electronic medical records using Natural Language Processing (NLP) techniques. Wang’s advisor is Chandan Reddy.

Sirui Yao, a Ph.D. student in computer science, is a research intern at Google AI in New York City, where she is studying noise and bias in dynamic recommender systems. Her advisor is Bert Huang.

Ming Zhu, a Ph.D. student in computer science, is at Amazon in Seattle, Washington. She is an applied scientist intern for Amazon Comprehend Medical, working on Natural Language Processing on medical corpora using deep learning. Zhu’s advisor is Chandan Reddy.

Yuliang Zou, a Ph.D. student in electrical and computer engineering, is a research intern at NEC Labs America in San Jose, California, where he is working on unsupervised scene structure learning. His advisor is Jia-Bin Huang.