About Me
I am a Staff Researcher at Samsung Research America. I received my PhD in Computer Science and Engineering from the Ohio State University (OSU) under the guidance of Prof. Srinivasan Parthasarathy. The focus of my thesis was on network representation learning. Before joining OSU, I worked at IBM Research Labs, India as a Research Software Engineer. I have completed my masters from Indian Institute of Technology, Madras, under the guidance of Prof. Balaraman Ravindran and Prof. Sayan Ranu.
News
- Feb '23: Invited to give Keynote Talk at AAAI GCLR workshop '23.
- Jan '23: Joined Samsung Research America as a Staff Researcher.
- Dec '22: Successfully defended Ph.D.
- Nov '22: MultiBiSage paper got accepted in VLDB '22.
- Jun '22: NRL Benchmarking paper got accepted in TMLR '22.
- Jun '22: FairEGM paper got accepted in EAAMO '22.
- Oct '21: Our work "LocationTrails" got accepted in ASONAM '21.
- Sep '21: Our work "Distributed MILE" got accepted in HiPC '21.
- Aug '21: Invited to be on panel on "Scaling and Debugging Deep Learning Systems" at KDD Deep Learning Day 2021.
- Jul '21: Contributed talk in KDD Deep Learning Day 2021.
- Jul '21: Presented "MILE" at Northeastern University in Data Lab Seminar.
- May '21: Presented "LocationTrails" at UT Austin for "Mobility Data and Modeling Group".
Publications
- Saket Gurukar, Nikil Pancha, Andrew Zhai, Eric Kim, Samson Hu, Srinivasan Parthasarathy, Charles Rosenberg, and Jure Leskovec. "MultiBiSage: A Web-Scale Recommendation System Using Multiple Bipartite Graphs at Pinterest." VLDB '22.
- He, Yuntian, Saket Gurukar , and Srinivasan Parthasarathy. "FairMILE: A Multi-Level Framework for Fair and Scalable Graph Representation Learning." arXiv preprint arXiv:2211.09925 (2022).
- Current, Sean, Yuntian He, Saket Gurukar , and Srinivasan Parthasarathy. "FairEGM: Fair Link Prediction and Recommendation via Emulated Graph Modification." In EAAMO. 2022.
- He, Yuntian, Yue Zhang, Saket Gurukar, and Srinivasan Parthasarathy. "WebMILE: democratizing network representation learning at scale." VLDB Demo 2022.
- Saket Gurukar , Bethany Boettner, Christopher Browning, Catherine Calder, and Srinivasan Parthasarathy. "Leveraging network representation learning and community detection for analyzing the activity profiles of adolescents." Applied network science 2022.
- Saket Gurukar*, Priyesh Vijayan*, Balaraman Ravindran, Aakash Srinivasan, Goonmeet Bajaj, Chen Cai, Moniba Keymanesh et al. "Benchmarking and Analyzing Unsupervised Network Representation Learning and the Illusion of Progress.", TMLR 2022
- Sahai, Saumya Yashmohini, Saket Gurukar , Wasiur R. KhudaBukhsh, Srinivasan Parthasarathy, and Grzegorz A. Rempała. "A machine learning model for nowcasting epidemic incidence." Mathematical Biosciences 2022.
- Yuntian He, Saket Gurukar, Pouya Kousha, Hari Subramoni, Dhabaleswar K. Panda, Srinivasan Parthasarathy. ”DistMILE: A Distributed Multi-Level Framework for Scalable Graph Embedding”. HiPC ’21
- Jiongqian Liang*, Saket Gurukar*, Srinivasan Parthasarathy, “MILE: A Multi-Level Framework for Scalable Graph Embedding”. ICWSM ’21.
- Moniba Keymanesh, Saket Gurukar, Bethany Boettner, Christopher Browning, Catherine Calder, Srinivasan Parthasarathy. “Twitter Watch: Leveraging Social Media to Monitor and Predict Collective-Efficacy of Neighborhoods.” CompleNet ’20.
- Saket Gurukar, Deepak Ajwani, Sourav Dutta, Juho Lauri, Alessandra Sala, Srinivasan Parthasarathy, “Towards Quantifying the Distance between Opinions”. ICWSM ’20.
- Saket Gurukar, Srikanta Bedathur. Time-series as Background Data for Relating Medical Diagnoses Terms. Proc. of the 10th ACM Conference on Bioinformatics, Computational Biology and Health Informatics (ACM BCB), 2019.
- Saket Gurukar, Sayan Ranu, Balaraman Ravindran, “COMMIT : A Scalable Approach to Mining Communication Motifs from Dynamic Graphs”, in SIGMOD, 2015.
- Saket Gurukar, Balaraman Ravindran, “Temporal Analysis of Telecom Graphs”, in COMSNET, 2014.
Patents
- Pranay Lohia, Saket Gurukar , Rishabh Gupta, Himanshu Gupta. Automatically Suggesting a Temporal Opportunity for and Assisting a Writer in Writing One or More Sequel Articles Via Artificial Intelligence. US20190197120A1
- Saket Gurukar , Ahmed Durga. ”Defect Prediction Operation”. US20180267886A1.
- Saket Gurukar , Sayan Ranu, Balaraman Ravindran, Subramanian Shivashankar, Ankur Dauneria. "Temporal Motif Based Approach To Analyze Devices Reconnection Patterns". United States PCT/SE2014/051303.
Work Experience
- Jan '23 - present: Staff Researcher, Samsung Research America.
- Jul ’16 - Jun ’17: Research Software Engineer at IBM Research Labs, India
- Jun ’16 - Jul ’16: Senior Software Developer at Codenation.
- Jun ’15 - Jun ’16: Software Developer at Codenation.
- Jun ’11 - Jun ’12: Software Developer at Persistent Systems Pvt Ltd.
Internships
- May ’21 - Aug ’21: Research Intern at Pinterest Labs.
- May ’20 - Aug ’20: Research Intern at Pinterest Labs.
- May ’19 - Aug ’19: Data Science Intern at Etsy.
- May ’18 - Aug ’18: Machine Learning Intern at Nokia Bell Labs, Ireland.
Services/Honors
- PC member: AAAI ’23, KDD ’22
- Reviewer: KDD ’22, ICDE’21, ICWSM ’21, TKDE ’20, Big Data ’21, DASFAA ’20, ’18, CIKM ’18
- External Reviewer: VLDB ’22, WSDM ’22, AAAI ’22, ’21, KDD ’21, ’20, ’19, ICDE ’21, EDBT ’21
- Awarded Graduate Research Award (2022) by the CSE Department at OSU.
- Panelist at Deep Learning Day workshop organized at KDD ’21 .
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