LIJUN DING School of Operations Research and Information Engineering, Cornell University 296 Frank H.T. Rhodes Hall, Ithaca, NY 14853 Phone: +1 312 877 9746 https://people.orie.cornell.edu/ld446/ Email: ld446@cornell.edu EDUCATION 09/2016 -present Cornell University, U.S.A. School of Operations Research and Information Engineering (ORIE) ◦ PhD Student ◦ Advisors: Prof. Yudong Chen and Prof. Madeleine Udell ◦ A+ or A in all ORIE, mathematics and statistics courses ◦ Cumulative Grade Average (CGA): 4.06/4.3 09/2014 -06/2016 University of Chicago, Department of Statistics U.S.A. ◦ M.S. in Statistics ◦ Advisor: Prof. Lek-Heng Lim ◦ A or A-(one only) in all statistic/computer science courses, GPA: 3.98/4 09/2010 -08/2014 Hong Kong University Of Science And Technology(HKUST), Hong Kong Department of Mathematics ◦ B.S. in Mathematics and Economics (First Honour) ◦ Minor in Actuarial Mathematics ◦ Cumulative Grade Average (CGA): 4.08/4.3 Grade: A ◦ Performance on Mathematic and Economics courses: either A or A+ 02/2013 -06/2013 Eidgen¨ossische Technische Hochschule Z¨urich(ETH), Zurich, Switzerland Department of Mathematics ◦ Exchange Study ACADEMIC BLOG I maintain a blog (https://threesquirrelsdotblog.com/) to post my discoveries of optimization, statistics and probability. These are small, interesting and original results that arising from my studies at Cornell. RESEARCH INTERESTS Lijun’s research lies at the intersection of optimization, statistics, and machine learning, where he works on solving large-scale and high dimensional optimization problems. By exploring ideas and techniques such as Frank-Wolfe, strict complementarity, and the leave-one-out argument in these felds, he is able to design computationally and statistically effcient algorithms for both classical convex optimization problems such as semidefnite programming, and newly arising nonconvex problems. PUBLICATIONS & WORKING PAPERS • Lijun Ding, Yuqian Zhang, and Yudong Chen. “Low-rank matrix recovery with non-quadratic loss: projected gradient method and regularity projection oracle”, arXiv preprint arXiv:2008.13777 (2020). • Lijun Ding and Benjamin Grimmer. “Revisit of spectral bundle methods: Primal-dual (sub) linear convergence rates”, arXiv preprint arXiv:2008.07067 (2020) • Lijun Ding, Jicong Fan, and Madeleine Udell. “kfw: A frank-wolfe style algorithm with stronger subproblem oracles”, arXiv preprint arXiv:2006.16142 (2020). • Lijun Ding, Yingjie Fei, Qiantong Xu, and Chengrun Yang. “Spectral Frank-Wolfe Algorithm: Strict Complementarity and Linear Convergence.” arXiv preprint arXiv:2006.01719 (2020). • Lijun Ding and Madeleine Udell. “ On the regularity and conditioning of low rank semide nite programs”, arXiv preprint arXiv:2002.10673 (2020). • Lijun Ding, and Benjamin Grimmer. “Bundle Method Sketching for Low Rank Semidefnite Programmin”, 11th OPT Workshop on Optimization for Machine Learning (OPT2019), 2019. • Jicong Fan, Lijun Ding, Yudong Chen, and Madeleine Udell. “Factor Group-Sparse Regularization for Effcient Low-Rank Matrix Recovery” Neural Information Processing Systems Conference (NeurIPS), 2019. • Vasileios Charisopoulos,Yudong Chen, Damek Davis, Mateo D´ıaz, Lijun Ding, and Dmitriy Drusvyatskiy. ”Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence ”, arXiv preprint arXiv:1904.10020 (2019). • Lijun Ding, and Lek-Heng Lim. ”Higher-Order Cone Programming”, arXiv preprint arXiv:1811.05461 (2018). • Lijun Ding, Alp Yurtsever, Volkan Cevher, Joel A. Tropp and Madeleine Udell. ”Storage Optimal and Effcient Methods for Solving SDP via Complementary Slackness.”, Submitted, arXiv preprint arXiv:1902.03373(2019). • Lijun Ding, and Yudong Chen. ”The Leave-one-out Approach for Matrix Completion: Primal and Dual Analysis.” arXiv preprint arXiv:1803.07554 (2018). • Lijun Ding, and Madeleine Udell. ”Frank-Wolfe Style Algorithms for Large-Scale Optimization.”, Large- Scale and Distributed Optimization, Springer, 2018. AWARDS & SCHOLARSHIPS 2019 Winner of the INFORMS Optimization Society Student Paper Prize 2016-2017 Cornell University, ORIE PhD Fellowship 2014-2016 University of Chicago, Department of Statistics Scholarship 10/2014 Hong Kong University of Science and Technology, Academic Achievement Medal 09/2010 -08/2014 HKUST -Dean’s List 09/2013 Hong Kong Government -Reaching out award 2012/2013 The Cheng Foundation Scholarships for Chinese Mainland UG Students 2012/2013 Lee Hysan Foundation Exchange Scholarship 05/2012 HKUST -MATH Department: The 7th Epsilon Fund Award to Top Students 2011/2012 The Joseph Lau Luen Hung Charitable Trust Scholarship 2010/2011 HKUST-School of Science Scholarship TALKS • Spectral Frank-Wolfe Algorithm: Strict Complementarity and Linear Convergence – at International Conference on Machine Learning (ICML), 07/2020 • Higher Order Cone Programming – at 2016 China-Korea International Conference on Matrix Theory with Applications, 12/2016 – at International Symposium on Mathematical Programming, 07/2018 • The Leave-one-out Approach for Matrix Completion: Primal and Dual Analysis – at International Symposium on Mathematical Programming, 07/2018 • An Optimal-Storage Approach to Semidefnite Programming using Approximate Complementarity – at SIAM Conference on Computational Science and Engineering, 02/2019 – at 2019 INFORMS Annual Meeting, 10/2019 INTERNSHIP & TEACHING EXPERIENCE 07/2019 -08/2019 ◦ Research Intern: Alibaba group, DAMO academy 01/2019 -03/2019 ◦ Instructor of ORIE 5270: Big Data Technologies (more than 50 students) 01/2019 -present ◦ Instructor of ORIE 6125: Computational Methods in Operations Research (PhD Level Course) 01/2017 -05/2017 ◦ TA of ORIE 6326: Convex Optimization (more than 40 students) 10/2012 -12/2012 ◦ MATH tutor of MATH support centre 09/2012 -12/2012 ◦ Grader of MATH 3121: Algebra I (more than 50 students) COMPUTING SKILLS & LANGUAGE • Profcient in LATEX, R, Matlab,Python • Language: Mandarin(native), English(fuent), Cantonese(fuent), Hangzhou dialect (native)